diff --git a/README.md b/README.md
index 8fd03bd96878b3798852eef9e26dbfb41d27e930..fdc5a3747fbfdebc996150b6cf29b3808cf7f925 100644
--- a/README.md
+++ b/README.md
@@ -270,7 +270,7 @@ What happens behind the scenes when we set `self.title` is that the result is pr
 ### Caching computations
 The `@cache`-decorator offers a direct ways to compute the correct result on an instructors computer and submit it to the student. For instance:
 ```python
-# example_framework/instructor/cs102/report2.py
+# example_framework/instructor/cs102/report2_test.py
 class Question2(UTestCase): 
     @cache
     def my_reversal(self, ls):
diff --git a/devel/example_devel/instructor/output/report2.py b/devel/example_devel/instructor/output/report2.py
index ec424f464f534d680f3b886bc61f5466a72130e0..3386669ee4d58b317291e03b7f7b8e3fa23e3d42 100644
--- a/devel/example_devel/instructor/output/report2.py
+++ b/devel/example_devel/instructor/output/report2.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
         self.title = f"Checking if reverse_list({ls}) = {reverse}"  # Programmatically set the title 
 
     def ex_test_output_capture(self):
diff --git a/devel/example_devel/instructor/output/report2_b.py b/devel/example_devel/instructor/output/report2_b.py
index f42d83d4d854736924402a42fb75a47e7e72aa29..98e3c25c76020d56ee6920c798996a54acd90cba 100644
--- a/devel/example_devel/instructor/output/report2_b.py
+++ b/devel/example_devel/instructor/output/report2_b.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 class Week1Titles(UTestCase): 
 
 
diff --git a/devel/example_devel/instructor/output/report2_c.py b/devel/example_devel/instructor/output/report2_c.py
index 8b386384e5672619f390c1cb458986fed8409a3a..c47fa0b31b2d016e4ae11ef4544fdfb960167834 100644
--- a/devel/example_devel/instructor/output/report2_c.py
+++ b/devel/example_devel/instructor/output/report2_c.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 class Question2(UTestCase): 
     @cache
     def my_reversal(self, ls):
diff --git a/docs/snips/report2.py b/docs/snips/report2.py
index e7aa0ed0811323a8cfe939ebc214aef6a1cae2e9..1eb0160a58ddbdf156da500c106263207fcb5775 100644
--- a/docs/snips/report2.py
+++ b/docs/snips/report2.py
@@ -1,4 +1,4 @@
-# example_framework/instructor/cs102/report2.py
+# example_framework/instructor/cs102/report2_test.py
 from unitgrade import UTestCase, cache  
 
 class Week1(UTestCase):
diff --git a/docs/snips/report2_b.py b/docs/snips/report2_b.py
index 5de6d0b254387e7a82b58906cedd82ccabd43215..64c65ee7ee98bdba6391fb85ba72d8b0786ade50 100644
--- a/docs/snips/report2_b.py
+++ b/docs/snips/report2_b.py
@@ -1,4 +1,4 @@
-# example_framework/instructor/cs102/report2.py
+# example_framework/instructor/cs102/report2_test.py
 class Week1Titles(UTestCase): 
     """ The same problem as before with nicer titles """
     def test_add(self):
diff --git a/docs/snips/report2_c.py b/docs/snips/report2_c.py
index aa444a6283536738901c1d496d0ccc32a9d6179a..84d7fd528956b821c42d629bde548865a1e186f0 100644
--- a/docs/snips/report2_c.py
+++ b/docs/snips/report2_c.py
@@ -1,4 +1,4 @@
-# example_framework/instructor/cs102/report2.py
+# example_framework/instructor/cs102/report2_test.py
 class Question2(UTestCase): 
     @cache
     def my_reversal(self, ls):
diff --git a/examples/autolab_example/tmp/cs102/cs102-handout/report2_grade.py b/examples/autolab_example/tmp/cs102/cs102-handout/report2_grade.py
index ed7227f24103a00dfc8b261b6795896bd2a4f4d2..cb89f5a40b86e7388e579a0696d75b02fc26b199 100644
--- a/examples/autolab_example/tmp/cs102/cs102-handout/report2_grade.py
+++ b/examples/autolab_example/tmp/cs102/cs102-handout/report2_grade.py
@@ -1,4 +1,4 @@
-# cs102/report2.py
+# cs102/report2_test.py
 ''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
 import bz2, base64
 exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example/tmp/cs102/src/report2_grade.py b/examples/autolab_example/tmp/cs102/src/report2_grade.py
index ed7227f24103a00dfc8b261b6795896bd2a4f4d2..cb89f5a40b86e7388e579a0696d75b02fc26b199 100644
--- a/examples/autolab_example/tmp/cs102/src/report2_grade.py
+++ b/examples/autolab_example/tmp/cs102/src/report2_grade.py
@@ -1,4 +1,4 @@
-# cs102/report2.py
+# cs102/report2_test.py
 ''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
 import bz2, base64
 exec(bz2.decompress(base64.b64decode('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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_19_of_26.token b/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_19_of_26.token
new file mode 100644
index 0000000000000000000000000000000000000000..379766ca8efbf72b3380fa54fa7150d2ecd7839f
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_19_of_26.token
@@ -0,0 +1,327 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_26_of_26.token b/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_26_of_26.token
new file mode 100644
index 0000000000000000000000000000000000000000..1d90ee18a59359a862d6aaafb545706ba2377464
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_26_of_26.token
@@ -0,0 +1,329 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105h.tar b/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105h.tar
new file mode 100644
index 0000000000000000000000000000000000000000..396f5e36905daaa79fe561da41530c166dd0d8a8
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diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy.py
index 1a8a796cd46a61ece38905cdf4375f025325649e..ce4fcd93ab73cf761dedd339da3ddfb6a75dabf6 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy.py
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy.py
@@ -1,4 +1,4 @@
-from cs102.report2 import Report2
+from cs102_autolab.report2_test import Report2
 from unitgrade_private.hidden_create_files import setup_grade_file_report
 from snipper.snip_dir import snip_dir
 
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy_autolab.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy_autolab.py
index 6494174e62992f8f70cb044306b7770a276b91e5..63db95ee34954055fd71e136d22ddcc678bdf78c 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy_autolab.py
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/deploy_autolab.py
@@ -4,14 +4,14 @@ from unitgrade_private.docker_helpers import compile_docker_image
 
 if __name__ == "__main__":
     ## Step 1. Deploy the report file.
-    from report2 import Report2
+    from report2_test import Report2
     from unitgrade_private.hidden_create_files import setup_grade_file_report
     from snipper.snip_dir import snip_dir
     from unitgrade import version
     print("version", version.__version__)
     # Set up the instructor _grade script and all files needed for the tests.
-    setup_grade_file_report(Report2, with_coverage=False)
-    snip_dir("./", "../../students/cs102_autolab", clean_destination_dir=True, exclude=['*.token', 'deploy_autolab.py', '*_grade.py', 'tmp', '*.tar'])
+    setup_grade_file_report(Report2, with_coverage=False, bzip=True)
+    snip_dir("./", "../../students/cs102_autolab", clean_destination_dir=True, exclude=['*.token', 'deploy*.py', '*_grade.py', 'tmp', '*.tar'])
 
     # Step 1: Download and compile docker grading image. You only need to do this once.  #!s=a
     download_docker_images("../docker") # Download docker images from gitlab (only do this once).
@@ -23,17 +23,17 @@ if __name__ == "__main__":
     instructor_base = f"."
     student_base = f"../../students/cs102_autolab"
 
-    from report2 import Report2
+    from report2_test import Report2
     # INSTRUCTOR_GRADE_FILE =
-    output_tar = new_deploy_assignment("cs105d",  # Autolab name of assignment (and name of .tar file)
+    output_tar = new_deploy_assignment("cs105h",  # Autolab name of assignment (and name of .tar file)
                                    INSTRUCTOR_REPORT_CLASS=Report2,
                                    INSTRUCTOR_BASE=instructor_base,
-                                   INSTRUCTOR_GRADE_FILE=f"{instructor_base}/report2_grade.py",
+                                   INSTRUCTOR_GRADE_FILE=f"{instructor_base}/report2_test_grade.py",
                                    STUDENT_BASE=student_base,
-                                   STUDENT_GRADE_FILE=f"{instructor_base}/report2.py",
+                                   STUDENT_GRADE_FILE=f"{instructor_base}/report2_test.py",
                                    autograde_image_tag=autograde_image,
                                    student_should_upload_token=False,
-                                    homework_file="homework1.py") #!s
+                                   homework_file="homework1.py") #!s
 
     # What can you do? Get a report class from the .token file?
 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout.tar b/examples/autolab_example_py_upload/instructor/cs102_autolab/handout.tar
similarity index 65%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout.tar
rename to examples/autolab_example_py_upload/instructor/cs102_autolab/handout.tar
index 8786bf46facaf94d6f8b944b1724ffbf3b06f3d2..75f2f0f49ebf7f1df224ef7628697989ad3ab581 100644
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout.tar and b/examples/autolab_example_py_upload/instructor/cs102_autolab/handout.tar differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/homework1.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/homework1.py
index 94004fc5d7ed38a9a3598d4b7ed9b0e08c6f6793..c774405dc693d104ed9b1f48df5554a12e3c9ae3 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/homework1.py
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/homework1.py
@@ -8,7 +8,7 @@ def reverse_list(mylist): #!f #!s;keeptags
 def add(a,b): #!f
     """ Given two numbers `a` and `b` this function should simply return their sum:
     > add(a,b) = a+b """
-    return a+b
+    return a+b*2
 
 if __name__ == "__main__":
     # Example usage:
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_grade.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_grade.py
index 0ee13a2da31594e56132628b27f81af994dcbb29..2d2ae9724d7307b9c5d30654bf31f68e3510d143 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_grade.py
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_grade.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 ''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
 import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/report2.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_test.py
similarity index 97%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/report2.py
rename to examples/autolab_example_py_upload/instructor/cs102_autolab/report2_test.py
index a1d345354964853c30d69b6db48eef127c4edb6f..14d21fa679ac5f1d6cb5c5c6f4f0259c2737e449 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/report2.py
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_test.py
@@ -3,6 +3,7 @@ from unitgrade.evaluate import evaluate_report_student
 from homework1 import add, reverse_list
 from unitgrade import UTestCase, cache  # !s
 import homework1
+import unittest
 
 
 class Week1(UTestCase):
@@ -63,7 +64,7 @@ class Report2(Report):
     version = 1.0
     url = "https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/tree/master/examples/autolab_example_py_upload/instructor/cs102_autolab"
     title = "CS 106a"
-    questions = [(Week1, 10), (Week1Titles, 6)]
+    questions = [(Week1, 10), (Week1Titles, 6), (Question2, 10)]
     pack_imports = [homework1]
 
 if __name__ == "__main__":
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_test_grade.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_test_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..d35d464081aea7fee536c44ebc291e882d67be65
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2_test_grade.py
@@ -0,0 +1,4 @@
+# report2_test.py
+''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
+import bz2, base64
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Question2.pkl b/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Question2.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..bcfd4d4c0ec3b7fa90b9d5945812dfd05623770b
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Question2.pkl differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1.pkl b/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1.pkl
index ad7ddfc809f5bda52c1d7e563ee22f36ab221123..d7e897ace5ae661bbe6e4d3d29bff2c3dbbea55a 100644
Binary files a/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1.pkl and b/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1.pkl differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1Titles.pkl b/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1Titles.pkl
index f0cd99c72858c45d52215386019e7a4ed35e3342..3f846dd3e070d58ba594674b8ac74ebd84837781 100644
Binary files a/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1Titles.pkl and b/examples/autolab_example_py_upload/instructor/cs102_autolab/unitgrade_data/Week1Titles.pkl differ
diff --git a/examples/autolab_example_py_upload/instructor/output/homework1.py b/examples/autolab_example_py_upload/instructor/output/homework1.py
index 4412ca41cb9875a1702b96b878a774bb854465b3..526045bf833b38d3538d8d913577a36f2401539c 100644
--- a/examples/autolab_example_py_upload/instructor/output/homework1.py
+++ b/examples/autolab_example_py_upload/instructor/output/homework1.py
@@ -9,7 +9,7 @@ def reverse_list(mylist): #!f
 def add(a,b): #!f
     """ Given two numbers `a` and `b` this function should simply return their sum:
     > add(a,b) = a+b """
-    return a+b
+    return a+b*2
 
 if __name__ == "__main__":
     # Example usage:
diff --git a/examples/autolab_example_py_upload/instructor/output/report2.py b/examples/autolab_example_py_upload/instructor/output/report2.py
index b0b015b1f22bf8fe736cf4164358ee0158f3401b..19dd8d59926a81b3788fecec1a770f0e1f625589 100644
--- a/examples/autolab_example_py_upload/instructor/output/report2.py
+++ b/examples/autolab_example_py_upload/instructor/output/report2.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 from unitgrade import UTestCase, cache  
 import homework1
 
diff --git a/examples/autolab_example_py_upload/instructor/output/report2_b.py b/examples/autolab_example_py_upload/instructor/output/report2_b.py
index e5dc8fe9178b7ec1199e0f74700381379af011cc..e14f75cf25d8da29f86a70d6cff1a0b0511646e0 100644
--- a/examples/autolab_example_py_upload/instructor/output/report2_b.py
+++ b/examples/autolab_example_py_upload/instructor/output/report2_b.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 class Week1Titles(UTestCase): 
     """ The same problem as before with nicer titles """
     def test_add(self):
diff --git a/examples/autolab_example_py_upload/instructor/output/report2_c.py b/examples/autolab_example_py_upload/instructor/output/report2_c.py
index 8b386384e5672619f390c1cb458986fed8409a3a..c47fa0b31b2d016e4ae11ef4544fdfb960167834 100644
--- a/examples/autolab_example_py_upload/instructor/output/report2_c.py
+++ b/examples/autolab_example_py_upload/instructor/output/report2_c.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 class Question2(UTestCase): 
     @cache
     def my_reversal(self, ls):
diff --git a/examples/autolab_example_py_upload/instructor/output/report2_test.py b/examples/autolab_example_py_upload/instructor/output/report2_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..7ca1c3de5380497a99e5b09b34b349394227e760
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/output/report2_test.py
@@ -0,0 +1,13 @@
+# report2_test.py
+from unitgrade import UTestCase, cache  
+import homework1
+import unittest
+
+
+class Week1(UTestCase):
+    def test_add(self):
+        self.assertEqualC(add(2,2))
+        self.assertEqualC(add(-100, 5))
+
+    def test_reverse(self):
+        self.assertEqualC(reverse_list([1, 2, 3])) 
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/output/report2_test_b.py b/examples/autolab_example_py_upload/instructor/output/report2_test_b.py
new file mode 100644
index 0000000000000000000000000000000000000000..e14f75cf25d8da29f86a70d6cff1a0b0511646e0
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/output/report2_test_b.py
@@ -0,0 +1,16 @@
+# report2_test.py
+class Week1Titles(UTestCase): 
+    """ The same problem as before with nicer titles """
+    def test_add(self):
+        """ Test the addition method add(a,b) """
+        self.assertEqualC(add(2,2))
+        print("output generated by test")
+        self.assertEqualC(add(-100, 5))
+        # self.assertEqual(2,3, msg="This test automatically fails.")
+
+    def test_reverse(self):
+        ls = [1, 2, 3]
+        reverse = reverse_list(ls)
+        self.assertEqualC(reverse)
+        # Although the title is set after the test potentially fails, it will *always* show correctly for the student.
+        self.title = f"Checking if reverse_list({ls}) = {reverse}"  # Programmatically set the title 
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/output/report2_test_c.py b/examples/autolab_example_py_upload/instructor/output/report2_test_c.py
new file mode 100644
index 0000000000000000000000000000000000000000..c47fa0b31b2d016e4ae11ef4544fdfb960167834
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/output/report2_test_c.py
@@ -0,0 +1,16 @@
+# report2_test.py
+class Question2(UTestCase): 
+    @cache
+    def my_reversal(self, ls):
+        # The '@cache' decorator ensures the function is not run on the *students* computer
+        # Instead the code is run on the teachers computer and the result is passed on with the
+        # other pre-computed results -- i.e. this function will run regardless of how the student happens to have
+        # implemented reverse_list.
+        return reverse_list(ls)
+
+    def test_reverse_tricky(self):
+        ls = (2,4,8)
+        ls2 = self.my_reversal(tuple(ls))                   # This will always produce the right result, [8, 4, 2]
+        print("The correct answer is supposed to be", ls2)  # Show students the correct answer
+        self.assertEqualC(reverse_list(ls))                 # This will actually test the students code.
+        return "Buy world!"                                 # This value will be stored in the .token file  
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/Makefile
deleted file mode 100644
index e511c68d3823b53c626fd1b1bd7e448b36cae9fd..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/Makefile
+++ /dev/null
@@ -1,51 +0,0 @@
-#
-# Makefile to manage the example Hello Lab
-#
-
-# Get the name of the lab directory
-# LAB = $(notdir $(PWD)) # Fail on windows for some reason...
-
-all: handout handout-tarfile
-
-handout: 
-	# Rebuild the handout directory that students download
-	(rm -rf cs105-new-version-handout; mkdir cs105-new-version-handout)
-	cp -p src/Makefile-handout cs105-new-version-handout/Makefile
-	cp -p src/README-handout cs105-new-version-handout/README
-	cp -p src/driver_python.py cs105-new-version-handout
-
-	cp -p src/student_sources.zip cs105-new-version-handout
-
-	cp -p src/homework1.py cs105-new-version-handout
-
-	cp -p src/docker_helpers.py cs105-new-version-handout
-
-	cp -p src/report2_grade.py cs105-new-version-handout
-
-
-handout-tarfile: handout
-	# Build *-handout.tar and autograde.tar
-	tar cvf cs105-new-version-handout.tar cs105-new-version-handout
-	cp -p cs105-new-version-handout.tar autograde.tar
-
-clean:
-	# Clean the entire lab directory tree.  Note that you can run
-	# "make clean; make" at any time while the lab is live with no
-	# adverse effects.
-	rm -f *~ *.tar
-	(cd src; make clean)
-	(cd test-autograder; make clean)
-	rm -rf cs105-new-version-handout
-	rm -f autograde.tar
-#
-# CAREFULL!!! This will delete all student records in the logfile and
-# in the handin directory. Don't run this once the lab has started.
-# Use it to clean the directory when you are starting a new version
-# of the lab from scratch, or when you are debugging the lab prior
-# to releasing it to the students.
-#
-cleanallfiles:
-	# Reset the lab from scratch.
-	make clean
-	rm -f log.txt
-	rm -rf handin/*
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/autograde-Makefile
deleted file mode 100644
index d768a52ad4b14903ca2d3d0cea8745d16ceff387..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/autograde-Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-all:
-	tar xf autograde.tar
-	cp homework1.py cs105-new-version-handout
-	(cd cs105-new-version-handout; python3 driver_python.py)
-
-clean:
-	rm -rf *~ hello3-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/autograde.tar
deleted file mode 100644
index e3f6068795cb9e02815d639fba64fe4d3ae7edca..0000000000000000000000000000000000000000
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout.tar
deleted file mode 100644
index e3f6068795cb9e02815d639fba64fe4d3ae7edca..0000000000000000000000000000000000000000
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/docker_helpers.py
deleted file mode 100644
index b4b885526bfe90b86900afb241496de2c7c84aea..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/driver_python.py
deleted file mode 100644
index 49a443dc051e8c745c096b613cb0ddf4ec262339..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/driver_python.py
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.version)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/homework1.py
deleted file mode 100644
index bd5258f7f5597728f597306d5f0c9927be6dbca9..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-462dc30ee9800e94c92dac8759133c0224cbdce8d4ba8deca101829a940d4a639772387ec4b286a2bc6e79f606607ea89853cdf4b6e83e920fd484e5f2a25d82 31240
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/report2_grade.py
deleted file mode 100644
index f74205d5b64eba088d62e54e7fb97267c1785733..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/student_sources.zip
deleted file mode 100644
index bb4071233d4b81173b73946b3f220c8b826d57fe..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.rb
deleted file mode 100644
index 6839a6381d5c9a0459273a3804f0888a10b476ef..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.rb
+++ /dev/null
@@ -1,11 +0,0 @@
-require "AssessmentBase.rb"
-
-module Cs105-new-version
-  include AssessmentBase
-
-  def assessmentInitialize(course)
-    super("cs105-new-version",course)
-    @problems = []
-  end
-
-end
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/docker_helpers.py
deleted file mode 100644
index b4b885526bfe90b86900afb241496de2c7c84aea..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py
deleted file mode 100644
index 49a443dc051e8c745c096b613cb0ddf4ec262339..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.version)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py-handout
deleted file mode 100644
index 49a443dc051e8c745c096b613cb0ddf4ec262339..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py-handout
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.version)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/homework1.py
deleted file mode 100644
index bd5258f7f5597728f597306d5f0c9927be6dbca9..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-462dc30ee9800e94c92dac8759133c0224cbdce8d4ba8deca101829a940d4a639772387ec4b286a2bc6e79f606607ea89853cdf4b6e83e920fd484e5f2a25d82 31240
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/report2_grade.py
deleted file mode 100644
index f74205d5b64eba088d62e54e7fb97267c1785733..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/student_sources.zip
deleted file mode 100644
index bb4071233d4b81173b73946b3f220c8b826d57fe..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde-Makefile
deleted file mode 100644
index dfcdcfda5aa8049ab3b62a997b374031687046b6..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde-Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-all:
-	tar xf autograde.tar
-	cp homework1.py cs105-handout
-	(cd cs105-handout; python3 driver_python.py)
-
-clean:
-	rm -rf *~ hello3-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde.tar
deleted file mode 100644
index 5217159da449d47c709258f3089da0ed705afe90..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout.tar
deleted file mode 100644
index 5217159da449d47c709258f3089da0ed705afe90..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/README b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/docker_helpers.py
deleted file mode 100644
index b4b885526bfe90b86900afb241496de2c7c84aea..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/driver_python.py
deleted file mode 100644
index 3542e09379b7aec9fa34126730ad9a5670160778..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/driver_python.py
+++ /dev/null
@@ -1,87 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/homework1.py
deleted file mode 100644
index 18576f18162b3e965b483dc0c9f2673d29b35a2f..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-bf53f370e71e4336d4a54c09f106ff88be0c37385c9ba6d9558657c25640e0166ca05e546617c8619f4d20e975652285268341097c88a559c4bfb73c809f1037 31256
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/report2_grade.py
deleted file mode 100644
index 7484d93eae4ad3d81e212ea0c2a5c8561c1761b8..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('QlpoOTFBWSZTWWL1f0cAVWb/gH/25FZ7/////+//vv////5gZT773q896+1fHgFHwp7r73kRAoFF6NSi29cI5aUlQHQOzQ693zn19tnpxfZh1E2xbZKX1opdjXXR3fPjrm80m1vcU76KcvQOj3buV3nkc3set7u+kjCvsb7feOtsjw3bep9ard62sgMytM27d2SKDsz3d48Br50m7Vve3nd8CilFO+wfG6647b22892PMnYwR993rb3LSw73elzzE5unc1ULzvbezDepckLk0e+80vvFcQzCfdQ6JLs219nvbXi76x9455Xu7vve9273YPUe8+XbbaGq8xR3uV886Kurvn0nxibaneY7t95ztxu53brS7Xdu2+7V2+3ub7CU0QQAmgCaCMiYCDU0xqJP0UeNUNG1P1Qep5TTJppsoPSYJTQIQRNNBATQVPYI1T1PUeKbSZBpp6j1NADQ2poeoABoJTEhBJkQ01T01PKmn6p6jNTRp+pp6SaekAGhoA0NAA0ZDRoJNJEIiaaVT/NIlP9JTeqfp6qfom9SnoZRk9TQaPRP1T1NNGDTTUGEAACJIggCaA0TTRpimaTTKYJT9NU/KamnqenqepHoNDUGmmjQA0CTUSEAmjQTKeITRqZTeho1J5qMoPRB6Ro09TagGgGgDRzofugvvPdQKgURVn8ClPlARR9ywkFAJCiT0KLFVFT/70eaysUhhP9/88QpfgQ6P61e/CPuWZPw/5P74rGJi6f8zm+M3D/P8EJFK5cJ2loTJCZN2/n1xP/FWL0cdcZfHE03WlLio+061BloaoizPPDa2rzKS71eunFjjvVRAsSn2/15I5vUDLd3R22crzjM8eLs0qFKLXmi6HMkXochk5S0nMrl8oP5nyJTj7v5X5IEv7+T6az14ziKf+ZzpOTulovvV8re6xgmPLbsMtjAzMMH/vLHHmMAREE6gQD4MRZAkEkSQIJFCRZFJJPwklCosBBV+xJciiNv8YBSm0gIpSQAGqJSAwgEDpA55YOjnEkBvd+D3V8rfmTfdv3G7aK5HGwxsJ7ibid1IFSgVYJBVlSNFVBRT9xhQYioCqQVBkRVSC3VEj+rp/618dhz69kP4+cXfxPgvq/5rVq1Mdib+uPutysoFCnlznYL8HFpdxJA7zQ5L64653OfLU6LYepso0iOadDt0lbblOehDWVFVEPpRyg69kHcmuOX9NvvV761LoaqIiIh0OmNZPVCFOeh/6NCCgqMcjL9S1tYWkM/k5/Vd/l5frssrx83vjrqOPG83ya6MZBxbCjfhGCRX+U2af+zKJ8rEbdl+EoTHvRtT8Pgjr7HX83btReM3zpmMC4uOR7IPhZ2QfTCelYsl6q7/Yu/jS+Qi9XqQJrBDps/TBhMrY/+N8Qmf33ZX3SPod6s4fPbgdu8RNsAkHp8hNGR7Ztywe33CBMCGdM68PFN5ZCP8JxJyv5LYxIKA7pDzlKIRavEEQi9FPTb8OT9hfsOEmj4+fzyyE0NR7PB5+yGnCZ/V4djNDLx+FunCj3f/vKXjJeI+TpyujXDQmn2fh+N+O7NHfpG3ZnfMznUOlGG6PSgzR/bR6ZaE4FUnXKdbsCmU2+K9pg+n18rDHW7PZqU5XXwGj6ZP/LoRlKsrzQS37sc8LY32SnWOa92M6UsezFqXD3785bqyk1+9PtJaY7N1+JmXdksVFXIppynBjTjS2m+ZtnwhL5q4+GcWq+FqM0kb3M+ceBY37Z93oXSOpp/bpV42Pfn0kxjOJL517NjC1iGN9N13khvPUQtJGn3zEdELrGDVlzJhcSnJUz4va2XXv+OOabSUJ3fCxGyPLJveU2H4rhMUP73gwm6rhCn5xanuC4t4S8xHj+XzlCTaFNUKKLZaShpHtHmkIgkCdbDjnYDoBEaGlN+SQhM1r67xDoZ3xut6CRe67/LgZzZkIZCd9NuXxdAhJcYh4B4TxmORGytGUmkUi8Hc2zw0cUw8jkOMduvKzrCzayRCIbT5sm3Jekcix8kJaBJIoM9b7i+U8ZOPV5+dvBLt7eHeo9NNDXfKTLrtbKgDdH7NXcW58kSiK3jrin0fDT9W2oQ4FDVDGnDhD4rsacM4FuWCytmBazuzPa7TTeAPbr7FWDiAwGKxde9A7PSru0+3cuTqzZ+W2t2xUNsJ5IBx3JhyeXsx+6z5eq22OQQvfYR+a3bvI4wbq/2SJCb+YLZBexW8fQ1mJ3SluviGXBPRI5iZhFRHyIDD18QHGIMhnN/0yloToc87sE/FtaDZ0Vt+lD126zneYCarSHde2eN7NTbkPY+XZdfR6D93cFQ8BG8W0uOxuQbeHV+dsanUc87Em54lR21HTMH3Pn143m9LR0E2YTGw5C/+ty79rN84C08y0Bkccu3WusYy4j47mPCsI67qfUirx9lIRLe8GeLtM3udOLtnYZBPM5b3rt22QImL/ltqL5rSyl445Qo/L7sJXzrryYvVG3XmaaLBG0t9LlCCW28j+y0wQqS1lZrlwgOdka4RHHa9Ycui387/MWf14YTw00FYCOWeF92QHHiU0enBsvy6fvUEK75h28PyCcSLi0bYZxgzbZqWQSMaMTIDqTY0gLZ7Te4m8i8sg2EY24H05s8XFlWdoOKBwsLWZsYnkUqU1tzz260lj6PGzwNNsWEmArj3zjOCOWEaMmTBNgzkcyGkLFXHyJNchWObqMHTtntjJY2Vej4nA3FHHaHLWXDYfE02xsBUottwofeZaT0g0CbVhx+0kRfoPqOClWcaiz20peJCQrTCo+LF6LqtUXEtytdeE6lhccovyuMy8yPfbekkMyEkG5NOuiewehJkUzFhlTc1qCt3W3lEkZ+fDIy6vt1Rwuu1BaLBlQ+HzzCqNNem/e7JCIdfEXJRJpMmmCXOkhM1A8P2PlvZZFRtuGrqYwEop/Lfr+/lWzW7xsJG9e2JpulbKNPCNJSYtOA+7eeqDhZka5GHRquye5yCWPMn90pFMrPBsCNJh9jWkz5eX0YZDmQdwvoMjGzEq1E1YLfkaa62jzofc9KOtsFefmlldXleQ5h2lveEDr6E1QUeUg7bUHgc7bdMbKZmJmhz7MOSfMEz4uwUTbPHY6UsNV0+3JJNeXXXlL2V7p2N5wsw4LqbWWeTOmzBGPlk9KleeIxLmaltzKD5+KrE0Y1bGi8Enn/SvGWLhvXSjaTMx9dQFfX+G+U7vz+S+VnRGtnYdRX89uiQNYucBr4rL60v6konqWubEeQQz7fnePXZsNl8zbpd27LzO2za+Edg5ZoUm7865iK5bpa/RKZFG1DbR4x7NGxc+E3XSwx2c4L/Xy17DE4hkY7DebSL1gVduPJ2YtqvyC+y/C6/ecS5rqO9XqpHtR0sp9OhbbTpVLLptCuVheZTr0mdGBuE7HtlRJQ5H2EWVRyQCLaokXjLlCEIJCZlvVGpeGORyKOcE3FdqHsmxuyNlNrNsXWmuWefa+Uby8puvAz28H7DY7SMqFiYVJGxVroWGy/uiRgzCaRxDA/N0dp9/qPmzQTfU2nFFiHwkpQ7SBA4e6rnx879CMCPUvvvozx/UPWjniiw0Hl0fYYHOuDXBwWs+Nw6rcU11vkRKVmfSzUriZDHUH6kfwVU0qRU5XaGulArYmW4HSSEoj9FlFGDaSopodJggsUa2OU9Nltpdu2zCrzpcsV6Qohu5wuCAnvMR+/W6wbXodDB2BYWzVk2myw6I1HU8DgyNja922WxArjkquG+opsmb1E9sQRAjffK5zDafxeisaDIJhDFUIwZsgO/KgizsekhjyMQRjHXjdiizSSZqwb0Pk62bDa29xzGiYe393U/Mgk0OLHGc98xs6OwudaaX4YwndGAp69hqVDZugwUiLrwpLDcaZEs3M2zKkqqWjpKZN7bAxwJXSHs5RrpaGh1EXZXlmUiTBqj4GXzFdMKGuuGCQk7YPQeVSy2KU3XnfolcI8BFoRir1ftMDwlZ7ZwksLCMUIl0EkKV9Zb5JMjy55jtzpNV6ElRWERmc7M6X2DmnWO3DIOaqIqKxAk1cpO3En4XPh+cc0RaPU3ejM0Xl7S7WdrLR3d2Nk4vj2V5TvkaV638NLa9DneNWy0g3WtlljSlmeGZFbWrhNpMhhBZpC23SHdSieJN/cruCHv2475lKOOrg6GzvPQ3RaZGh3UEcicO0RyGBHGD63OKB9B8czfO7EFyZdM+l19pK3eq0ptWE4iwnc24qPCHHCjFZFR85FjynKDDLWyvS+998ZWBXxlXGSNnnhg3enO5l+t67TghMDh3ilh5c8erViMBbdDOsUP4qn7+GWnF3krTvOsebxQTZuxZg78h/F7jwIdGOaJA71vHSDMulByRYE2Etj1LCcIrtM71biHrO8Z0250a9s+HheLzr4U2Wopzgw3M03NER4iLhzHfdcVyNcM7K3sUeEYW0PMPNMXY2qpJjwKnG6VpL82Utp1w1R2LYmpd4w5v0rt7LUWvS2J3XUp0wlsxPS8Uk4kb1982lD6umU32GWjCMm5gu+ZZY9Dndd1ZzYKdLjFvbInuN5UMRCAgKtghYV3CgtZFxxz9FMjygqdgj1GbDsBu5dJf0LVLwA/L9kivn06MWbu3ws2bt8Q3gvz2eo9mo7AhzAchQuYjvBH2oJib3OOUa4aw+DnRvTTO+upJrV15UHIuAQ6/X+aL8T3mw9e+GCcP2Dj7OC0YrQbFp8bWuBxxwHQkMkwpYu5m144RSr1z6+5/RLpSFF73qN7vEV6RI7CxC4niTdYp5F2w+0e2ymP9bqs+9rU9ytzyiX9v2bNu19Vh3PbPCaj9OtZSsfC23zPZWtd1jxS+ks3l63wnbbhZ4Sts1sezy8bapYrlTOC3yZHoBwcbbIdu9ECxDAL72bGZ08JT4Dr59sCE8d0W+l7sAz1JEBz/1T8bPruw7OvpyvJ4vX54xnrX37NLKT4X9uGXB9c6Jmw3y9fFW/HoUqMYRxez0pCpKqHgVgjeN9r+opqBWEUWotQ5LZDIxSo9VQbYH3v9esNX7DJc5Mg80wisVHO3lan3UOtExnrpBunH2X65Y+17fMi9Wo3/+Pdmac8cTJ0YqGZ5OMzLg5BYz0GiqzTrFrG+hYZE06JEyOW3UME8j86RZD4/TLisrAV5qFdJXSa/ks0/o3f5H9Aw46t1eXHXEsNIqxB3+PtmaF/3/o/n8eDh7DyNeu7MXM+o3MP03gm3TtZPKMXof6qztMawVhoTTP82HVyXcrDil43TgeNl1Nu8ph36M/S6disqLpFfSHZsSx/fdaJ2Aeso/YfN+biWMCk/ExKTx8/Z+H7gPHD2in8PdKgwaoB5mcMNUQkDDxd+xCfBA3aH2Y+Y1nL5vh1oiqqqxA4pA2bNWsp255ionQMoZFFVVkMtKgGiGmmVoZ6/Y5gaFn31RSCh8oyV7qlZjbZbZVtjEKsZCqyVlWMkqChX8jZCSAJB0+fc+xyXE6Dd0dxKVHISAL9b96cmiTTJt9iTYJNoRFSTSHrtdFJRfYTgJAszZOhMxSZ+mzQxBX7I8fWH5u3ziX+K5zmlb/ajsNIbG8+BtC28RtjSCeSJiBq9k8IbVhdNseP8bD8jV3dnWXv6q7lTMVs/ChbVcFFvjCvu8mC7mf2S5jOYZKMuYy0Wqp1qnIqIi0krh36fELLP4WMCg9PNvki5qn242jzm/4SlyVxlbmQIcCTIaiSJW/cRi5+0MnPayMGj6gieDvzg0ZHwYFb3RSgvnFS4lUHsLBEneZvKGTVMM0JswhvYbSrlK3DxNWuVYaF1OGTwDIhu74jbri2nsbZ3HjbzevMLNqxUDc3OqHMwgQ1KTKOFth2ISbKtNAWdsWjIaCHWqRcYh9a2dbfu1Z3aSLq/gX9sWa7vZj7q57tnc3BGGOx29x4GjnQsmwsZF/zIbA1MPHhZneZmGdBvzdUwLpCDVxXW33chLEwZ2JQ9M9ddmXxMJvVt70fRr6JewkaEd56zbxrnk22b7SVaL8nsq5XOsqSkeo5TfBOW54c9fm6WTreDJCc1FlTG8tTdl1u/Ccy1+ab4u6adqkQ+cRM/LcTtMKfSY646Y0W03tRQQRq43wXXBA+SzHRySD0IM+gvbrxRs900joNfeQQyOj5sn+P/V+TNHbjM9ObLU/6U5hzOHjun8pclrWL3f5l5vS5V8e67vpy9NIFou6H4yfRKUlbxWioqx9NyUUnXye6Enl1/K/2anO/8EcPo7x8ZdML2FG59Q9gocJfhnHKZ2cp+BTGLvqZ44yphUuVe++6HmWHEh96kPOwL3ppN59XOibluiL8uuy8yx2cHh0rUOmKLIX1CzUOtegeeVxPzrzq+V4/X38GHpLFlHSujUJ9ke+Yrco0Y851D8vBs/ze5+DHs8qeK5XT3qzdTpZMxDUpfniXU/yv96zsbXKS8Xqjfxd+vTft2zrS47HzWeYOxrRaN/O0qLGOmFmPqX2w8002Myz2kiNsu6tIoxqwm1OA5szcgILYomibsX3bsb5CorDvCVI+WUvxYk/En9HXh4RrioDY3ztLTv7no5eq2rKqnjn6pkW9Py9dHmbRsp3oUMRDsmd0IqZnFDR2Q8oSHciNzM1xQ751DkUvPVx4KsnqpyduUp0nrZlbJsc8IJd0Fbr8WZBBaciMMWu/b5Y24z6LPDy6Ronfy3vh/6b2awvbGl7nrPqw0m3GvZVQ9VESunl9vzxjIVeZWV1Xxt+w+cZcc1614TSn1uQrU9n7cr53U3Vcp2WxJHfpdxkd2Dbl6lwvHSM6lwsI9TypurLenVZRv77iCtX6ZPdTGcJXym8Q+yXgoyelslqDK+euM7fPit16KfoevXfj40VG/TuYo08Q/hjMzD+sTE8P4Vvvg3f7I+z1xrdeeSuJ8zFLX0vGajmfCDtUKm99b1DuiBOvXg/g/ZhWME+6uFKcdZ8bXnbEVTxmfbBPR+oi5w8Z215XfwzGZm5qofDvJ6e+5N7+ONuj3naK1nqQvfs5lAr1679bJ3Ra/meZd0hIJx69YKHr4Nv3TuyCNm2AEmkT2n5STDe5eu2rDoLBDEDUiLiSUm7tsIb2TUMFmghERjuwn3y2eFYol5RIgK7589Pf2sFwNHBI+vAa9MSE6A29zpmTN7d/GZwgvX0573JF7fGSPfuPgVjjuTzcWEy1AehX8WsTXCM5K7erYP3xmerU5mP93PPav/qfa+0t6N60ST7r82N6h6be3VW2y4190EpvcNfd6JET2VAlLZUpxn0CntvCuzIl0rT42Vzm+LHDJzWtDHT0Pw9O2qz0lRDLgkalX4eJ41WndCMuOnXTlyS95d2xiyQ3QljF3QlrEpAh2OF96vmIecHO3HrIwznAb1co7390WzvxwxsKeX0urThanNNKacqm4EX42Qx1mjoE9eYetPRPc003XnxEe6w4PXi0utt+Z9UUtvLzByX17caOV5+GX3wlZuRk7IWdYIXSB0yBri6sKxxGnOzVdnWpfYPwjg2EiwlLuiWU709c5nVtLDCjj67zCU7bfDmqaSt52W35T7+P5R0YiLHPLz6444jt1RiZdmNJm7fffxZvo67Lul1+WRFpZcSKOT4M+UtKCR/SOv0v66YOvOWrPBAcHuzokT/MW0tw5I775FqNlXC5DQi5u3OzcTeym7Z3UbA13Q3bs+Zj7zJP08Cxg/Diyx3FiE+ep6hOrQPQMiLMDgTb7ryTcE5rb7DkWAcq1CqO2Y2hOQVEXXHq+ysq1PXfQsYxN8+u7+Md4tHwb7CruzZLU+eFkpHvTpubYYwYPB7HL50GiEP5ou2tcUPaJpJjEtMDsOD7qNBj5Hs9AkO59HwDE9Jx25hsEM3sQzsLaw1Xbc2iCsnmQKaTp9Y14/NKXbQqdju5Oe80lS1iS0YzU3n5bffWdmnbfWz9qll9LpIEfcnBRVUCjYaI8CbtcK+Aw/DyQMSYwVMg4dmubOwXDFMajcpK5+DHEaSbQ8AZthjMOWXnhQpwk4thpJDsU4cGaKLHhtcjIAtuHM+cI0WAzROhLr8A0HUOGqIEiPLqKvp1FsUopKMdZc/h7O/cZ61I6Q8E3FFyhuFDVEGBrJ5MJzHF2n2wwNWnKNCZiaP0VQmO/uFRCFgLsjLjs3j0aQ2YNh5PCC4BCYFcTVNlz5XbMDRqZNZU1kaC0HuZKLDuNwVoGUyQzVBFDzGo7Q7c8wGcZuDYBC4HHZmoI2bTmg5IsPTxMwU4GDtoc0lKB0MftPFo8WK0xjGg82fFu6S81cfVOqoyTAqhRHI3D5shBVzjtUWIlJzlvvgvQqMM04l7Asrrd1u6kYvQ6Fj2XlbZY4IEiOhnZMjphlcRnVvkiUaJmNeMzPd66xlBPZtIeDZc1JgSHLxMIRs5Oe3E29WO7Q2nTE+DF4fnOzQFAOD1JB4pSg9128Mf9AT2BQD6m1fwnz9DyyPzvfq9pVCzNNfshWfBNdgaIkQE1cPbzcD2GXSGSFSaUa3IMcaRBZYyWqF9ZPo4ZFjTUmcUlI7MWknCyQeXDt2R1bSA/oFPIcC37R1VMHyTJMFC5kHh9uw7x/u6+ajpn7c/ltVU2fifGX+GFjEVnoVe2RC/Vz+FqJSEtG6y/Svb1ioqqAnKqaopTyHbXU4iKoqooMdDYljiHv60Gzr2Hjv3e6e49l3tlqT4FkkmUYDkCQyaQwZM2pheXm4MP8llLzs9EeuDWl0OTw+sN/qj1fbFKCCuD7hN0UmRIzg0jG7KXUHoFI83UPR6M/R44+Euyzv686eBi7pJJkyBIFVUUVVf3kp9EtERQUVVPGOzp2peMZPxyEwkGrht39/g3YJ5TBrMdHXUOG/d3BW07UksUvYF/Dhw6K2JnTJPLQlEFkqHInS2T409k41r7Le1P63utWm087axF7IVb6uHpGJLnG2yVvk3iu3NO1vrMvUTqbGwJKkklu5srzltZErmytYxWcpKMDxs7OWTlamkmQkIw7rU29mLznOLfOMJFxpZrNGZh9E6xWEaRNZuZdPr+GJwOktZytpuV8Mb29wkiN3uh98vCSVNN1jeF3xrNkRZE2i87a2jlu9TZ90bNCu9PpraR0nmNpxT6jArzjOUktitPCTyXlnt6eoiKZK81dOkKcUajt6+x0O/kE7s28ntoUjnQNoeBRgxVRiiMH05wxRmoGG6hmkWKKIxfLJrSSUNaocs1vQDKrnMbnJ1NB1MkGTAfHR4HR54yDsCCoxVRFYmGnabdeDDFEYiiLEdHdhkpfymSRsUQG/KrlaRtlF6HOumOfT011iOMmjbcz0kc5SnnmqOMYt59Z3zCS1qX2jDpyFp6o8+JxtRIoxBU02hMkylPnT7u+UazqtXWorFy7IS4nUk6Sy9Pl1mbEgSEe1jVTti5l9nd62fUQ83BbVgqdolFyjbxDitXjOoxqI3iDWZMnSNkIxh8YOCS6LYvE/HYTvNUTpy8byYFhNIfLwK0JCRBUTi8o1xHqM5ulXPTYfXN7/u4R1gbZ2cHdlNz+5Xh904rBm6cEbLqm2N89FzRvtDi3VRju2vKNTztjAZBt18zvBodJ90DiEbMyHSRwudpq3QozfwLlfpsozFgkKYZVD9iDmdnZsMvvsZtgmZCA3/SVCkDeSGZKqKiUcIbnyHaZXWMK9QNp2ysmSfRGugk6TQjXxCMYYD3gbMyHy8DGm6luueK4tO6yje8JFVFSoOQ7ueOvuDt95fMkj6X/VH2Xy7fc9qP4/mf4W4Kkk9V+ePlFxT5KBsPUiL5EqOpN74cAvHPciEjsHIf5SY/Qfh5eJ+Z27dTD65b9q69br+9ftisRXlMQ814LYk37O1qfhD/oNvqle4TFWEect4MMdEDXIbbjYQOu5N2I6166y5WD22F3PFJMNsWKxfHel7XFphuDpQFJO1Id8LFelS+VrFOtZPp19O9eCOvN57U35jrGKnf3Wa8WhtOF8zM0lGpbV2W3J38Hm1bU/RMSKaE6tx1O/2xVfVGJnPk9V4PF/U8frvPl+SrXhUxOUNOpgVy8dxzv7v41/ICEuUd7Nl2+L+X/LiIEX/IhUBZJVfylKB+l0aoE0BqwikklSTSQKwUILBxpJFJArJiTGSBKNyt0GBDGAa+g8/AO/wSaQmz+VLKc65q1Qz4wS5PYM0X32tITFDDYdle+1WX6VvmbINGZjDl+tXmixTouEDwbI8FGETUpKciXlqsuaeoIr+nHgXnBi1h8YLhVKHwZRHdzzybZxFE5mue5niuNbucVyKjnnWdQ1RjWATlvR+w0ygs34GR1+ihq2FFcpcbybbLdi0s2UifbbpZO+1a92TZhe6GczsIsSjL9dxg3KdhpYW1vgkthedIolPs+ciyYpuxi5ced3ZT48qmM7YNCH1vI0yMut4lZhvxM3XexyKmEvyzx8ISg/DEKP6TrGLIQ5E0CRdbd4NRmU6CJTu+Ct2eP6gV9r/pYID5fxH1v/Punw66K4GCZwIwQYqVn1meAHdTRPvYGz9c52c7Pzas6T2QkYYX8Kh6AsykdR2bL9f/ZPxXNUPl9774911VIKq5byG7pC57soKGhvWYH9qP+57+bh8klt/xvqHd+bHMYOmhA7QaKRKwIXIoSrPncwKRCgOs9pzFmiij+qXD3tkXf3d1O9H9WeR/0CQOEDo7GdrCx0HQOhj2iQ07EMmO8yIg1ANMROfx//h6HgqfjU2Fo7NJtHgHqPAuGOKBRU0iQyKKPUuM4ehTgGAj6FkQkSEAiq6OWn0clzXfTrQ+w7/9HOVRRz99MS1v0Cw3A7NsCDvhJhynKPXxE7nfr6NhpE6bgResWRjDm6SMwYj58jo0Eh2TNv83q7gy25mdx1Qe1HEEgRqHVkxt9DtK1IE/f4s0YGZ3kjG7SjXyf0e2frN4ii5uYX2GumI3IZHCfEGkA46SozLcyIgChX7hZZ0Hvq7pgwKo9UhKCfy9gVLHvbqlVVl5BRzQnnLLJu8wWFw1Kmw+IxfgaH0aGD1ap2/YVKHyRLfyZmliiG8NlAE2fXFmk32smeRL8nswuoTXyQrYSGlUmwzpl7Dnf9Xo5wqUPRELHx05AyHMKcD4CHVKvLCEkkykfmskUGLPmi8yX/bPNnqk+Un/fyLEl+znbLhz8V+sQnk2a86MhBCsssiOc4JmAIzxJKVsJ3nulEe7lIzn6TZHz3N/1p/Tf0Zm5Ybzf5s3IzuJWs/G3mmRe4n/BodBdqT8s858PRkGOWjqHbQqUcTFGuu7jAPqBgIv1VQjBJ0JpGxxPP3SrD/b8Yxs/P76xXigzumNjOWvHy91YFGCAEnD/d3LtOrjrAS5P4LseSfygOCa+w9ciyGlYR9X19a3ss4+NN6VRFCaYBU8e3qwyKgdU4T8ntZXuQ+FOPj9vF4P1IxOQWz6+27vNTa7y9047uWSrPD4ZKmsGs9o7RzD4FgT5VJ0Uv2VPMrtafibSQcItD0/a7hfWsQ4t8dKk5VwJ1gtrfA8XvYEBLwE6xh7acxTHsQbY905Q8xAl1xAVzfQim7+X+PbVPvDpKFLmlLiDLt7vqYnlZU27BwSp678MudZPvc+viV6ux+O3GsLXoZfk84uLKOpH1GPBtJrv1O5F9OVA1+J9ZcfdXvh4HVMtERhBHNNCZITW7iqufWunTHmiRBnNTHL/svkUCSesPE4d/V2ObkjniEq8znWJUYnXDmyOgh4a9GNy+mXnOc21/I5eN80J7Yu5mYZxEoy7nWNYekka7/oEwC6j4iQ1aD5UTW86JXpQ43fTfBFhjHyyT4u1zS/izOnIpVUfGuq6RRTmquJRQU7crx5Puo3ZlaMEYD5Wl4MyugNTM2WjdfbZtcJhSPc1mn7aX10V7Oarc6lII6vDTBhfRUrqoO2zfdT9Oy7Fe6i7oc6+Fm7FIgrO7qsNjIkSIp0nBHvf0M0XOb9FE8ahI4qIEyQky+VouDKPq3ZL3+fNqmrQ9iVTt5c5pfbz5urVkGNtcNVKx3wqcxRTDqN/3oKAojjgIwpWYgToX505IyEkbFKhFcHxujBZ8yGtF6708/Mgn2v4pvR908s5skuDsd+r7U2IkyqqqfpxKkakz+12JRKFiI/P56gvbGJpCXKS9i4w85V80sZupK6BLVDyndKV9VB6ZuNXpblmdvFz0kKw4q1H/FM9726PnxpHir9u/dIOCLLu6MMVLCyfzbIAhBu3UGd6ZVNQxjUOmHz27NdzTq4Fn0wOuKvZGn2odZ2xmtcpTk6m9ImtYj75kFPB62PyXqo/psidJzxXl67NcAOy3+z7Ofj39FWMTmTPjivia1e7atpJPZ7XY9P/Dxjxh6qqnbESwu/HBPGRPYu+wNKUYeZTKW+VB8+C1rU5DagdpUQd4aCBGiOhzTVDhns6TaL8fxqxBdq57cTXOkVucmivDj/TPW6tbd2/fWr8fVxsKHCaoVfkv07NCHUeg+NrecWjzOQoekipcmURp/x9dQtgQ/VnZLmyMA4zCPqr1VdXsIHwoUxtpp8ZEggTNS5JxmpiMxJtnxAhsjxT6EpPn6HILBAVCRxREZK0fQ6jUusTyPaQYFwoAoMw/EMBHjkBgPIXPs5DaHq7dxzwYcMDcZOCzjMZvIUrBwKAoPe2Os0hzgBvqKasEkUkJsHSHqD9onDfDrMgu4dhaxUFZNaE3B9AFyWiybD4zlmG8h7pNgcsatYr1AUEs+s9uc5yTLOjVzFjQXl02B8tQnzj8XeR5B1muOkdYa+vgeYQxo1CauJIaGFNMsbh5BycFdZCBFdy7HZzfIkxCimQhGYhq5aCKbAoPu0i0m0MdckhIeggXXZspdhT4WQ1hiUAaQWh7Mz02IHoDuMg2Blk5J0yodSOIEGBSQLTSJYOo1nKGA4kQegH6iAFIZrA9okDQuvLpuNcwUPXz9Bm4jbkttEs6cIXzhsUnYSJonojOqFZ0GiJsFIzJLPpChwgsPp9OAh7vrXGWvpNAuixggigo4myRERPEDrAqSZgcpyLOHXDlwOSZYPzBQYDM30a7kqIhvMVAnahc0F+6WKGxGIjL9xB+obtS/g3DsnKj8p3hOPEow9cKOCQPPuztiBRmeVTae5IfxQkBWEUA5SWborD1/0SFGa+9fT7LHzbD3T83PQNXZtxYFgopFGCCgHaGngJyVQB3wkykmYsEQGROqYOR0ofAcggwRXEKu0iqsCiAgMZaVhf4OA3POKqAqqIqH8ZYCh0fAuEKkFKVCoNBoQ0lrmZMAYtu8nXR2/7YEjA98oBGHAdmcMrgaBRSgaGD0Fe5LRxNWjsy7pbvHiQMk02RQepxHMDFx0zYl2lxLHUdAg2TkVCP93BOgt2lFhj0Q7AesP3ymhhKILFhFiMYgQpQoKgaaQ4SkGLO/BYw55DuyCT2iCMghwEywCHWQMnhYjo3ZjmSA59BHK8JmLoSjpQJVmuR0qdSa1Nd6BaId6ep2AzGohgDfus+YRBO84h4HkVIMh4JWUmbFWMHsEzAHu3P2wv3JEwc4cxA+4Eib0gEQkQYkTTkQHAy1xDikRKiVOReoF9tn35cdoRhxVsEtKWAwpIMyAXbxQIxZCEBkFgQEIgZ9MF+529QbwC2KvxxhYfP+DKTYTgwhzSwd41FO2u49uLhbAUMr9R0lGg8T0XoI5Hk94WDIMyqu4oYJpgaDOmxmZZGAHQ9skVWQT+r2KU5p1miTXpksli1BYU4GsUKxQyMjuBcaA8AzW38U4rVHjw6E0VVLsP2BsEPOAeF5Bqom4EsWDoNPr9ROONVMP0P4jfL43pCq+QrJOta2jc14fUMc0H+n9wvr7Aj7WZYMaYjbnIf5ObgPLTpJVcmUr+UuqOj47aPvk7YxwNShBoKJP/LCs3yeqjHBCkQ6Tnl9p3wokPpg60TAugUbCG/4z/DnwU1D8hshomihpJJBNdrFhkGAGJ99X8g61bbA/RPpbJmongcpSBGRUBTm6GoPEdCb4fj/GaRnO0VBgosVW904HnhYH6RB/BmPMCPEdB6IDCfuR3YO+UBwMB0exDoGnjo3coD/2pSN00BQIkBUdoaQdUhpIP0EjQRgM68CmRmQsocs2OFqJH3Qvgc80LaeqTj+39d/Kgdf7MuKfqfAYB29kokxFh9uoUHxZbYTJj96DcslySEips5gJAeB2uthqzDhcNAAhD6qe7zuZhJNRzhopyYxVYUK0fwqn5uAH9cDOEDRp495N2EKBD0JidD7CkxDmPRLW1dURPPyC5za/OwxsYheiBcu0i0F5Ne1GwaTtrESOFBWZYo4h8HAZymA4J9pkCURDEfO1EIEMcSuEDEUOxD+ELCcgf+wytA8KP8P+ta0ZIayFIbCtEDSgGt8ZAfmUTzokURSCArEPOUSHkhQtkbd4S0uVSwxA8dByG3rMc83uCSJUdR3ViCUsIc5WAsbSLt2NNsGUmphl4QZhKwmMSthnLAJFaxYMEArtqETMldP17Ks3ZdpcaDIZ9p5Xi2EeXIy3+sGQVtUoDYJjQiPDvOKaS1LdpthZIk7N3W+2hqfztVdkBWQRNreyKdsEWxOR6/nNhn9P8H5PxH9JRixeJ4gc0g0sCx7TxKI2QuTCZBh4KnqQNgGzEWxFKCmL5pZebsPTH5++3EueTJApKqmKteEufKM2yYBJDg8Q+S6Rl2lXKpASFZgKNTI4BSFLaGNwKSmw3H0iUIrD3XHOrg3w+1JMkA5/W3aJdxW0ty4o5jkxqIW1tbmFXKVGqRlU+u7+r5FdO4yjrJQb6cB7tp6yLUEnsGk24NjnpOHM/AkbW+LPrxf8VVQtRj7/CG+QIMF3h0feNtAlxZ0YwhaKZ7Q+YroemvT5EZGzEf5t1D7yAdk1BJ1KWrtoe3SDq1H4BAv+57+BsN3uV52w8QqhQELGROvyWaCeUJInB0JlRzeQVOeuIWC0LKKDlk5vcWFifjE89ohi0hMDVCRBaWlGkx6PHqdnONkucfXdN4/vWtksZovctoBKXILCon3I7JVIq4qsexqLNO8k/enLxZY5vT0XcSi0QtISaDDykgQjdnyY9NZpYZYH4nYCjG6cOY+dQ2xltzDnAijG+PnxGv7MQsGyMrjPMNnjc33OLDhla24CzUYB0NTOpQSVqG/kR/EjaXxz1YfXHQw4pDPGn/RyasyaxiQwoElpPWXWc0bb79BaOiNu5s3aOpujJ0Zytr67HSB9BsdpZUOwOqWqFbGpWkcRrbJ1pEsmmXjchFXNcPCDvVWGmzu+HjFFCIe25z31ZJQ9i7LR1g5oQXvu+1MPjdztePDji4CRujGm7k38rH5dPwzd42k3WY6xGGZ+RQs/ZGjNbQ7LD00A/SiTx2sbgxSg8yGBCXIoPibIz4MtyFzNnBFjcRit3ozggvA8BZOJMFMRb0SyCSAml1M8bVc8baZYKFF7yNMElJqiN7pt8Z+Syat8aggtDPBVTgPhUuOdYxomNwdNERBptPDxJSaYlZKSe94zeX2441hCo3netcbbTKdNpZWDKHJuou6gqPbqWwqQsuyEn6LaVrbpCBSWqt5HpRDYUDUn1VaC0CcpjbEKwy5di4ktFzEHbFklVgWW8b6cEmfvC7Uv328dvTh5XwLTRS61YdyMOxuyJBCiy+E6i116cPVAVYD+LbFDYBUzeAWNoEcBxVJkzNmqDST2MnaE1Es/eDFmTwelDeTcjTQyh5nnWvK1Jw7TTNdPi+ejUzl6dIiyPLXhOaf0wZUWmwaW6pEupWTfwnC9BzffPMO9uO4ImH5h5HTp0ZRduzZEJra9TxbN7GOBw0HYMcUDiblGlyz7o4gmdszSLFQ8oR725wsrwzjUTGnaOcUSxOUutStXTu5N6idVV81lQ64q4kzVFFy95RrVndEwsJJv2zlQJMhkIQiyJcNjikDWFgMFNcSjY4jgrcYrCQQ3BQR3mK5rExDEEoGyZhkXQYhsZgFIfBuajEbpkEMcxbme4NmstIfaTBZLQm2Q6/Twj5HgT82ziGGw0L+MeuToNZuAzk4Qk/vpggokERQYlmvz9AygMQJ4GQOg8Iw4tToR1v4mInFxdkSrocXLz810QK8W2ghA5TuyEIZTtwYBrdCUnUpYvvbCbGaODPf8KMvrOa+Yal/jLBbqY+AWMO3nNZyQ7TcirkYOQ42Q1u8oDebwoyjmQT6cP22FOfpx1iAp9Bnm9HIauIbSCH7wg7AyRP6Ij9BpR1D9R0Gmw6kWEK6Si/cnXkTblmhoO9QKkvkl+7jbPt3wCxMGlElRJJRAYBUAL6E0ntP1GvIAzhPtsP0ypXLR9GOYfMP7nW7VDvQyzqePs+FHT0ngYF7WAQqCdVyGzogLUMe4G7dlVo1IVIdB6fPEI79NLwZB+0xGRBGEGRRw2IOA6h8QwXL1E7dR9vlh459vhBv0+I7knbI8lu57ZYjGSoKhnIeoigc0xZ+WYSUHDYNuJMeNAFmstAaHYcnME3nC23V5eqYo3CBM3AzN7GPUNxqEmlmaoFmhriZm/MuSHgJ1cAUScCWXPD205V4qQKZIycDbs5LEgSaI0JrUDYiO9mTAy6+Xietqu8z9/GJuzOalD2oLJJ1BQjA7n6Bs/bIUIuzdZ2bbAHyZUmdk62Gw6Rq3DhXT6LhyZuPncrbXtzKM6BtFjsxkqmYLmGa16vPGc2XDeEeFWhRO70vBw4zw48u+++qfPPvSIMZ1oCjAOyQ2nNlAUiJIAGQ0jcD4QkHaNNAjECLBZIrFIqenwqxE2IAZ6AbAXYNk70GCLCIAa69ifmKUR+r8+BgKCDJ7Y2cDZHaEzBGBRvmSFCyeesPZkh+sKiSJJvAwZddfd34gHMABxQjMgxYHv9ZzwYQ8I8MFaY8kLCfvjuBu8hAxTRn1P5f9sMh+YzbHkHkSBJErxphRQ1CukU7VWJgWShOpH/IiIe85vR1znt6vaeB8y0dUQ0SSZoLEGNLBGK0pWFSwQrIUCZaYz1Gm4wJoGCIxACqIKSiBSyyKIgxViQjBEVRkWW1JQ/qxEKJgkxlGYljCn0b+RvM9NSqK/4hv4Rp5B2jT1hA8abVuQDSg8pFRC0VIRVNJgYhZQe2iUfyD+BPw/kPxjCEyANDMjTwLO6frhyEO76qJF7ZEJ0Bs6P1vqdgvUPZAhCRgECjlKA4r8QwPyYj+276/qPZ2oqwxMRuTWwHt8PIgT9MJX+ZOQOe2doWlyLFiyXjAzEYhHIiExAVJKuWG1+BoAw2CJEYzs05LqapKKMH6TBORjP+sajFWIrIkXvE0JmGvjWBj0R7s6faMRX9tP2/s0ZffVu6fw/sXhOEx+/p4gwphgbRGynp130jhB30qr1eWpz/K+mxKOGdl9p6iocmYeR+VDoOWMYoF8HQ9BrDkTVymM6q1sX9v2neeBtHvSNqK86otVC7SLRIYUKwn1umEwjEBIqnmiMnyOQ9gYE2hgW8FlClkpJ0aczKUDCez5/IrDskgc8dAuQRGMVHWWDwG2gbJwgZTpRBeF2jELJVDIdvmzMHEnRNZu21uLjuQ587GA6bbbIFFA9L28t7TsIkHgBE3W2hSI7C2g1wIEFZFSECFqROctE83LWW6Vdk99hjAWWUgDXRdDIXEIvTBqCkkGbY2ss/sDZgyAhZfKcBqGoSZt6Zhjj8zoUXLKQEwRZT8fQf50hTRKB2kE/vMKyFSVFKxtGRLGQUFKhRIsiJSADFSQnWxjYq/voQfGH9B0AyBkrngFRs6AuDYlDtiwOmB8fmO0aoV2rYrWYkWARy5vRlnv6eMjjM5X6NKDs2qjFVIkVUGtxjoMICCl7wPCwiXEkPxkYRb0KtsoPWcqTAO7GZZ6WH54cCiqKGjtKsE84YPyeXXAoH0wPrStpBZCZUb2hJ8ByPA+oNXrJJp7AFSJEDtOPDs6SCyIUcx16jkSN9vKJ+h5A2/Ks9fY/MfEz1owe2OOJxWl9cshFY1TH7vdIrE0k9e7WIPG2tXfvbS1WzCYuVDGcUXpXDjKFbHLwq4Wu99ZpFd3smM1oHdHLCsUWU1enrVZp2wW8a76d3bwbLDZOKJ4EDab1+Q2HyuXH3r1Dm+OgNIfB7yIHYB8Y6UAhADvg/7SAi4Q1BAHf6RdGQYgVAkAOHsPWG/BVD/TPH44FAYSfOeSUD8RoVSn200OjRUb4YUY5WthS2W0qWfVZTLFBRZbdkDIyQ/dL5MhD0JAFFBSQ9bDsgmGeU+aWwgoapQsWBPV5zwO8K0EDvmgQ7yeraFjRRy6L38INGpA2KhBV0B8C+jLjY8Do7KaY7/SScGHap+Oa/XLd59LuWEH9J63Wd8p0VYQ8s7VSWDBfhMSCmOowCywxpcOHLyC9BvuMXnYcJUHSsDF0b4sIksUIDIiGNU0Wktsktv4S5mhRn2FoGkTsF1qe4SFDDgdshocouut6U3GdeCs+EYCwBGRBCKqkIoSCsGCRkBYQ6t3URU/NP/xBoYOHR0JC6AdIAfNpINC9IQNxAOgIiyemiUQgiMFVFirEnknX1AdgShwXkHpQp7V7SId5DdxQsJzZm9oQRJmBhJyZeLKBDAkOePQDSZUv+wTy9eZvA/CVVEy0I8oCfpIh8CJv17d3JDrUQ/ScqHw3ncbtLuUdIUZUFaBH+XZrEuHae2GjOEIAfV8endR7pEi9QL4hc92s5rFiixGMkHgYXmBWD1BClPWaQzQX1We1UkNQUZwLZJAyMHsOESg9W6mRVEI9ghyLyaDMLDE2/SdZDM1rX4OFWxA/aw0UZo026i2yojyJD7rvqrlSZQuEQxDI1ZSuHlZzcPvpMjMGUTbJiX7pkDjLPld4E8YjQOlT1l8JfQRblyaWYXO/Gg13TUivke+YLWtFL4ObucyPioSEXVS2uzXhAh83MZSGxEsDQg4RtcfcOtPtPM/2tjl/J0ByB1QdfdlqfUMRe4HDmjref7+kAhBjGQgSAhkyABAmOPEp/HlL4d310/wQTlENo2AD7DIZiWJB0DpXeIqmlJmJNt9ijuUJ3oEnObuTdMlSlVlpVrDRvNakFeMxD5qX9UaBtSl1lBRthRgrhUtrEUYUQilVKxRtCtWbSg8BQZNSmxFiXWSKlEoVpYNSpaddcHG6IOIBALiwBxQaP+BiG42GMPHy0GOJ2RJ6H3EAtPICGwYhxhwo4ICJSsCv2OIPAeY2DiUICnKfOpew6g5DxKdJQQIFJPN9Pf6wznEFhr6QNF013IqCgsOnYFD5sXZvITjxixkcI7KsERFJLRugTmKqBVKFEXiF9f4ZlocAsBRAp0lBDSbVeD5w0ioUbv7OJdVDUY0D4vI62GoeDEpmzFjaAG0cDT9WrfBZ4W2ECMOAsUOSdMUdgkywLTnwCiZbBIRAioRViPt29yoRYGjL+2yLiIalSImgA4DrsGrp4+ByFXQ525uOSckIkOzh3KZPPgtwgwbbo7GXWx9m99u+6CljecEbZOd1Ge4tJlQk7IZICKiDVZ1KOkIdOXQqLSV6vIdmfQu/QYFjGl9YMJtFcCYzfKiBIF1p3/pVIbaiGn7iGLWwbAJSkBR17/M4FjgTp76H9EwIcidShz9YW3kJN5CmCVUWlBKRWJBEogsaQUKrCLBGIQWo2jBStgkgJx7DGm3KZgHaNUEOUqMAikHEzg4wMjUeFWwoS5v9ycxfppwtkGRGNbKK6FJyvN22zZdBaGvcxaXoAkF5gVC5HadB22I7ncsJPy4vDudtl6DpIDvxCOCWoYCH8sRRocDHBso2U5S7aM3Ho2eMNvzThHqpKMrVZtQB6TprCSbiNlXjW23o26N9f2iooEOZ00GrDRYS/M6u/deumNEQIECXoTVBAblbAMRUq0iA+5ejKAQSmdEoctYamMFBX2oci8pMMB4gynLgyRyHGtAa3d6DcuxE0FoMm0N0zA0FKQQEEUSDDVyISVsYmh2XiZM5uriMFgXlheKTPUcGi6tjWWAZqyBLhkYDe2YnFDUiiklGEqojFYJiEoglzTmhUh1clNUNLl2O4cndXYJNY67DguVmZjGbIwoSLDMyzssxi4EU2yPoO1g2Gx0w9RVBI9EL5MDPU2SyIkgJjFNURvAvHVFG8RUqvkV4F8EkB2joEKCDgCUlAUUSBBzoto06/SV2dxmGRFwOUQFRT68jLBrehkgqoJ3WUTlW+E4SFy3sqcycMNMOoAqwtgTiWC2eK4yKw0FBC7LCGTDCcxARKxmQlkRDRDCNDWGBxAmSSmtzCDcKSgmJFICIoKRQUBZFIoIMhBQYriUqECIahboUiPg3A5iBjcYsNMkdAEUG0FQ0LnSBCXxPR66CMsompOZIY/ZsCv8SK7iiJIi1qULbujXx3n95CPaO7USKsnBgEYsrUdXCl7Oyx5EsPcll7AuhQYSdgwRhJE66DuQ5ZcqPXYY0VlgJki20j5aaqL1emUTnId529k+iJ7vfoohkKxYTgwmY0JRgHGQ/O8QhqSURIkAiAiAwkWBEYLBGELREChsaCsQQWksKUK0EoGRPn1oznWsYoltYIiCIDEQSGVHHndr2NCPIorQMuNgdKapDWCHiYp+Q5Yh4xhjwq2kD6hiJo9Ged+/9Y0FRIE0kB4hfXkWuL0Uv0kzsyRUoaIeRe1aBHXQUmoRP1kYsV1w0nOmtjc5b+ueknTLkOR5y0gPZKPuUoZFtGggLtOKZCDICbswWA+xDmgjfp+RAGEUgWQzKQclwQDgaFOUcRR/sBfL6zX0kYIjsUgwkhCEYEYCaT9jtLJc7IGP2yvTgusUuXoLBTeQIh8M0wLCP3wEPSBcIkikIkFhPGhYIFlVZIFBEQArDl5yluDoChHEE3RT+lHOKZ5tIiVagbrpt8IZiN3eQdZF22foJxOblDA2HSmZsAOZwVOvaukgVEwccE9gBcbWohrDOihkQX9zGwKwoOMA5RQ0yGDIwZjrKVDNKArukKI92FFD0ydEgZmJXoj/XlobGmWhWoLK2utFGxPJUwDBxCBQYDsMpIsgB1ABxIgpuIgAUBJJNeKRPI/uP3f46fU6PuFKlcYFHGLFpJ0w7JNggMIGvpZxOpgT8jAPFEgJYgCRGcU3+5CDgXCBCGg1tsT7hZyvGPR1EhAg7cVHpFHqB7g1aTifx++zISaRGHzn3i5++3BrImgtFRQg4AJ0nqo834qoQyMUeXUVT7eYgdHiwqT0sWKLXQcTqKYlRPOlKEX1sCcD3F6izG6ZGPk9fuzI+UpLO+EL9tTM1W5CJmlI1qIZCkEiNhkwQYCW0AkBljCGkgI0aAzM5IXGgxBoxHFQ9LYOr0EA4j0H508QgWAgh9IVtl54ZPwBgbzsAgHmYliIXMJvLwZ/I82dzyPnuH86SFE49N5x1RwdkPKSYxOQCiSGVCc8lKz2nfLlp6JQ5gPqffOQHiQCPQbhf2olNzir6LImSkhEsB2DW5L3/bmQ3FJTTQH4hKG3YBexfma7bCypywhPPzmVzaT9WE0WDCGQcOU3pLhS8+4RuptTPM/Gi5AdGosujMVVQIgyAgwIgwBZFBhJIioxZBCCQmMbR59ScbPYc+G650/duxtRpyiH7ncdHWVIFCpCjZRbhfe5PMTkGG7fQXV7qbsLwLTvvXWWutWKPw39mtMWf90qurRb1+xc6ZteMqZD8yP/tWJIgsqjZGyiRtlx80zNjfyU+Vk5zDfFNp3et3E3ttTNvqA+c1QUGHsGSC0I1/cThwPpTnbIdAMAzCmgIjREsAYYxxa9zRoQghdR0rFzoSiLMesYemWgDcPl6cO4MEqYeAw9ra0OfFChiiR+Nz629XJWk9yhehJ/dBx2uqgbW7+8Ui0YrTBnWWTkY4vRLyE96Lt1XVlTg+Qn1iCRSD1yekoME04UBwK22osNgx4cC62eBiYuiKGySzpO7tBYYlR+SqD1OF8CsgoyKbwQQtH6zMxjaRQYkRDZmYSLFIiWN0NAKSCSsKyoojFHELTR0qADz6RwNfTgWWqGO5RRcZaBpoSrRKCTKzdNWNkse5cLLzLlZdvFEujZmnDaG4JAohEaNKLsNmpqaZlBAsbrAjBU2B3XLZdNVhQ3uEEyZECoYaBpGH1kYQ70PuIIXFejUcOui+GwNs5gpk15muDPogFSZgqMWBFUUTD1wOZ0aknsJCYHAILbhX5Dm7sZKZHWCCbdUzzU7mzFi7BqSqGUHw8QODtNEDfSbzezGl55Htt2NyQmbJZJs3iwRSwXMaQ5Cy8SZrw91qSQ8YSig7aaXiUd3QFeLmhxOeciqDMxr8GgnBqTYEoQGBrRXLMByyyjRN0L4ULlComn8MYdAh4fVSFBHqCTP3Pd5h4Lk9XcwGEzc6nR4E4Lgm7HBCqoKiGxMRQY9nMWaba4pPoSp3pt6OtXSEFCFsU2RkNXJTnAvAolRdvJT73hRfm2yy0xDGxidJfJIverUaYkmBQUQ7pI4KOZ7NzV0A0Koya5h+3xahxO48QcO5FTyCFrkX7qdON0O29Yy1pQSSJCK0wBzRVL0i+KAe1A/mYTtPyyDSIe4CJqIHDZSmwGBdqIgSJPBTaln4mhyhpikhGAh5qn4MN3bieiO2Tj1lrTQ+Aifp3eIbT4GWXKI/KOSHOnMSyXCRISSLEYZlEYLHRX0uIkq3DCSltUGiBBYtwZQLETXgCGAl29LUShJFkIwQrIgIQEYCxFSpLQbBSEWSEFFigUCWMoUQLBAQoDELAGCCMkYkYWfA+BIkBZFkNh2p8qScwIL5opoHovZsMDTYcOmgiBwBsgz6/sMP6mKmRj0M9/qVnG28Pqr5dm1cGRyNLHn+EfHO/ONzR8e1+c7vZGjhkI5cNQZQf4vUBnBvC+HeWDvxNkeyt8MP8T7vAoyzT+tsGtPNaxWXIStzAF/vjszYtisDEIdIff0nVBvkahmcCR4iDNWTbAWjgtOI1hJVDuWXRE137hqbDYPPiWeWUDP2YjhGTTvYqijneD5LGHytK9DtO2pKJc24X8J8Y3XLSWW+KkWblc8w7Uiec1AyjPeJVeHTKnBxKTUflT1mq+Ym2RPOGzDx4HIoqbl3oqGgn8REN6zzcsmWtCkxJSuIt4W2Yi96aDGWh6mmPFuZ1NGmTWcUrfdD7HjcGXc3MMw85p1tG8NvF41QfbjObNrbMUa2qriYrJnawNp02DxHZzDtqoda3uawoFAHP9Xg/S2+A0zcjjYQH0Gc9TckRkN0QMwP2CAeZgMkYPpRswzSzHqWOYOQH5+lNkfeTyeoFJtIe1Hn2mtYL6Q3nhrOC9UMUd1Ka2vHMY8AymzCJhj/m3ef6MvicEkpbU4OyMuN7jvp6Ocnk8K7YqpZTW6bdMUWdDrqiTiIPdemkJQqeSLjyx3ueheOJfUxGDTKpryMQAoSCMLXH17T6z82E1YBmPYn1F7DcgBQepa00C29rDVL+X5c5kGOLtJ2z7IDp0qFO+yk68vf5CE8RJrNAdJo2qbRgjcb9c0UyHpKmFnIhURjGpQVSHDKwjgCBQN7LJC2GBN6JU2TYGFLEgMCZnizaQJF3Qpjzvdny69he5MfuPpKbNh2mCSQE/F7aLntzBZRmWyD8tUR3qUNiWMZGMmkLhSpFEKyXRkJQxNHxjrE1LiO6YuqWWl23C3i7w8CI5CmRmJhRxELsDEVyoqgqtuYq2ymipVJhaDFlCzoOufEk97FdRN2+hS/AN0AHqi6YNxLBGaa6POiHTdwl5Updaw08Tz9iqa1NwxXMzaBcywSEXiqoisVY8q3YIV5cv8m1MOY5YmXyZiJMzgiHKkHPKSO4Nl4xgQLFl3gkGmwXVg+8nTCxi1oDvZIQ3+sLaHQNwxxQUN3g5wNKIgmh2G6vJQI5tYXg0dcBhrouSWBbM995fGhxqQNSKogqKxYisRYiPAqOYGB/dEwyFItSlpUgCEiCRAFhCJ1pDrhAslgMGX1LbLPcG7B2XSOt5U0rpJYDE1kpgtUREMtS0LCYWskrCFwaQAUxDCG4koHkIJJyzw9Zk9UaItS+Nj2VOCYRyh46aGRyJsgwzNM6KQZWoqWsOIkteU4mrFXVid/UQyamvx95CBrFleJJU9D8QDjRj1KyabzJ35XQ4C6OKZh8q/GxoC95Ggu2gWBi5KmBiQxTaDAaM4z7yeI7R1BG93LGUctUgB6LQvM+lnNZQROZOlip9B3JCFz6oY7Iygz2WsFQaYHt8e48tfDlunobGo9AfwIrDydGo5lZZS6o49E9boWlcPRq5fE1u9BCZvODMnZYts/jAk3YGQyXRJxRJ7aCmC7RJ+hbWCa0iLNUPh6RzfEZhnY3Zowz55VRS0HBKJd6ut1RKpRkHL+mvCWJh0wcZWNum1RYaczFakeTKKCpiG3c5gcQ0LQgs0OGEWCDMINQFzpDO7cRxRz1hijdgN7GJe1Mp7byrayIag1RxT4Fi6N0G1K23F0IizSheF8NOnbv1cdQ5VCIkhOBhWEjO87CnUqePMy3ek4LEChTjOXTDk5LAlGCG1OTIcxWV44KBxqpRqdWHNcNXDk2biGHE2BSgiTL9MRU+NVGBD4mNpqaKIVRIqfkrS4y+cvltrmBSTY8iFUwEtcyTGnY3yDszYHs87okNGrVSMuLIKdC5g3eJksInXdutGXx41oTYwQRiiMOTRqga1JgPKCjKFIiEohcwRO0powbA3EG5SKrQKhq2dFJsNbKFxuryMyWpnUvFEbeUxWjdYrWs5nKxjZmZsSwkwxETwNhQ2BNBkqjCMWGbDJRJYTQ2bhUSiWWHmIhsrPI8o0h0YwJy4hVM8pbe3t9/fuHaRCchyZDoEIjYxFgzrPXGMSamTU1ZQwiJNmEpqCU0eaEMrwQenh6zB9RibV2jMGm0zs5+GEEx3oiQjdHAl4WVPaonONjgAa1fydtOiJYgLILiGZYsN+ik3dLvRyLiuRBAthGEPmEKVKbzwNCCIkTQYZBAYsFkVlqOgpDGLMhLBPE49t5D5p5dHbqU8rvEqKtLRNymIwRcmW4BaaO5aAaBMfMHqUcI2Nfqt06oQZ09YcKIExiYo8XTKUy+gWIkWiG+IkLGp9V1xAhjcCMREsItKfJ9GZqqMb89ohwSOozyKloLXcUc8EBJwAyDycqklNEymtYbjgXN6ObBfsgjQpUESiHoilIZCgzptlalLtz8qulsOe4BjYFLCJs2uAVvGKm2WUpMZPwcTX00YuUEMe48/QKAFAoHLfYxiJmnYFYKocWGfHHsQ8Ow8jSGY8wFIaFwmZiPGjWE0EUyVFGY2SkmGrBRAjdpLF0aZcpjEeXRoPUc1v5+zeWmIPFlGRhtKH8eOhtMswzsuBHmIcAQnMSEK4tPvw85mBtQJ2sJrATrVVV5zdQIOAM/LLWkRhTk+s35FmRqr56OVyqqBxlVRVh2IUojDzEwDxCWH6slC6C4tW+Lktr4skpKEUPQ2AMDjBc5cBxqWoz7DsTNU5rljSRSQIBEYgeJZhStuShE2ARFKFwDn37Hz9/V29NVCmElUHYe54mJjfEyGjld4xClYaA1URBI3WVy5DE1LAxBTMgJkTFtsh7Dw8vTrmH3DS9VyJINCNOxLKvUbFLo+OibgCwAxQBMXhiBrViCl+KZhG75CQhFBynY8iWN4vV6hXcJzWsvOIc3KZTiRXMmCJkgnXkU20kYJBGIrCGNHsSk4/8mDACQZAQv55kB0y64geI+64GA6gHMmIvVESMD6Iiwg7ED88dCJ2AXHMGQ/3Hi8CJI0tQpaCWE8ADZ7ZP3fq+WB291Rh5koFJl6a97zYLD5KyGXqFSqMVf6+O9Ytr7qetGGiXJ0I3aHuYWxQEgd+CeIXCiPYliJDqMQwIBBmcJp2ViCLcTcdhQTCN/B9EDYDIOQZt2faur9ubTEDCQxRjas/4YBRQERYIgQUEJnUIzCBzxCGJIYWNqR8DsNvH8AhEclTTevvoKnE9PPaXC59fyCw+Yv6ggPUZ9gZ2T1kT7/RPWtv0tyDIsEKFCUHthJMp9PMV3preMTSSXR4UTqta3woyU2bbsKIexlkC9uR8YqspLuENAL3gwxnLPtl1WSsgySwo6z4C5PtmwMTEPYZGCnNHxcIQgAhUAzTAyS3qmuicnnfs7q+ft788Kvzfw1sG83IdaUSD0BuF3lBaAZUJbgRapjCfaJpdDPg+KtryPnDadXd4wugGeCmNJZgB86MVgMAZCjAKkhRnrSMUQVUJBTk8WoEAyO09NxlZBek8omf103fVoIb7vw341vvONkfeisPnVqF+BqQtY2wfedahv07HkeRO3ccSddZ6/CqGCVju8hqx7gljBxayZkjxhJVTyXUY7YhmLqVaVVuHY2S68CB7LAnc78EE36xTPFzhpCZqBpMjViIlg6FyIrp7/Cjs4nus/NCTmQ0ly07aFE/6P4GHPVhfq/GGHJ+K7emT4h3ApAzg+kT4+R8ExvR+7Ud/Isaf2H9D+wVh3fwJtg5CP3lPPW5jCg2DhGf/KHT6/3z/+LuSKcKEgxer+jgA==')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/student_sources.zip
deleted file mode 100644
index 1c7054920d7d9ebff314ff8df914324ae7c4103a..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.yml
deleted file mode 100644
index e13ff06a3ec4cf0051bbb98ec1b330e3c45ec35e..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.yml
+++ /dev/null
@@ -1,33 +0,0 @@
----
-
-general:
-  name: cs105
-  description: ''
-  display_name: CS 102 Report 2 (Scored using autolab)
-  handin_filename: homework1.py
-  handin_directory: handin
-  max_grace_days: 0
-  handout: cs105-handout.tar
-  writeup: writeup/cs105.html
-  max_submissions: -1
-  disable_handins: false
-  max_size: 2
-  has_svn: false
-  category_name: Lab
-problems:
-
-  - name: Unitgrade score
-    description: ''
-    max_score: 16
-    optional: false
-
-autograder:
-  autograde_timeout: 180
-  autograde_image: tango_python_tue
-  release_score: true
-
-# problems:
-# - name: Correctness
-#  description: ''
-#  max_score: 100.0
-#  optional: false
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/docker_helpers.py
deleted file mode 100644
index b4b885526bfe90b86900afb241496de2c7c84aea..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py
deleted file mode 100644
index 3542e09379b7aec9fa34126730ad9a5670160778..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py
+++ /dev/null
@@ -1,87 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py-handout
deleted file mode 100644
index 3542e09379b7aec9fa34126730ad9a5670160778..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py-handout
+++ /dev/null
@@ -1,87 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/homework1.py
deleted file mode 100644
index 18576f18162b3e965b483dc0c9f2673d29b35a2f..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/report2_grade.py
deleted file mode 100644
index 7484d93eae4ad3d81e212ea0c2a5c8561c1761b8..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/student_sources.zip
deleted file mode 100644
index 1c7054920d7d9ebff314ff8df914324ae7c4103a..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/Makefile
deleted file mode 100644
index ea7c9d2e41f6b768d3fc89ab2f087c1bdcdecac3..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/Makefile
+++ /dev/null
@@ -1,51 +0,0 @@
-#
-# Makefile to manage the example Hello Lab
-#
-
-# Get the name of the lab directory
-# LAB = $(notdir $(PWD)) # Fail on windows for some reason...
-
-all: handout handout-tarfile
-
-handout: 
-	# Rebuild the handout directory that students download
-	(rm -rf cs105_new_version-handout; mkdir cs105_new_version-handout)
-	cp -p src/Makefile-handout cs105_new_version-handout/Makefile
-	cp -p src/README-handout cs105_new_version-handout/README
-	cp -p src/driver_python.py cs105_new_version-handout
-
-	cp -p src/student_sources.zip cs105_new_version-handout
-
-	cp -p src/homework1.py cs105_new_version-handout
-
-	cp -p src/docker_helpers.py cs105_new_version-handout
-
-	cp -p src/report2_grade.py cs105_new_version-handout
-
-
-handout-tarfile: handout
-	# Build *-handout.tar and autograde.tar
-	tar cvf cs105_new_version-handout.tar cs105_new_version-handout
-	cp -p cs105_new_version-handout.tar autograde.tar
-
-clean:
-	# Clean the entire lab directory tree.  Note that you can run
-	# "make clean; make" at any time while the lab is live with no
-	# adverse effects.
-	rm -f *~ *.tar
-	(cd src; make clean)
-	(cd test-autograder; make clean)
-	rm -rf cs105_new_version-handout
-	rm -f autograde.tar
-#
-# CAREFULL!!! This will delete all student records in the logfile and
-# in the handin directory. Don't run this once the lab has started.
-# Use it to clean the directory when you are starting a new version
-# of the lab from scratch, or when you are debugging the lab prior
-# to releasing it to the students.
-#
-cleanallfiles:
-	# Reset the lab from scratch.
-	make clean
-	rm -f log.txt
-	rm -rf handin/*
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde-Makefile
deleted file mode 100644
index 132cbaf68c797bdeafa87c17fa6fab2e1c41bf78..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde-Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-all:
-	tar xf autograde.tar
-	cp homework1.py cs105_new_version-handout
-	(cd cs105_new_version-handout; python3 driver_python.py)
-
-clean:
-	rm -rf *~ hello3-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde.tar
deleted file mode 100644
index 0b7539927b932f17726ef3659895ede0fbd31807..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout.tar
deleted file mode 100644
index 0b7539927b932f17726ef3659895ede0fbd31807..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/README b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/docker_helpers.py
deleted file mode 100644
index b4b885526bfe90b86900afb241496de2c7c84aea..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/driver_python.py
deleted file mode 100644
index 49a443dc051e8c745c096b613cb0ddf4ec262339..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/driver_python.py
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.version)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/homework1.py
deleted file mode 100644
index 55f96f90371e3b69cde9e6abaebe2a6409993f3b..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-2f101f3fc3a6837d2244a450e165b31acda8a83d0af230ab51bcbadcd7371e88f4329f4d3366ebeeec5cb1e10738a3729b108fd880bd278f54477e5e003a15c2 31240
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/report2_grade.py
deleted file mode 100644
index 2f3e2d766a3dbd871523e373f4420ee5921da44b..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/student_sources.zip
deleted file mode 100644
index 9d307cc1b71b8470bf731a5ae210cc5d8471f22a..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.rb
deleted file mode 100644
index 7d5b5b88f6484d3cdfc01aaed8f758dbb2094e0d..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.rb
+++ /dev/null
@@ -1,11 +0,0 @@
-require "AssessmentBase.rb"
-
-module Cs105_new_version
-  include AssessmentBase
-
-  def assessmentInitialize(course)
-    super("cs105_new_version",course)
-    @problems = []
-  end
-
-end
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.yml
deleted file mode 100644
index 25461e45d118a5da0610e1f7283d6f53d9ca1e33..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.yml
+++ /dev/null
@@ -1,33 +0,0 @@
----
-
-general:
-  name: cs105_new_version
-  description: ''
-  display_name: CS 105 Report autolab v2
-  handin_filename: homework1.py
-  handin_directory: handin
-  max_grace_days: 0
-  handout: cs105_new_version-handout.tar
-  writeup: writeup/cs105_new_version.html
-  max_submissions: -1
-  disable_handins: false
-  max_size: 2
-  has_svn: false
-  category_name: Lab
-problems:
-
-  - name: Unitgrade score
-    description: ''
-    max_score: 16
-    optional: false
-
-autograder:
-  autograde_timeout: 180
-  autograde_image: tango_python_tue2
-  release_score: true
-
-# problems:
-# - name: Correctness
-#  description: ''
-#  max_score: 100.0
-#  optional: false
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile-handout
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile-handout
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README-handout
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README-handout
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/docker_helpers.py
deleted file mode 100644
index b4b885526bfe90b86900afb241496de2c7c84aea..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh
deleted file mode 100644
index 05a006e95e416fa5d5088f1d61479f73901588c2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh
+++ /dev/null
@@ -1,33 +0,0 @@
-#!/bin/bash
-# driver.sh - The simplest autograder we could think of. It checks
-#   that students can write a C program that compiles, and then
-#   executes with an exit status of zero.
-#   Usage: ./driver.sh
-
-# Compile the code
-# echo "Compiling hello3.c"
-# python3 -c "print('Hello world from python 2')"
-# python3 --version
-python3 driver_python.py
-
-#(make clean; make)
-#status=$?
-#if [ ${status} -ne 0 ]; then
-#    echo "Failure: Unable to compile hello3.c (return status = ${status})"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#    exit
-#fi
-#
-# Run the code
-#echo "Running ./hello3"
-#./hello3
-#status=$?
-#if [ ${status} -eq 0 ]; then
-#    echo "Success: ./hello3 runs with an exit status of 0"
-#    echo "{\"scores\": {\"Correctness\": 100}}"
-#else
-#    echo "Failure: ./hello fails or returns nonzero exit status of ${status}"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#fi
-
-exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh-handout
deleted file mode 100644
index 05a006e95e416fa5d5088f1d61479f73901588c2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh-handout
+++ /dev/null
@@ -1,33 +0,0 @@
-#!/bin/bash
-# driver.sh - The simplest autograder we could think of. It checks
-#   that students can write a C program that compiles, and then
-#   executes with an exit status of zero.
-#   Usage: ./driver.sh
-
-# Compile the code
-# echo "Compiling hello3.c"
-# python3 -c "print('Hello world from python 2')"
-# python3 --version
-python3 driver_python.py
-
-#(make clean; make)
-#status=$?
-#if [ ${status} -ne 0 ]; then
-#    echo "Failure: Unable to compile hello3.c (return status = ${status})"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#    exit
-#fi
-#
-# Run the code
-#echo "Running ./hello3"
-#./hello3
-#status=$?
-#if [ ${status} -eq 0 ]; then
-#    echo "Success: ./hello3 runs with an exit status of 0"
-#    echo "{\"scores\": {\"Correctness\": 100}}"
-#else
-#    echo "Failure: ./hello fails or returns nonzero exit status of ${status}"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#fi
-
-exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver_python.py
deleted file mode 100644
index 49a443dc051e8c745c096b613cb0ddf4ec262339..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver_python.py
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.version)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver_python.py-handout
deleted file mode 100644
index 49a443dc051e8c745c096b613cb0ddf4ec262339..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver_python.py-handout
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.version)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'homework1.py'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/homework1.py
deleted file mode 100644
index 55f96f90371e3b69cde9e6abaebe2a6409993f3b..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-2f101f3fc3a6837d2244a450e165b31acda8a83d0af230ab51bcbadcd7371e88f4329f4d3366ebeeec5cb1e10738a3729b108fd880bd278f54477e5e003a15c2 31240
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/report2_grade.py
deleted file mode 100644
index 2f3e2d766a3dbd871523e373f4420ee5921da44b..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/student_sources.zip
deleted file mode 100644
index 9d307cc1b71b8470bf731a5ae210cc5d8471f22a..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105b/Makefile
deleted file mode 100644
index b12dc571349b4501f1e9bc7b1c45858ad52b484f..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/Makefile
+++ /dev/null
@@ -1,51 +0,0 @@
-#
-# Makefile to manage the example Hello Lab
-#
-
-# Get the name of the lab directory
-# LAB = $(notdir $(PWD)) # Fail on windows for some reason...
-
-all: handout handout-tarfile
-
-handout: 
-	# Rebuild the handout directory that students download
-	(rm -rf cs105b-handout; mkdir cs105b-handout)
-	cp -p src/Makefile-handout cs105b-handout/Makefile
-	cp -p src/README-handout cs105b-handout/README
-	cp -p src/driver_python.py cs105b-handout
-
-	cp -p src/student_sources.zip cs105b-handout
-
-	cp -p src/homework1.py cs105b-handout
-
-	cp -p src/docker_helpers.py cs105b-handout
-
-	cp -p src/report2_grade.py cs105b-handout
-
-
-handout-tarfile: handout
-	# Build *-handout.tar and autograde.tar
-	tar cvf cs105b-handout.tar cs105b-handout
-	cp -p cs105b-handout.tar autograde.tar
-
-clean:
-	# Clean the entire lab directory tree.  Note that you can run
-	# "make clean; make" at any time while the lab is live with no
-	# adverse effects.
-	rm -f *~ *.tar
-	(cd src; make clean)
-	(cd test-autograder; make clean)
-	rm -rf cs105b-handout
-	rm -f autograde.tar
-#
-# CAREFULL!!! This will delete all student records in the logfile and
-# in the handin directory. Don't run this once the lab has started.
-# Use it to clean the directory when you are starting a new version
-# of the lab from scratch, or when you are debugging the lab prior
-# to releasing it to the students.
-#
-cleanallfiles:
-	# Reset the lab from scratch.
-	make clean
-	rm -f log.txt
-	rm -rf handin/*
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde-Makefile
deleted file mode 100644
index f07ac0d3757170e32ab3584241fddea0825b44b2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde-Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-all:
-	tar xf autograde.tar
-	cp homework1.py cs105b-handout
-	(cd cs105b-handout; python3 driver_python.py)
-
-clean:
-	rm -rf *~ hello3-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde.tar
deleted file mode 100644
index d918a132bd4f491b2df40f93a4a19b87efd9d7ee..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout.tar
deleted file mode 100644
index d918a132bd4f491b2df40f93a4a19b87efd9d7ee..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/README b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/driver_python.py
deleted file mode 100644
index 78e248e085b8de1a55f12d412520bc828dafd5ac..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/driver_python.py
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'Report2_handin_16_of_16.token'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/homework1.py
deleted file mode 100644
index 22d3556a6adf524702c6829e95415abcb0e5aaed..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/report2_grade.py
deleted file mode 100644
index 6a3e210416d3f1d38a3d87397ce71e63cdcc8c4c..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/student_sources.zip
deleted file mode 100644
index 7256169a6f823cce5b36856a58c7d94cec8c8d79..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.rb
deleted file mode 100644
index bc7d741ac450871b0062ea2121915feab1d1c057..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.rb
+++ /dev/null
@@ -1,11 +0,0 @@
-require "AssessmentBase.rb"
-
-module Cs105b
-  include AssessmentBase
-
-  def assessmentInitialize(course)
-    super("cs105b",course)
-    @problems = []
-  end
-
-end
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.yml
deleted file mode 100644
index 9c5d9f56c3165485281e508c4bd3367f56f5d91d..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.yml
+++ /dev/null
@@ -1,33 +0,0 @@
----
-
-general:
-  name: cs105b
-  description: ''
-  display_name: CS 105 Report autolab v2
-  handin_filename: homework1.py
-  handin_directory: handin
-  max_grace_days: 0
-  handout: cs105b-handout.tar
-  writeup: writeup/cs105b.html
-  max_submissions: -1
-  disable_handins: false
-  max_size: 2
-  has_svn: false
-  category_name: Lab
-problems:
-
-  - name: Unitgrade score
-    description: ''
-    max_score: 16
-    optional: false
-
-autograder:
-  autograde_timeout: 180
-  autograde_image: tango_python_tue2
-  release_score: true
-
-# problems:
-# - name: Correctness
-#  description: ''
-#  max_score: 100.0
-#  optional: false
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile-handout
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile-handout
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README-handout
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README-handout
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Report2_handin_16_of_16.token b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Report2_handin_16_of_16.token
deleted file mode 100644
index 22d3556a6adf524702c6829e95415abcb0e5aaed..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Report2_handin_16_of_16.token
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-2673de03a1dd2c7cce073a5f05532ee5a90d5af1632134c954b072b79e128692ee64f95183249b6e9750be00390bedc51d1e021825a6da9e2d0ddc6e5780534a 31232
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh
deleted file mode 100644
index 05a006e95e416fa5d5088f1d61479f73901588c2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh
+++ /dev/null
@@ -1,33 +0,0 @@
-#!/bin/bash
-# driver.sh - The simplest autograder we could think of. It checks
-#   that students can write a C program that compiles, and then
-#   executes with an exit status of zero.
-#   Usage: ./driver.sh
-
-# Compile the code
-# echo "Compiling hello3.c"
-# python3 -c "print('Hello world from python 2')"
-# python3 --version
-python3 driver_python.py
-
-#(make clean; make)
-#status=$?
-#if [ ${status} -ne 0 ]; then
-#    echo "Failure: Unable to compile hello3.c (return status = ${status})"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#    exit
-#fi
-#
-# Run the code
-#echo "Running ./hello3"
-#./hello3
-#status=$?
-#if [ ${status} -eq 0 ]; then
-#    echo "Success: ./hello3 runs with an exit status of 0"
-#    echo "{\"scores\": {\"Correctness\": 100}}"
-#else
-#    echo "Failure: ./hello fails or returns nonzero exit status of ${status}"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#fi
-
-exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh-handout
deleted file mode 100644
index 05a006e95e416fa5d5088f1d61479f73901588c2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh-handout
+++ /dev/null
@@ -1,33 +0,0 @@
-#!/bin/bash
-# driver.sh - The simplest autograder we could think of. It checks
-#   that students can write a C program that compiles, and then
-#   executes with an exit status of zero.
-#   Usage: ./driver.sh
-
-# Compile the code
-# echo "Compiling hello3.c"
-# python3 -c "print('Hello world from python 2')"
-# python3 --version
-python3 driver_python.py
-
-#(make clean; make)
-#status=$?
-#if [ ${status} -ne 0 ]; then
-#    echo "Failure: Unable to compile hello3.c (return status = ${status})"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#    exit
-#fi
-#
-# Run the code
-#echo "Running ./hello3"
-#./hello3
-#status=$?
-#if [ ${status} -eq 0 ]; then
-#    echo "Success: ./hello3 runs with an exit status of 0"
-#    echo "{\"scores\": {\"Correctness\": 100}}"
-#else
-#    echo "Failure: ./hello fails or returns nonzero exit status of ${status}"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#fi
-
-exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver_python.py
deleted file mode 100644
index 78e248e085b8de1a55f12d412520bc828dafd5ac..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver_python.py
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'Report2_handin_16_of_16.token'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver_python.py-handout
deleted file mode 100644
index 78e248e085b8de1a55f12d412520bc828dafd5ac..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver_python.py-handout
+++ /dev/null
@@ -1,92 +0,0 @@
-import os
-import glob
-import shutil
-import sys
-import subprocess
-from unitgrade_private.autolab.autolab import format_autolab_json
-from unitgrade_private.docker_helpers import student_token_file_runner
-from unitgrade_private import load_token
-import time
-import unitgrade_private
-
-verbose = False
-tag = "[driver_python.py]"
-
-if not verbose:
-    print("="*10)
-    print(tag, "Starting unitgrade evaluation...")
-import unitgrade
-print(tag, "Unitgrade version", unitgrade.version.__version__)
-print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
-
-
-sys.stderr = sys.stdout
-wdir = os.getcwd()
-
-def pfiles():
-    print("> Files in dir:")
-    for f in glob.glob(wdir + "/*"):
-        print(f)
-    print("---")
-
-handin_filename = "homework1.py"
-student_token_file = 'Report2_handin_16_of_16.token'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
-host_tmp_dir = wdir + "/tmp"
-homework_file = "homework1.py"
-# homework_file = "homework1.py"
-student_should_upload_token = False # Add these from template.
-
-if not verbose:
-    pfiles()
-    print(f"{host_tmp_dir=}")
-    print(f"{student_token_file=}")
-    print(f"{instructor_grade_script=}")
-
-
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
-
-if verbose:
-    print(f"{token=}")
-    print(results['total'])
-
-format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/homework1.py
deleted file mode 100644
index 22d3556a6adf524702c6829e95415abcb0e5aaed..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-2673de03a1dd2c7cce073a5f05532ee5a90d5af1632134c954b072b79e128692ee64f95183249b6e9750be00390bedc51d1e021825a6da9e2d0ddc6e5780534a 31232
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/report2_grade.py
deleted file mode 100644
index 6a3e210416d3f1d38a3d87397ce71e63cdcc8c4c..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('QlpoOTFBWSZTWdsoDegAVWL/gH725FZ7/////+//vv////5gZR73vVe96j7xe9MQfLe77e9e7ddUCgUXRqUK9jUe9ugVTovXuHFG8++8PXts+h2UzbQvZl0DL60Cgevb3e++vfPb5pp123ns08fRykAPe99TfXfcc7sPPpWyR9t2KntH301Xc9NV7CT7y7Z0aPNdaHaaKS6Odju5W63Lu+dLke0b7y+lAAr729G4WvuNtr7zdZ9dyghV97jEPvYq62y87jtjfbiUdPt3y8Q5vc7bu7rsWj7r405n1qG2hvu0OiRRq33d2exp7Ht2j4vKdq02GUt332+z1y9q9z6zfZ5zT7ANXnz6LxYy9273mN2c+fduz5rZrWWptfY3bz7PMJTRAjQIAmmiaJgTJMjUejKaJtDRAPU0BoaANBkYSmgQQiaJoJqep6p5pU/EiepiPaoBo0Gh+qAB6jRoxAAAlMSEEIUxU/1NU/1INqNR6np6pp6ntSemJNAeoAAyZGho9Q9QaNBJpJCENTJpkCaaTTTRpoTTTUPUPyp6NR6n6oAbU9T1NAaANACJIggAho0mmgZJp6jRoQ0U/VPCnhT2qeU9T0n6jFD1NMmagHpBISQjQEyAJtT1MTUxo0mFPTEpp6mnpPSeU9Tamg9QekaNqGnqB0ofugvkHuKBUCiqVf4kU+eAij7hSQRAJCknzqLFVFT/98/xwuqhpPp/1uFL/ZDo/Cr34R/BZk+n/J/iFYxMXT/ic3xm4f5/84JFK6cJ3LQmSEybx/Frmf41YvVx1zl8czTd8K3FR911qDLQ1RFmeaG1tXmUl3q9dOLHHnFRAsSn3+vJHV6gZcO6PG3K9YzPPm7NKhSjK9COIzsjlDJSZncxg12+WH5j5S8T5Pp57IEvo6vtvnv6TiKf9ZzpOTulsv4leWHnZgmPLhuNNzAzMMH/nLHHpMAREE7AQD5WIsgSCSJICJFCRZFJJP1ElFRYCCr9ySyqI2/ygFKbSAilJAAaolIDBAgckDjhg6OMSQG9H3vRXrb6026N++3ZpfE78DXQnvTtJ7qgWUFWCQVZZGiqgop+thQYioCqQVBkY22xDdSCT/Hh/6y68Tgy4o+zgG9Gs8lcX8JkyZGnwjfyj625WUChTy5zsF+Di0upJA7zQ5L7Y7Z3OfHU6LYepso0iOadDt0lbblOedDWVFVEPrxyg7dyDqmuOX+m33q99al0NVERFMjI0bLTBjHddrP3msovHejlNP0vZlQ9dKdjn+bH///NWtOfp9keO4ceOJxk2MZSDm2VG/njJIr/ZNmn/h0th15w48NWu9onvh5SuXzQ7vKp/9p88NQvzxTWaTSdT64PzW8YPzwnpWLS+NeX1r1dKXkIurqQJrCHTa++DKZWz/3XiEz/ZjpfGR9zvVnD7cMjy5CJtkEg9/tGq0ndcuXPMvnGDQMUaj39bXZpGfjdVoYe2aCFwSNkta1UzI+sGUzFl/bn7+WdBm4Djsq9nV1W0jVK+ZN8u81K6mp5N/QlSfX35dfHfMfy7Lddn1k0xww2dYuhOn1fd/a/LByptVFtXNopF6wZMTd2OaClH+dHppsTgVSddJ1xyKaTb718zJ9v3+tjPfjru3lOuN4DZ9tH/s7EaSrK5sJcuOeuWEcrSnWPBfTOdKWe2bUxHvy1lxrKTX5J+BLbPdxvmamPjLNRVyKbdZwZ06UwpymY22hLznl3tWin3ootNIvSUuUbFBv98u3MpNGpg/hpV52Pfr2kxjOJL6179mFrEMcabvxJDeuohaSNPxmI7IXeMGrLmTC5lOSpnze1td/T9qOqbSUJ3eqrGKONi9LJqvlPJMTH8Xgqm1WSFL0FhLgD5Fvt4iuv3dReWWsv2MdXvgylqVjuJc2MosDi4GM8AOwEm5VqvXYRVWV+lnUaKb1yucBIvqu/28DObZCGQnfTcF83QISXOIeAeE+ZjkRsrRlJpFIu50NmdmjemHU4DeO3X9lnaFm1kiEQ2nx5NuS9I5Fj4IS0CSQkCbVcR9GyZqZ7bO9BnmsL4uhWTkhOp1Q8OiqwgBqa92beVxYIRBpKzWdpHp78fbpjGbyhvQxtz5w+a8WnDOBhpktMJgYM7sz4O003rB7dfgqwcwGAxWLr4oHZ6VejT8OC5O7Nn571w2sSuBOyAxsuMvq8mv9Mn1vFccHUELyyE+LLt7SOkHGv9ciQm/tBboLsVuPsb5id0pcbxDLmpe2cw0hmAz5ygz+bkAgijSKHF67W1l15zasck/Rt9BtaLC+1D68JEsS4mo0h3X0nlizU35j2fP43X1+0fzdwVDwEcRbS47HBBvv3freNTqOutklzcTjnhGloPre3TK8qYLA0E1oTGI5C/ubN33UL5wFp5loDI45dutd4xlxHy4MeVYR34U+4irr+qkIlyeDXN2mcnO3R21saBPU68nrw4WgRMX+rhUXwwLUuOOUKP1/LKV5139WLqjcbmqaLCOBh73KEEuFyP68DJCpLfK2/TnAeFo35RHTg9YcxjD+F/gW/4ZZTy22FYEddcr46AdOhTZ6c20/Tt9yghY/AdvT94TiRiYDbjWMmbhNS0CRnRiZAdybG0BhPgcnE3tLloNxGeGR+fVnjEtVnaDogcLGDM2cT0KVL1vrrx3pLH1+dnkabZYSYCufjOM4I6YRoyZME2DWR4ENIWaxPyJNihWc40YO3lPhGiztV6PmcziUcdocwZc9x95twjcCpRcMRQ/I02ntBsE2rDj+RIi+w+8cFKs43i14UpcSEhYGVR82Loxq1RdDDTB16TqWMTrF9MTUuaH2YXSSGZCSDimnXZPYehJkU1FlpTi2CCuPfDrEka+zLQ07vw3o5447wWyyZUPzfbMKo239uXJ2SEQ6+8XVRJpMmmCXO0hM1A8P4PnxZZFRvgNXUxgJRT+zjv+Wlbb8fqsSOS+cTTdq2o08o2lJjA5j8eR8YOdtDfoZdmq7J8XIJZ+BP8ZSKaW9GyI2mH6WwJn5e37stBzQPMX3GhnbMq1E1YMPyNt+/AedD8XpR1wgr4euWmNetyHMO0t8QgdfWmqCj2SDtug8jre+2NqZmJmhnxw5J+wEz6HYKJtno2OlLDVdPvSSTXj214y9lfCdjicLMOC7m7LPYzpswRj55PbUr1xGJczUtwZQfsc1WJoxq2NF4JPX7bxli4b3aUbkzMfdUBX3fp4ynd+v5t9LOiNbdh1FfxW6JA1i5wGvksvvpfuSie8wc3I9oQz8PtePlbcbrzOG2Pluua4W4PlHiOWaFJw/Wuoium7WvxlMijdDbjzj36Nlz5TdaWM93hBf5dd/iZnQNDPccjgRdZFXbp1dmMKr94X6b5Y35HQxbGjvV6qR80drU/PsYYU7VS07cArpYuaTr2o7MDcp2PhKiShyPvIsqjogEW1RIvOXKEIQSEzLkqNS4Z6HUo5zTdF5Ie02OOhupwZty7036a6+T6RyLlONwNeHN/E3O0jShZMKkjcq12LG6/nEjJmE0joGR/B2dp+r4nw1QTfecDoiyHykpIdpAQOHadJb+VOZFRHQpwvgWy+46TM8plA0Hu5fuOBxjZjZslX6zB2WhRjtPAiGUl+1yssSZDHcH7kf1KqaVIqdcdjftQK2TLiDpJCYj8llFGDaSopodJggsUa2MX92daN+z0oMPV7XS+4LQ353DYQFep0P8/PeRvPsdjB4BYW2rJubLDsjUdzyOTI2N3w21sgVx0VXLfQpsmb1E+MQRAjjjK6zDafzeisaDIJhDE5iKlqEBwzUEUNxzkFeJWCK11yuxMs0kmasHFD5O9mxtb+o6jRMPb/V3P3UEmhxZ5znymNrR2F4VptfLOE7oyFPf4m8qG7jBkpEY3CksuJtoS1c1bUqSqpbOkpk3wsGeRLGQ9usb9sA2O4jHS5bSRJg3o/MafArtlQ378skhJ2yehKSd8g6Ui2zhpYs4BlmMuVsLbi4lzdjdWKSwsIxQiXQSQpX2lvkkyPLntHdzpNV50lRWIjU8La0vYc27x5ZaB4KoiorIEmrpJ26FeVz5fqHNEWj3HD0Zmi8vaXizxZaPR3Y2nF5eNes7yNq9789sK9jwuNW2BBxwbTTOlLa5akVwauU2kyGEFtoXDGQ7qUTzJv9FjzQ9+GfKZSjjrEOxu4S0LoomRgO6gjMThuiMwqIyqe9zKYPgH36nKeOYLqy7a9sb4EsOSrSnBZTiLE8W4lR4Q44UYrIqPrIs8pygy032r2vd+UaWCv1SrnJG72Qwceedyz60w3SqQmBw4RNVeTm/Vp1ioUbQthWY/mqf08stOLvJWnedY9XigmzhizB6dB/b+o8iHRXwRIHetx0g1MZQdUWCbCW56licIrwNbrWIes8RnTcHZr3ny8rxedfmpstRTnJhuppuqIjzEYjmfLHErob8tbVuwnRlhM9Y/1Udi+mCsSY9ZY63lgS/g0lxPLLgjuuCamPthzntXj3wRg9MInjjSnjlLdoO2VfaDZxP6LlapsjTunAadaGaVzg99xkyS85scfJnNwp0xM2+cifE5FQzEICAq2SFlXiKDBkYnTX300PdBU8RHxNWHYDj17S/hW9L1gfh+mRX2bdmLcfL0tu48ohvRfrt8j57x2BDmQ5CheAj1Aj9TC4a9EIXrEWQ74c67b9WbDYWWV+DlvIViAyP9v+GL9B5mwejbdgm79w4+G5aMVoNi0+ixYhCEAjGxNodtEhqWYgVfhMNXg9E8due+KcvlT0Nya/RlnkbIXifYMNdU7OPA+Qe+2ev5GtT9TYJ8VhrpEv+X6d3Dg+9Zeb4Tymo/ZvrKVnyww9b2rWvGzxS9JavL5PlPDDK3pLC2+z29v1YVSzXWmsGHtZHuBwcbhIdvUiBZhkF7s2czt6SnzHX28IEJ484w9745BrvJEB4fyz+q34Y5ePf36XJ5vX7Yznvr9m7a1J87+WWnN9+tE02t7Lx7pz6epyZShlx+HmoxZC7DoE55b6L8VNQKwii1FqHBbIZGKVHlVBtgfi/yaw1fuMlzgyDxTCKxUc59bU+CHXyTGvDaDlwj9WXDXT5vh7EXWCOf/PXU28M8zR0ZqIzq4zMuDkFjPIaKrNOsWsb5FhkTTokTI5bdQwTqfvSLIfR80uKysBXioV0ldJr91mn+G1/c/wGG/K3V4cdbywtCSVIFj2byWJfk/F+PpkytxaE1twqiUnqMVB/RvBNunayekYvQ/0rO5jWCsNCaZ/hw6uS7lQW4905YroeWpVDkG8kfwqVQkmdCUoi94ebYlj++60TzAeoo/UfF+xxLGBSfkMSk8fLr/V94HXn7h3d/nteINjAlxqpCwGNgiVj9THdEDt4Pu1+g5nj+j6uaIqqqsQO9IHTpy5lezfcVE9IyjIoqqshtxYBwhxxtiGejwcwNCz8aopBQ+uMleipWY22W2VbYxCrGQqslZVjJKgoVfnbISQBIOnzbns5LidBu6OpKVHISAP8X7ZwaJNMmz4JNgSbIRFSTSHotdFJRfgTgJAszZOhMxSZ+22hiCvyjz90P1dvOJf/NznNK3+7HYaQ2N58DaFt4jbGkE8UmIGrzTshsrC6bY7/aw/stXa7HLL07q1KmYrb8qFurgot8YV+jyYLuZ/KXMZzDJRlzGWi1VOtU5FREWklcO/b5BZZ+8xgUHt9W+aMWqfqzwHkv6Ip1WJphqQIcCTIaiSJYfiRm5+4MnXiyMGj6BE8np1g0ZHwYFb3RSgvrFS4lUHvLBEnpM3lDJqmGaE2YQ3vNyrlK3D1MSuFIYF2NuR4CxDvM7h3dty6fJm9D1nz+NwSZamgNGjsh4uCAgxDJxjazTyISbKtNAWd2LRkNBDtVIuMQ+1bOtvnqzrpIpOncp8YoYcHoV+U8+DWuXBFWNxu7GxgZ4CsZkFSX+MRmF2R7t8MvYWJ2cNrNdTJMIQzyFdbfy5CWJgzuJQ9M8q7mXxMJvVt70e5XuF2EiojY8S3Jr3LWd9YhpIl0eya6vWiiGR4F03dOUc2z189KEsLwWITmEUJyi8mm25a0ptK0mp6pvk7pp3UiHziJn58CdphT7ZjvjtjRbTe6KCCNXHGC65IHyWY7OSQe0gz7RfDXmjb3TSOg3+AhKR2e2S/n/D69sHh02vt1yZV/gTNM2055k/Pbkt9Yu7/Bev3uVfPzx9VOvvpAtl5w/ST7JSksOi2VFWPsuSik6+b3Qk8uv1v9+pzx/Xjl9HpHyl0wveUcH6B7Chwl/RrHWZ49Z+hTOMf0M8dJUyqYqvqvjDzLHQh+SkPOwXem03n3c7JuvGIvp33XNM93N4dLBDpii0F+gWqh1v7B7JYk/YvYryuP3+zmw9JZso7V2ahPciHliSLFOMrQ+TweL+fZ8ivXjN4nmtPFULqWCsZiGpS/XMup/W/7Kzs3cpLzeqOPN379uPHjOtLnwfnk2BqMMCzMu2NosQigWLvJbVdL1HIQvhuJEcJedaRRjewm3nMc3auQEGEUTRN2L48c7yFMnV3hKaPVZL3Vke5PzdbbRhlOAxL2xk0r9nmZvVbrKqnjr6TIuKfp67PM2janihQxEOyZ3QipmcUNHhDyhIdyI4MzXNDvnUORS9dXHksSeqnJ26ynSe+2mEmz1ygl5wVxvmzIIMDqRlm2P7umNuM+ezw8ekaJ38t74f5d7NYX1Y0vU9Z9OGk2417c5w85xElpx+PpFbBOlpKy1XlR9w9q2ccw6T2lNS+TkLBPb92l54041cp44RJHq2x6SPPJuK+K53HSNamIso+LypxrLknVZRy9WJBWr9tHxpnOErym8Q+6Xoo0eaxSwgsvSeVsfSs7rmpet59L5eUycX04FZmDxD7VtKUP0iUSyfad71Lv8I+HSuF1ysTylyKzWHseLTjOW0HkoVOT77qHdECdfLJ/R/HKsZJ+NcqU6b59MHnhEVTxmfhBPZ+4i5w8Z3r2Xf5sxmZuaqHw7ye343Jxfyxvs953Faz3IXx25lAr17uO9k8Itf7nmXdISCeu/eCh8ubcuM8dAjdwgBJpE+B+BJhvovlhVh0FiBdDOEJLq1DXzsCbIuZEkciAwgx55T9Ut3pWKJe2JEBXlPw2+zyYMQaOaR+/kNdMSE6A39TpmTN8OPOZwgvX2Z9Lki9/KSPjwPgVjjuT1cWUzBAe5X6NZNiI1kseSwg/qjU+O88DP/p4a8F/8T8H4GHZvkiSfjfVjkoenDy3rDCXSv0glN8Rr4+6RE91QJS3VKdJ9gp87hXdoS7Vp99q6zfNjno5vrQrpzPs57sJ20kohlkSGmp/ZvN854O6EWcdOtM3JF3l57mLSG7Es4x7Et8SkCHY53urzEPODwwz7yMtZwHJYqPU/0jCd88s7FPb+d1gc8E5ttTbrU4gi+dCGO80dgnv1D1p6J9DTTdevMR9Vhye7m0u9t+6+GGVum8LktNcal1wxcltBDUlEORqhUrMgkyB0yBsTGsKziNvC29ePepew/OObZSLEpecS0ndPXWZ3baxlRx9/IylPDD08FTaWHhbC+k/V0/AdGYiznt9m/PPMdu6MzTxzpM48r36M33d92PbG+mhGBbEkUcnkW4yaSCQ/ONfY/TBg1zs07ZEBkdrYEhP5lGk3Pqj1XkYI3VcMUNCMW8tbcSb2px3edGyN/GG8t3wY+DSX7dJQ0Py2ooecoYL3RecZxYB1jSY2s5zJt+NyTc05vw+s6lgOtahVHlMbYnIKiMcTw+NZVqeV9CxjE3z5Xf2R3i0fcb7hV1zZLU+aGS1j0ONcyz6KM8o80M114qpk8VY7ViXncNWaNBoNZ5jlXTi2NngeXiSFUfD5g2HtOvo3BwIL5QaYXBhqu3FtkFZPMgU0nT7439PhKXlQqeLu5Od5pKlrEloxmpvPz3+zWdtO+NbfxUsvsdJAj9CcFFVQKdDhHqTt5wv4jT9Xigak1os2DKwXp1uDhEiJoTjKanriiEyqwg5BmzDGYcMvG6hTdJvbDSSHMpu4M0UWPDa5GQBbcOZ8oRosBmickuvvDQdg3ZmgG0LbmJbHMVeiERC/OWP7+vq1GTOkNYh2I1ELEFYIKQYmGcfamPhOZaT3MuM2ORGhMxNH41QmPT6hUQhYC7Iy47N59mkNsGw9rxguAQmBXM1TZc+F2zA0amTWVNZGghAuyZnIDsZA9Qm00FEkCEg9Cx4B4UoAm2bIMQGIYNsaJAhQXNWFNCTHv2LQU4GDxoc0lKB0Mf7zzaPNitMYxoPVnxbukvXXP4zqqMkwKoUR1OI+rIQVc6cFFkSk515XguhUYZpxL6wtXfj3x7kZvQ7FntcrhLPJAkQmRjYcDpTCzCPVsVhRlDEld7ievlV8Ej24EPBuxakwJDlxMIRu6ufPM4d2PPY4HbM/MxcP1njsCgHB6kg+pKUH0x5Bn/EE9wUA/Q29fA92x7bj7n4MnvJBtXsy+xEv0sy0BgxiYDXhy+mdz9GfIP1IHZkXUiE1GSRB5OEkEqzMcmycwNV0YkgdmdFJKDKLKB6cPHhHdtID847tZAMvvI8Gg+LTaC8xTDP4vfsPET4buu+NPv0+6inOVD3vWz96qtYnbUnTGwhfjn+aiiSQlgZQeGj2+aIjFYKsWOUWwf2tfae6+bqIiCisYmho2OedD189g3PSd2vLynkem7YM6DDrM7yMtqKLEgxuIbV6DSaTqDV/psv4L0R84KWdyWPrDw5/KXy/GK1EFsn4CbupMiRrBtGmOsvIHoFI9nr9QfH47e+efpLtbzl6hJkJJCZJhJBP79v3paKKsYqvOUqtnIh2fPt8nr7hYSDe4cOXp628RPKYNjhjzddw58vMKNgeSSWaXzDny7dszo6MWjqRM0nV5UIrb40pCl7orO1Eb7zoSqmdTTHGcmHjhzGC6vPCjWyVNurIfURVOFFhTJJhBp2jCxjOHdU6qNazhol8qRD09tT0yQmMLdxTqsVnGDLvVvD5jCxjGYI1nOEa3m1toShY5I8msXnW2wNS55J3T32SkzGcLclWzwIdk6TPMGNY3NXSwQndEKoVad75242lnKyqQsoyRpRbyoei3ws1OHV0oijZRqp1etSk1CqMznWsZadSsxh81WNR5e33VLfENdsm+j00OuEusBtB6qoIMWMGJHz4yYqLqBhttlDbYWCMRivohpiXGaAeXDpmw9AMqucxwdHY0HcyQZOAfk5neOuzgosFXwpRVYCoqInYdnPRpERRFVBYbia65kIu18daNExRAcdKultG8ovQ530N16+u3fi760a5XO35qawns7zVHm8b37c81CVRxjTvhPvNQc3G9TytPeWQgp6qrm0YnaLkrVrNqikySfne61bss6jWruRISGS97G6rVYJwTw8RtXPE5ImMu9wTHEYy4ppzjzDjN5d5t1nMa2jI/ZXtZWYmXwVXJwhzEmGMZn83AneMM0C1w9aKNw81bwnrjE0mZQONup4fRMakzrGkZXXbgfWq3/JyjvA3Ts4O7Kbml/Bh+E4rBm7ckbXdNs4z2XVHG4cXCqMejadex9TrpYwGRjhfJ4NMuEFCFtmQ6SOV1uat0KM3/ZLnjwUw2BIUh1YeEHvO3t3n5Ml3xYwDp+BSVANaDwGqZJJCjRjJdDqTh5SSXEFCN1lYjki2gk6TEW7hS5R9VBT8gOapE3cKNN1LddOa5tO6yi9sDSKY0GcNN2rxBr/rftbZ8s+mvdjbp7plZ/v8Z6Mud32b0vvT5ZwZ+VQrp76JzZeWrr1xgHIz1oiR6RlT4WR9B9Xj6z4xeDYZ/bbiyLTpsv8X+gdhi5Kuo2WuLQbk6dVnX/AfwDJ5xeQaMEM6jLxoRzsFixbdGQgdeabxR3r33y62HwsRDeaGaShMkySZLzzRHY6xNOQeKBUntSHTCxXkqXraxTlqG9Jek5XQpbKuDk9hShMkjHi7SyThNFEtiItDE0NtLA25XHLvKzWH2VFivAmssavj74qvpGJnPseq8ni/o8fwXn2fpq15VMTlDTqYFcvHoU8fd/df8QIvcnjudHw+h/Z+vEQIv2oVAWSVX9hSgf0OjVAmgNWEUkkqSaSBWChBYONJIpIFZMSYyQJRuOnkEAxCYCXc2uHq9EmkJtfypanhXVYKGfOCXV7DNF74NITFDLceNfVgrX2reZug2ZmMuv8yubLqmjgQOHhPrqdJhXZhkt3WMmbw8QmPtzvM5wYtYfGC4VSh8GUQ8zHpEZuoUJ4tuOnPVbrg8YtcTF71pWCrE65BOXJH7TbSC3LI0O/3UN7ZUWKl0uTbdhuW1t1In5YbWnfBb/PRtQu6Gc1sRZKNP5MTJus7G1jCt4JLcXO0USn4/aRaYpuxm5iex3ZT6damc8INiH33I20J81sPQM5NRYRipjtJEepbulCgfFMIf3HGNNMZCrmDZjlx3q9J3XjLXY97y8HX9IPNln6EFB6/+Tv/L6z26cBYkBwxGXFiiMufNRwA2NQt91gwPgZYGWB9t6c4cEWJRO9sOIG1UE7J4418v5C+NLIj1dncPnqSMG227tAjPwhS6lAgqXlM5/mz8D0c0D4tvb/5mwDv+zZuEO3eWKbG+XL5hC5FCVZ8rmBSIUBznkOEpQhD9jsHctJj+7df4WfVq0n9oWCBRGeLO1izoOwdjPyEhp2QyY9RoRBvANsxOf0/qHjVjI/syOBoKW7veIek8C4Y4oFFTSJDIoo9K4zj3KcQwEe5ZEJEhAIqujodu+6RlLHJg/fPZ+zkO454fZTMwb+MWXEHZtwQeqEmHKdY+XQTuerf7txtE6cQRdZsjOHOMkagxH26Ha2LlMXq9Xu7w29G40HdA+SHWEgQ4B3MTj403zkCV6PYttRtPQXL68qNHGfd+F/qbCEhJjMQtyNFRhLKYG194ZIG/JpjhriwgBIFfrMMPSfgV7Zo0Ko+UhKE/zfKFmD8jlqqSSaJg5qw3rIIGy9AgIYskjE+wlHkVP01Lny5vP7SmidjC0/Rib85az6eGIEd3dsW7+FjVy3t82fG8ufxY8tNitgLEvjVYnA/3vZwBFB7EwgXnXgCZjUSND4kOpqfGqEkkykPnOxEwrQ84paRT+M5M85p7JP/u6lkl/P4YS5+H1L9ohPJtV7EaCCFa1ojwnBMyBGuZJSwhO8+Moj6dZGs/ebo9OK++/+jNzpLlz8RxeLVCtWJbKpyZeZpmaDn6lUYY7Cft11nz92gZ6bOodtio5sScwftswH6wTAhL9bwY0MWxmCdDsvFopWD/X/shIebWrlxML8rhIQzR8XJ1K4dQGANwPt3PpPBCPON8s3volk/2wHtTcZP0SZhpyR9n3ZmqHa/tcqUkhCQNKYB0ZYZwQySAtNwl6norLsh6qVfL45UqfijE5BbfX4Xd5qbXpL3Tju5ZKs8vzZKmsGs+I8R1D4FgT5VJ0UvyqepXi0/M2kg5RaHp/F3C+5YhxcY7VJ0rgTqiXWqHqdSBAJeBO1U9tOYpj2INse6dodyCXdqBjrnsTFebz/0cb7Xsyq46pzdUQ5Oz0e5idbKmzsDglTuflHNpXv67s01s8C+zbjWFrzsvxecXFlHYj7DHg2k136nVF9OVA39577MfKzzpwaxS3JNII6poTJCa3cVV17q7dseqJEGc1MdP+V9CgSTxpy9N+Lo65snXpCVeZzrEqMTrhzZHQQ9OvZWiebe7u5df5Hia1bCfNTMXFObhKHJmO0aw9JI13+2TALsPiJDVoPiRNbzolelDjB8sJkKbjj3ciO2smrH2UOMx0kkheb8odCQp6Le8pQr2bZr2fvp27l4YIwH4tXqzbKByZuzEcv8+HY6TSkfc3dP7iZ50v8nouO9kYMeTpwsWb64pxQOajRUX4Y1Q2+eFVB3zyuduqiCs93lgdGRTQm1WgnvvmctjfXLfzc1288U7dswYosXraLgyj3bWS9PZmypJ3Dch0jDSsSS4V9OVphK76WdJMs2HbUcdQ8ju/DBQFEddROHTyzBqP6WmiIqYk1MRPI8qTKlDzQ2AvldPP1oJ+T/Um934z01myT52Hx9N8WdwseHh28+3TomzL7bDSaR4zP0+XOC94xNIS6SXvXOHntj656p1K3Al5oea3M8YUHvm41e2Gmp5dHPeQrHRYI/0pnu+Gz69KR9Svw5cZBzRbHzjLNSytP4boAhBrq4Wk7J3Z0UTOjoj6R45SMb7yG80HZMzN4pp+SHWuEarfpKcnU3pE1viP8EyCno9bP1Xxo/vtE6TllPj0xakAOyv8Phn5cOanWsrSZ88V8jWr4bVtJJ7/g7H3f5/pH0h8LCrURPO/9HKeOxXhfPIeV2w9F9p9ZsfPkta1OQ3QO0qIPSGggRgRoZzacOFtzpNsv6f6asQY73Pnmb9aRXFyaK8+n+Se/GtcOPLlWr9Pj0sUN6uh5bpdM8GDqdz7Yj60zOeRwKHrIqXJlEan/b4Ulogn+eNhs6WIGtWY/PPPKlYiDysIU5IWedJiGAqspSV9WVMapiua7AEYp62fMyM92x3BQMBuAsvQwi1lPZMzUusT2nuIMC4UAUGQ/sBQw3wwBQ3gk/v4CkHWtijhMWmCmTK8ivqmrqRCNDoIBA7lRzmIcQAa40mrBJFJCbB0h6Q/GO3YnIwC1k6y0jJAki6IDrD6wLLaEi6T5joxDYJ6x0h0Xz0CS5AODQfsP1UbcMq2cvxIMCSkxmH3XGPoN87vI8B1muOkdYa+3ieQQxo1CauZIaGFNMsbh4Dk4K6yECK7l2Ozp+BJiFFMhCMxDV0UEU2BQfi0i0m0MdckhIdxAuuzREtBF2UgzheQAxBKC6MhuoYeAPCYBoDLJyTrlQ7EcQIMCkgWmkSwdhrOgMBxIg8gfqIAUhmsD3CQNC68uu410hQ9vVyM3EbcLbRLOnBK3pgSDoIMLj1QjnQrOQaImwKRmSWfMFDdBYfN5bhD1fSuMtfKaBdFjBBFBR1OkiIifKBxgRJXgbVtKNPGjbpNrLrH2hAsF5ohlqSxEO41YE9qGTQX8JYobCMRGX76C9gnmkP9JsYIqkL853BtthyS5sOaIYPXlvjECm58VOw98h+tFCSIyAHiOTUIkzxf1NkMiXclu66PkxOo+3ggOVRmtQFA2NkUYIKAe0OPgJ4qoA90JNpJuLBEBkTymjxPUh+I4BBgiuIVdkiqsCiAgMZaVhf8u4bTviqgKqiKh+4sBQ5HvNAlUkLJAqShzgaS1zMmAMW3rJ20c/6XIMQ8SgIRNpNN6LqQYBCNgYFjxmG5vXBrC+JPdbh6+QoTjgwxKyOso1myiozYl2lxLHYchBsnBUI/z4pyLecosMeSaANwftKLkRogSMYRYjGIEKUKFgccQ6yoMWfJowicFO3AF/CQISQQ4iZYBDtIGTxsR0bsxzJAc+RHK8JmLoSjrQJVmuDpU7E1qa70C0Q9ael2BG+YlwNmux9JCBDuN4fA9ipBkPgl2k3Yqxg+sTcAfd2v88LeZYXOAbhD+4IKb0gEQkQYkTTkQHAy1xDmkRKiVOC9gL7rPyZc9oRhzWYDjZEIlgkeAJOvtgDGRREIpIghAYBy9aL+97PIO4Axir+aMMD8H3sF0jtiJubBNg1FPPXoPdi4WwFDK/YdZRge47ycE1T3t7AgKhYd5NRgmxigwLO0FjLIwA5PnkiqyCfd7FKc07TRJr0yWSxagsKcTWKFYoZGR6AXGgPAM1sfl5rKPHjyTRVUuw/SGwQ8oB4XkGqibgSxYORp9W8fNfI7vUH8YrYeloMH8R5MI9mGUXM9/rEczD+X7x/m6Ar3pPOjXoFwwqenVpHtw4RSbWo2/rKkNnfTT6ye2MdDZRBoUk/94F3fZ+SmuqFRDpODbmdyUKfYk0QTAugUbCG/55/h1YKah+A2Q0TRQ0kkgmu1iwyDADE+yr+0O1W2wPon0tkzUTwOgwgQzJgBhRqg4BxKgm7/P5mCLWxicFSZQVW+k4HnlYP2CD4f8WD2IQM7CMO2g0X+dnh0SaqDUWDb7GG0cfBg6pQD/5ZUcrQKCJAVHZDSDqkNJB+BI0EYDOXYUyMyFlDhmw4WokfJEzGGECSGhK/q+SfSwMn66lNm/wDQGXgUGLEWHy1Cg9rLbCY7/24E0ZDQqLJDPiAkDbzzbJkXsG+QYADAj73b0+ciwJK51BopyYxVYUK0fyqn3cQP7oGcIGjTz9gtZocGDuxQ5t7R2KBxO6iL9Uwx8/gEjjl84IzDcNUQ0alhJQ0vb1hMDofC7kGbUJkKIcwd6uE9pcK5HuMARBoLxd1QYwZfeTYwvEg6EiCNYfkF9MOuH7vxmZCbZmEsDtLzQ6QA7J9EgP6FE+ZEiiKQgEkYHpKFOtKFsjb1BLS5VLDEDw0G408ClrN5gkmHTXM2nAlEggvRTCQ7pErdjTbBlJqYZeEGYSsJjErYZywCRWsWDBAK7ahSJKate9inWHTwhxMGQz2PC72wjw5lNX7A3B1WOBaDSoiPDvOKaS1LdpthZIk7N3W+2hqf1NVdkBWQRNreyKbdCEnSNC2/GYCfzfJ8J+UYxYu07AN6QaWBY8p2FEbIXJhMhE0yQ1wDAAwMRbEUoKYvuSy9HaeePl6bdhc8GSBSVVRkkrubPzkdS3CCm2bw/LlRmYlyWoCQrMBRqZHAKQpbQxuBSU2DtP7QlEVh9514K6O6H+dJNkA8PzOYiZkVtLcuKOY5MaiFkcjlURuoRjkQnIt9l8O8nJqMGs44GuOA9+09JFqCT1jd6Q4UeJy5n6i50P0Nceuv3zKU9gj376XvBhnfhDPNZJGDeNjPCBRZihuD2CznGuPkKhUheL69UF5hgdDzA3ypFTpgunEFmzHzgwt9q6thiZ+ieJ0G4JBsBhQ0k8/ZhwJ8QkidXgm1PR7BU8L3hgLRZRw9KVr6iAgR++I+zQhjRCYGwEkGjRbTR732PcPL0zwv0z2cYc+ha2Sxmi9y2gEpcgsKifPHZKpFXFVj2N5k3bsv4EzOsmRnOHgzmSi0QtISaDDykgQjhnyY9us0sMsD8zsCZW6cM49FDYlmuVcyETK3r6VjD9cQqmKLLK3UNnng44ObDlla3yFmowDoamdSgkrUN+SP30bl8dd2H1z2MOKQzzp/1dGrMmsYkMKBJaTzs6taZje+gsDRGPAxbdGpdFjRnJ401xNIHwDZ4llQ7A6paoUuOobCNw6zZ2ZESRhya0QQm4bb0g8k1hps8Ph4xRQiHtus+mrJKHsXhaO8HVCC+OH3TD44c8Xjy55uAkbsxpvQm/nY/Tp+Wb0jcnCzHeIwzP0KFn740ZrcOyw9NAP2ok892NyYpQPcQUIS4FA+4yi/DkvEExcmyFWhFNw9GcEF4HgLJxJgpiLeiWQSQE0u5nndXPO9MsFCi+JGmCSk1RHF03GM/NZNW+NQQShzwmZ4B9plvjFVgitA7OiEQOndPT1EpNMSslJPfEZvL7551hCo4nitc73Mp02llYMocm6i7qCo+GpbCpCy7ISfstytb7QgUlqreR6UQ2FA1J9VWgtAnKY3iFYZcuxbiJRMVA8uKyGahW71qrwJOfyi1Zftd5686vJdyiaJrWdA4EVdi7IkCFFl8p1Frv25eqAqwH822UNgFTN5BY2gIaw14YRiueGAZL9UXmDmNj84XsYTbOmB3E7Ua0ZR9DxrXW1Ju7JpmuT2vfo1M4cqUISZlhOrRin9uDKi02DS4VIl1KyceU6X6AznnbrG8sbBFx9Y7GmmjZGcuq2EJra9TzbN72ORw0HgMc0DibpGl0z8I5gmd5mkWKh5Qj4t1hZXlnGomNO0dYolicpd6laundyb1E6qr6rKh1zVxJmqKLl7yjWrPREw8Kz+jXJwWJEgIyLDQd03gh2hgGCmuJRscRwVuMVhIIbgoI7zFc1iYhiCUDZMwyLoMQ2MwCkPe3NRiN0yCGOYtzPcGBe1UJzhYkWqBwimf8sYTaah/XgYpYwDIt8xOS8TQawMV2ov86iIKJBEUGJZr/TyBlAYgTsMgcg4ZMW7oyIU19piJxcXZEq6HF08/nuoFeLnMMQptbERGU57mAa2oSk5Sli+bEK4asXlcfRBq2c4bZAzJftKCuVNdgUXdPEZzhDzm5FXIwchxshrd5QG83hRlHMgn04fqsKdXXjrEBT5jPN5cDVzDaQQ+4IOwMkT98R+Y0o6h+o5GWk6oSIldJRbzPLAdWGMDge5QLJnimfPrZnwvYFiYNKJKiSSjAaAjACcQ8TyHxM+ABkY/dQvW45th345h8Q/udbtUPWhjRtOrz/eTXyOBgTvoAsNiWTsDlYYDxht84N2diq0akKkOQeXskBmHVeTEskDnAGRBGEGRRw2IOA1xvcE2avoLyufh758qee6B358h5REa0HoSeUecSEVY0CYc4D4EKBzTFn7cwkoOWwb5kx50AWay0BodhycwTecLfCvL1TFHAQJm5GXsTrDUOBI3VwQsZGhhibMSyp5yHVtBRJ1Jhk+H6q7X5WCFisX0nXu8MFBebKE1qBsRHezJsM3dPE68Zh0Xv5a8r44meeF4VagsknUFCMDufiNn8JChF2cLO23gD5sqTOydbGw6Rq3DlXT6LhyZuP2HK3r4ZlGdBW5kdUbGMVQZuUmmtnrM06cMQpZSSYOI2spWWoTcX23W5c97fgzIEybMgOJgNJDZOLKApERQA4JYTQH5UUnUlNAjECLBZIrFIqd/hViJsQAz0A2AuwbJ60IkJEYAF8+EPtKKIPz/vwMBQQZPGNm42R2QmYIwKN7xSgpd97HCynzkkILBdgFzDlX9vddA3AAb4DHAL2A+T1HVBhDwjxwVpjwhYT7o7gbvAgYpoz7H9f9MMh+IzbHtD2kgSRK8aYUUNQrrFPOqxMCyUJ2I/1IiHyHT3ds6ren3HgfEtHZENCra4UwIyikhGSUUrCpYIVkKBMtMZ3Gm4wJoGCIxACqIKSiBSyyKIgxViQjBEVRkWW1JQ/pxEKJgkxlGYljCnybfWbZnlqVRX7Bv5hp1DnGm4ENdGEkqyBeIPQRUQtFSEVTSbG4ZIE+FGn3E+1+4+1iI7gHKO5z8DJ1fzQ3kO/6aJF7pEJ1Bs/Jy/M+l2i9g+aBCEiwGEP5CAc6XyhoPzaSefH3ew7tzMEIuGcTWWg9fu+8QT8ul8+pMg59ad0LS5FixZLxgZiMQnYJhm2AxWcMNl+Q0AYbAiRGM5tOC6mqSijB+w0TxNb/6xsYqxFZEi/ATgm4c++6GPIj0ZyfEYiv2J9n3aMvHG5dD7vXL2Xsp92EuogKBcSMqQUwi1pmLDWmlzcmFZv6ZnyChpvormPQRG1qz2n1sNhtta0BvpeB1mUNosm0vfLM6aX1fMdR2GkXUhqoT67TLYTqMlFMKFYT6XTCYRiAkVTvRGT8hwHgGBNkMC3csoUslJORpzMpQMJ4ezqWJ71Q8mcyTgGEYyQnaYH0EzmTIelDaepEF65iMQwloyHh6UJGw29sDK75EM2rBytBMbGNIYBxwbo3lwvaeYiQeIETdbaFIjsLaDXAgQVkWCIJlhDyMYfN48zHi5hPwMNaDDCoA305RkMiEX1QagpJBmzG1lnpGzBkBCy9ZuGoahJmzyZhjj63QouVoQhYhI0fezD9EEouNAaFIffiVFKkqKVjaMiWMgoKVCiRZEhQgEZIKOeZhmN/4wgeAf2GsDEDEdWINGSIC1Eg3UWhBGgmj5DpFgGG18DypFzMC3ZzrFm7q7fZc3uLX3ZUHXqkhGSSDBkVBvaa9JpAQkNaQ+jCENEFP1rEYrQSSrBi5zah3Bz2vKO1o/WjSQkIOHMSwQ9QXP0+jQhQT2ofnhWoSRRwo2SiD7joPOfjDP4CuX1ASJEiB5znx83WQWRCjpOfMcCGradoj1LgDT63fp6ZsOeHQy43VKlOU7N+oshFY1TH6vVIrE0k9erWIPG2tXfwtparZhMXKhjOKL0rhmMGnSjyklBtYxtLQl2vNMZrQO1HLCsUWU1eTy1WadmDKxvpvMKwmJgUmBOaJ4EDab1+A2H23Lj8i9g5vjoDSHvfWRA8wHzx0oBCAHrg/yICLhDUEAd/eLoyDECoEgBx9h6g34KoP0vx+m4gFzfnO1EA9ZYbbIdLLDsWIx3swoxytbClstpUs+eymWKCiy1WAhZip+orbFE9kECQkCQU+ETrSF4+g+ltESQM2iRkQfl9R5zuCsiAdzkCdw/LqCxKKOjle/hBo1IGxUIKugPeWy4c1HYcfRFE1r3FVjdLNTivX0Fpa/jlqsFE3zGlerTsNIQe68u7EBTN+lWIZi+CghmRdLhx6OAvI33GL1MOMqDpWBi6N8WESWKQCLCBvbKWktsktv5i5mhRn+AtA0icwutT1CQow6ntkODxi873JXIzz0XfrGAsARkQQiqpCKEgrBSDFCRE6tfURU/an+hBoYOHLkkLoB1gB8Wkg0L1ghrEDiDCRfbQ0IiIwVUWKxg/TD3ewD3g0m0ngT1wK+dfORD1kN3NCwO7E2SiBCDiBeD0RtexQQLkE4M4g0mVL+4T2+rM3gfklVRMtCPQAn1kQ95E369u7hDtUQ+s6EPfvPQbtLuULEIYQJlEL7NGcRYOk8jMuRjGAez08mqHlkSL2AviFz49Z02LFFiMZIPEwvMCsHsCFKeo0hmgvpsfhkgpmFGKFoqhgXPvNGQ4fTJ0zJJCEfWIci5NBqFjM4fnO8hJZVmzwMFoA+5Cq9Kte3YPba9nYWJw4+vDTfcXnQTIZE9MddC6s4uH40mRmDKJsyYl/CSgzHX2niBXSkNA6VPWXwl7aLcuTSzC5340Gus1Ir5HvmG9biv7bPP6cE9iiQjjSXmdTsDBL6Kd2tE7hLA0IOEbXH1DrT4nefvlMtX4swMgM6B1+jLU+kYi+gHDpjrer7OsAhBjGQgSBBjAAgROvrMf6dl/m7/v4/5wML2s73WBXA2il9hY7Q7cuohlG91LvR5S3e427hqnttNqxKlKrLSrWGjbNakFd8xD10v1DQNlKXWUFG2FGCuFS2sRRhRCKVUrFG0K1ZslB3CgyalNhFiXWSKlEoVpYMZGSGTJeX3QYK8AYFhJgK9Aof5F4ajQXs8fblL7zoaF1voYBTOUGGI0w1o0w2wCEKkiFeW8HiPSbBxKEBToPlUvYa4bj3DtiOCBA6G9P4O/3BRtgSYw4gVSrhkioKCw9XQKPzazDuITv74sZHSPS4CIikmI5Qh6i1C2QKMntDXb9vIxmwKAgwixIFKy2PfNVKxgF68PRyGODFejYPveR3sbw9GJTN2bHAAOA4G37d7fmWuWFiBHb5j3JTVYb2AvGxj5bBR47iCMAZIEVYj7tvoVCLA0Zfwsi4iGpUiJoANgs9Bm5ObsOAlmQ6dUIWhYZYigbncXauNcRBk3DZ2NO9n3cn4csYKWb2AjhJzzoz4mBMqGrEigZwIel9HBvVErTpju9+ux7DLJe8x/jMizG16wZTaK5Exm/KiBIF3p6v2KkNwRDT+hZNDrdYXvcDGl9fkcSxxJ1+uh+iYEOCdih5e4M7xF7xLESqi0oJSKxIIlEFjSChVYRYIxCC1G0YKVsEkBN/AyWZ4nIA+BLQTxKxAYkHEzg4wMjUeFWwoS5v+NOkv104WyDIjF83H5swuDcfKLMpIMA3+bGBdAEguZFQxR5ztKeEO+qMy9dnW8fQ7bLyOsgO/EI4JahgIfsiKNDgY4NlGynQXbRm47tnjDb8U4x7KSjK1WbUAd511hJNxGyrzrbbu26N9fwFRYBHsbbhxWoGJ83aZ+ycc1ghAgQJexOmDAtycgKJMm6mB9T5xwENMqaSm7hqYwUFfghyLyhoIBWwmcwoEzMoYuZAvDxYYp4EIsGwVVhBhkgWDGUIBAhIRQqLuRCStjE0Oy8TJnN1cRgsC8sLxSZ1Mljtuk1ToCW6oKcMjAbzzE3oakUUkowlVEYrBIgpiBDlqWKkOrkpqhpcux3Dk613BJrHbYcFyszMYq4pUMRSVGTGYQu5QMhqWew5xJYNLph6SqCR5QvkwM9TZLIiSAmMU1RG8C8dUUbxFSq+BXgXwgoTqTmQKCTYIWFApRQScqZz6dvyl9/xOQcDJseIgKin82xto5vpZIKqDOeiC2zQhaUixXXHwo2XYs5QCUJUCOYwM5bybrJE5lCF2LCGTDCcRARKsbI0sIFxLDKC9iwYoNlaL4NhG4UlBMSKQERQUigoCyKMgQIokgSK4lKhAiGoW6FIj4NwOkgY3GLDTJHQBBBtBUNC50gQl8Tu9VBGWUTUnSkMfv7Ar/Iiu4oiSItalC27lr57z+8hHzju1EirJxYBGKczHLsiXR0Udo6HzsorEKg2DQlyDQxokiedD3IeO3jT8+BrhWYAmyLjUfjW0ydXtaHgJ3HPre5h08rlECyVGRHEsNrNCUYBvkP4O8IaklESJAIgIgMJFgRGCwRhC0RAobDQViCC0lhShWglAyJ7NaM41rGKJbWCIgiAxEEhtTv8HsfW0R8SlwC7XQHCzIkZQYbi0fpNtkbk0W6ZTjA/iEyEVW+lI937BOFRIE0kB9QXr1MHF7qX2kzrIZGJvhVzU5YhHXQUmoRPzEYsV1wxOJGdNWNtvE9w+S3KQrqMpQea1fB2pMy3qig07+uMIG0DClCwH30OmCN+v4EAYRSBZDMpByXBAOJoU6BxFH+IL7fvGvrIwRHYpBhJCEIwIwE0n6XaWS55oGP4JXfgusUuXoLBTeQIh780wLCP2QEPlA0DBZBIkFhO2hYIFlVZIFBCEAConR1FLcHQFCOIJuin3I5xTPNpESrUDddNvfDMRu7yDrIu2z8xOZ09AYGw60zNgB0uCp27V0kComDjgnsANEzKJ2hypQyIL/LjYFYUHGAcIoaZDBkYMx1lKhmlAV2pCiTTEokDqs5ihmYld0f4ZaGxploVqCyt1hc2J7VTAMHEIFBgOwykiyAHYAHMiCm4iABQEFW+uDDaeM+L+2j1y57ClSuMCjjFi1J6oeuToIDCBz9TO86og/oiB3whASxAEiM5pv+NCDgXCBCGg1tsT8Qs6HnHl2EhAg7cVHrFHsB9AatJzPz/JZkFvCETsPcVb9sqxKiwuEg2xsEOgBnCeeG/4yDC4tDw5CR+/UIOPfEpfbGRkFrkczsKYlRPKlKEX1MB7Dylo0nfZGBb0/L1K49RGUeBCK98V5kp3DE3So3kQ2FQ0J0IwMOA1OYCgcmMIaSAjRoDJlJEjOFgzljWzB+doDs7iAcx5H7KeYQLAQQ+kK2y88Mn3gwN50AMDzF5Q0GKGuzep2Hi1Yyx6cSdTbHV1duY9fpTzsS60w7jgAokhlQnHBSs8TplyqOqFBkhNk5PAHmQCPI3C/7USm5zV7rImSkhEsB5h0bZ7/w7iz1yTCNg+4L2enWF2L6m/hYtU65Qm5cisjQX5TWEBNFQ38DZhSCyeXoITUh1hy3P2IuwHp5GGU3VVQihEGQEGBEGALIoMJJEVGLIIQSE1rsHw5J34fyHhpy+Cfy5g4o12YH5e048ilCiSEKNlFuN97k9JOAw3b6C7J8bNRNIY/Pq+4y61Yo+/b7taYs/8JVdWi3l/Hc5M2XfKmQ+/l/qdCpg7sOScnFOVvD8M5cjv+hn4VnEQVblI2s08Iqk7oil0B2F6CQInAiwWhGv5k48T6U6myHIGAZhTQERoiWAMMY4tfG0aEIIXUdKxc6EoizHtGHfLQBuHw78PQGCVMPATPIqpnFeggmkNndDtXJCzyuX2Y+MsfSEHa6qBtcP8RSLRh8SW9UqJ8l5tFCPtZLjMPhZ1fYT+YQSKQfOT6ShonHWgdS9mKKjEaenSVMeksrVBNhilRwnPzA2iyifpkD8jpfgXYKbFc0QQtH6TMxjaRQYkRDYzMJFikRLG6GgFJBJWFZUURijiFlTtmAF38y4HH4cDRpgx3KKLjLQNNCVaJQSZWbpqxslj3LhZeZcrLt4ojswS1DCDFCKBiCkJiYxLAYLq6tmUECxusCMFTYHdc2mpWbOHPWGDR4EKm3MlhE/SMRPngfiIIXFeWo49tFtukNTuCoujE0JH60ClxCSEZEGSQkIWNyGTmXV4CjYMQQW3Cv1jm12KZKZZsYNtkp6ZdZypML3CpaylCH3uoDlThCw/QdR1Kb9R4HyaOD2Qi7ZtjutmQxzJ0mkOBZeZNK8fjtSSHjCUQOmKJcxDw8YTxu9hrOBbSQLy2XpcBaXEugSiAwOaK5ZgOWWUaJtQvZQuQIxln3poyAw3+u+nRXkCym6Y+IlGLmEh2kGT28HuuDQfNO3XVC2hYh0TUUGPXuLGWqt8H64U90NvLtV0hBQhbFNkZDVwqckNIUaydfCz892cfwapo00SlpRsX6sx/O6crRWgbjmWqnm57T8fqnHeB3nCdViidPWrzkNx1hA8KEkdoMqw0vhFjfZB02mMtaUEkiQitMAc0VS9IvigHuQP2sJ5z7cg0iHxgRNRA47KU2AwLtRECRJ4KbUs/OaHKGmKSEYCHkqfjYbvPid0dsnPtLWmh8BE+vd4htPeZZdAj8I5IdSdI5DQLBFWSIwzKIwWOivlcRJVuGElLaoSiCSMmgjQkYQ7dgQwQu3pag0QWRRiQKiwCAgjAWIqVJaDYKQiyQgosUCgSxlCiBYICFAYhYAwQhFYwYlPmPMLBCRZFNJzh9EF3Awb3pswDrrHEsRyBjFGFMJQEhRD1fUMP38VMjHoZ8PpVnG28PtL4tm1cGRyNLHm+5HxvheeBU9tpcDPyh0ZMhGbhhBZB/l6AM4NtTl3lg9OZsj31xhh/kfo8ijLNP95sGtPNaxWXIStmgM/MOqrWaMaGIQ6Q+/pOyDfI1DM4EnkIbzRnLYNJ0LTeNYSVQ6Fl0RNdNhLUFAscjt2hwM/fiOUZNO9iqKOuIPmsYfK0r0O071JRLmdr8j7R3bh0lbvtohXMNxxBqTK2mFBey/WNxu92ajLy9QVk+6GotHrEUmZHkxRBzYsiipuXeioaCf5hEN7p6uWVLfcVmrMLMmXFtmIvemgxloeppjxbmdTRpk1nFK31h7PRcNmzk1VDvbDXE5lczOt8B+GM5s3bZijW6q4mKyZ3YG502DzHZzDtqodYXpKdVAoAz/Rkfg16hgzZjjVQHrLW1LkhGwcohVA/AIDu4GxNHqRxRVXVHiZGaMwHz9iaw95HF5wJDTQxwQq8CUoEuTE4vKMj2YRIWGhl4XtbTXeGyraIuUfRXmv8+z1ejRpem1CxOVJ7jpp5HGTq7q7MVUspralKUyQk2RTlxE4iD6r00hKFTyRcezHpc9i8cy+piMGmVTXsLABxhDDIiRvr7H6j/CyJqwDMfMn1F7DcgBQela00C29zDVL+37eoyC7bsL5L8UDb2zA5uhxs9vb2EDciGmJAymjZU2Rgjcb9M0UyHlKmFnAhURjGpQVSG7KwjgCBQNtiyQthYHC41DAcALFLEgMCZnizaQJF3Mia4l4cm3PoLWHf8DeQuLgyqhiSBnr2wbrxzBZRmWyD9eqI7alDYSxjIxk0hcKVIohWS6MhKGJo+iOsTUuI7MiVsdNjwnB3i7w8CI5CmRmJhRxELsDEVyoqgqilW4oNMdNotJhcGSPE5Pvg+F66h17KFL8Q3QAeyLpg3EsEZprl5UQ67uEvKlLrWGnmeXsVTWpuGK8jlKEnIwFGTvVURWKsfG9uiF+O39MtIXmJMLuHz4kITM4oh0JBzykjuC2xjAgWLLvBIOPAnch+Uwx15pobB6GQg/aGFDsHEY6IKHH0c5m1EQTQ7Dd3koEeDWLhM+TtITpnRXtOex53h7aG+pA1IqiCorFiKxFiI7io5gYH5RMMhSLUpaVIAhIgkQBYQieaQ84QMJgDBmeS4yz1BtYOxdI62yppXSSwGJrJTBaoiIZaloWEwtZJWELg0gApiGENokoHUQSThnZ6DJ3Roi1L22Prs6ppHaHy8cGx4k6QYbnG9Kgy8izFhvElrwm81Yq6sTp3ELN2/1aVEL2ka7xafZPeBL5RnVJFy2GE2bZR0GU703D+Nn8WHMNaWUNTEMCMnEiYGJDFNoMBoxY/FDvJqJmDLa+i+DMM1AOumFXnztaqIDRwo5E0kd54UMZY9jL9DTgZNFUEYomHd17js2b+Xhu1nAr5eE3lYVLRnmOdsVuxx6T3qhaVw9Grl8TXD0EJm9YMyeFi2z+0BJwwMhkuyTiiT4UFMF2iT8VW0CrKRMm+B6eEc3xGYZ3G7NGGfNKqKWg2QxEziW0mIZlGQcv7K8pYmHTBzlY323UWGnMxWpHkyigqYhuHOoHENC0ILNDhhFggzCDUBccwXp3hG2OO0FMacB3yVL2plPbeVbWRDUGqOKfAsXRug2pW24u0xNHDhrZ/TxZbdu7flDhUIiSE3GFYSM6TmKcpU7eJlu2k3LEChTfOHTDg4LAlGCGynBkOIrK77lA31Uo1NnRpqFuGjBikUMVaFaCWbPtqYv2sYmhD4mNzU0UQqiRU/RWlzl85fLbuYFJNjyIVTAS1zJMadjjIOzNgez1uiQ0atVIy5sgp0LqDh4mR2GRnaeZIfm5kRQmECGKIw4NGqBrUmA8IKMoUiISiFzBE5ymjC0DmIcyJJwDCuqdrEZHWVBMO7TY5ktTOpeKI37JitHCxWtZzOZllpVcrpIiWYajAKDABuFmpCIxSomAlMRTorcrbMWC0XS07klbLbqO0aQ6MYE5cQqmcId316e3ew0zIGwGCGMghEbGIsGcs9EYxJqZNTVlDCIkuKFCyGQsa2FJ5gYdvH5TPNgi5YbRINe03Z8/TrsYFVjC5DdHAl4WVPconUNjiAa1ftdtOiJYgLILiGZYsN+VJu63ejkXJJwJAM2YiesQpUptnYaEERImgwyCAxYLIrLUdBSGMWZCWCdpv43gPXOvI58pTrdsSoq0tE2lMRgxulUlASFjEvYCoaNwchcZ2YmX4Xxx0IM6esOFECY6OkfR0ymjiwyiTQhv6Ake7g/R06GCQ9QIxESwi0p9b5MzVUY32WiG5I6jPYqYgt9xTwggJOoGAdnRStShwdEkNxxLm9HNgv34I0KVBEoh3RSkMhQZ12ytSl259tXS2HVcApAMxAwxno0wrcYqcJaSkxo/NxNemzGKghj6Hs7BQAoFA68rMZiZp2CsFUOLLXpn4ocdDs75VHugZiYOFSRCzZcKsKSJTRRmNkpJhrAogzUsMNQljosYsNwwwPQ4x+7x2IVAWyZyZJQhxfyS3qEToFILIM3CbQgO4USt8qeKeoxA1QB5xHQAnmqqr4HbQQdAb/GYtRGFdn853bGGxyv9enjktsDfKqirDmQpRGHeJQGcFEeVKBNY+RYZqxb2zQm3Z0y88azggggxhiByYGVmToOhGRJHDYoxGkNgwIjEDxLMKVtwoRNgERShcA6t+x8vk5enkkZExuQOg6NxZW0Jlw4baq1kRtowBtiIJHLtkyQxNSwMQUzICZEySqpTgatvVnknsNL2XIkg0I07Esq9hsUuj46JuALACYgRNQbAOOSWMdWyKQ4fiNjGXkL+iWHRrEuXeJLUI4apLiEHDtMJzIrmTBEyQhntKMJQsSCQjCSJDGjzJSb/1GCgCkUIGvx8hCdHUm4HiPx3AwHUA5kxF7IiRgfNEWEHYgfZflQjoAsLIDSPwM7vGMScJGEJAZELMAXG1L9PV3UHNzxNG9kBsV3bOzfYoPTMCNsySFUXq39d+9Ytr7qe1GGiXJyRu0PxiZvAIIfPtD5QyFI+tMESHkahoQBI4o5ddXSEes6TzGJEh1cq3wHWMewN09/6n5L8PRNhCCjFGNqz/hgFFARFgiBBQQm9hGaQPCIQ1JDSxxRPpOQza/aMEx4JIxtPngR8xu4qdgsV7flCw+Qv+oID2GPmDOl3DDyzHdJVemVZIsiQIEBQHloSVy+fUTwMyvWmYJKodMFxU3OmHKSN8RAOMfJySAnPA+6ZrSXQh0AvgFBhjjR9hdcRyDJLCjrPeLk+6bAxMQ9hkYKdMfFwhCAECkDGFyK2nU6KHonCfb21+Dn3Y3kk+n9daSXm5DtSiQeQbhd5QWgGEEVsGlImmL9gzCoNeT0TM9p7gzHFz7kVAGfBTXEw0A/eRisBgDIUYBUkKI7oMZCBIqEgpw8WoEAyPOd9xj1CTse9MW/edpN6YBDfL7L5YXvKuKPrROr2wooX2GEgoq41PrNZw34YmhoNhiKENa0a3dIIEOmWHoLdLgEOlQ4tZMyR4wkqp5LqMdsRRhds3kXQG4zS68SB7LAnod+CCb9Ypni5w0hM1A0mRqxESwclyIrp9fhR5uZ8dn5GN8KDEsU+mCYz8X52jDJETq9gUYHrlzyNLsDECCCrzeM9nYd7RxM+/YSdhkV3zH555h5Dd/gYroyI/vM+rXFHRh1KwqX5mVx7v4F/+LuSKcKEhtlAb0A==')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/student_sources.zip
deleted file mode 100644
index 7256169a6f823cce5b36856a58c7d94cec8c8d79..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde-Makefile
deleted file mode 100644
index c3596436ec9a956e5a3986977181b35860df0ed5..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde-Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-all:
-	tar xf autograde.tar
-	cp homework1.py cs105d-handout
-	(cd cs105d-handout; python3 driver_python.py)
-
-clean:
-	rm -rf *~ hello3-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/README b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/docker_helpers.py
deleted file mode 100644
index 806c2b39c6782ed377ab0d4cf70a36d03940fd7b..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None, no_cache=False):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/report2_grade.py
deleted file mode 100644
index 0ee13a2da31594e56132628b27f81af994dcbb29..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('QlpoOTFBWSZTWZ6nU0IAVV9/gH/25FZ7/////+//vv////5gZR73vVe96hxwfVD4XDfezyVBIFF6NShX1lVbt00Yge9bo3e7M8+94evZOjN77ePajXW622Ul60CQa73d5773z2+3bbJq9xLAM+mNA+99et8+9Y83YdlvK+yrtuwj4PvpqY09ToKfe9n22ijNe7uCzRSmhSvveerysvmU0O09174FKAtvvb0cdWvcbbW5vserpCCH2PE5qw22y+89xtj01RpS9ee9dC9zndu3X14uee98SXe2iEkb7tOqJtotrWtuZbPZ597Tyr1s7q193DqLzvhvbT72evlm7PrlOzRptffPpOmL6223vMd2czfbudmXWl2NLfd123z2eQlNEEACAICnkAE0ExMSjyGFDQ9NT1B6jEAyDyAlNAgiCBAEyJppk0SPUeRPKZD1B6j1AAD1Gh6gZAAlMSEEJNU8VP00U/SmntKeyU9qYp5qIfpIGnqaNAD1NPUAGh6QaAk0khJoBNMgKemjIjU9U/Kn6j0p6jxT0mnpqPKPUZHpqNGQ0yZDIaCJIggAmmjUZBNkp4TRoNVP0U/VPTao9NT8qfqjTRtT9RDIAA00wkJJoICZBGmaJpomp+im0mSafomoNMg9Rk9TQBoA0ADdaH+mC+99rQKgUFUq/1EU+MBFH2ikgiASFJPgosVUVP7/h78LqoaT7P9bhS/2Q6Pxq9+EfhsyfZ/i/rFYxMXT/ic3xm4f5f9YJFK6OE7loTJCZN4fy65n/krF6OOucvjmabthW4qP1nWoMtDVEWZ4YbW1eZSXgV66cWOPOKiBYlPv/XkjpeoGXDujw25XpGZ58XZpUKUZXjRxGdkcoZKTM7mMGu3sh/4ewvE/X+znsgS/JzfTae3KcRT/xOdJyd0tF+dXyt77GCY8t2plqwMzDB/6yxx5GAIiCdoIB8GIsgSCSJICJFCRZFJJPxklFRYCCr+pJZVEbf9oBSm0gIpSQAGqJSAwQIHJA44YOjjEkBvN9jzV7LfQm3Nvwbs0vgd2BrmT2J1E9dQLKCrBIKssjRVQUU/gYUGIqAqkFQZEVUguWkj/X5/7eju5nf0c4fr7xevuPwZ4/+7y5cmPCN/cj625WUChTy5zsF97i0upJA8Bocl9sds7nPk1Oi2HqbKNIjmnQ7dJW25TniQ1lRVRD7ccoO3cg6prjl+hvwK99al0NVEREIdDpjaT1QhTnof+jQgoKjHMy/StrWFpDP6HP9t3+P6q1px8fjHZqOPG83ya6MJBxbCjfsjBIr/fNmn/pyifKxG2t+EoTHxR7k/H50dvudfxdu5F4zfJMxgXFxzPdB89nZB9MJ6ViyXsrw9y8OVL5CL1epAmsEOmz9UGEytj/yviEz/G7K+6R9DvVnD5W4HdwETbAJB6vQNVtPdgvNrmfvGDQMUaj7/U147Rn+uFWhj9+bCEwd0h5SlEIsXmCIRcinqw+fm/YX6nGTR9fl5SyGqV5l3zDypYU1Pb3+hKk/V8ue/pvNP+/G3qs/UTbHDHR1c6E6fN9f4vwtcqaVRZm5pFIvrBgxN3Y4oKUf30emWhOBVJ1ynW7AplNvrXvMH0+znYY7XZ67FOd18Bo+mT/39SMpVleaCXDfjnhbHCyU6x0XwxnSlj2YtS4e/hnLfWUmv4J9xLTHXffiZl3ZLFRVyKac5wY05Utpwmbz3hL6K5+GcWq+FqM0kcXM+kdyxv90+71F0jsaf26VeNj36dZMYziS+mvZswtYhjjTduJIb01ELSRp+MxHVC7Rg1ZcyYXMpyVM+L2trt5ffHSm0lCd3wsRtHnk4vKbD81ymKH97wYTdlyhT8xanyBcm8ZfMR5/b5FCTaFNkKKLW0lDSPePNIRBIE64GM7wOwEm5VqvVYRVWV8GdRopvXK5wFi9vOfk0UzikIpCb3rkz0zgEJLpqOA4nJFKQnTTFTKtCRSWTgwq5syyHY0GY7dQ6shqyRCIan3cmuC9I4Fj4YS0CSQkCbqvIfo3LNfTt2d7GelrjboWU5InVYRMvJa2VAG6Py1ectyyRKIreOuKfR8NP2bahDiXODEb+npqbH1rClAM9ut7c8AM1IlM4sGu8Ht1+JVg5gMBisXXuQOz0q8mn28FydmbP0b1w2KhtieSAcdyYcno9mP32fR61vZ0BC99hH5rdvMjlBvr/bIkJv4gtYL2K3j6G0xO6Ut98Qy4p6JHQTMIqI/AgMPbyAcYgyGc4fTKWhOh0zu5T+tvGxu1rXHez7tTOzgTW0juvvrnbNfj0Hy/T33X0+ofxdwVDwEcRbS47HBBvt2fpvGp1HTpsk4NSccbYysg9r2csL5UtVpkJrITFw5C/k2LvrQvsqFp5loDI45dutdoxlxHx4Md6wjtwp9ZFXj+KkIlweDPF2mcHOvJ2zsMgnmc+D13brIETF+/dUXrtLKXjjlCj8/vwlfOu3Ni9UbfeZposEbi31OUIJbryP7bTBCpLaVm2XGA6WRthEctz1hy6LfzP6yz+vDCeGmgrARzzwvuyA5cimj04tl9un8FBCu9Y7eP5BOJFxaNqZxgzbpqWQSMaMTIDtJsaQFs9xwcTeg4MweBHTXJ+bszxszhnaD1oHDJpmbpFdS8F6306eHaksfT42dzTbLCTAVz75xnBHRhGjJkwUwZyOhDSFirj8CTXIVjm+jB17p7oyWNlXo+JxN5Rx2hy1lx1PrNN0agqUW64UPwMtJ6QaBNqw4/cSIv0H2HBSrONhZ7qUvEhIVphUfFi9F1WqLkW5WuvGdSwuOcX5XGZeZHxtvSSGZCSDemnXRPYPQkyKZiwypva1BW7tt5xJGflhkZdr7tkcbrtgWiwZUPn+UwqjTbrw4OyQiHX1i5qJNJk0oJc6yEzUDw/gfLiyyKjfAaupjASin8+O36utbNrvOwkcF74mm61so08I0lJi04j7+B7IONmRtkYdWq7J7nIJY9Cf3ykUys8WwI0mH3NaTPw9H0YZDmQd4voMjGzEq1E1YLfwNNtrR50PvelHW6CvT5pZXV53kOYdpb3hA6+lNUFHnIO26DudN7642pmYmaHPvQ5J90JnxuwUTbPHsdKWGq6fRJJNeTtryS9lnhOxxOFmHBdjdlnmzpswRj5ZPVUr0xGJczUtwZQfPmqxNGNWxovBJ6fXeMsXDevSjcmZj7KgK+z8vGU7v0/JfRZ0RrbsOor+W3RIGsXOA18Vl/Gl/aSiexa5qj0BDPu+Tx7bNTW+Zu0u7tbzO2zc+Edg5ZoUnD9NdIiujdbX6JTIo3Q248Y9mjZc95uuuTHXpBf7ee3YYnIMjHU4G4i9YFXblzdmLar8gvuvwuv4HIua6jvV6qR70dbKfToW2061Sy67grlYXmU69ZnVgblOx7ZUSUOR+IiyqOhAItqiReMuUIQgkJmXBUal4Y5HMo5xTcl3IeybG/I1puZtV202yzz7nyjgXlN94Ge7i/Yau0jKhYmFSRqq10LDW/viRgzCaRyDA/Hq7T8PYevNBN9jcckWIfCSkh2kBA4dZ0ltwpxIqI5FN19pZh9BymY4TKBaHr5fsOBxjZjZslX6TB1WhRjrPAiGUl+pzE3EyGO0H7SP+aqmlSKnO7Q20oFbEy3g6SQkyPtsoowbSVFNDpMEFijWxzf1WW2l2/dMKvOlyxXqCiG73C4ICfAxH8NrrBtsjqYPAFhbasm5ssOqNR2O5yZGxu+G2tkCuOhVct+Apsmb1E+GIIgRxxldMw2n8XorGgyCYQxOYipZQgN2KgihqcZBXeVgitc8L2JlDSSZqwcUPk7WbG1v3HSNEw9v7ux+ZBJocXTGc+Exs6OwulaaX4YwndGAp7dhsVDXfBgpEXXhc8+Z36k9nOzdjBOFPd0lRT6yHTkncj59kePfQaHaIuyvLMpEmDZHzmXrK6YUNtsMEhJ2weg8SO9o5LZ4Xz5Oad4mkTaa417jYuy6PdnNVhYRihEugkhSvtLfJJkeXPtHdzpNV4klRWERmdLM6X2DmnbHdhkHRVEVFYgSauUnbkT0ue/5xzRFo9Zw9GZovL2l4WeFlo8ndjacXx99ec75Gle2/jpbXqdLxq2WkG+1sssaUszwzIra1cJtJkMILNIW66Q7qUTxJv8FdxQ9+7HhMpRx1cHU13X2OUZVI3G1CdRMO+TqGhHTR8DOmAe4fPmcJ3YgubLrn1uvtJW8FWlNywnEWE7m3lR4Q44UYrIqPnIseU5QYZbWV633vwjKwK+cq4yRr5Qwb+ON5Y+dLdZVITA4bomqvJzbNp1ioUbIstrMfZU/l3y04u8lad51j0eKCbOGLMHl0D+z7juQ6Me1Eg744HSDsbmD2IyFMJeD4MlQjHkduFrEPWeIzpuDq17z373i86+FNlqKc5MN0mm6URHiIuHMeF1xXI2wzsrewnRhbM+YeaYuxsVSTHiVOV0rSX44y3HbhsjsWyal3nDnDSu7stRa9LYnddSnXCWuJ6niknEjgvzzaUPs6ZTfUy0YRk3QF4TLLHodLru1nNRTpcYt75E95wKhiIQEBVsELCu8UFrIuOWfppkeiCp2CPYZsOwG/n1l/mWyXiB9v3SK+WnVizf3eNmu/hEN4r81nsPdsOwIcwHIULoI8AR+VBgNe+ELrQWR8sOtey+7VjwLLN9nmuQrQBkf7v2JfieRsHbtuwTd/SOPfuWjFaDYtPjbOYQhAIxsTaHbZIblqIFXxmO7s989duu9Or3vUcHeIr1iR2FiFyPMm6xTyLtT8o9tlMf63VZ+DaT7Wu3WJ/4/xeHl5P4rn6H1XNKP1+OJnL8619L5xjHnl4vi5ZvL2vhO23CzxlbZtY9no87apYrnTOC30Mj0g4ONukO3giBYhgF97NjM6+Mp8R18t0CE8d8W+p7sAz2JEB0/on52fZdh2dvqyvJ4vX5RjPavx10spPjf3YZcX2zomabzVMetZ6c7pVCBUp9vS2NNpEwHYGZ1JuncpqBWEUWotQ4LZDIxSo8qoJug9P8dwt/vkpzRKFpkKSVJIU37No9CHX1pjPdpBw3R92G7PL4Pb5IvVqOP/b45mvXHEydGKhk3Y4zMuDkFjPIaKrNOsWsb5FhkTTokTI5bdQwTsP+CRZD5/llxWVgK6aBq0NWi/qdWvrw/qX1iozs3b0orzTotCSVIFj17yWJf3/X/Z0yZW4tCa24VRKTzmKh+reCbdO1k9EYvQ/11ncxrBWGhNM/uw6uS7lQW4905YroeWpVDkG8kfuUqhJM6EpQmbzB5diWP+N1onlA9JR/Kez83EsYFJ+4xKTx9/q/H+kDzw94p/L4SoMGyAeZnDDVEJAw8XfrQnkQOrg/Vr7joPD7vp6ERVVVYgdyQOfPl0FenfcVE8wyjIoqqshtxYBwhxxtiGdve5gaFn7iopBQ+qMleapWY22W2VbYxCrGQqslZVjJKgoV/vrISQBIOn0bnr5LidBu6OpKVHISAL5Pwzg0SaZNnvSbAk2QiKkmkO210U0l+AnASBZmydCZikz9dtDEFftjx9cP0u3upf5bnOaVv8EdhpDY3nvNoW3iNsaQTyIqIC3ujmjCSodpuln9lUexNLDwbR8dWsWpmK2/Khbq4KLfGFfk8mC7mf1S5jOYZKMuYy0Wqp1qnIqIi0krh36/ELLP5GMCg9Xo3yRtqn5cbR5L9kU5q4ytzIEOBJkNRJErfvIxc/aFh08LIwaPwBE8nl0waMj4MCt7opQX0xUuJVB7CwRJ5TN5QyaphmhNmEN7Dcq5Stw9DErhSGBdTbkeAWId5ncO7tuXT5M3oes+PvuFm1YqBubnZDmYQIalJlHC2w7EJNlWmgLO7FoyGgh2qkXGIfatnW301Z10kUnTtKeyKFu56FfbPHc1l5eCKsamvU0LTG0VhiQZF/zIbA1MPHjZnzGZhnQb83VMC6Qg1cl3L+G4VYcCG4pExh6FuhbSsHJjaTNHYuwtkNFRGh2FnBr7yyx3ziGkiXJ7E16vrRRDI6F6btTlud+nb6Otk64gyQnNRZUxxLU3gu133nMtfom+LumndSIfOImflwJ2mFPqmO2OuNFtN7ooII1ccYLrkgfJZjq5JB6iDPqF7deKNvdNI6DX6ZCUjs9sl/T/V6tsHf02vt1yZV/UmaZtpzwp+K2XtWL3f1r5vU5V8e+7wpz9VIFou+H5SfRKUlbyWioqx5UswYTX6DzgSdtfjfo3vbn786Pc8M81tUL2jByfMOwUOEv2ZxzmdnOfiUxi76meOUqYVLlXwvuh5lhyIfgpDzsC96aTefa51Tc98Rfl263mWOvF4dK1DpiiyF9Qs1DrbqHlK4n5LyV8rx+348WHpLFlHWujUJ6oh52SZL85zD8vB73+j3PyY9nnTxXRdferOFOlkzENNSfHCTqX/B/crLi6kkls85l+zvnlfrrZbasNTvkbBuMcSzM+MbRYhFAsYe227CXUchC8ORYrdLvrSKMbMJtjiOa5uQEFsUTRN2L7t+N8hTJ4d4SpHyyl+HEn4U/qdd+8a5qA2cZ3LTx7no6PVbxssYc6+e7Fzh9Xjs7vKOFfOBSiR0qbQjFzOKGjwQ8oSHciODM1zQ751DkUvTVx3WJfCnJ25ynSe1mVsmxzwgl3wVuvxZkEFpzIwxa79vKdl2fFZ3+TpGieDlvfD/z3s1he7Gl7z1ny4aTbjXtYxHqoiV18/t+cYyFXmVldl8bfwHzjLjmvXXeaU/c5CtT2ftyvndTfVynZbEkeGl3KR34NvXsXG8dIzqXCwj2PKm+suCdVlHDwuIK1frk91MZwlfKbxD6y8VGTzVyWoMr51znfzxXC9Sn6Xr18c/Gio46+RijTxD98ZmYflEolg+k776l7+uPXyrbeuFhPCXArNW+TxZOMZaQdyhU4Pteod0QJ17cH8X7MKxgn31wpTltPla87YiqeLJdIJ6v2EXOHjO9ed38MxmZuaqHw7yer33Jxfxxvq953Faz2IXv25lAr16+O1k8ItfueZd0hIJ6fD4QUPbxbhvndkEa7oASaRPcfaSYb4L221YdBYILoZwhJdWoa+lgTZFzIkjkQGEE82E/CWvjWKJeiJEBXhPpp8e5guBo4pH2YDXpiQnQG/c6Zkze3jxmcIL19WfK5Ivfxkj38D4FY47k83FhMtQHpV/JrE1wjOSu4K2D+EZns2Ohj/36Z7l/+T7n3FvVvaiSfffmxwUPTd3bK22XKvwglN7hr7vTIietQJS1qU5T6hT33hXXIl1rT67K5zfFjjk5tWhXLifHjrbOzKSiGWBIaan8djac7XdCLHHTrLFyRe8u/ViyQ3UljF3UltEpAh2ON96vmIecHS3HtkYZzgOCuUeD/CLZ344Y2FPR9Lq042pzTSmnOpvBF+NCGO00dQnt0h609E+RppuvTmI91hyevm0u1t+Z8MMs+vxDgnr23g4Xltye8ENcxDkdkK8UQSyB0yBri6sKxxGnSzZdnbUvsH4xxbCRYSl3xLKd6eucztbSwwo4+3AwlO23x6Kmkrellt+U/Dl9o6MRFjno8tsccR27UYmXZjSZv4X38mb6O3W7rdflkRaWXEijk8CzfJpIJD8Yz8n5WsGeNjTswIDA62WkhP3lGk3HmjwvkWo1q4XIaEXN3Z2byb2U3699GwNt8N3a+tj1pmf7NpYiT23sWJrLEB/wU/OQ68g9RFhI6zmTb77yTcU5tb7jmWAc61CqO6Y2hOQVEXXHT7VRWp7l9CxjE3z7l3747xaPW33CrrmyWp7IbXZ91xrzrXso1yjyhqwuKqZPTWnFaFz3DVmjYZms8pzrli2Nnge7xJCqPj9AbD1nZ1bg4EF90Gkm5hqu29tEFZPMgU0nT7Rty9cpd1Cp2O7k53ymlS1iS0YzU3n5b/HWdtO+NbfwqWX1OkgR9ycEhJJIBzZhC6jc6Yf7SV93kgJZpkdqC1RenW4OESImhOMpqeqKITKrCDkFWGGMw4ZeN1Cm6Te2GkkOgpu4M0Uw8NrkZAFtw5nzhGiwGaJzS6/ANB2jhqiAbQuOoltNRV0QiIX1lj+r1eG4y1pDWgeKNxCxBWCCkGJhrH7Ex8551tPwMwNWmTMxMxNH6KoTHl7hUQhYC7Iy47N49WkNsHQ9bxguAQmBXQ1TZc+N2zA0amTWVNZGgtAXVMzkB1MAeoTaaCiSBCQeJYdA6UoAm7tyGwGIYO+7SBCg4OzCpCTH2dzMFQDE5syGbdmEYj9BwVcEYZoxxzDoUxvI2/mrj7J1VGSYFUKI5m8fNkIKuctyixEpOc+F8HCFbDNUT+MM48d/DfwI6PZ7jL54ManpygSEPEvQsDnRhSY10bEkyGLLjnJXPDplsEOZcSHg1uakwJDl4mEI15ue/E3drHfobjrifOxeH5js0BQDg9SQeaUoPhdwDH/OE9QoB9TbL7z7eD44H2vsy+JINq7M/oRL7WZ0BixiYDMl793f85boD4sIkzPtmBbmTijKGFNVvsZa0y4pqSHLZnTUko5TWUDlOHh4I7NpAfyCryHAz+JHi0H1NNoLmi3QPT8eB6SfTy9V41OG35rvCps+x8Zf44WMRWexV7yIX6en8FqJSEtHMEHu9SFUATwb+hzz31Hrvk8DBERGCaLYq7KEHK2QTNjGXDg3A2ec2W4nyLJJMovHIEhk0hgxZtxcXHAL/8cZehnoj3wUsdyV3kG/2x7fvilBBW99hN2KTIkZQZxjdlLuB6BSPLtD0+zP1ejHwl7/X0e7b5AEUFRRVRURH5Uvyy0UFkRUHnGq2dBDq17fR1jBQ81Dw8fk989gvKY1qGtfi67Q47+8KBYdySWCXuDgb+teF66TlKfWK4mKh+/dZ1+JVM61v9mNbo0ktYeK3iQ1wsvqMVELGDGi7nDLGuMvQnzic1WMVt9YxQ6zGY+FDbQhMkITLhwu+Bb1OKp43T1KT0luMpIw5MGXhZqKQkI2+DKzEcazT5MRvMy8LI5NTOC8GHw9YtPCJd3fbusixWffdZMVD3TqB871eFViFSTQTExmLF0omDBad0TxuTZeta3io27FrMaxuClm0TCQ8RUzuZFdlTGJwiLnOLs1iMyLSuR3VNUZia08Terjw9XrdLfOGuUm+jwodOEuusG0NURRiiIqIsRAe/jJiMEU1Aw2qGtLFESQJdpVyxMqoDth1qsvAFLBm9pydTuOgO05GHI4D29B3DnTxLBYKqggKxV5nPlhpWPmasWHm4KdtsIu98NaNE6NjA56quq2jnKL0Od9M3X09EuMGdY3w++MUeUysdfVrjcJPxxw5UaiNP4bJxJw+HSxxYkJLU4zebrGbmqvJiJqASbnDwXq4xT5i5lISSZkj2Mb4svZ6W1yb2msJcdGWZ5akNo6cdbvV3ZnjxDdZzw9caUcOnffCMk9Z2Zxw91kjPGzJei2Nbn4cCd4wBGtuRWoyidSds54vU8k41aSQkNImaZ0qxt9K6fWnM5d+vbgfe7v9/KO8DLohwd2U3NL+5h+E4rBm68kbXdNOzjPVdLOMQ4uFUY8m15xqem8YDIHC+LwaZcIKYQm2zIdJHK6bmrdCjN/1y548P32M2RCFQdbwHig9x3d3A69HP92peoiwgHZ9RSVANyJyGqIwo1YzVp0Jw8pJLiChGFisI5IszEnSaEWdwX4tIOwDRJkylCLyKrRatFnZyyuyjJ4IUd7uwYBlTPyDT96+xJH0v+mPuul3fB7Uf3fi/z24Kkk9V9+eycGfYoV0+2ic2Xlq6+5GAcjPuIiR7YyP8JMfoP2enzPxdu3Yw+yXCxsspN/0X84pCG5RODaUyTiUnbus6/3D/kMveL7g0YoZ4GfShHWwWjFx2ZFFfcz2J7ePb5tenkXo5GZPckmnGLFYvu60zpdYmnIPFAqT1JDnhYryVL2WsU5aye+fnU8IU91jTldxTCZJG/N2nlOFItLuREoYmhtpYG3K45d5Waw+yosV4E1ljV8+mVX4IxM583qu7xf4Hj9l58/y1a71MTlDTqYFcvHkOeHr/Q/rBF608Nzm9/xf4f82IgRf30KgLJKr/CUoH/N0aoE0BqwikklSTSQKwUILBxpJFJArJiTGSBKNytkEAxCYCXaaXh4eKTSE2f40sp0rmrVDPjBLm9gzRffa0hMUMNTsr4Wqy/St8zWDRmYw5/qV5osU6NiB4PCPmo5ilMlORLy1WXNPUEV/BHcvODWVp60ZixaHo2RHdzwybZxFE5muerPGuNbuLmvExffWlYKsTrgE5cEfrNMoLOGBkdv0UNmworlLleTbW3VaWa0ifdbpZO+1bd+TZhe6GczsIsSjL9Vxg3OdhpYW1vgktS86xRKfZ8iLJim7GLlx5O7KfLnUxnbBoQ+15GmRPitB6BjJqK2LlMdpIjwbv7oSh+SIU/4nkMYiUzZBTn0c/fN5HbcTWOPjW/f5/pBc7v8FBA+b8p8f/f8J6+2iuBgmcCMEGKlZ8bO8DrTRPqgYPlNYNYPxW62R30VSohfsUPEFmUjqPPnn2/3E/Jk5Q/d+P1D68tqCqlPEYw3hDeTODjQ3tMD/qj+w+PRw/BJbv5X1Dv/HHcIOveURUb3YtkDLDSByl5WMCIQQDrPac5ShCH8rsHuW00/y5X7mfj3bT+gLBAojPQnawsdB1DqY9wkNOxDJjwMiINgDTETn93+AeuUYn58TmMyJWW9cA7zxLBe6AhHoIZiQo9C4zj3KcQwEe5ZEJEhAIqujqp7tZGErsGD7Dy/m4DuOdPjTEtb9AsN4OzahB4Qkw5TnHt5Cdzw29OppE6bwResWWMOb5IzBiPlkdWguUxev0+zzBt6txoO6B74dgSBDgHcxOPjTfNIE/h5s0XmR4EiWFXLdl+/8rf4GIhISoqBHEtqMJZTA2vwDJA35NMcNcWEAJAr9xYw8x86vVNGhVHxkJQn8XuCzB9rlqqqmiYOZsN8xBA2HiEBDFiSLj4ko7ip91SR8M3p+RTRO1hafvxN+ctZ9HDECO7u2Ld/Wxq5f7fdr0uYP6mPOmxWxFoXjVaHM/0vhzBFB8EwoffXcCZjMSMj2EOpqe+qEkkykPjOwiYVod8UskU/QcGec09iT/w5liS/X0tlx6ea/UITybNeSMhBCsssiOk4JmAIzxJKVsJ3nvlEfDnIzn6jWPlc3/Kn9N/VmbnhwOHzZuRncStZ+VvRMi9xP+xodBdsT9GeeHT69obNu+Oot5iQ3loZzr3oD6waBjf1yDGhi4MxTodl6dlKwf5/+EJDy3rBdDC+bhIQ1R9HV4LAdQGANwPy8n2nZCPWN+ad79Es540HqTcZPukzDTkj6vszNUO1/W5UpJCEgaUwDo510ghkkBmnCfk9rK9yHwpx8ft5vB+lGJyC2+vtu7zU2vKXunHdyyVZ3+GSprBrPhHhHSHwLAnyqTopftqekrwtPzNpIOUWh6fwu4X2LEOLjHWpOiuBOqJdaoep1IEAl4Cdqp84eYpj2INse6dodyCXdqBjrnsTFeHxfycb4fMquOqdDqiHJ2eb1sTssqbOwOCVO2+yObSvTruzTWzwL37cawteJl+R5xcWUdiPsMeDaTXg1OqL6cqBv+k99mPlZ504NYpbkmkE600JkhNbuKq6euuvXHoiRBnNTHR/230FAknrTl6b8jo65snXpCVeZzrEqMTrhzZHQQ8NedaJ5t7u7l1/ieJrVsJ81MxcU5uEocmY6w6p8JIx39hFAuo+4SHUoP6SIxqOUpwoN6fnWxjtSl6aZnr7dTjPr3PPsVVUfdfHKiinbb3FKFenbNen9tOrcvDBGA/I1exm2UDkzdmI5f9+HS6TSkfW3dP30zypfu7bjvZUELbzastLzun42Hlh1jr/DiQSXtskYsv4VXS2iCs9fjgc2RTQm1WgnsvkctjfXLfyc11dGKdW2YMUWL2Wi4Mo9e1kvP05sqatDVDpFuVYklur48LJhK98rHSTLFh2zHHTHA6/vwUBRHXYJw6eWYNR/C00RFTmbMxE8DupMqUO9DWi9t6efzIJ9z+ab0/fPLObJLi7Hhs+5NiJMqqqnxwkpDTTP0diSJIVYj8nC2Cl2MTSEuiS9i5w89cfTPSnUrcCXih5rczxhQfZTjV625Zndyc9RCsOStR/uTPe9uj58qR5q/dw3yDiiy7vjDFSwsn69YAhBnm4WSdk7s6KJnRyR8I7MJF1+xDd6DqmZm7E0+5DrO2M1tlKcnU3pE1tEfnmQU8XrY/Neyj+qyJ0nLCe/lc1IAdlf6/Xj3buKnWsrJFm1Z9xbbS9raNIkc+jser+rzjzh6qqnbESwu/dgnjInqvDId7th6L6z6TY+e61rU5DdA7Sog8oaCBGiMjGbThws1dJtF+791WILtnPfibZ0itzk0V48v6Z7XVrbv4cK1fl7OVhQ2V6HlrLljawcztPlEe5MznuNSh7CKlyZRGp/y+NJaIJ/3xsNnSxA3t4L1P1OOcFB8KBkTbLXSqRQgKl05VZlzEZiTZnxAhzj3J/jSp+LzOwYCAqEZehhFrKeqZmpdYnrPYQYFwoAoMw/kDAR6ZAYDwLn45BhA2aNJLaomMQwYuJSvVNYUiEaHQQCB7lR1mgdAAb40jVhBZBR6ycw94fmJ2dcPI2DMh6DFioKrogOsPuAstoSLpPoOrENgnzDpDqvnoJJ0AQFR+I+N1zCeOUNXOUZlnZGwPm1CPeL4LeR4DrNcdI6w1+Tie4IY0ahNXQkNDCmmWNw8BycFdZCBFdy7HZy+JJiFFMhCMxDV1UEU2BQfs0i0m0MdckhIdxAuuzZS7CLxpBrC5ADQEoL0ZHKhh2B3GIbAxxWSdkqHajiBBgUkC00iWDtNZ1BgOJEHmD9hACkM1gewSBoXXl2XGuQUPk6+Zm4jbhbaJZ04JW9MCQdBBhceuEc6Cmcg0RNgUjMks94UN0Fh7/HcIef6Fxlr4zQLosYIIoKOpzkRET3AeQESVwOK4lG3pRx2nFmFj8oQLBc2QzpKJEOs1YE9SGT9uwZ+AsUNxGIjL8UHzE80h/jNi5FUhfUdzMa6jklyYczQweWFITAKMT0SGo7lPwhICsIoByJZuisPD87ZDJL3pd3jR7dD1H5uaA5VGq1AUDY2JowQUA9Qce4TwVQB64SbSTcWCIDInjNHgedD6TgEGCK4hV2SKqwKICAxlpWF/i3Dad0VUBVURUP5CwFDkew0CVSQskCpKHRA5maOQ7BGTPgPrp6v7NCRgfQUBGHYPPeGFIMQhGwMSx7DHk3vg1jeJPlbn8eooTawYYlZHYUazZRUZsS7S4ljtOYg2TgqEf7OKcy3eUWGPNNAG4P9BRciNECRkSLEYxAhShQsDjiHZKgxZ7dGDDgp5MAX9hAhJBDiJlgEPIQMnjYjo3ZjmSA58yOV4TMXQlHYgSrNcHSp2prU13oFoh8yeh2BG+YlwNmux9hCBDuN4d56VSDIfeS7SbsVYwfQJuAPr6n9kM9kYXOAbhD9AgpvSARCRBiRNORAcDLXEOiREqJU4L2gvss/Pl02hGHRWwONkQiWCR4Ak7PVAGMiiIRSMCAhEDPshJ+k1dYbAC0ZJPpYlg+75YLpHbETc2CbBqKd9ec9mLhbAUMr9p2FGg9Z2WgNYnsXgFBiGRJZXQYI0YZmUVGRjiYAc3vkiqyCfx9SlOaeQ0Sa9MlksWoLCnE1ihWKGRkecFxoDwDNbfh0WUePHmmiqpdh/ANgh7oB4XkGqibgSxYOZp9PoJ0xqph9T+4b5fTEMp95M8qnHLQPSej6xOkD9/yJ8vKFfFJ8NiObaLnhU+G/cPnxyFJxajb+wqQ4fLTh7h6MZclNECUFC/22CsZ2/PRfbAqEDkcG3Q7koU+9JogmBdAo2EN/0z/n14Kah+I2QZvOCiG2xGuqKE2JgFz8Mt7A60lWwPqn1tkzUTwOowgQzJgBhRqg4BxKhHu9/3mkZzuKgwUWLDfkqB65yH6xB+7/ezH1Aj6x0HqgMafFHhi75wGZIN35EG4TrWqiGcD+Ts6HK0CgiQFR2Q0g6pDSQfvEjQRgM5dJTIzIWUOGbDhaiR8YXpOOIEkNiV/D5J+RgZfbUps7+waAz5lBipjaPdUKD1MtsJjv/lgTRkNCoskOvzgKC4HJa0zVkHCwZgCBn34u/3WMgbeo6AziyYxVYUK0f7ap9nED9IGcIGjT09RN2EKBDuTE5vgUmIcjulrau2Inv/UFzlr99hjYxC0GFiyiEoFm9e1CoNDtlxDWECZFEOgfQ4DOowHBPuMgSiIYj77UQgQxxK4obkgeyQpDuD+4N8Q+FP+/9d6YRU6RLA6i9CHOAHTPjID+8onvRIoikEBVgegoU7EoWyNvSEtLlUsMQPDQcDb0Mdtq90ElQ1XJ1rEEpYQ5ysBY2kXbsabYMpNTDLwgzCVhMYlbDOWASK1iwoIDrVcImZK6fn2lm1l2S40GQz0vC72wjw5lNX8wbg6rHAtBpUTLtbzimktS3abYWSJOzd1vtoan87VXZAVmCZy1eSS2wRbE4Hl/yNgz/Z/k+0/eKMWLtOkDekGlgWPKdJRGyFyYTIMOaw1wDAAwMRbEUoKYvsSy9XkO+Pu9Fu0ufGKhYW1irfbMn+EZ0yaBJDse4PryozMS5LUBIVmAo1MjgFIUtoY3ApKbB1H4xKIrD5XXero64fxpJsgHf9jmImZFbS3LijmOTGohbW1tURuoRjkQnIu+y+Pyk6txi1rHA3xYC5bT0EWoJPmG7yDhR4nPofwLnU/U1x7K/nmUtOIn7e+l8QYa33Brm8kjBvSxrhAosxQ5B9AtZ0rp6ioVIXF9m6C8hgeh6gb8yRU7YLt0Barz8QQS/1t5bFxh2P8ygO8HcSAQQJmRx5wVE+QJInY8E2p2+kVO+9wYC0WUoeGzuupAQI/QI8rRDFpCYGqEiC0tKNJj0+fadnlnfflnz8Yc/ItbJYzRe5bQCUuQWFRPpjslMhphNI+TUWad5J/GnLxZY5xT0XcSi0QtISaDDykgQjhnyY9Ws0sMsD8zsCjHCcOkfNQ2zLcGHORFGOMfPEa/jiFg2jK5z0hs88HHBzYcsrW+Qs1GAdDUzqUElahv2o/sI3L46dmH1z1MOKQzzp/z9DVmTWMSGFAktJ6y6zmjfHHUWjqjfkbbwjscIydWcrd9tnWB9Bs8JZYHQNYW+BWxqVpHEa2ydqRLJpl43IRNw23pB3TWGmzw+HjFFCIe26Z8tWSUPYvBaO0HShBfHD7ph8cOeF47883ASN1Y03kTfysfVp9KrwzizlbTuk1VPqKLb0Tc2xxHS08VAfaiTx3Y3JilA9xBQhLgUD7jKL8HJeIJi5NkKtCKbh6M4ILwPAWTiTBTEW9EsgkgJpdjPO6ued6ZYKFF8SNMElJqiOLpuMZ+Syat8agglDngmZ4B9plvjFVgitA7OiEQOndPT1EpNMSslJPfEZvL7551hCo4nitc73Mp02llYMocm6i7qCo9upbCpCy7ISfqtytb6wgUlqreR6UQ2FA1J9VWgtAnKY41FkNmZyLiS0XMQdsWSVWBZbxvpwSZ/QLNl+p3nnxq8l2lE0TWc6BuIq7F7IkCFFC+U6i1268vVAVYD+LbKGwCpm7hY2gRyGvDCMVzwwDJfsi9Acxsf5EvYwm2coGwdcGtGUe141rstSbuyaZrk9T3aNTOHk6REmZYTq0Yp/VgyotNg0uFSJdSsnHecL1DnHO3WN5Y2CLj6x2NNNGyM5dVsIVZrO99LZvYxyOGg8AxzQOJuiNLoz8I5gmd5mkWKh5Qj3t0wsrvnGomNO0dMUSxOUu1StXTu5N6idVV9Kyodc1cSZqii5e8o1qzyRMLCSb/bfOWJGDBCEWRLhscUgawsBgpriUbHEcFbjFYSCG4KCO8xXNYmIYglA2TMMi6DENjMApD4NzUYjdMgTfkSaOXaGxrLSHqTBZLQmzIcv5d0ew6R/HAxSxgGRb6Cc14mg1gYrtRf66iQJCEERQYlmv5OQMoDECdJkDkHTGG7ujIhTX1mInFxdkSrocXR5+i6gV4ttBCCm1sREZTo3MA1tQlJylLF8mwmwtIoRx7HE0sDfKwL2b+wgI5sm9AQT7uBgao7jNBX7yBmYuY5WQ2PAoDgcAoyjmQT7MP4WFOfbjrEBT6TPN7OJq8gbSCH9AQdgZIn88R+k0o6h+07DLSdcJESuRRbueeA6sMYGQ9agWTPBM+Gtme69IWJg0okqJJKICYB0AD8BXHtPxMKgFiF90DfWnT7nPlSwPYP8zrdqh6kMaNp19/yTXzOBgTzUAWGxKZ0hysMB4w2+AN2diq0akKkOQePpiDMOu8mJZIC9IgjCDIo4bEHAdQ+sJs1fEXdefd658Kd+sDvx4DyiIzoPQk8o74kInQaBMOcB7SFA5piz+jMJKDlsG+ZMeNAFmstAaHYcnME3nC3wry9UxRwECZuRmb2MesNQ4EjdXBCxkaGGJsxLKneQ69oSEHaKil2/THhOTQwibab4G3ZzUNg3m1BGtMB0YYbuyw0DLt5+J67VeUz9/OJuzOalD2oLJJ1BQjA7n8I2ftkKEXZws7beAPkypM7J1sbDpGrcOVdPouHJm4+blb17cyjOgbRY8hyNtpA31ka15XjfOLLhthHdVoUTm5SstQm4vruty57G+1mQJk2ZAcTAaQxSOLKApERQA4JYTQH2IpOwllCDECLBZIrFIqebwqxE2IAZ6AbAaiTIfNAYIsIgBrl3p+opRH5v24GAoIMnhGzcbI7ITMEYFG9xIUKXfexwsp8SSEFguwC5hzr+PddA3AAb4DHAL2A9/pOuDCHhHjgrTHhCwn9EdwN3gQMU0Z9r+P/jDIf1GbY9YeskCSJXjTCihqFdgp3qsTAslCdqP9xEQ95y7vJOu3o/AfE+/JT0sDokkzQWIMaWCMVpSsKlghWQoEy0xnWabjAmgYIjEAKogpKIFLLIoiDFWJCMERVGRZbUlD+jEQomCTGUZiWMKe3b6jbM8dSqK/mG/YNOwOiNO0IGujCSVZAvEHqIqIWipCKppMDELKD30Sj5Js/b+J+2MIS2QBoZkaeBZ3T8IcCHm+uiRe6RCag2df4PndgvYPkgQhIwCBR+BQHRfpDWfbsK9+n5fWe7vhkiYEOUdFg9/o8CCft9L5/RTIOe7O6FpcixYsl4wMxGIRyIwzbAYrOGGy+w0AYbAiRGM6GnBdTVJRRg/lNE8DW/8o2MVYisiRfaJwTcOjuuhjyI82cnwGIr+VPy/p0ZfKrdofb96XZdlPyxmFEBQMCRlSCmMW9M0Yb00vP1Y1q/NNeQobb0V5z3kRxas+J9jDgcbWtAb7XieozDiLLiXfmmtNL978B4HibReCGqhPKQqWE7BkophQrCfQ6YTCMQEiqdyIyfUcB3hgTZDAt3LKFLJSTkaczKKAsPDt2lMPLJA646BcgiMYqOssHgNtA2TjAweUIEm21oRgWGqIp09GJc3i4LM16prKS3IOjKjAWlbaQEIC6l28bU/QNIPECJuttCkR2FtBrgQIKyKkIDKiEdBTR38cynjKoXraLWCiiMAc4VBkMiEXzwagpJBmzG1lnmGzBkBCy9k3DUNQkzZ5Mwxx9DoUXLKQEwRZT7uQfnSFNEoHRIJ+FhWQqSopWNoyJYyCgpUKJFkRKQAjJBRzzMMxv/TCB4B/qNYGIGI6tIRMogLUSDdRbEEaCbPkO0WIY8XzPNIsZAZ6fVd49vj6/ho7pvL+zih6OlUYqpEiqg1rL8S8AgKXvA8LCJcSQ/kkYRb0KlWLF1nFDwDrtco9jR/GjaQkIOHnJQM9IWPx92aCA/Yg/EyahDaQsIbHBi9pxO0+sM/iK5fYBIkSIHedOPl7CCyIUcjyajgiaWW4Y+ltQy+pUy7n2OrnYiZ3w8PCeFJL6SRBCsapj973pFYmknr3tYg8ba1d/K2lqtmExcqGM4ovSuGYwadKPKSUG1jG0tCSw90YzWgdqOWFYospq8nlqs07MFu+uephWExMCkwJ0RPAgbTevxGw+u5cfevaOb46A0h8H5iIHlA+mOlAIQA+aD/UQEXCGoIA7/MLoyDECoEgBx9R6Q34Kofvnj8mBgYS9R8FDA+YsSSGeZFissaE+YMY5WthS2W0qWfNZTLFBRZbdiBZip/KVtiieqCBISBIKfGJ2JC8fOfW2iJIGbRIyIPz+k7zuCsiAdzkCdw/PqCxKKOrne/hBo1IGxUIKugPgX0ZdLHidPoiia38iq0wlmp0XX7JaWv0y1WCid8xzd87ykbhY7Mc6pLBgvwmJBTHUYBZYY0uHHq4C8zfcYvWw4yoOlYGLo3xYRJYoQIsIG9spaS2yS2/YXM0KM/SWgaRNAVe7yIJRE2nRTI6mTRWyFSzHncrHayAsARkQQiqpCKEgrBgkVCRE69fWRU/NP/5BoYOHPmkLoB2AB+rSQaF7AQ1iBxBhIvroaESEIkkkJGSMSetPJ2geUJQ4LwHsQp717xoPAZu86CgW65scGDGK4FmLi1VqIEC5BODOINJlS/zCev05m8D9sqqJloR6gE+4iHwIm/Xt3cIeRRD7jqQ+G885u0u5R0hDGBMxC+zZrEWDtPazPJjGAfR8OrdD7jaGntBfELnt1nKxYosRjJB4mF5gVg9oQpT0mkM0F9Fj9ckFMwoxQtFUMC59htYQPfrjSbbGM8hkK1GDDcGRsOP3jssJLNasHCrYgftYaKM0abthbpUR6CQ++76q5UmULhEMUmcE7aEtFjKPJipNUNQZg0qZPkKQXjr4niBXSkNA6VPWXwl7SLcuTSzC54MaDXWakV8j3zDetxX8bPF5cE+dRIRxpLwuq5CCXtp160TrEsDQg4RtcfOOtPgdx/G2OV+zMDIDOlNfny1PoGIvnBw5R1vX9/YAQgsYogoJGIAIMPR6Df+z06+z3f4t//CG2sxb1rAnMbRItsKOsOvHoGYtWskWXHydcnTkuGqeq02rEqUqstKtYaNs1qQV3zEPRS/SNA2UpdZQUbYUYK4VLaxFGFEIpVSsUbQrVmyUHcKDJqU2EWJdZIqUShWlg1KkhllcvhBgrgDAsJMBXQKH6C4bjYXR6fVaUodiYbzXYgCEcwQXCZBoxk5kgEQqSIV7t4PEeRsHEoQFOo+dS9h1BwPEp0lBAgVB9H393xDF3hImjkBlJlosskBQWHn5hR9+sw6yE7u6LGR0jzuAiIpJiOUIectQtkCjJ6g11fm5GJ5gwCDCLQgUrLg++bqVjELru9HUaYsV0bw+iSO2w2DxYlM1xY3ABuHA0/Ts3zrPC2wgRhxFilNVhvYC8bGPjsFHjrIIwBkgMkYj7NvnVCLA0ZfpZFxENSpETQAcRwgL+XT0Go8kOd2bjknJCJDs4d6mTz4reINa474jb2ZTm6Jx6NKL5LwBnG0OV1NDMwMQtExJARUQbLOpR0hDpy6FRaSvV5Dsz6F36DAyx34xBzTRjkoZv1WgSBfC/l+tXDeSIavyEMabBsAlKQFHZvL3GxBsLl5ON9KmI1Y5swcOoRoIvcJYiVUWlBKRWJBEogsaQUKrCLBGIQWo2jBStgkgJv3mSzPA5AH3iWgngViAyCTcsQ1EFS89DxNxiRp7WN5Lk7TioVEyZ8XH4pD4rn7ayTswzDhyRmamAWDUazENGdp1kXMzlIZFp5upcO5baS6TqGC33BrBFQTBB9jRRocDHBso2U6i7aM3Hds8Ybf1TjHtpKMrVZtQB5jsrCSbiNlXpW23dt0b6/QVFAh5ttw4rUDE+LtM/VOOawQgQIEvNOmCAd8nICiTJupgfS+UcBDTKmkpu8TaHBgMelDJnZFQgLNCpmlBVVKUZuwLw8WGKeBCLBsFVYQYZIFgxlCAQISEUKi7kQkrYxNDsvEyZzdXEYLA1vQ1tGnWbmi6tjWWAZqyBLhkYDejMTehqRRSSjCVURisExCUQIctSxUh1clNUNLl2O4cnWu4JNY7bDguVmZjFXFKhiKSoyYzCF3KCkjmo/A9TBwOc5p7y0FnkmuIhy6ZkMhCCgmMU1RG8C8dUUbxFSq+JXgXwSQFtFmIIDFgCIiAQg2DFlCs9NfIno7jkHAybHgICop/n2NtHQ+ZkgqoJ68KHqrYjtUuW9VTknHDTDtAKsLYE6FgtnjJuskToKELsWEMmGE4iAiVjMhLIiGiGEaGsMDeBMklNbTCDcKSgmJFICIoKRQUBZFIoIRRJAkVxKVCBENQt0KRHwbgciBjcYsNMkdAEEG0FQ0LnSBCXxO700EZZRNSckhj8tgV/1IruKIkiLWpQtu56+m8/4EI947tRIqycWARiytR2+ayez2YfQOD60wzmGUUGEnoGCMJInlQ9aHht4U+3A1wrMATZFxqPyVti+P0NDwE7jp2Pcw5c7lECyVGRHEsNrSgaIgY2T9JiiXVohBggMAhAIirAiMFgjCFoiBQ2GgrEEFpLClCtBKBkT060ZxrWMUS2sERBEBiIJDand3vS+hoj4FLwG3dgHOzJIzBhyLR/A42RyTRbtlOMD6xpjKralI9P8wnCokCaSA8wvrzLXF6aX6SZ2ZIqYm+FXNTliEddBSahE/AjFiuuGk601pqxxt6XyH1W8xCvAzKDytX0u1Jmd1RQab+ppkDaBhShYD5IcoI37PiQBhFIFkMykHJcEA4mhTqHEUf0BfX9pr7CMESdcgkRURGIMZA5n6J2GQ0exDf8TfdgusUuXoLBTeQIh8M0wLCP3wEPMBoGCyCRILCdVCwQLKqyQKCQgAVE6uspbg6AoRxBN0U/1o5xTPNpESrUDddNvhDMRu7yDrIu2z9BOhy6gwNh2JmbADk4Knk2rpIFRMHHBPUAXJmUTqDlShkQX+DGwKwoOMA4RQ0yGDIwZjrKVDNKArtSFEebCDYdFLISDIuTsa/nxzVGjpk1BSSskyxsT1qmAYOIQKDAdhlJFkAO1V6EQYdowACgJJJrqSJ2Hzv3/2U+Z0fApUraIUS0ZGSoPJOxdJAIiGjlHedcQf3xA80IQEsQBIjOib/ahBwLhAhDQa22J+wWdT0jz7SQgQduKj2Cj2g+cOnmeo/P9WRSTSIw9J+Aufrbg1kTQWio2CHQAznPfDv+qQYYFod2RI/juEHDk0RfXGRkFrmdDtKYlRPdSlCL6WBOJ7S0aTvZGJb4fN4LA+8RlHYhFfGK5lTwGMuyI3kQ2FQ0JzIwMOA1OgBQOUOEmigrMzAyMm2WFAuChcV0g5Kg83YMDoPM/OnoECwEEPrCtsvPDJ+AMDeeUCAeRcoaDRDXj3qeJ6d2ksfDQng2x1hXs1HVwZ0yJdaYdZwAUSQyoTjgpWeBzy5aeKUMkJsnN4A9CAR5m4X/KiU3OivdZEyWEhMQB2DW5L4/lzIbkkppoD+oJQ2/AL2L8zbdYWVOeEJuHArIyF+E1bATRUNtxowpA7NwzITUh2Q5bn50XYDzcjDKbqqoEQZAQYEQYAsigwkkRUYsghBGGlK8WtiNIPrNZKH1R+iIFCQnU2Qfn6m3EdQokhCjZRbjfe5PInAYbt9BdXz03YXgY/Nq+sy61Yo+zb9OtMWf+kqurRby/ducmbLvlTIfDL/a6FTB3Yck5OKct7l6ZTfQ38NPlZOZDGWYRwtsOIxhNomF1A9otgkETgRYLQjX9ZOPE+tOtshzBgGYU0BEaIlgDDGOLXtaNCEELqOlYudCINJ36xM5OmArB83LDuDBEeHiJntVUzouggmkNnuh7F1Qs83L2Y+ksfjCEV8MKFnqf3ikWjD4kt6pUT3Xi0UI+tkuMw8Dt1XsG/WIJFIPlJ9BQ0TjsoHYXpxRYcxj2dhk07SytUE2GiVHOdfnBtFlE/hIHvdm+0mAU2K5oghaP0GZjG0igxIiGxmYSLFIiWN0NAKSCSsKyoojSQogdNHSoAPP5w4GvRAstUMdyii4y0DTQlWiUEmVm6asbJY9y4WXmXk3urtDLo2M04bIbQSBRCI0aUXAYLq6tmUECxusCMFTYHdctl01WFDo1hg0eBCpt0EsIn4RiJ80D8YkDQrz1HHyUW26Q1O4Ki6MTQkfuQKXEJIRjAiqKJh2wOJyNSTvJCYG4ILbg18Qph4GSmR1ggm3VM+1TubMWLsGpKShD7esDnThCw/UdZ1qb9R4Hv0cHthF2zbHdbMhjmTkaQ4Fl6E0rx9tqSQ8YSig76aXoQ7ukJ63dhvOZcSQLls+1wFtcS0BQYDgdCK5ZgOWWUaJtQvTQuUKiafsTRkDDv+e9OivaFlOU09JKNHMZDWIaXnxOu4NB8k6tdiFtCxDmmooMfR2mHHTe5H7oU90NvPyK6QgoQtimyMhq4U5wLwKGsnZ32fbdnH59U0aaJS0o2L9OY/a6cq4knAoKId0kcVHQ929q6AaFUZNcw/d5tQ5HI9QQO5CSPYDKsNL6YtL2Qdtpd1TgNuJCK0wBzRVL0i+KAexA/zsJ3n5ZBpEPaBE1EDjspTYDAu1EQJEngptSz9JocoaYpIRgIe5U/aw3d+J3R2ydPIWtND4CJ927xDafAyy6hH4xyQ605EslwkRFWSIwzKIwWOivjcRJVuGElFVUgNECCxbgygWImvAEMELurJWFEkWQjBCsiAhARgLEVKktBsFIRZIQUWKBQJYyhRAsEBCgMQsAYIIyRiMSnynlFghIsimk6Q+qC7ggSehkMg8844LGmw4dNBEDgDZBn6nmMP04qZGPQz5fKrONt4fEvm2bVwZHI0seH1x8c7843NHv5W4mztqM1pjNkDOjJh+XqAUBb765LIOOu1yPZXGGH+J93coyzT+xsGtPNaxWXIStzAF/qHZmxbFYHEIdkP35jqg1Y6guNiR6CC2kjNBKNjuWydMMzpBsdnkZE72EtQUCxyO3WHAz+LEcoyad7FUUdOIPksYfK0r0O08b2YLZtwvxHvjdctJZb4qRZuVzzDupE8JqBum/cLV3dMqbm8pNR+qnaar3CbMid0KIObFkUVNy70VDQT+EiG9c9Llky1oUmJMLMmXFtmIvemgxloeppjxbmdTRpk1nFKX6Qf0/SYMu5wYZh5zTrccQ3EXjVB9uM5s3bZijW6q4mKyZ3YG502DxHZzDtqoda4uawoFAGP1YH2tfULWbEcaqA+YsszLyQiwL0QMwTmCglrUGRWJ4M0QlZI6i5DE2ATZ4NZD8Seb1AkNSGPJCx5EzAl6MVHExY+XCEhU6HJpeOYx3DKbMImGP+beU//svicEkpbpweJypPWc9PI4ydjursxVSymtqbOmKK2RTlxE4iD3XppCUKnki488eVz1LxzL6mIwaGYXw5GIAUJBGFrj6dp9p+bCasAzHyp9hew3IAUHoWtNAtvYw1S/r/LrMgxxdpO+fJA29swObocbPX1dRA3IhpiQMokpJFIYI3G/RNFMh4yphZwIVEYxqUFUhuysI4AgUDbYskLYYE20SpgOAFiliQGBMzxZtIEi7oUx63z59WvYWsO/0neQwMAzVDEkDPn4wbrjVDag1lsg/VqiO2pQ2EsYyMZNIXClSKIVkujIShiaPjHWJqXEdqYuqWVjwnB3i7w8CI5CmRmJhRxELsDEV5MZgzHJq44VpZamloawos8x5T60fC9dY69lCl+IboAPbF0wbiWCM01z91EOy7hLypS61hp6Hu9Sqa1NwxXMzaBczAUZO5VRFYqx8L1aIX5Nv6HFNO47XcPpxIQmZxRDqSDnlJHcFtjGBAsWXeCQceBO5D9xhjrzTQ2DzshB/INGJ5A5CdTC5z98Ok33ZRgyIXZLOhnnWRqBV2axC0rmr1HRseV4eqhvqQNSKogqKxYisRYiO4qOYGB9YmGQpFqUtKiBAWBBgBIiMOcE5ohYbARGZ4rjLPOG1g7F0jrbKmldJLAYmslMFqiIhlqWhYTC1klYQuDSACmIYQ2iSgdggknDOntMnXGiNxk1xPqi2ssx4I5Y4mBxFohouY3hGDV5FmLDeJLXhN5qxV1YnPrIZNTX3c5CBrFl9xJZ8H6wHXDHxVk46zZ69so6DKb4Yh9UfpsaAveRoLtoFgYuSpgYkMU2gmChdNfIzkPUPIE618bYJ4ZJAHqphVz747rFBE5J2MVPoPOkIXPshjsjKDPZawOhnZB7/PvPRt48989DVqPQH8SKw8nRsOZVndQcek96oWlcPRq5fE1w9BCZvSDMngsW2fvAk4YGQyXVJxRJ7aCmC7RJ+hbsE1pEWb4Hp4RzfEZhncbs0YZ7JVRS0HBKJd6utJiGZRkHL+qu8sTDpg5ysb67qLDTmYrUjyZRQVMQ3DnSBxDQtCCzQ4YRYIMwg3gZnSGd24jijntDFG7Ab2MS9qZT23lW1kQ1BqjinwLF0boNqVtuLoRFmlC8J9uVNVWGzHNMpIDCCjiRKiLHS6CQ2po6aqN4tGR0gGDMzStUaNDoKYqEGEjRKNUkqazkYGbaGJo2dGmoW4YKKZDDibApQRJl+uIqfGqjAh8TG5qaKIVRIqfoVpc5fOXy27mBSTY8iFUwEtcyTGnY4yDszYHs9LokNGrVSMubIKdC6QcuXY6KRtwndkfTN2IwKhAhUkIVGjRqga1JgPCCjKFIiEohcwRN6ZZBsDcQblIqtAqGrZ0Umw1soXHdpscyWpnUvFEb85itHCxWtZzOVjG2ZmxLCwhkTpNgobATQZKowjFhmwZKIp0VuVtmLBaLpadyStlt1HaN0NGtCZcQqmcId315erew0zIGwGCGMggZCdkyFgzlnbGMSamTU1ZQwiJNjCU1BHJGiCGV4IPVx9pg+wxNq7hmDTcZ2dPHCCY74wuQ3RwJeFlT2KJ1jY4gGtX8nbToiWICyC4hmWLDfnSbux3o5FxXIggW2YiegQpUptnSaEERImgwyCAxYLIrLUdBSGMWZCWCdRv4XgPROzkdHKU7LtiVFWlom0piMEXJluAO5JstANAmPoD1lHKNmv026dUIM6esOEyBMYmKPN0ylMvoFiJFohvrEhY1PquuIEh5wRiIlhFpT6nxZmqoxvptENyR1GelUxBb6ynfBASdgGwenwskrRwdEkNxxLm9HNgvygjQpUESiHdFKQyFBnZbK1KXbn5VdLYddwDGwKWEYxyaYVvGKm6WUpMZPxcTX00YuUEMfA8uoUAKBQOfCxjETNOwKwVQ4sM+WPYh4dh5GkMx8oG+NC4TMxHfRrCaCKZKijMbJBKi1BBg1ZRFFkKJ2Immhcc8zvOevt7NCFQFomcmSUIcX88tlCJ0CkEMDLMYyCA7hRK3yp4p6TEDVAHpEdAEOckkivedVBB0Bv8kxaiMK7P2nXsYbHK/ip4ZLbA3yqoqw6CFKIw7hMA6pCw+4lAm8fUsdVaN8ZsTbs6Zc9a1gggg0hoB2ZGiGflPKmapyuWNJFJAgERiB4lmFK24UImwCIpQuAde/Y+739vf2VUKYRtD2Hs9xqa64mw08MzWoVWHANsRBI5dsmSGJqWBiCmZATImLbZDvOns688k9Rpe25EkGhGnYllXtNil0fHRNwBAAxQBMXhiBtViCl+KZhG/8BIQihRj5auSxvF7fQK7hOVrL1iHLqMp0IrmTBIcQE5dhTZpIwSCMRWEMaPQSjj/8LEgBIMgIX92ZAdMuuIHiPtuBgOoBzJiL2xEjA+iIsIOxA/PHQieUDROQMh/MdTuIkjS1CloJYTpANjil+Tw91B5+uJo72QGxYeyePfYoPhMBqshtkovVv7t+9Ytr7qfIjDRLk5o3aHzsLYoCQPmwTzBZKGdkLEIJ1l0uQASOKOXZV0hHsOR5TEiQ6+db4DrGPaG58v653V37nAgQUYoxtWf9MAooCIsEQIKEBxpGN4BwYCXVLyMtIM7zsNW/7SKQmSppvX30FToebrtLhc+34hYfcL/hCA9py9gcrJ2kT9zkTtW33tyDIsEKFCUHOhJYL8O4nYzN70zFJVDtguim5sRDBs01VQMo8zLIF7cj4xVZSXUQ0AvlBhjOWfQXXEcgySwo6z4C5PsmwMTEPUZGCnKPi4IiAIWAbpoZJj4zopPB739Xrv4vV7d9Kv1/jWkl5uQ8iUSDzDcLvKC0AyoS3Ei1E0xfnGY1Br2/dmp8T8Aajo6+SKgDXa2WxVGgH5UYrAYAyFGAVJCjO1IxSBIqEgpw8WoEAyO881xlZBek9cTP87tLfPQQ33fl451xxONo/GisPnVqF+U1IWsbwfjO1Q38OzqdRtbFCGzmO3DpBAh0yp8BLstgh0qHFrJmSPGElVPJdRjtiGYupVpVWgNxml14kD1WBPO78EE36xTPFzhpCZqBpMjViIlg5rkRXT83hR5eh7bP6oSckNJcp9sExn6X72jHKInh9AUYnzzB5NLxDQCCCrneM+jxPlaOhn9PAk8TJYfrn7E8h5HL+wwWuFM/rL/NlpTXQbBwjP7aHT6f4z+8XckU4UJCep1NC')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/student_sources.zip
deleted file mode 100644
index 55a16af51438d24edfa0bb491efe79cddcdfad66..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile-handout
deleted file mode 100644
index 6d094e3a3869dfe9ee9e51a06150c6999c402286..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile-handout
+++ /dev/null
@@ -1,7 +0,0 @@
-# Makefile for the Hello Lab
-all:
-	echo "Makefile called... it is empty so far. "
-	#gcc hello3.c -o hello3
-
-clean:
-	rm -rf *~ hello3
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README-handout
deleted file mode 100644
index 8eea4bef3abb4665581173c4843b6155b3dc59d2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README-handout
+++ /dev/null
@@ -1,15 +0,0 @@
-This directory contains all of the code files for the Hello Lab,
-including the files that are handed out to students.
-
-Files:
-
-# Autograder and solution files
-Makefile                Makefile and ...
-README                  ... README for this directory
-driver.sh*              Autograder
-hello.c                 Solution hello.c file
-
-# Files that are handed out to students
-Makefile-handout        Makefile and ...
-README-handout          ... README handed out to students
-hello.c-handout         Blank hello.c file handed out to students
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin.token b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin.token
deleted file mode 100644
index f046391c8732e92e92c7e7fb4a706c7a6fa559ec..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin.token
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin.token-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin.token-handout
deleted file mode 100644
index f046391c8732e92e92c7e7fb4a706c7a6fa559ec..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin.token-handout
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/docker_helpers.py
deleted file mode 100644
index 806c2b39c6782ed377ab0d4cf70a36d03940fd7b..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/docker_helpers.py
+++ /dev/null
@@ -1,197 +0,0 @@
-import os
-import glob
-import shutil
-import time
-import zipfile
-import io
-import subprocess
-import urllib.request
-
-def download_docker_images(destination=None):
-    if destination is None:
-        destination = os.getcwd()
-    if not os.path.exists(destination):
-        os.makedirs(destination)
-
-    print('Beginning file download with urllib2...')
-    url = 'https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/archive/master/unitgrade_private-master.zip?path=docker_images'
-    result, headers = urllib.request.urlretrieve(url)
-
-    ex = result +"_extract"
-    zf = zipfile.ZipFile(result)
-    zf.extractall(path=ex)
-    dockers = [f for f in zf.namelist() if f[-1] == "/" and len( [s for s in f if s == "/"] ) == 3]
-    for f in dockers: # zf.namelist():
-        tmp_dir = ex + "/" + f
-        if os.path.isdir(tmp_dir):
-            dest = destination +"/"+os.path.basename(tmp_dir[:-1])
-
-            if os.path.isdir(dest):
-                print("> Destination for docker image", dest, "exists. Skipping download.")
-            else:
-                print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
-                shutil.copytree(tmp_dir, dest)
-
-
-def compile_docker_image(Dockerfile, tag=None, no_cache=False):
-    assert os.path.isfile(Dockerfile)
-    base = os.path.dirname(Dockerfile)
-    if tag == None:
-        tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} .")
-    return tag
-
-
-def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination):
-    """
-    This code is used to run student unitgrade tests (i.e., a .token file).
-    Use by autolab code.
-
-    It accepts a student .token file which is extracted, the 'correct' instructor grade script is copied
-    into it, and it is then run.
-
-    :param Dockerfile_location:
-    :param host_tmp_dir:
-    :param student_token_file:
-    :param ReportClass:
-    :param instructor_grade_script:
-    :return:
-    """
-    assert os.path.exists(student_token_file)
-    assert os.path.exists(instructor_grade_script)
-    from unitgrade_private import load_token
-    start = time.time()
-    results, _ = load_token(student_token_file)
-    sources = results['sources'][0]
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-    print(f"{sources['report_relative_location']=}")
-    print(f"{sources['name']=}")
-    print("Now in docker_helpers.py")
-    print(f'{gscript=}')
-    print(f'{instructor_grade_script=}')
-    gscript_destination = host_tmp_dir + "/" + grade_file_relative_destination
-    print(f'{gscript_destination=}')
-    shutil.copy(gscript, gscript_destination)
-    # Now everything appears very close to being set up and ready to roll!.
-    d = os.path.normpath(grade_file_relative_destination).split(os.sep)
-    d = d[:-1] + [os.path.basename(instructor_grade_script)[:-3]]
-    pycom = ".".join(d)
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    pycom = "python3 -m " + pycom
-    print(f"{pycom=}")
-    token_location = host_tmp_dir + "/" + os.path.dirname( grade_file_relative_destination ) + "/*.token"
-    elapsed = time.time() - start
-    # print("Elapsed time is", elapsed)
-    return pycom, host_tmp_dir, token_location
-
-
-def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file, tag=None, instructor_grade_script=None,
-                          fix_user=None,
-                          # grade_script_relative_destination_dir=None, # The relative location relative to the top-dir containing the package. Example: irlc/project1
-                          xvfb=True):
-    """
-    xvfb: Control whether to use X-windows. Works on linux. This seems like a good idea when using e.g. gym.
-
-    This thingy works:
-
-    To build the image, run:
-    docker build --tag python-docker .
-
-    To run the app run:
-
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/app python-docker > output.log
-
-    """
-    Dockerfile_location = Dockerfile_location.replace("\\", "/")
-    host_tmp_dir = host_tmp_dir.replace("\\", "/")
-    student_token_file = student_token_file.replace("\\", "/")
-
-    # A bunch of tests. This is going to be great!
-    Dockerfile_location = os.path.abspath(Dockerfile_location)
-    assert os.path.exists(Dockerfile_location)
-
-    start = time.time()
-
-    if fix_user is None:
-        fix_user = os.name != 'nt'  # On Linux, this should probably be true to avoid problem with edit-rights of docker-created files.
-
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
-    from unitgrade_private import load_token
-    results, _ = load_token(student_token_file)
-
-    sources = results['sources'][0]
-
-    if os.path.exists(host_tmp_dir):
-        shutil.rmtree(host_tmp_dir)
-
-    with io.BytesIO(sources['zipfile']) as zb:
-        with zipfile.ZipFile(zb) as zip:
-            zip.extractall(host_tmp_dir)
-    # Done extracting the zip file! Now time to move the (good) report test class into the location.
-    gscript = instructor_grade_script
-
-    # if grade_script_relative_destination_dir is None:
-    #     student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    # else:
-    #     student_grade_script = host_tmp_dir + "/" + grade_script_relative_destination_dir
-    # Get relative location from first line of the grade script.
-    with open(instructor_grade_script, 'r') as f:
-        student_grade_script_dir = os.path.dirname( host_tmp_dir + "/" + f.read().splitlines()[0][1:].strip() )
-    print("student_grade_script", student_grade_script_dir)
-
-
-
-    student_grade_script_dir = student_grade_script_dir.replace("\\", "/")
-    instructor_grade_script = student_grade_script_dir + "/"+os.path.basename(gscript)
-    shutil.copy(gscript, instructor_grade_script)
-
-    """
-    docker run -v c:/Users/tuhe/Documents/2021/python-docker/tmp:/home python-docker python3 -m cs202courseware.ug2report1_grade
-    """
-    if tag is None:
-        dockname = os.path.basename( os.path.dirname(Dockerfile_location) )
-    else:
-        dockname = tag
-
-    tmp_grade_file =  sources['name'] + "/" + sources['report_relative_location']
-    tmp_grade_file = tmp_grade_file.replace("\\", "/")
-
-    # pycom = ".".join( sources['report_module_specification'][:-1] + [os.path.basename(gscript)[:-3],] )
-    pycom = ".".join(os.path.relpath(instructor_grade_script, host_tmp_dir)[:-3].split("/"))
-    pycom = "python3 -m " + pycom
-
-    if fix_user:
-        user_cmd = ' --user "$(id -u):$(id -g)" '
-    else:
-        user_cmd = ''
-
-    if xvfb:
-        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
-
-    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
-    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
-    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
-    fcom = f"{cdcom}  && {dcom}"
-    print("> Running docker command")
-    print(fcom)
-    init = time.time() - start
-    # thtools.execute_command(fcom.split())
-    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
-    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
-    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
-    for t in tokens:
-        print("Source image produced token", t)
-    elapsed = time.time() - start
-    print("Elapsed time is", elapsed, f"({init=} seconds)")
-    if len(tokens) != 1:
-        print("Wrong number of tokens produced:", len(tokens))
-        print(out)
-    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh
deleted file mode 100644
index 05a006e95e416fa5d5088f1d61479f73901588c2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh
+++ /dev/null
@@ -1,33 +0,0 @@
-#!/bin/bash
-# driver.sh - The simplest autograder we could think of. It checks
-#   that students can write a C program that compiles, and then
-#   executes with an exit status of zero.
-#   Usage: ./driver.sh
-
-# Compile the code
-# echo "Compiling hello3.c"
-# python3 -c "print('Hello world from python 2')"
-# python3 --version
-python3 driver_python.py
-
-#(make clean; make)
-#status=$?
-#if [ ${status} -ne 0 ]; then
-#    echo "Failure: Unable to compile hello3.c (return status = ${status})"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#    exit
-#fi
-#
-# Run the code
-#echo "Running ./hello3"
-#./hello3
-#status=$?
-#if [ ${status} -eq 0 ]; then
-#    echo "Success: ./hello3 runs with an exit status of 0"
-#    echo "{\"scores\": {\"Correctness\": 100}}"
-#else
-#    echo "Failure: ./hello fails or returns nonzero exit status of ${status}"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#fi
-
-exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh-handout
deleted file mode 100644
index 05a006e95e416fa5d5088f1d61479f73901588c2..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh-handout
+++ /dev/null
@@ -1,33 +0,0 @@
-#!/bin/bash
-# driver.sh - The simplest autograder we could think of. It checks
-#   that students can write a C program that compiles, and then
-#   executes with an exit status of zero.
-#   Usage: ./driver.sh
-
-# Compile the code
-# echo "Compiling hello3.c"
-# python3 -c "print('Hello world from python 2')"
-# python3 --version
-python3 driver_python.py
-
-#(make clean; make)
-#status=$?
-#if [ ${status} -ne 0 ]; then
-#    echo "Failure: Unable to compile hello3.c (return status = ${status})"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#    exit
-#fi
-#
-# Run the code
-#echo "Running ./hello3"
-#./hello3
-#status=$?
-#if [ ${status} -eq 0 ]; then
-#    echo "Success: ./hello3 runs with an exit status of 0"
-#    echo "{\"scores\": {\"Correctness\": 100}}"
-#else
-#    echo "Failure: ./hello fails or returns nonzero exit status of ${status}"
-#    echo "{\"scores\": {\"Correctness\": 0}}"
-#fi
-
-exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/homework1.py
deleted file mode 100644
index f046391c8732e92e92c7e7fb4a706c7a6fa559ec..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/homework1.py
+++ /dev/null
@@ -1,178 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-adca3cb343b7bc8f011548d2b96fcc1200c144bca8eb8b0201bd51bf36f33cd38a7edbd0891d876637239289cff3ba5796157937beca05e25bad6e423e9dd7c7 31228
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4J69WzxdAEABDnkb6gh68K1MW+XxsudM+mkbOKPi5w3cW98IKURyTqPOskDWl/kpdzHePJ97Fi29AX9L47BffuuaDInSMcOlB+hSYwXh4eIvGBiJzOR3DZslH5ojCyC/PUCsXpAp42h0w6Tj/Yv
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/report2_grade.py
deleted file mode 100644
index 0ee13a2da31594e56132628b27f81af994dcbb29..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/report2_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report2.py
-''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
-import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/student_sources.zip
deleted file mode 100644
index 55a16af51438d24edfa0bb491efe79cddcdfad66..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105g/Makefile
similarity index 65%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/Makefile
index e991641bdf70c045e3b72044b76e97fd1351801b..bcb753ff998de674b26b9ee7cd1918f37ef8d5ba 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/Makefile
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/Makefile
@@ -9,26 +9,26 @@ all: handout handout-tarfile
 
 handout: 
 	# Rebuild the handout directory that students download
-	(rm -rf cs105d-handout; mkdir cs105d-handout)
-	cp -p src/Makefile-handout cs105d-handout/Makefile
-	cp -p src/README-handout cs105d-handout/README
-	cp -p src/driver_python.py cs105d-handout
+	(rm -rf cs105g-handout; mkdir cs105g-handout)
+	cp -p src/Makefile-handout cs105g-handout/Makefile
+	cp -p src/README-handout cs105g-handout/README
+	cp -p src/driver_python.py cs105g-handout
 
-	cp -p src/student_sources.zip cs105d-handout
+	cp -p src/student_sources.zip cs105g-handout
 
-	cp -p src/homework1.py cs105d-handout
+	cp -p src/homework1.py cs105g-handout
 
-	cp -p src/docker_helpers.py cs105d-handout
+	cp -p src/docker_helpers.py cs105g-handout
 
-	cp -p src/report2_grade.py cs105d-handout
+	cp -p src/report2_test_grade.py cs105g-handout
 
-	cp -p src/Report2_handin.token cs105d-handout
+	cp -p src/Report2_handin.token cs105g-handout
 
 
 handout-tarfile: handout
 	# Build *-handout.tar and autograde.tar
-	tar cvf cs105d-handout.tar cs105d-handout
-	cp -p cs105d-handout.tar autograde.tar
+	tar cvf cs105g-handout.tar cs105g-handout
+	cp -p cs105g-handout.tar autograde.tar
 
 clean:
 	# Clean the entire lab directory tree.  Note that you can run
@@ -37,7 +37,7 @@ clean:
 	rm -f *~ *.tar
 	(cd src; make clean)
 	(cd test-autograder; make clean)
-	rm -rf cs105d-handout
+	rm -rf cs105g-handout
 	rm -f autograde.tar
 #
 # CAREFULL!!! This will delete all student records in the logfile and
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105g/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..38762ae540905f49114e373eabc8ab7f47500186
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp homework1.py cs105g-handout
+	(cd cs105g-handout; python3 driver_python.py)
+
+clean:
+	rm -rf *~ cs105g-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105g/autograde.tar
new file mode 100644
index 0000000000000000000000000000000000000000..6375936fe5c1d126dccfd77d2419f492ed414334
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105g/autograde.tar differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..377b9185d32da385258f262ba816152ee9ed3dbf
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/Makefile
@@ -0,0 +1,8 @@
+
+all:
+	tar xf autograde.tar
+	cp homework1.py cs105g-autograde
+	(cd cs105g-autograde; python3 driver_python.py)
+
+clean:
+	rm -rf *~ cs105g-autograde
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/Report2_handin_3_of_26.token b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/Report2_handin_3_of_26.token
new file mode 100644
index 0000000000000000000000000000000000000000..0d5f0f19880b0fec6bb8527ea936c152eef61eac
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/Report2_handin_3_of_26.token
@@ -0,0 +1,185 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+4b2e693ccae11acc624db22164a31a59224d82e4da245938243b4ebd5ce53631fbe7d28c60e05ee4696bad86b748a0317e09927211a37fba7637adfe44c7f47f 32400
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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+a.
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/deploy.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/deploy.py
similarity index 86%
rename from examples/autolab_example_py_upload/students/cs102_autolab/deploy.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/deploy.py
index cbfc07e836708a6c9560ec7a99c951c54cda8721..b311122a682185bf51192c38d8b4fb97e019b9a9 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/deploy.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/deploy.py
@@ -1,4 +1,4 @@
-from cs102.report2 import Report2
+from cs102_autolab.report2_test import Report2
 from unitgrade_private.hidden_create_files import setup_grade_file_report
 from snipper.snip_dir import snip_dir
 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/driver_python.py
similarity index 85%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/driver_python.py
index 5f81a1a9498cc96dc44883e9ba64d7997949b5a6..9b7535e8542f1ef840372b73ed7b7b191b527dc0 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/driver_python.py
@@ -31,8 +31,8 @@ def pfiles():
 
 handin_filename = "homework1.py"
 student_token_file = 'Report2_handin.token'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
+instructor_grade_script = 'report2_test_grade.py'
+grade_file_relative_destination = "report2_test_grade.py"
 host_tmp_dir = wdir + "/tmp"
 homework_file = "homework1.py"
 # homework_file = "homework1.py"
@@ -50,15 +50,16 @@ print("student_token_file", student_token_file)
 for f in glob.glob(os.getcwd() + "/*"):
     print(f)
 
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
 # run the stuff.
 if not student_should_upload_token:
     """ Add the student homework to the right location. """
     print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
     print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
     shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
+else:
+    # Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
 command = f"cd tmp && {command} --noprogress --autolab"
 
 def rcom(cm):
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/homework1.py
new file mode 100644
index 0000000000000000000000000000000000000000..c314aab912bd438c5947d99a871a63989dc90dcd
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/homework1.py
@@ -0,0 +1,18 @@
+def reverse_list(mylist): 
+    """
+    Given a list 'mylist' returns a list consisting of the same elements in reverse order. E.g.
+    reverse_list([1,2,3]) should return [3,2,1] (as a list).
+    """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+def add(a,b): 
+    """ Given two numbers `a` and `b` this function should simply return their sum:
+    > add(a,b) = a+b """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+if __name__ == "__main__":
+    # Example usage:
+    print(f"Your result of 2 + 2 = {add(2,2)}")
+    print(f"Reversing a small list", reverse_list([2,3,5,7])) 
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/report2.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/report2_test.py
similarity index 97%
rename from examples/autolab_example_py_upload/students/cs102_autolab/report2.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/report2_test.py
index 532e19592a94eda30064939b50b16c89d9aab129..039ade86a6d8886ed0a17f87637047907a4f3fbb 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/report2.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/report2_test.py
@@ -3,6 +3,7 @@ from unitgrade.evaluate import evaluate_report_student
 from homework1 import add, reverse_list
 from unitgrade import UTestCase, cache  
 import homework1
+import unittest
 
 
 class Week1(UTestCase):
@@ -61,7 +62,7 @@ class Question2(UTestCase):
 
 class Report2(Report):
     title = "CS 106a"
-    questions = [(Week1, 10), (Week1Titles, 6)]
+    questions = [(Week1, 10), (Week1Titles, 6), (Question2, 10)]
     pack_imports = [homework1]
 
 if __name__ == "__main__":
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/report2_test_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/report2_test_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8beb75a59c69a11a44c230aeea7d7784b980423
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/report2_test_grade.py
@@ -0,0 +1,4 @@
+# report2_test.py
+''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
+import bz2, base64
+exec(bz2.decompress(base64.b64decode('QlpoOTFBWSZTWUtahigAVk1/gH/25FZ7/////+///v////5gZh73nrz3r7Lx56dA+F7fbe9uxiFUKobLaUK9tFW7dAqgOTRl7ON0d7e3Z5dVtg1Ci1pSl60AVRdm7y+dd3j0e7O93vNPD6PkkDI7u+97nfffeu585K7z3fdmle9d9vDvd4fUqnK33q2Cnzne7vZ10tfTq5aZtRXrVu533vd9PgVnTt01vJPfAoFFt329G4W++8bbW5vY+ufIQT19ufd3K9mG2q3ee49tr328T0Nb3fbe93D7e89zdmtx7C3vtU3u1pDbQzCmk2abZ5On29R9PX3mPK93Zt10glLu+fAarT6+Y+nzjn33wc9T3gfPpj7u7Xb3zde253vvevrC29dLsaN9ve9d77ue+wlNEEAJkCaAptGiYINVPehqNTammNKGj0JoepjU9QDTJ5QEpoEEQQJomRkEm0ykeU09qI8kaDQ8oeoBo9T1AAAAJTEhBCTUp/pU/Q1T2qeFP1TelPR6p5qn6iDepBmpoyDQMmgZqGm1AASaSRCE00wTTUJ6k/TTUep6TTQgP1QeoNMQNDT1NBoAA0AIkiCAJoZEwjRomaj1MlT8k8VP1T1Gj1G2ppM0maNQPUPKHqaPUPQSaiQQEGpiaGTSYU9I08qeyKNGQ9NTT1BpoGhoDQNAAdKH6YL7yAqBCKv+8iVB+UBRH3wBASQUAkKSepRYqoqf/er04XVQtH0/6XCl+ZDo/Er34R92zJ9P5H+MVjExdPzzm+M3D8v5oWK11YXxdRUkKlXf/lv0v6FkXgxrps9dJpu1KXhMfxO2IHJQ6YhXHlBmXU3DJd1OOd2OO9YkFq0+PxbE653hS5bR38Mx45tfT2nVWopIouCLocyRehyGTlLScyuX3QfxPuJTj7f8b8kCX/fm+ms9eU4in/ac6Tk7paL+ZXyt7rGCY8ttxluGGUQ/wyxx6DBURBOoEA+hiLIEgkkFBEihIsikkn6ZJRUWAgq/jBsqiNv/EApTaQEUpIADVEoQiIEDVA00YODS0kBra+V2rxa7Ey2t+NuzS9h1YGuYnwJ0E8agWUFWCQVZZGiqgop9DCgxFQFUgqDIiqkFuqJH/Txf87OfadGzbD8fQLw5z231f8VrrqqXCN/LH1tysoFCnlznYL73FpdSSB4jQ5L7Y7Z3OfJqdFsPU2UaRHNOh26SttynPBDWVFVEPfjlB27kHVNccv6j8UvfWpdDVRERCHQ6Y1k9UIU56H/g0IKCoxzMv6FrawtIZ/O5/tu//U/Sq04+Hujr3DjxvN8mujCQcWwo364wSK/4zZsPx22w5Zw4c2rXe0Tzh5SuP0w7fKp/9p7oahfjFNZpLjmeuD32dcH1QnpWLJeqvD1rv5UvkIvV6kCawQ6bPygwmVsf+V8Qmf3XZX3SPpd6s4fRbgdvARNsAkHs9Qy+J9zKePfWz5hBgJKZT4elnq4xP0ZXijT6KxHJg7pDylKIRYvEEQi5FPLD3836y/ccZNHw83mlkJoaj2eDz9cNOEz+rw62aGXj77dONHu/+eeXjJeI+Tpyujq50J0+b7v4vwtcqaVRZm5pFIvrBgxN3Y4oKUf2UemWhOBVJ1ynW7AplNvgvYYPp+TnYY63Z7tSnO6+A0fTJ//XQjKVZXmglw3454WxwslOsdS9uM6UsezFqXD38M5b6yk1/BPsS0x3b78TMu65YqKuRTTnODGnKlt+lG894S+iufhnFqvhajNJHFzPpHcsb90/N7C6R2NP7tKvGx79OsmMZxJfTXt2YWsQxxpu3EkN6aiFpI0/GYjqhdowasuZMLmU5KmfF7W128vvjpTaShO74WI2jzycXlNh+a5TFD+94MJuy5Qp+QtTsC5N4S+Yjx+PmKEm0KaoUUW60lDSPYPNIRBIE1wMZ3gdgJNyrVfVuoqrK/VzqNVTeuVzgJF813+XAzm2QhkJ303BfN0CElziHgHhuZjkRsrRlJpFIu5zGzOfRvTDpOAZjt1DqyGrJEIhqfXya4L0jgWPjhLQJJCQJuq8h+jcs19O3Z3sZ6WuNuhZTkidVhHTyXelAHMz6d3nL8WkIUMkwzeyHu+7t+PGkTUoaoY048YfFdGnDOBblgsrZgWs7sz2u003gD26/GqwcwGAxWLr5kDs9KvJp93BcnZmz9G9cVrErgTsgMbLjL6vJr6Mnm8i44OoIXlyE+ajt4kcs5G+z98yQm/iC1gwYrgPuLpid0pb74hl/Lk8FToJmEWCPykBj6+YDjEGYznH65S3E6HTS7BPzbag2dFbfpQ9dspXF4mo0h3XtnhczU1xHsfp8Lr6vUfxdwVHESExFtLjskcEG+3Z+m8anUdOmyTg8Co9mo65g+58+vPE3paOomzCY2OQva3R38LOM4CxPMtAZHHLt1rtGMuI+fgrHe4R24UuRE6V+ykIlweDPF2mcHOnJ2zsMgnmc+D122sgRMX9m1Rem0speOOUKPz+7CV86682L1Rt95mmiwRsW+TlCCW15H77TBCpLWVmuXGA6rI1wiOWz1hy6LfzP6Sz+/DCeGmgrARzzwV92QHLkaKfFsvjp/xUEK30jt8vzicSNmhvA6xyzeVKeoSdLYogPgUx4QGq2ODibzl5ZBuIxtwPqzZ4uLKs7QckDhYWszYxXUvBet9Onh2pLH0+Nnc02ywkwFc++cZwR0YRosLCpNgzkdRDSFirj5Eh7nFY5vowdO2e0ZLGwq9HxOJvKOO0OWsuO4+Bu2jcCpRbXCh+BlpPSDQL6NZJx+0mRhoPqOClWcait2pS8SEhWmFR8Rr0XVaouRbla68J1LC45xflcZl5ke63HB0kMyEkHmmvPdPoeyWReBc9b820gxv4a9sSjPzYZGXY+2qON12oLRYMqHv+iYVRpr04cHZIRDr4C9qiWlk0wS51kJmoHh/A+PFlkVG+A1dTGAkib778/llWzW7xsJHBeyJpulbKNPCNJSYtOI+/geqDjZka5GHRquye5yCWPUT+6UimVng2BGkw+xrSZ8vP9OGQ5kHcL6TIxsxKtRNWC35GmupaPOgpzdawU5+Esba8riHKu0m6BA68E04Jm0gdrphmY3XZV4V3cu8DPrw5J6wmfB2CibZ4bHSlhqun2ZJEY9nXHsicq+E7HE4WYcF2N2WebOmzBGPoyeypXpiMS5mpbgyg+PNViaMatjReCT0+u8ZYuG9dKcWbXPPiBjz/V52Tb6/Jnqttyb8OhqY/xy0WBvWkqhb2qx9aX9hKJ6lrm5HiEM+3vePVZuN18zbS7t3cHbWfJ+Y945ZoUnD9NdIiujdbX55TIo3Q3jxLxztLiktJUnlYY7uqC/1c9esxOQZGO44GxF6wKu3Lm7MW1XwF8b8Lr+ByLmuo71eqkHVWf05lllOqlXWPVqGemjJ0rHuo6sDcp2PbKiShyP0kWVR0IBFtOJC3ScmIQgkJmW9Ual4Y5HIo5wTcV2IeybG/I3U2Zty66a5Z59j5RwLym+8DPbi/Q3O0jKhYghPSDcq10LDdf2xIwZhNI5Bgfl6O0+70nlmgm+psckWIfCSkh2kBA4dJ0lrwpxIqI5FNr7SzD8x60dOaLDQevL9hwOMbMbNkq/SYOq0KMdZ4EQykU4uVlcTIY7AfsI/cqppUipzu0NdKBWxR7QqqLEfhsoowbSVFNDpMEEmSE6dlF/izpaN+flIYer2ui/EFob6HDYQE+BiP363WDa5GRU3Aqq5p2F0qFAyRbGZoYFg2N3w21sgVx0KrlvylNkzeonwxBECOOMrpmG0/i9FY0GQTCGKoRgzZAeXRQRZ4HskMeZiCMY7c8MUWaSTNWDih8nazY2t/MdI0TD2/TM+pBItHFjjOfCY2dHYXVWml+GMJ3RgKevWamA8PODlSRvgLnnzO/Uns52bsYJwp7ukqKfWQxwJXSHs5xrpaGh2CLsryzKRJg1R7zL0ldMKGuvR0KLZ0XcuSO9o5LZ2XtycyeYTSJtNcNeYwPCVnmnCSwsIxQiXQSQpX2lvkkyPLxqZ31Tpt6SorCIzOqzOl9g5o/bfiHNUEUFVAk2Oku3sK7X2/OWaItHsOHozNF5e0u9ney0au7FycXZ0rynfI0r138NLa9RzvGrZaQb7WyyxpSzPDMi2xNXCbSZDCCzSFtdId1KJ4k39qu4oe/bHhMpR3VwdRu2lkXoomUK0h1IjEThuiMQqIwqeTmEwe0PhmcJ3YgubLpn0uvtJW8FVUpssJRFhO5t5UeEk44UYrIqPnIseU5RhjlrbZ0wwfhGeNoWeM9LaTRr80MG/jlgWPupbtKpCYHC+Jqryc2zasRgLbqZ1ih/FU/n3xlqzjFFad51jzeKCbOGKFTbEP0dDQh0V6kSB3reOkGZdKDmiwJsJeD4MlQjHkduFrEPWeIzpuDq17z373i86+FNkKJuYFWxlNsZkRqIuHMeF1xXI1wzsrewnRhbM8B5pi7GxVJMeJU5XStJflxlsdmGqOtapqXeMOcNK7ddqLXpbE7rp9MI3Ynk8Uk4kcF+ebSh9XTKb7jHRhGLdQLvmWWPQ6rruxnOzUelbzIglsbygYiEBAUbBCwrvFBayPYc/RiedyZ2CPUZMOwHDq65fetyXzAfH7JFfHbqYs27vms3b+6Ib5l+az1Hr1HYEOYDkKF1CO8EfagmJva45RrhrD3udG9NM766kmtXZ4blM5gEr978MX1nebB5dt2Cbv3xx825aMVoNi09ds5gpSgVFIsHXktPLOcoRSr1z7PU/ol0pCi971HB3iK9IkdYWcjxJusU8i7cfaPbZTH+91Wfe1qe5W55RL/n9m7bZ9Vh3PbPCaj+fWspWPhrX0vnGMeeXi+Lns8/kfmta5z8p1nxy+fs+vWEui9t9oNfYyPQDg420h270QLEMAvvZsZnTwlPiOvo2gQnjui3ye7AM9SRAdX9E/Gz8l2HX2eWV5PF6/RGM9a+7dpZSfG/twy4vrnRM03e969Gtu3qGhxwh4XbxSEyTMPsOgTllvlvpXUCsIotRahwLZDIxSo8aoNsD6/8GsNX8BkucDIPCmEVikO8W5O6PSh18ExntpBw2j7Mds8va9vmRerUcf4e7M6PJw4HGk4NxnFtl3VjcFjOsaFVmHFrWN7ywyJp0SJkctuoYJ0n0pFkPk/OlxWVgK8KhXSV0mvx2afybfjz8gw3426esPKqWdiUJJMgVfn1ESJfu/z/6ObLWhYE6ztNCUR9ZTQfxXgm3TtZPRGL0P9lZ3MawVhoTTP7cOrku5UFuPdOWK6HlqVQ5BvJH7VKoVlIuEZO8PLwhZ+fElD5QPQUfiPb+/MyzIdj85Qdj0ezx/H/eB44ewU/o9sqDBqgHmZww1RCQhV7fsRrBA36H7uPibDl8fl2IiqqqxA50gbduuwp3Z5ionSMoZFFVVkMtKgGiGmmVoXzdDdhgWfbVFIKH3IyU7VSsxtstsq2xiFWMhVZKyrGqpoEga/+bISQBIOn2dz18lxOg3dHUkYbguwH3/ZNDBJhkyehJkCTJCIqRpQdndSOSi/ATgJAszZOhMxSZ+u2hiGPvT2vJH1zl5xL+m5zmlb+3HYaQ2N57zaFt4y2lUM86TEDV5Jzw2VhdNsd/2GHvaqnozD76OqlTMVt+VC3VwUW+MK/J5MF3M/olzGcwyUZczlEWqp1qnIqIi0krh36/OFln3sVFBx4N3ouap9uNpOJr8ZS5q4ytzIEOBJkNRJErfuIxc/aFhjuoRUtPEIlgbY1LSwepUVHuilBfTFS4lUHtLBEnlM3lDJqmBoQZhFe2cWs2llh4zVrlWGhdjhk7wyIbu+I223Lp8mb0PWfH33BJlqaA0aOqHi4ICDEMmUcLbDsQk2VaaAs7sWjIaCHaqRcYh+rZds/ytJ0wkXV/Av7Ys15PZj8ldPJs8HAIwxuN3Q0LTG0VhiQVJf6hGIXsj0awy8xYTscNLG5WC6EIp2K62+/kJYmDO4lD0zy13MviYTviXfTHwb4E5EjAjue8z6NxwZy79ohpRPq+U3C4xaiGR7jhN8E5bnfp2+jrZOuIMkJzUWVMcS1N4Ltd95zLX6Jvnd007qRD5xEz8eBO0wp9kx2x1xotpvdFBBGrjjBdckD5LMdXJIPYQZ9gvdrxRt7ppHQa+4ghkdXzZP8v+b9/NHhzmevSy1P+VOVcsq8bJ98nJa1i939K+bycq+Pdd305+VIFou6H5SfulMrXqu6tYj6rkopOvi90JPLr+Z/x6nPH8ccvo2jtk6YXMmXn1j2CQS/HOOdTr5z8CmMXfWzxylTCpcq9990PMsORD8FIedgXvTSbz7HOibnviL8uzdeZY7uLw6VqHTFFkL6xZqHWvQPNK4n5l5lfK8fs93Fh6SxZR0ro1Ce5EPK4kWFN8rIfB4Ot+7o+BXnvm8T6Lr71Zwp0smYhqUv05l1P8z/cs7N3KS8Xqjjxd88r926y21YbjukahmVqSR/C7fCTExx2cJlPnlpN6M6dxyjneSI3y760ijGzCbY5DmujkBBbFE0Tdi+7hjfIUydXeEpo8LEvKsjyT8nWmkW4TgNnGdy08e96Oj1W6yqp46fZMi4p+j11eZtG1PFClEjpU2hGLu9YKneh2hIbJOTa8dMDedQ5FL01cd1iXwql2901deOeupbp25gn4wY3x0ZkEFpzIwxa7+rlOy6m+Ru5YQ6I0vd7Zv/C2RWa74dLxfF+6nSd3h17aqHqoiV18/yfTGMhV5lZXZfPb+A+cZcc1613mlP3OQtJ8/4uvFbvzw5fv1Eo+PffrJ9HLea+dcbx0jOpcLCPneVN9ZcE6rKOHfcQVq/TJ7qYzhLiaeIfwn5KOr0tpagyvlXOd/LFcL2KfpevXjn56Kjjr5GKNPEP3xmZh/WJiX5jvXHF8P9sfb641wvTJXM+hiat8zxZOMZaQdqhU4Preod0QJ168H8H68Kxgn31wpfr4166etRGE8Zn3QT1fsIucPGd687v4ZjMzc1UPh3k9nvuTi/nxvq953Faz2IXv25lAr168drJ4Ra5vKTukJBLHr64KHz8W4b53ZBG7aAEmkT2PiSYnzPt2aQpDUQxA1RFxJKTf22EODJqLCTVEDIQx3YT3y3d9Yol4xIgK8J89Pd2MFwNHsSPw5G4TEidAb+Z0zJm93HjM4QXr6c+VyRe+yRHXePUVBx3J5uywmWoDzq/k1ia4RnJY38FdI/dEz06nUY/9OrPZf5J9n2LejepEk++/Njgoem3bqrbZcq+yCU3uGvu88iJ7qgSluqU5T6BT13hXdkS6Vp8LK5zfFjjk5rWhXLie3jutnZlJRDLAkNNT9uprOdruhFjjp1li5IveXduYskN0JYxd0JaxKQIdjjfer5iHnB1W49kjDOcBwVyjvf2RbO/HDGwp5/qdWnG1OaaU051N4IvxoQxnKZkEs8YedrzJbFrSpPhhEdKBgcsKJZ0b6nqwys5aheSyzuqXra5yWkENSUQ5GaFSsyCTIHTIGuLqwrHEadVmq6+ypfYPxj2NzJkmfoietcJ8dqPg3fJzbj+PoczWtfL3K+8692dcZT7+XxHRiIsc8/m1xxxHbsRiZdeNJm/hffyZvo7N13S6/r1I0Z2SW5XJnzlpQSP7I7fU/rpg7dMtWeSA5OllpIT9xRpNx5o775FqN1XC5DQi5u3OzeTeym/d3UbA13w3bu9LHpTM3+GRAmF88oIFgQIG+Lt7RHCoeImZCTYHEm33Xkm4pzW31nMsA51qFUdsxu5UhgRvZ7v4ValR755JHHE78e+Z+wealH9F33CrrmyWp+5Da7PrJqvcrp1h0cP1mc4yVIh/BLtmuKHsE0kxiWmB1nF99Ggx856/QJDufT7wxPI5bZhuEM3rQzsLZhqu29tEFZPMgU0nT6xry/HM/PZg97u5VcTSVLWJLRjNTefjvn7r1w1cc74fwyxH5KVBPlaBRVUCjaaI8xN+yFe0w+3sQNSa0WbBu7GuFnILhimNRuUlc+XHEaSbIc4M2YYzDgy8N1Cm6Te2GkkNhRm2MwUWerjNDQAvmJqfMDKLA1gnOl18w0HUOGqIEiPPqKvp1FsUopKMdZc/X7PXuM9akdIeKbii5Q3ChqiDA1k9yheZ7m6n4Io43lGhMxNH4VQmPL5hUQhYC7LZ0UvDa3DShsPc8ILgEJgV1mqbLnyu2YHLni9BXoGUMQfFkpgeJ0BeAbTZDdUEUPA1O0O3PMBnPN4bQIXA59uagjZeZsKaEmPLQsgm4FTdaOWpSQOhj+41aNWJ2sVraHBnrR3SXzVx9U6qjJMCqFEczePmyEFXOWyixEpOc+F8F6FRhmnEvWFldbuy7sIxeh8xl88GNT05QJCFguBqPNioZCb06MzIcwign7moebi8psJ7NiHg3XNSYEhy8TCEbubnsxNuxju0Njpie9i8PzHXoCgHB6kg8UpQe27gGP8wT3BQY+ttV+U+Oq2mftXZZ9o7iTKjlvwYemSNFhMoQYJDP0wN27f9F+hPugUsdMPr4XP2UWPsQpmQkyYje3llOHNE0AxniXoWM3uaFRA4glmh1YVChFH7oKEmmxw4I2bBAfnFPkOBh8h1VMH5kyTBQuYQY+Py4niP+XwpR0z7un8Fqqmz7Xxl/lhYxFZ6lXvIhfp6fmtRKTJaOYIPP3CsRSMRROu1lLKj7fAvo13JiKRBjBUTBUYlTLFE8OzZV6BpmnbyOOvX1vE56wwZ0HUY53kZW4osSDG4hrXoNBxDT/HGXmZ8ke2CljuSu8A5euPX8opQQVvfUTdikyJGVsjOWN+Uu4HoFI8e4PT6NO/sx75dXhW3up3iQhJkkkgkUQy8ItWrbQIKoWbYWNsNkYdFkn6+WAmEg3OGu/u726xPLOgNbfwddgcN8+0ExadqSWKXsDftfcxxWKukPzo/VKJqVObqiUW1NYtP+9bxa1p5fNTF1WN5U5IzG61A9GkGXgRqqJuJzeqU3N3FI8ceSGwyEbdjFqTiFvZtQk2CxAi54xIRjFzGBxhGMxjnD4lTEReIh3zWKylGJKxGB6mqulWDExm6xNGncqb63sjDMM7oSFpFYm8dshq4hvNsqzBhNEalys2zotIdQauzTzCjSzlQhpFlYzmS80lCd85d9YHRRcmIwquKe1p5gkpXbkTl8Cm8awW+QnUaRh6xeHvv5+jod/IMc6YObY66GnCOuRG0nSURgiKqor9ZPNwumKIs2hMmb4MKVF0qqII9OgmSRJ2Ahh5cbqwW9DGEwM9z23HU6Hc20lnJDSEZHImi0e/R4C53XOXEmQhkhIrFEYIvJKoLF5Gc+poFBRkWMZsNpY9NqQF1evWg0Btwd5onRyd/IuPZmDlLfuc1yPlD9fX1S54ybcdZFxNPXZ9zi+FGR7PLFmevfJpnjh3UcPVLFLiZd+BYjdot8vGXtSJJHDvjGnzJjUYZ+K2Rd6zaWWSRL628Cuq3mEZp3hYmPXI4IdjOs53rFwpcVcTVVOpw/DzmsKTFo41N4biTxDdxwnxw78HC3Op4xb0ReZ6SYnirecJlxoriTVArJpiljd++wTczjfnnXK41luyxa3mJL2sSwQ0HJh2zr250RPnO/5en0Hi64ATp0N0r1eUtO7l4Od9YBLDDB16clcI7Jp5ONGVuzgoxOokyp4dzOY8zHk2fOLmeuOURSY0w3RIW3htMLhDVlx+qywIhJN0RNTV1DjvutTrP8hzvGe/h+zYxydXcFUItXDa9j8UHBdR2dexguCt/DFm4MhhJg6vrHYvCgcSIIREngHWIWdOigMEydkmkp4jyjLHdoS2oUtm2yXhvEb4itVnuTpt1IQLTR3Bjnm1P0RMYHFSakKdNW11qwpHU7td7gMcpYWrTlB31UvJztJY1huqZr6OD2kmCmEMZvZp4hd/avsSR8H/XH3Xy8Pa9qP/P3v9FuCpJPpfuz2Tgz7FCunvonNl5auvTGAcjPSiJH6QyP2XR9s+95/Oex173tHT7F+Pau3a6/wXzisRXkmIKW2KVv7t15h+8P8Az+gfeRMkh6zRxRPRAdMHn25linvZ5U82nl82O3UrZqXc70kw2xYrF7+CXudYmnIPCgVJ4pDmwsV4ql6bWKcdZPlPyqeEKe6xpyu4phMkjfm7TynCkWl3IiUMTQ20sDblccu8rNYfZUWK8Cayxq+fjiq+uMTOfN6ru8X9bx+q8+f31a71MTlDTqYFcvHkOcvJ9j+QEXgnLM2vR639v6rRAi/soUgLJKV+8UoH9bo1QJoDVhFJJKkmkgVgoQWDjSSKSBWTEmMkCUblXkEAxCYCXYaXh3+CTSE2f5qWU6q5q1Qz4wS5vYM0X32tITFDDcdde+1WX6VvmboNGZjDn+KvNFinRsQPB4R8lHMUpkpyJeWqy5p6givtjuXnBi1h8YLhVKHwZRDzMeURm6hQni246Oei3jTxc14mL760rBVidcAnLgj9hplBZwwMjs+qhq2FFcpcrybbrdy0s3UifbbpZO+1a92TZhe6GczsIsSjL9ezlvbWTvk1jiCV4HB80WlXv/KRmhU7HRzZ9Tuyny51MZ2waEPreRpkT4rQegYyaiti5THaSI727u6E8Vz9aIWfmMDGIlF5IKbdm3wmcjlmJeOPSt+/4v4QXO7+egger6T0/8/ynr7aK4GCZwIwQYqVnpZ3gdaaJ+GBg+U1g1g+/brZHfRVKiF+ZQ7gWZSOo83Nnz/mJ78nGH2/X7h8ctqCqSniMYbwhvMzg40N85gfwR+893U4fJJbfxvqHPu/DbvEL7yxTY3y5fMIXIoSrPlcwKRCgPdPQeBKYx/2Kw+Suxx/n+f7WvgR93xdx+ML8FUCxo7Gduu88YQQHYad4kNOxDJj5jcQQcADbETm2H8g8okWH9lhuLh2aTWtsHzHoJBSjAOOrhiGRRR4LjDh3qcAwEe9ZEJEhAIqzW7O3dukYSwYPiePdwHcc6vdTAsb8BX7wdm0CDwhJhynOJfPyFDnfz8NxpE6bwRgsWV8Ob5IzBi3x2nobFymL0+Hv7w28+40HbA+eHIJAhzB2sTX0O0rEgT9/ize6WBmeBMljY5dsv7ftb+RkISEqOYX2GymI3IZHNPcGkA6NJUZlvZEQBQv0GGHYexXomjQqj3yEoT8XpCzB+Jy0qqsvIKOaE+Qssm/0BYXDVU2nuMXl3mR9uZgeeh6/xKaJ1MLT82JvzlrPhzYgR39uxbv3MmeSfw+/ndlL9CFqEhpwNst00bPBf814+AOzj0xCx79OQMhzCnE+UunJy8WiKrHBXDLUiYVod0UskU/A4M85p7En/u5liS/X1Wy49Xiv1CE8mzXmRkIIVllkR1TgmYAjPEkpWwnee+UR7ucjOfkbo+m5v3U/139GZueHA4fNm5GdxK1n5W9SZF7if8Wh0F2pP0Z5z4+jIMctHUO2hUc0JOWv00YD7wTAiT8tUQiQeEMmWJd8Nlm4fu/gUVR5b3B6YG/JpaU5693n9U2HKDAFofw/UfiPhpXoF8L4PlrDXqsOtm7U+XBrcxqX8ns1xlkVM/VRlhVEUDSmAdHOukEMkgM04T8XtZXzIfCnHz/bzeD9CMTkFt9fbd3mpteUvdOO7lkqzv8MlTWDWfCPCOkPgWBPlUnRS/XU9JXhafmbSQcotD0/hdwv3liHFxjrUnRXAnVEutUPU6kCAS8BOsYe2nMUx7EG2PdO0O5BLu1Ax1z2JivLz/ZvVPxDpKFLmlLiDKpbXRMjq7OilQKBDR3PyxzaV6Nd2aa2eBfqW41ha8GX5HnFxZR2I+wx4NpNeLU6ovpyoG/ne+zHys86cGsUtyIwgjpTQmSE1u4qrp611649ESIM5qY6P+u+goJJ405em/I6OubJ16QlXmc6xKjE64c2RyIenXnWiebe7u5dfseJrVsJ81MxcU5uEoZdztGsPSSNeL2yYBdh8RIatB6kTW86JXpQ43fTfBFhjHyyT3e661PrZPDA0kkheZ+ONFFPLb1FKFefbNeH006Ny8GCMB9LV6WbZQOLN2Yjl/kw53SaUj4t3T6Ezvpfu+WxZdNAhbe9qy0vidPxsPch1jr8nEgkvdZIx3vtZ0aqIKzx7sDmZFNCbVaCfBe847FXWcexRPNwkc1ECZLLuyXV3EpEzi6W7M984mkiTuG5DpFuVYkltXw4XzCTvlV0kyxYduYoph1G/7UFAURxwE0cOt2NI/Q0YIhJFxNTETzO2kypbU7kNcL55J5/Mgn2v4pvR92XHmyivXUPP01yZwFjo6OXXvw4Jkyu2oYTCLER+f01Be8YmkJdEl7Vzh564+melOpW4EvFDzV0pX1UHlNwxRZ0ulmdvJzyIVhyVqP9yZ73t0fPlSPFV24b5BxRZd3RhapX2T9OkAQgyycLJOyd2dFEzo5I9sdeEi6/eQ3cg6JmZutNPtQ6ztjNa5SnJ1N6RNaxH4TIKeD1sfmvVR/KyJ03UnjTfyvakAOyw9Ppy7d+KnWsrJFmtZ9pbbS9raNIkc+p2PL+rxjxh6qqnbETzv/HynjqV4L45DvdsPRfWfSbHz3WtanIboHaSiDaGggRaRkYzacOFm50m0X9f9dWILtXPZia50itzk0V48v6Z63Vrbv4cK1fl6uVhQ1V6HlulyxtYOZ2nxtbyi0eRzFDyIqXJlEan7flSWiCf+cfzXG7qYgczhCededWq2oQ8oFFpVUXmxYIgS8SrkzvEtGWkyZ6wIbY9CfeSk/U5OQWCAqEjiiIyVo+p1N0m8h9o+USISDgDhkP5AoYb5sAUN4En6sBSDprYo4YbsDaMm5ZvmM2yFKwcCgUPlmHwHMHSAG+opqwSRSQmwdIeAf5x27E4mAWtDsLWKgrJsQm8PvAXJaLJtPecsw4DHiNcG0rLRJcAHBoP0H3UbcMq2OX7yC0kpMbA+rUJ5j8neR5h1muOkdYa/RwPnCGNGoTV1khoYU0yxuHmHJwV1kIEV3LsdnR9RJiFLFEY7hz9lBkPIFD38xJYdIb9CqSHaQLrs2Uuwp9tkNYYlAGkFoezM77EDzB5zQOAaaTSHY0njhMwEiFQQt2kLB1Gs5wwHEiDxB+wgBSGawPgJA0Lry5XGugKH0dPEzcRtzW2iWdOCVvTAkHQQiYJ1IzWgpmoYImQKRlyVPAKDNBYfV7twh2+xcZa900C6LGCCKCjqbZERE7wOsCpJmBynIs49cOXE5Jlg/IFBYZOrN5VOkIOpboK9xBK/DgJ6B0kGRGIjPzF+tBHJSvf6xzhuTVR+g74fBJy5FGT2wo6EgerjnbECjM+RTed8h9aKEjCKAcSWborDx/okKM1+lfD3WPLSe0/q5qBq7N2LAsFFIowQUA8oaeAnJVAJsRcFcSRIQCLDpbnOdED5zIIERFcQq7JFVYFEBAYy0rC/x7htOqKqAqqIqH0lgKHE+E0CVRSlQqDQaENJa5mTAGLb2k9FHX++5BYHtKARhxHbnDK4GgUUoGhg9pp3rz0RyxpZ336PdyLDI4MMSsjkUazZRUZsS7S4ljqOIg2TmVCP7OCcS3cUWGPFNAG4PzymhhKILFhFiMYgQpQoWBw4Q6ZUGLPh0YMPNIeO0JPeIIqQOshpkCeQQ0nTYzZzak1FCa9YzTCOpJshRyQJVmuZ0qdSa1Nd6BaIetPU7AjfMS4HDfZ9IiCeY5w7jxqkGQ7krKTNirFJyIYgE9Guf2pbsWFzmDcIf3hBTekAiEiDEiaciA4GWucoB1pES0SpwW4L5Wfpy69oRh1q2CWlLAYUkGZALx7YAxkURCKSIIQGAa9iL/Q7uoNgBaMkn1MSwff9uC6R2xE3Ngmwainc/eeqjTiYzBWXM5Dlp6Dsk4Jqnk3mCAqFg73cUME0wNBnTYzMsjADi90kVWQT9XsUqaw8hsXftW4WXQWSHSbyQKzgaDoecI40B4hmBb/T1rKPbw4poqqXYfzBrEPKIeN4kqmHMELLDrNvo8B7c6py+E/SJjT3sDR/AOujrWto3UvD6wG/T8Rfk6BH3MyhXjZ4DbOQ/0ZYi1rsS3rZVf3zLTzfNjT3E8Ix0NlEGhST/qwVjOX0UX2wKhA6TmbdR2JSp/mSaIJgXQKdhDf8Z+7pwU1D8hshomihpJJBNdrFhUiAZz8FY9YeSSXwD534S4ayEPScjJBNRUBTnCGoPEdCb4ff9xpGc7ioMFFiw379QPPCwP0CD3feMHmBHq9BCY8lIFlX2o8MnfSA0JB2/dQ7Rr18HMlA/7sqOVoFBEgKjkhhBxRDCQe8kaBGAzXcUXGXCqYaVYFBtCKX6ND5NaYNs6lqjPxeh/cQGX8N1ano7hgGz7vTLEmEWHhSFA8GVVQlun34EwXDAqLJDj1AKE5HhOETdqHLAaABCH10+vzuZhJNRxDRTkxiqwoVo/XVPlwA/VAzhA0afR7SbsIUCHcmJxfcUmIdB3S1tXVETz+AXOjX52WNjEL0QLl2kWgvJr2o2DSd9YiRwoKzLFHWHycBnOYDgn8hkCURDEfO1EIEMcSuEDEUOxShN4fwDG0Dxo/b++tSMkNRCkNZWiBpQDU+1QfoUTwRIoikEBWIeBRIdkKJLI28AlpcqlhiB46DmNvWY55veEkSo6jY4glLCHOVgLG0i7djTECKTUwy8IMwlYTGJW6M5YBIrWLBggFdtQpGZK6fk2lNrLslxoMhng8F3thHg5lNP2BkFbVKA2CY0Ijw7zimktS3abYWSJOzd1vtoan4GquyArIIm1vZFNuhFqJoOv5jIL/H0P2z3T85QIKCmc3gaUQaWBY8p0FEbIXJhMgw51TyIGwBgYi2IpQUxfell6PQd0fL1W6y54skCktrFW/DMn2hnPJoEkOl6g+zlRmYlMlqAkKzAUamRwCkKW0MbgUlMg3nxEoRWHocdCuDhD+JJMkA6Pc3aJmRW0ty4o5jkxqIW1tbmFXKWEqkZVPhd+/6SuW4yjrJQb6cB9O08CLUEXiNJt4bnPQceo/USNm+pn15P+1VULUY+3whvtBBgu8MH0Hd0CV0jBxwgkhnO4PgNgcW48iHIqjEf591D85AOyagk6lLV3UndpB1aj8AgX/2vr4Gk19leEsHeFUSAQLEWHHqsZEPSCsMlUabmfMSEbtAcEoEmccNpqi6EBAj8BHmtEMWkJgaoSIa0tKEmPR49h19UbpdUfC6bz/Va2Sxmi9y2gEpcgsKifPHZKpFXFVj5NRZp3kn7k5eLLHOKei7iUWiFpCTQYeUkCEcM+THs1mlhlgfmdgUY4Th0j5KG2Zbgw5yIoxxj5YjX8cELBtGVznpAZ54OODmw5ZWt8hZqMA6GpnUoJK1B+tN/WRuXx07MPrnqYcUgs86f+DoawZNYxIYUCS0nrLrOaN8cdRaOqN+RtvCOxwjJ1a4L3jts6wOthk8IZUOwNYW+BWxqVpHEa2ydqRLJpl7jGqnNcRlN3QYDTZzxGXjNlCIfDdOm/LeCix8C8Fs1BzQgvjh90w+OHPC8d+ebgJG6sabyJv42P0dPyzeUbk4WY7RGGZ+goWfxxozW4dlh6aAfrRJ47sbkxSge4goQlwKB9xlF+DkvEExcmyFWhFNw9GcEF4HgLJxJgpiLeiWQSQE0uxnndXPO9MsFCi+JGmCSk1RHF03GM/FZN8vW8IWhneqpwHwqXHOsY0TG4OmiIg6d09PUSk0xKyUk98Rm8vvnnWEKjieK1zvcynTaWVgyhybqLuoKj3alsKkLLshJ+q3K1vrCBSWqt5HpRDYUDUn1VaC0CcpjeIWQ2ZnIuJLRcxB2xZJVYFlvG+nBJn3BZsv1O88+NXkuwomiaznQNiExW9nJAhRQpgnUWu3Xl6oCrAfxbZQ2AVM3cLG0COQ5rCMVzwwD681kXrBozGHy/1Jhcxm6dMDaOxGmhlCZ3fGqSZOSYZjR3vRgxL0dXCIkzLCdWjFP64MqLTYNLapEupWTx8JwvUc4526xvLGwRcfWOxppo2RnLqthCrNZ3vpbN7mORw0HiGOaBxN0RpdGfhHMEzvM0ixUPKEfBumFld841Exp2jpiiWJyl2qVq6d3JvUTqqvpWVDrmriTNUUXL3lGtWeaJhYSTftxq2LEiQEZFhgOEzghvCwMpDewo2OI4K3GKwkENwUEd5iuaxMQxBKBsmYZF0GIbGYBSH0tzUYjdMghjmLcz3BgXtVCeiFiRaoHCKZ/rxhNpqH8+BiljAMi3xJxXgaDWBiu1F/5VEgSEIIigxKmPy6gygGIE3FwNQ3Rhm7oyIU0vxGHnFxdkSrocXR5KlyrpshCCmrYiIynHcwDW1CUnplLF72wmwtIoRx63ESwN8rAvZv8CA5tJvQEE+3gYG5HaZsKuTg5DjZDW7ygN5vCjKOZBPrw/2WFOnljrEBT4mebx5jV1htIIf2BB2BkifpiPxNKOofsOJlpOnTRRES3QUW7HjgOvDGBmTOQCyZ2Jnq1sz4rzhYmDSiSokkogLAOgAfgK4+c9JhUAsQvjA31p0+znvpYHpH+l1u1Q9aGNG06e77E18TmMCd9AFhsSl1BxsMB4YbeoG7OxVaNSFSHEO7wiEdum8mJZIC9cQRhBkUcNiDgOofaGC1fAXbefHynwp3boHfjwHJREZ0HoSeUd0SEToNAmHOA9xCgc0xZ+WYSUHLYN8yY8aALNZaA0Ow5OYJvOFvhXl6pijgIEzcjM3tY9Q4HAkbq4IWMitDRibMSyp3EOnaEhB2ksud33qcq72CFRWL0nDh0WKC7GUQ3yAdBmG7ssNAy7efietqvKZ+7nE3ZnNSh7UFkk6goRgdz8Bs/bIUIuzhZ228AfFlSZ2TrY2HSNW4cq6fRcOTNx8nK3r3ZlGdA2ix2Y2MYqgzcpNNbPWZp04YhSykkwYjhbJWWoTcX13W5c9rfazIEybMgOJgNIYpGKaAkGEJAAyGkbgecJE2jTSIxAiwWSKxSAPf41YibBAM9ANgNRJkPVAYIsIgBrj5k/CNER9X04GAoIMnZGzcbI7ITMEYFG9RIUKXfexzWU+JJCCwXYBcw41/b2l0DcABvgMcAvYD5/A6YMIeMeGCtMeaFlP7I7gbvMQMU0Z9T+f9uGQ/MZtj3B7iQJIle2mFFDUK5CncqxMCyUJ1I//iIh850dfb029XvPWfWkp4MDlJJmgsQY0sEYrSlYVLBCshQJlpjPIabjAmgYIjEAKogpKIFLLIoiDFWJCMERVGRZbUlD+/EtBEwSYyjMSxhT4dvcbZndoqip+sN+YadIco08oQNdGEkqyBeIPORUQtFSEVTSYGIWUHuolH5wPy/nKn5YxIkxAM2YmjmLO2fypzid/woWTzLAeoObq+qeecCTsJ5EERYgQKOBQHUv0hrPr2FeWn7PqPh2wyRMCHRHRYPX3+JAn6YSv8E5A8d0ZwSSvFOQqEpzHJw4hG4Sy8rBis0YZL5TABZkCJEYzY04F1NUlFGD79E7DW/9A2MVYisiRfhE4E3Dl1XQx4kTmZxewYivvT3/g0Ze+pPDPwfK8oyiL49PEGFMMDaI2U9OvECLkGjIDq5Vi//Y+FgzmVII6j2DsbJpLY/0oNTaWMUC9zoek2ByJryM3x1vjJ9n0nyHqOJPkgy6K+xaZbCdIgUUwoVJPY6YTCMQEiqdSIge44B5gyQ2QwLdyyhSyUk1MN3dFAWTo8fEqJ5VQ6mbCTQGEYyQnQYHrJnImE60Np2ogvTmIxDCWjE6/ViXN48HQa9Vayy7kOnOxgOm22yBRQPJ7uWLfKMEnSAw5r4hUITgXsN6CCSRZIIgl1CHUWw8OWwt0q7J62GMBZZSAN68oyGRCL2wagpJBmzG1lnWNmDICFl6ZuGoaJJmzxZhjj53QouWUgJgiyn3OIftJCmiUDlIJ91hUJUlRYUtGRLEIoKVCiRZEhQgEZIKOeZhmN/74QPEP6zWBiBiOzcgw1qAYsqhW2cIFMCuH2juJoGnJ6HlIa4gZ4ei7x8vd4/Ho6pvL+PhQ8/OqMVUiRVQa3mOkwgISGMIeqyEMEF/XWIyapJJnBJ4nZB2Dx1uYexh+KHSUtKNPQVYJ6AwfX59kCgfZA+pK3EFkJlRwaEntOc7j8Az+Qrl9YEiRIgdx18OzkQWRCjoOl5uYTSy2GPqNwZfWqZdr6nRzrRM7oeHhPCkl8xZCKxqmP4fhkViaSevh1iDxtrV38raWq2YTFyoYzii9K4ZjBp0o8pJQbWMbS0K7XkmM1oHajlhWKLKavF46rNOzCSsb6bzCsJiYFJgTrRPEgbTevyGw+65cfnXqHN9ugNIeb6yIHYB8Y6UAkAPXB/WQEXCGoIqb+8XRkGIFQJADh7DwDfgrA+t9fvyKAyX5j2QoD4GBVKO5MDgwUjefCjHK1sKWy2lSz1WUyxQUUKqsBCzFT8xW2KJ7IIEhIEgp8oPKCYTznwlsIKGsoWLAnzeg7jzBWggeZyBO0fo1BYlFHPxvfxg0ahDYqEFXQHuJW16oPOcet2dk2ncRF03kmfhRu/7ycTryeUSZ1BFvjSvVp2GkIPW8u40BQFCGYrZIQzIwpcObhvF6TdcYvQw5pUHSsDF0bosIkwpAIsIG9spaS2yS2/MXM0KM++WgaROQXWp2CQow6TwkOB1xeV8iVyM7tF36YwFgCMiCEVVIRYSCsIkGKEiJ0a/iRU/nT+JBoYOHHikLoByAD5tJBoXkCGsQOAMJF91DQkERgqosVjB9kPJ4wPKDRMpOgnZAp7l7iIeshu60LA7sTZKIEIOIF4PPG1ECBYgnMzgDSZUv9Inu8MzeB+WVVEy0I84CfaRDzIm/Xt380PQoh9pzoee89Ju0u4F0hRlQVoEfx2axLh3HvhozhCAH1/Hluo9qwZPAJPkDR7eg7cMKYMYqTrNtOxdp4BClPA0hmgvqsfdJBTMKMULRVDAufE4xKD5t9MiqIn2xKL3GSHMGpwOXznmwMzWtfg4VbED9rDRRmjTbUW0qI85Iffd9dcqTKHMJkMidcdcxdWcLh9hJkZgyibMmJfqEoMx18jxArpSGgdKnrL4S9tFuXJpZhKNJ1CuMViFK8e2kFrWil73N/VMj4KEhF1Utnk5wwS+Wnk1onkEsDQg4Rtce0daew6j9Mplq+/MDIDOlNfpy1PqGIvpBw6I63p/DkAIkYxRBQSMQAQYdnYZ/o8ePd3/Tn/mgnKIbRsAH3GQzEsSDoHSvAVU0pMxJtvWo7nG3cNU9FptWJUpVZaVaw0bZrUgrvmIee32jQNlKXWUFG2FGCuFS2sRRhRCKVUrFG0K1ZslB3CgyalNhFiXWSKlEoVpYNQ6Hczmy6cQNYAgJGZANbAzn7iwzMSiPR5WtSh1phvFdaAIRzBBcJkGjGTmUAhCpIhXlvB4D0GwcaEBTnPoUvYdQdB6yj3u4sEEKSej7/dmGc5wWGzxAaLpsuRUFBYeLaFD4YuzgQnPzxYyOEdtWCIikmI5Qh2lqFLIFGT0Bro/X4kI1CAHEDtcOENJtV4PnDSKhRu/r5F1UNRjQPg8jssNQ8GJTNxixsAGw4Gn6dW96zwtsIE39Y8EoxTDOoC6ZFvVkFDpwIIwBihFWI+/b6VQiwNGX91kXEQ1KkRLQDUZwu5dXnNw8kOduTjknJCJDs4dymTy4reIN7baOxl2WPu4PtwugpY3mBG0nO6jPcWkyoYqJFJqmNRDpebU0pRKaNLc3nxudxdRn0LvwMCwbS+sGE2iuBMZvlRAkC7Kd/86pDbIhw+gsmh1usL3uhjS+vyOBY4E5eul+qYEOZOpgd3iGdQi9QliJVRaUEpFYkESiCxpBQqsIsEYhBajaMFK2CSAm/mMlmdhxAPiJaCdhWICZhDWZQ1oMHB9jxTjEnf8jHmetO1PgMCY1soripOd6O62bLwNAcO9NBqgBcNRrMg0w7j0FPNDvqjMvXVyeHpdtl4nIgO/EI4JahgIfjBUaHAxwbKNlOcu2jNx27PbDb804R6qSjK1WbUAd5yrCSbiNlXrrbbt26N9f3KsMwCPNtuHFagYnxdpn6pxzWCECBAl5p2BgW5OIFEmTdTA9r3xwENMqaSmbpMoaGQZe1KLz1SWWDnBlGjYyRuGbsC8PFhingQiwbBVWEGGSBYMZBAQRRIMNazEV1SjUujW2bm+5dXEYLAvLC8Un1Mljtuk1ToCW6oKuGRgN5Zib0NSKKSUYSqiMVgiIKYgQ5alipDq5KaoaXLsdw5OtdwSax22HBcrMzGKuKVDEUkVkxmELuQIpuAfSdrBsNs2p4FUCzrTGkQ13S4WREkBMYpqiN4F46oC3iKlV8ivWa2goTpJyIFBJsELCgUooJONL2bd/eV5fOahoMmRyEBUU/DkZYNj0skFVBPHCk7L5ITpkNGfHXth17cyeABcJMBOssFs8VxkVhoKRKwKRLNiw5MAglYzISyIhohhGhrDA3gTJJTW0wg3CkoJiRSAiqgpFBQFWQZAgRRJAkVxKVCMQ1C3QpEfFuB0ETG4xYaZI6AICNoKhoXOkCEvidvhQRlgU1J0JDH8mwK/cRXcURJBWtShbdx19e8/YQj3Du1EirJwYAxka3Hj6ak8vls9g2PkSy9oXQoMJOwYIwkid9DxQ7Nuynz4GuCswBNkXGo+mpVMnT7mh5hO06+T2sOjjcogWSoyI4lt2GtNCUYBmQ+l3hDUkoiRIBEBEBhIsCIwWCMIWiIFDYaCsQQWksKUK0EoGRPDWjOGtYxRLawREEQGIgkNqdXmed87RHkUVoGXPYHiTWQ2Ah3mKfecsQ74wx3VbTA/AMRNHpzzv1/hGg0FBmED0hu08ZsofXjq33aWQyMTfCrmpyxCOugpNQifykYsV1w0nSmtjd57+E7ycr9RRb1mgsHle33y9mGjFsWDTv5RhA2gYUoWA/Ih0QRvy+REGEUgWQzKQclwEDgaFOccRR/UC+77Df2DEhCcJBIioiMQYyBtPxTiXC52EDH+SVddQpYtQWCnvkCIeeaYFhH8ICHeBcIkikGCSI66CkgFNRWSBQRGAFYdncWTQTkFITcIeVU/rRzimebSIlWoG66becMxG7vIOsi7bP0k6zo5wwNhyTM2AHQ4Kno2rpIFRMJvtD4wDRMyidAcaUMiC/s42BWFBxgHBFDTIYMjBmNTSGaUBXakKEdrChQ6rmpIGpmV5tan5dblm1tK3BZW6wubE9ypgGDiESgwHYZSRZADqVesgim4iABQEFW+uDDae2fN/uo9bo+MpUrjAo4xYtSdsPPJzRAYQNHRHedMQfzRA74QgJYgCRGdab/ghBwLhAhDQa22J96M5zrjx6iQgQduKjyJCeMJ5w3bTtPr+5cUkwiMPGe0q/xtWNMiaC0VFCDgAnafLT6vvtENjVPTxLX7twhw74lL7oyMgtcTrOopiVE8qUoRfBgQ4HwL1FmN0yL/H5etwPqKhY7US33U4mYVCEWh0J8jFCSCRGxkwQYCW0AkBljCGkgI0aAyZSRIzhYM5Y1swd7YOrtIB1jxP0U9YQLAQQ/yBW2Xnjk+YMDedgEA8jEsRDSkfH1NeJ4btNXPjpK9ckG8r9m47OlOuolYww4GgBQkhdITTQopnOabVaqOmFBkhNk4vMD1kAjxNwv8yJTc61e2yJkpIRLAdg6Ns8/u3FnlJMI2D+oJQ2/AL2L8zXawsqc8ITcOBWRkL5TVsBNFQ12OeDgKk6uYhMSHGGuZ9aLkB06ll0ZqqoEQZAQYEQYAoCgwkkRUYsghBITBjcPRqnPZ8Tow3XQn1XY2o12iH0eJ195ZAoqJTyUzrNdU4TtHzETy9VDUk9NmomkMfVq+Jl1qxR+Db8GtMWf8JVdWi3j9u5xZsu+VMh8eX8zoVMHdhxTixI2y4+RizZH8dPlZOZDGWYRwtsOIxhNpmz5APA1QUEnmGRJKQl/KPX1n3Id0yB3hEDiFlAYSjDADbdm8vtlOUBELqOlYudCURZj6Bh3y0Abh8u/D0hgldvWRPrzMTu3gUjIKe6nsnnpp5N30j3kn9kHHa6qBtcP7xSLRh8SW9UqJ7rxaKEfYy7tbqypxfGT8IgkUg9cnsKDBNONAcSt1qLDaMePEutvcYmLoihtks8R5O0FhiVH7VofK6X4i7BTYrmiCFo+wzMY2kUEEiIbGZhIsUiJY3Q0ApIJKwrKioxRxCyp0TAC795cDh9bAstUMdyii4y0DTQlWiUEmVm6asbJY9y4WXmXKy7eKI7MEtQwgxQigYhEaNKLsGxqamqboYGi2bCbEziDuuWy6arChvcIJi0IGjG5TopHrFUIetD7yCFxXjqOHoott0hqdwVF0YmhI/bAKkzBUYsCKoolnNA0mpiSdBITA3BBbcWvuHNrsUyUxs2KNtkpwavbOiWsGEtZShD7OkDjThCw/UdJ0qb9R4nz6OZ6oRdpNsd2ZcxzJ0GkOYxuvWTSvD4WpFPWjRQd1SpO0o8/WFetzQ3HRORVBmY2dzQTpbJzBKIDA5IrlmA5ZZRom1B8sHGDQi16aVGwIPf9WYoT0BdPzPj4Bw5m8LToIMno4HjcGg96dGulC2hYhzJpkCM5bixlqrfB+2FPbDbx9CukIKELYpsYpz+azihpCjWTp81nz3Zx+TVNGmiUtKNi+3MfndOVorQNxzLVTvc9B9jtnDqA3mUNrpSu72OJyO89gUHpRU9wQtci/fTpxuh3XrGWLSgkkSEVpgDmiqXpF9qAe9A/oYTuPxyDSIfACJqIHDZQOwGBdqIgSJPFTaln4mgMoaYpIRgIeSp+Vhu7sTtjtk6/QWtND4iJ9u72htPMyy5xH5M4QO6HaOQ0CwRVkiMMyiMFjor3XESVbhhJS2qEogkjJoI0FiJrwBDBC7elqJRBZFGJAqqkoCEBEgsRUqS0GwUhFkhBRYoFAljKFECwQEKAxCkCJAhFYwYlPYdgsEJFkU0nanzpJzAgvhFNA9N7dpgpqg21KQtCrAbIM+b3jD9GKmRj0M+X3FZxtvD5F6tm1cGQ8Q6U9v9EPdfbfO0qeeyWxj2w6MGQjFwtgsQf08gGcG0pg7yYNsJUI5zvqw/afPoTLGaX62qW2vKtVi8uSlhygL/QOzNi2KwOIR0hnI79IpBqx1BcbEj0EFtJGaCUbHctk6YZnSDY7PIyJ3sJagoFjkdusOBn8eI5Rk072Koo6cQfFYw+VpXodp3BJDmNr9Z9g7tt0lbvpohXMNvcHZkR5GIC0X3EnStSmdFls40svvc7kuu4ikzI7sUQc2LIoqbl3oqGgn8REN6z0uWTLWhSYkpXEW8LNwidM6CrdD6mmPFuZ1NGmTWcUrfWH7HjuGzZyaqh3thrccQ3EXjVB9uM5s3bZijW6q4mKyZ3YG502DxHTNOt8RrfnN40oKAdfV0PsVzoN6rqMrSA+kznscEiMhwiBmB/AIB5mAyRg+pG2GaTMcig5UxAfHzJrB75G95wJDTQxshV2JSgS9GKjiYsfLhCQqdDk0vHMY7hlNmETDH/BvKf++XxOCSUt04OyMuN8xuVkxDdVaSpMlUspramzpiiziOuNE1wzDx35TQaR2eSLjz8qjqVfO6jVRGTTKprzLABxhDDIi4+G0+w/QwmvAMx7E+svYbkAKD1LWmgW3vYapf3fj0mQY4u0ndPyQHTpUKNOBQ57eW0gPQJNZoDimjZU2tLBG432TRTId0qYWcBCojGNSgqkN2VhHAECgbbFkhbDAm2iVNibAYWRghEHieuPEQWTmSozqnn15bzgYwOf6p4FGRkGyWJJAT7nZRc7MwWUZlsg+7VEdtShsJYxkYyaQuFKkUQrJdGQlDE0eulcRdOIWGRK2Omx4Tg7xd4eBEchTIzEwo4iF2BiK5UVQVRSrcUGmOqqF5KC9iiR4HF84PjeukdeyhS/AN0CQFOqLpg3EsEZprj5UQ5XcJeVKXWsNPWeXrVTWpuGK5mbQLmWCQg75JIQkkVY8q34IV58v721MOY5YmXvzER1OmEDlBJrorOYL4RiCFlyc4QSZ9A+aB+yZZ77GLWgO9khMfsC2h0DeMckFDf4OcTSiIJodhvg8qBHubJwDR8ORhtxtJcmqPY+Fy4XLMGpFUQVFYsRWIsRHcVHMDA+yJhkKRalLSpAEJEEiALCETvSHfCBhMAYMzuXGWdobWDsXSOtsrpXSSwGJrJTBaoiIZaloWEwtZJUkLg0gAsxDCG0SUBxEEk0Zu5i5wjQi0lb6j2VOKYRyh36aGRyJtgwzNM6KQZWpUtYZxJVOiZt6ZJL0w07BLN2/16QUL2ka7xafZPMCY0Y9SsmnAyeGV0OAujnTMPnZ77NgYwsoLtoFgYuSpgYkMU2gwGjFj80O8momYMtr574MwzUA9loFsT8I7rFBB6E5MVPed7CESPgimKZOFmMQDoZ2Qezx7jz6+HPfPQ8Gt7B/kRiHl0eI51xW7HHpPeqFpXD0auXxNcPQQmb0gzJ4LFtn7wJOGBkMl1ScUe6igpgu0Ufgt2Ca0iLbVD4ekcTuHKc7GnMFOfohmhRKDZDETOJbSYhmUZBy/qrvLEw6YOcrG+u6iw05mK1I8mUUFTENw50hnENC0ILNDhhFggzCDUBccwXp3hG2OO0MUbsBvYxL2plPbeVbWRDUGqOKfAsXRuqNqVtuLoRFmlDGPXp028dc7UaSQUhJCbjCsJGc05CnGVOjhMt20m5YgMGZmlao0aHQUxUIMJGiUapJU1nIwM20MTRs6NNQtw0YMUihirQrQSTL9cRU+NVGBD4mNzU0UQqiRU/QrS5y+cvlt3MCkmx5EKpgJa5kmNOxxkHZmwPZ6XRIaNWqkZc2QU6F0g4eJkdhkZ2nmSH5zxgTIYIIxRGGhgxQGMSWDogoyhSIhKIXMETlKaMLQOQhyIlVoFQ1Y6b0NaULjdXgZoyrva3ME38LitG1itazmcrGNszNiWEmGIZHQoHCgGkMlUYRiwzYMlElhOROO+OxpNR4WYiGys9B5RpDoxgTlxCepfCHd9eXs3sNMyE0DQuGoIRGoxFgzW+aMYkxLmJqyhhESbGEpqCU0dSGR5wQ9nf7TouoxNq7DMGmxnZ1eGEEx3oiQjNNMUkQzMepkTpGxwANav4u2nREsQFkFxDMsWG/Gk3cnejkXFciCBbCMIciBRUKMLajQgiJE0GGQQGLBZFZajoKQtiy4SoJvM+VaB2TjqbNZRxrK0pFWi0TaUxGCLky3ALTRzG6BMGH1A85RyjZr+nY6dUIM6esOFECY6HRH1umU0cZhqmDYJPiKPDQ+G3aWMDxAjERKhFpT3PczNVRiXwtENyR0DPBUxBb6CjmSAQdoGAdXPStShwdEkNxwLm9HNgv5II0KVBEoh2xSkMkEZytlaliQk/U8sRXpIBcAzEDDHTq1BjgYweU9Zkxk/FxNfTRi5QQx7TzdAoAUCgc+FjGImaewahpDF07vJ18qHE6FZ4pVHwAZiYOFSRHfRrCaCKZKijMaBSTDWBRBl2ksXRplymMR59Gg9R0W/T2by0xCb40YF3Eo/t663E23DfDIEfKQ6QQnlJCF6mvrh6DMDcwJ2sJsATrVVV6DfQIOAN/TMWojCuz855NjDY439GnZktsDfKqjJE0CUUQibyFgNalJ8FoK3k5OWq2mTnrYyS8tDE9rrBChDTRpA5ZGiGfYdiZqnRcsaSKSBAIjED2lmFK25qETYBEUoXAOnfsfL5+ru5VUKYSVQdh2d5dvsYbDTszNahVYcAbYiCRy7ZMkMTUsC0FLuAlxLWqqQ6Ddx6tdIek2zx4jBRpRoqbEpV6jYpdH26JuALACYgRLwxA1qxBS/FMwjf8hIQig5TreQoNGG5+oV3CdFrL0iHRzmU6yK5kwRMkIZ7SjBpIwSCMRWEMaPIlJv/yYKAKMICF/LMgOmXXED2j8LgYJqAcyYi9URIwPpiLCDsQP0Y6ETsAuOYRT/ga3cRJGlqFLQSwnOAbHZJ971e7A9HjYw8EoFky9lerwwWHvrIZeoqVRir/85+eRku+6n0Iw0S5OKN2h9LCxigJA9eCd4WShnKFiEE6W6XIAJHFHLlV0hHkdB2OJEh08a3wHWMeoNz2fdO2u7c4EBJCMhI2rPy4BRQERYIgQUEJvYRl4BzMBLql5GWkGdxyNW/7CKQmSppvX4UFTrO/ptLhc+z5BYfIX/KEB6jPsDOl3DDyzHdJVeqVZIsiQKCgaCaLCuD+G4rtTY88TSSXR3UTqta4QoyU27rsKIJZQRjY+qZrSXIh0AvzA4VdufpJZrGwGGIFHUeYuT754BiYh7DIwU6I+1whCAECgCiJCZmgXBrXG2W5fs6P8erspJJL6/xe4UlmwdIUUnfDyknUUMQOFIZ1jJbGJP5ROGUM9v3a3PI/TDcdXk74XQDO5TGkswA+hGKwGAMhRgFSQozypGKILJAUU5va1AgGR3HfcZWQXpPdEz+ym76tAWfh58c644nG0fcisPnVqF/OL1QYUbwfcdqhv4dnU6ja4FEVttO7lpBBDVLD0FulwCHSocWsm+Zl22Vku5qZS6olNtTJpZOQeU4w1J1kD2WBPS78AE36xTPFzhpCZqBpMjViIlg4rkRXT6/Gjs6z4WfmhJ0IaS5ad1DCH/efMzTWoV8nxCzQ+FZOrJ6g2gUQLzPAT4+o9zDgj/hqO/nLD7D76+sVh3fwJtg5CP3FPNW5jBwxGmmfwodPh/Gf4i7kinChIJa1DFA')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/unitgrade_data/Question2.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/unitgrade_data/Question2.pkl
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/unitgrade_data/Week1.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/unitgrade_data/Week1.pkl
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/unitgrade_data/Week1Titles.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-autograde/unitgrade_data/Week1Titles.pkl
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout.tar
similarity index 65%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde.tar
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout.tar
index 8786bf46facaf94d6f8b944b1724ffbf3b06f3d2..1948e65c340da2782da924a12bc2991dd79dc8a7 100644
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/deploy.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/deploy.py
new file mode 100644
index 0000000000000000000000000000000000000000..b311122a682185bf51192c38d8b4fb97e019b9a9
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/deploy.py
@@ -0,0 +1,9 @@
+from cs102_autolab.report2_test import Report2
+from unitgrade_private.hidden_create_files import setup_grade_file_report
+from snipper.snip_dir import snip_dir
+
+if __name__ == "__main__":
+
+    setup_grade_file_report(Report2)
+    snip_dir("./", "../../students/cs102", clean_destination_dir=True, exclude=['*.token', 'deploy.py'])
+    pass
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/homework1.py
new file mode 100644
index 0000000000000000000000000000000000000000..c314aab912bd438c5947d99a871a63989dc90dcd
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/homework1.py
@@ -0,0 +1,18 @@
+def reverse_list(mylist): 
+    """
+    Given a list 'mylist' returns a list consisting of the same elements in reverse order. E.g.
+    reverse_list([1,2,3]) should return [3,2,1] (as a list).
+    """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+def add(a,b): 
+    """ Given two numbers `a` and `b` this function should simply return their sum:
+    > add(a,b) = a+b """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+if __name__ == "__main__":
+    # Example usage:
+    print(f"Your result of 2 + 2 = {add(2,2)}")
+    print(f"Reversing a small list", reverse_list([2,3,5,7])) 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/report2_test.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/report2_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..039ade86a6d8886ed0a17f87637047907a4f3fbb
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/report2_test.py
@@ -0,0 +1,69 @@
+from unitgrade.framework import Report
+from unitgrade.evaluate import evaluate_report_student
+from homework1 import add, reverse_list
+from unitgrade import UTestCase, cache  
+import homework1
+import unittest
+
+
+class Week1(UTestCase):
+    def test_add(self):
+        self.assertEqualC(add(2,2))
+        self.assertEqualC(add(-100, 5))
+
+    def test_reverse(self):
+        self.assertEqualC(reverse_list([1, 2, 3])) 
+
+    def test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+class Week1Titles(UTestCase): 
+    """ The same problem as before with nicer titles """
+    def test_add(self):
+        """ Test the addition method add(a,b) """
+        self.assertEqualC(add(2,2))
+        print("output generated by test")
+        self.assertEqualC(add(-100, 5))
+        # self.assertEqual(2,3, msg="This test automatically fails.")
+
+    def test_reverse(self):
+        ls = [1, 2, 3]
+        reverse = reverse_list(ls)
+        self.assertEqualC(reverse)
+        # Although the title is set after the test potentially fails, it will *always* show correctly for the student.
+        self.title = f"Checking if reverse_list({ls}) = {reverse}"  # Programmatically set the title 
+
+    def ex_test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+
+class Question2(UTestCase): 
+    @cache
+    def my_reversal(self, ls):
+        # The '@cache' decorator ensures the function is not run on the *students* computer
+        # Instead the code is run on the teachers computer and the result is passed on with the
+        # other pre-computed results -- i.e. this function will run regardless of how the student happens to have
+        # implemented reverse_list.
+        return reverse_list(ls)
+
+    def test_reverse_tricky(self):
+        ls = (2,4,8)
+        ls2 = self.my_reversal(tuple(ls))                   # This will always produce the right result, [8, 4, 2]
+        print("The correct answer is supposed to be", ls2)  # Show students the correct answer
+        self.assertEqualC(reverse_list(ls))                 # This will actually test the students code.
+        return "Buy world!"                                 # This value will be stored in the .token file  
+
+
+class Report2(Report):
+    title = "CS 106a"
+    questions = [(Week1, 10), (Week1Titles, 6), (Question2, 10)]
+    pack_imports = [homework1]
+
+if __name__ == "__main__":
+    evaluate_report_student(Report2(), unmute=True)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/unitgrade_data/Question2.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/unitgrade_data/Question2.pkl
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/unitgrade_data/Week1Titles.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g-handout/unitgrade_data/Week1Titles.pkl
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g.rb
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rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.rb
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g.rb
index cf285db3bd5a91ba7023b67b4a39ba3cf18af258..48723003d37b9a966960dc2c1eca57b2622faadb 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.rb
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g.rb
@@ -1,10 +1,10 @@
 require "AssessmentBase.rb"
 
-module Cs105d
+module Cs105g
   include AssessmentBase
 
   def assessmentInitialize(course)
-    super("cs105d",course)
+    super("cs105g",course)
     @problems = []
   end
 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g.yml
similarity index 70%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.yml
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g.yml
index 127159c8cd03e7ebddfa3f7a5b5727971a9a6ffa..75b5ae0511a0bba2dc84f3015752ae50f60f1116 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.yml
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/cs105g.yml
@@ -1,14 +1,14 @@
 ---
 
 general:
-  name: cs105d
-  description: ''
+  name: cs105g
+  description: 'Upload the file {homework_file}'
   display_name: CS 106a
   handin_filename: homework1.py
   handin_directory: handin
   max_grace_days: 0
-  handout: cs105d-handout.tar
-  writeup: writeup/cs105d.html
+  handout: cs105g-handout.tar
+  writeup: writeup/writeup.html
   max_submissions: -1
   disable_handins: false
   max_size: 2
@@ -17,7 +17,7 @@ general:
 problems:
 
   - name: Unitgrade score
-    description: ''
+    description: 'Automatic score as computed using the _grade.py script'
     max_score: 16
     optional: false
 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/handout.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105g/handout.tar
new file mode 100644
index 0000000000000000000000000000000000000000..c998314848846c61b4b4b4776c319dc8e97bbf9d
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105g/handout.tar differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/Makefile
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/Makefile
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/Makefile-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/Makefile-handout
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/README b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/README
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/README
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/README
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/README-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/README-handout
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/Report2_handin.token b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/Report2_handin.token
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/Report2_handin.token
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/Report2_handin.token
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/docker_helpers.py
similarity index 98%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/docker_helpers.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/docker_helpers.py
index 806c2b39c6782ed377ab0d4cf70a36d03940fd7b..0b82a931c0268a356ee54f777fbc7ed0ef095e3f 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/docker_helpers.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/docker_helpers.py
@@ -38,7 +38,8 @@ def compile_docker_image(Dockerfile, tag=None, no_cache=False):
     base = os.path.dirname(Dockerfile)
     if tag == None:
         tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} .")
+    cmd = f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} ."
+    os.system(cmd)
     return tag
 
 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver.sh
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver.sh
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver.sh-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver.sh-handout
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver_python.py
similarity index 85%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/driver_python.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver_python.py
index 5f81a1a9498cc96dc44883e9ba64d7997949b5a6..9b7535e8542f1ef840372b73ed7b7b191b527dc0 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/driver_python.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver_python.py
@@ -31,8 +31,8 @@ def pfiles():
 
 handin_filename = "homework1.py"
 student_token_file = 'Report2_handin.token'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
+instructor_grade_script = 'report2_test_grade.py'
+grade_file_relative_destination = "report2_test_grade.py"
 host_tmp_dir = wdir + "/tmp"
 homework_file = "homework1.py"
 # homework_file = "homework1.py"
@@ -50,15 +50,16 @@ print("student_token_file", student_token_file)
 for f in glob.glob(os.getcwd() + "/*"):
     print(f)
 
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
 # run the stuff.
 if not student_should_upload_token:
     """ Add the student homework to the right location. """
     print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
     print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
     shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
+else:
+    # Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
 command = f"cd tmp && {command} --noprogress --autolab"
 
 def rcom(cm):
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver_python.py-handout
similarity index 85%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver_python.py-handout
index 5f81a1a9498cc96dc44883e9ba64d7997949b5a6..9b7535e8542f1ef840372b73ed7b7b191b527dc0 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py-handout
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/driver_python.py-handout
@@ -31,8 +31,8 @@ def pfiles():
 
 handin_filename = "homework1.py"
 student_token_file = 'Report2_handin.token'
-instructor_grade_script = 'report2_grade.py'
-grade_file_relative_destination = "report2_grade.py"
+instructor_grade_script = 'report2_test_grade.py'
+grade_file_relative_destination = "report2_test_grade.py"
 host_tmp_dir = wdir + "/tmp"
 homework_file = "homework1.py"
 # homework_file = "homework1.py"
@@ -50,15 +50,16 @@ print("student_token_file", student_token_file)
 for f in glob.glob(os.getcwd() + "/*"):
     print(f)
 
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
 # run the stuff.
 if not student_should_upload_token:
     """ Add the student homework to the right location. """
     print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
     print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
     shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
+else:
+    # Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
 command = f"cd tmp && {command} --noprogress --autolab"
 
 def rcom(cm):
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/homework1.py
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/homework1.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105g/src/homework1.py
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/report2_test_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/report2_test_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8beb75a59c69a11a44c230aeea7d7784b980423
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/report2_test_grade.py
@@ -0,0 +1,4 @@
+# report2_test.py
+''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
+import bz2, base64
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/student_sources.zip
new file mode 100644
index 0000000000000000000000000000000000000000..bedf1661c157074734fff12860900ef41ef0a3a2
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105g/src/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105h/Makefile
similarity index 64%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/Makefile
index b9c752894264c4bac9843a2d1bc1fb171a8881d1..df7fc93e26d08d2d19649b0d2aeb786e580a481b 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/Makefile
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/Makefile
@@ -9,24 +9,26 @@ all: handout handout-tarfile
 
 handout: 
 	# Rebuild the handout directory that students download
-	(rm -rf cs105-handout; mkdir cs105-handout)
-	cp -p src/Makefile-handout cs105-handout/Makefile
-	cp -p src/README-handout cs105-handout/README
-	cp -p src/driver_python.py cs105-handout
+	(rm -rf cs105h-handout; mkdir cs105h-handout)
+	cp -p src/Makefile-handout cs105h-handout/Makefile
+	cp -p src/README-handout cs105h-handout/README
+	cp -p src/driver_python.py cs105h-handout
 
-	cp -p src/student_sources.zip cs105-handout
+	cp -p src/student_sources.zip cs105h-handout
 
-	cp -p src/homework1.py cs105-handout
+	cp -p src/homework1.py cs105h-handout
 
-	cp -p src/docker_helpers.py cs105-handout
+	cp -p src/docker_helpers.py cs105h-handout
 
-	cp -p src/report2_grade.py cs105-handout
+	cp -p src/report2_test_grade.py cs105h-handout
+
+	cp -p src/Report2_handin.token cs105h-handout
 
 
 handout-tarfile: handout
 	# Build *-handout.tar and autograde.tar
-	tar cvf cs105-handout.tar cs105-handout
-	cp -p cs105-handout.tar autograde.tar
+	tar cvf cs105h-handout.tar cs105h-handout
+	cp -p cs105h-handout.tar autograde.tar
 
 clean:
 	# Clean the entire lab directory tree.  Note that you can run
@@ -35,7 +37,7 @@ clean:
 	rm -f *~ *.tar
 	(cd src; make clean)
 	(cd test-autograder; make clean)
-	rm -rf cs105-handout
+	rm -rf cs105h-handout
 	rm -f autograde.tar
 #
 # CAREFULL!!! This will delete all student records in the logfile and
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105h/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..4886586aa04b4fa0a8db4e10f42bd7d3a3db1f2b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp homework1.py cs105h-autograde
+	(cd cs105h-autograde; python3 driver_python.py)
+
+clean:
+	rm -rf *~ cs105h-autograde
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105h/autograde.tar
new file mode 100644
index 0000000000000000000000000000000000000000..56f6c6aba52c46c1992144324f142db798345513
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105h/autograde.tar differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/Report2_handin.token b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/Report2_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..379766ca8efbf72b3380fa54fa7150d2ecd7839f
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/Report2_handin.token
@@ -0,0 +1,327 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+47655d0753e025d6b3b20db676ecc36fe8124fb1af5d2933b475e0e5ff511d76e94036b02cf3e5949bcc17d82112f1f73e0e2e0ad97945d989a56f7943e40f39 58044
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..553b297f4123b99d794be4be5e97d573c3906378
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp homework1.py cs105h-handout
+	(cd cs105h-handout; python3 driver_python.py)
+
+clean:
+	rm -rf *~ cs105h-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..e627a7473b7c94be7380bc9cd86ed3d653539af9
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/driver_python.py
@@ -0,0 +1,92 @@
+import os
+import glob
+import shutil
+import sys
+import subprocess
+from unitgrade_private.autolab.autolab import format_autolab_json
+from unitgrade_private.docker_helpers import student_token_file_runner
+from unitgrade_private import load_token
+import time
+import unitgrade_private
+
+verbose = False
+tag = "[driver_python.py]"
+
+if not verbose:
+    print("="*10)
+    print(tag, "Starting unitgrade evaluation...")
+import unitgrade
+print(tag, "Unitgrade version", unitgrade.version.__version__)
+print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
+
+
+sys.stderr = sys.stdout
+wdir = os.getcwd()
+
+def pfiles():
+    print("> Files in dir:")
+    for f in glob.glob(wdir + "/*"):
+        print(f)
+    print("---")
+
+handin_filename = "homework1.py"
+student_token_file = 'Report2_handin.token'
+instructor_grade_script = 'report2_test_grade.py'
+grade_file_relative_destination = "report2_test_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "homework1.py"
+# homework_file = "homework1.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/homework1.py
new file mode 100644
index 0000000000000000000000000000000000000000..c314aab912bd438c5947d99a871a63989dc90dcd
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/homework1.py
@@ -0,0 +1,18 @@
+def reverse_list(mylist): 
+    """
+    Given a list 'mylist' returns a list consisting of the same elements in reverse order. E.g.
+    reverse_list([1,2,3]) should return [3,2,1] (as a list).
+    """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+def add(a,b): 
+    """ Given two numbers `a` and `b` this function should simply return their sum:
+    > add(a,b) = a+b """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+if __name__ == "__main__":
+    # Example usage:
+    print(f"Your result of 2 + 2 = {add(2,2)}")
+    print(f"Reversing a small list", reverse_list([2,3,5,7])) 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/report2_test.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/report2_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..039ade86a6d8886ed0a17f87637047907a4f3fbb
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/report2_test.py
@@ -0,0 +1,69 @@
+from unitgrade.framework import Report
+from unitgrade.evaluate import evaluate_report_student
+from homework1 import add, reverse_list
+from unitgrade import UTestCase, cache  
+import homework1
+import unittest
+
+
+class Week1(UTestCase):
+    def test_add(self):
+        self.assertEqualC(add(2,2))
+        self.assertEqualC(add(-100, 5))
+
+    def test_reverse(self):
+        self.assertEqualC(reverse_list([1, 2, 3])) 
+
+    def test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+class Week1Titles(UTestCase): 
+    """ The same problem as before with nicer titles """
+    def test_add(self):
+        """ Test the addition method add(a,b) """
+        self.assertEqualC(add(2,2))
+        print("output generated by test")
+        self.assertEqualC(add(-100, 5))
+        # self.assertEqual(2,3, msg="This test automatically fails.")
+
+    def test_reverse(self):
+        ls = [1, 2, 3]
+        reverse = reverse_list(ls)
+        self.assertEqualC(reverse)
+        # Although the title is set after the test potentially fails, it will *always* show correctly for the student.
+        self.title = f"Checking if reverse_list({ls}) = {reverse}"  # Programmatically set the title 
+
+    def ex_test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+
+class Question2(UTestCase): 
+    @cache
+    def my_reversal(self, ls):
+        # The '@cache' decorator ensures the function is not run on the *students* computer
+        # Instead the code is run on the teachers computer and the result is passed on with the
+        # other pre-computed results -- i.e. this function will run regardless of how the student happens to have
+        # implemented reverse_list.
+        return reverse_list(ls)
+
+    def test_reverse_tricky(self):
+        ls = (2,4,8)
+        ls2 = self.my_reversal(tuple(ls))                   # This will always produce the right result, [8, 4, 2]
+        print("The correct answer is supposed to be", ls2)  # Show students the correct answer
+        self.assertEqualC(reverse_list(ls))                 # This will actually test the students code.
+        return "Buy world!"                                 # This value will be stored in the .token file  
+
+
+class Report2(Report):
+    title = "CS 106a"
+    questions = [(Week1, 10), (Week1Titles, 6), (Question2, 10)]
+    pack_imports = [homework1]
+
+if __name__ == "__main__":
+    evaluate_report_student(Report2(), unmute=True)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/report2_test_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/report2_test_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..d35d464081aea7fee536c44ebc291e882d67be65
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/report2_test_grade.py
@@ -0,0 +1,4 @@
+# report2_test.py
+''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
+import bz2, base64
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/unitgrade_data/Question2.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/unitgrade_data/Question2.pkl
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/unitgrade_data/Week1.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/unitgrade_data/Week1.pkl
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index 0000000000000000000000000000000000000000..d7e897ace5ae661bbe6e4d3d29bff2c3dbbea55a
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/unitgrade_data/Week1Titles.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-autograde/unitgrade_data/Week1Titles.pkl
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index 0000000000000000000000000000000000000000..3f846dd3e070d58ba594674b8ac74ebd84837781
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout.tar
new file mode 100644
index 0000000000000000000000000000000000000000..89891a8c82f05e7f426bd4034d18da34f73c476b
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/homework1.py
new file mode 100644
index 0000000000000000000000000000000000000000..c314aab912bd438c5947d99a871a63989dc90dcd
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/homework1.py
@@ -0,0 +1,18 @@
+def reverse_list(mylist): 
+    """
+    Given a list 'mylist' returns a list consisting of the same elements in reverse order. E.g.
+    reverse_list([1,2,3]) should return [3,2,1] (as a list).
+    """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+def add(a,b): 
+    """ Given two numbers `a` and `b` this function should simply return their sum:
+    > add(a,b) = a+b """
+    # TODO: 1 lines missing.
+    raise NotImplementedError("Implement function body")
+
+if __name__ == "__main__":
+    # Example usage:
+    print(f"Your result of 2 + 2 = {add(2,2)}")
+    print(f"Reversing a small list", reverse_list([2,3,5,7])) 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/report2_test.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/report2_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..039ade86a6d8886ed0a17f87637047907a4f3fbb
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/report2_test.py
@@ -0,0 +1,69 @@
+from unitgrade.framework import Report
+from unitgrade.evaluate import evaluate_report_student
+from homework1 import add, reverse_list
+from unitgrade import UTestCase, cache  
+import homework1
+import unittest
+
+
+class Week1(UTestCase):
+    def test_add(self):
+        self.assertEqualC(add(2,2))
+        self.assertEqualC(add(-100, 5))
+
+    def test_reverse(self):
+        self.assertEqualC(reverse_list([1, 2, 3])) 
+
+    def test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+class Week1Titles(UTestCase): 
+    """ The same problem as before with nicer titles """
+    def test_add(self):
+        """ Test the addition method add(a,b) """
+        self.assertEqualC(add(2,2))
+        print("output generated by test")
+        self.assertEqualC(add(-100, 5))
+        # self.assertEqual(2,3, msg="This test automatically fails.")
+
+    def test_reverse(self):
+        ls = [1, 2, 3]
+        reverse = reverse_list(ls)
+        self.assertEqualC(reverse)
+        # Although the title is set after the test potentially fails, it will *always* show correctly for the student.
+        self.title = f"Checking if reverse_list({ls}) = {reverse}"  # Programmatically set the title 
+
+    def ex_test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+
+class Question2(UTestCase): 
+    @cache
+    def my_reversal(self, ls):
+        # The '@cache' decorator ensures the function is not run on the *students* computer
+        # Instead the code is run on the teachers computer and the result is passed on with the
+        # other pre-computed results -- i.e. this function will run regardless of how the student happens to have
+        # implemented reverse_list.
+        return reverse_list(ls)
+
+    def test_reverse_tricky(self):
+        ls = (2,4,8)
+        ls2 = self.my_reversal(tuple(ls))                   # This will always produce the right result, [8, 4, 2]
+        print("The correct answer is supposed to be", ls2)  # Show students the correct answer
+        self.assertEqualC(reverse_list(ls))                 # This will actually test the students code.
+        return "Buy world!"                                 # This value will be stored in the .token file  
+
+
+class Report2(Report):
+    title = "CS 106a"
+    questions = [(Week1, 10), (Week1Titles, 6), (Question2, 10)]
+    pack_imports = [homework1]
+
+if __name__ == "__main__":
+    evaluate_report_student(Report2(), unmute=True)
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/unitgrade_data/Question2.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/unitgrade_data/Question2.pkl
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index 0000000000000000000000000000000000000000..bcfd4d4c0ec3b7fa90b9d5945812dfd05623770b
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/unitgrade_data/Week1.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/unitgrade_data/Week1.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..d7e897ace5ae661bbe6e4d3d29bff2c3dbbea55a
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/unitgrade_data/Week1.pkl differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/unitgrade_data/Week1Titles.pkl b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h-handout/unitgrade_data/Week1Titles.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..3f846dd3e070d58ba594674b8ac74ebd84837781
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diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h.rb
similarity index 74%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.rb
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h.rb
index b115a01143a9ecc95eda6fbb126244631c5a74fe..969cdb6f7cbd6ecd529e5a708d46000c61534bd3 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.rb
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h.rb
@@ -1,10 +1,10 @@
 require "AssessmentBase.rb"
 
-module Cs105
+module Cs105h
   include AssessmentBase
 
   def assessmentInitialize(course)
-    super("cs105",course)
+    super("cs105h",course)
     @problems = []
   end
 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h.yml
similarity index 64%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.yml
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h.yml
index 91c6ac44dbc6297ed69997a00abb8c897b7dc890..8684bf28d0eeab31e5ad7e0a5ca6a8b8da259344 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.yml
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/cs105h.yml
@@ -1,14 +1,14 @@
 ---
 
 general:
-  name: cs105-new-version
-  description: ''
-  display_name: CS 105 Report autolab v2
+  name: cs105h
+  description: 'Upload the file homework1.py'
+  display_name: CS 106a
   handin_filename: homework1.py
   handin_directory: handin
   max_grace_days: 0
-  handout: cs105-new-version-handout.tar
-  writeup: writeup/cs105-new-version.html
+  handout: cs105h-handout.tar
+  writeup: writeup/writeup.html
   max_submissions: -1
   disable_handins: false
   max_size: 2
@@ -17,8 +17,8 @@ general:
 problems:
 
   - name: Unitgrade score
-    description: ''
-    max_score: 16
+    description: 'Automatic score as computed using the _grade.py script'
+    max_score: 26
     optional: false
 
 autograder:
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/Makefile
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/src/Makefile
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/Makefile-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/src/Makefile-handout
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/README
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/src/README
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/README-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105/src/README-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/src/README-handout
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/Report2_handin.token b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/Report2_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..379766ca8efbf72b3380fa54fa7150d2ecd7839f
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/Report2_handin.token
@@ -0,0 +1,327 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+47655d0753e025d6b3b20db676ecc36fe8124fb1af5d2933b475e0e5ff511d76e94036b02cf3e5949bcc17d82112f1f73e0e2e0ad97945d989a56f7943e40f39 58044
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/docker_helpers.py
similarity index 98%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105b/src/docker_helpers.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/src/docker_helpers.py
index 806c2b39c6782ed377ab0d4cf70a36d03940fd7b..0b82a931c0268a356ee54f777fbc7ed0ef095e3f 100644
--- a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/docker_helpers.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/docker_helpers.py
@@ -38,7 +38,8 @@ def compile_docker_image(Dockerfile, tag=None, no_cache=False):
     base = os.path.dirname(Dockerfile)
     if tag == None:
         tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} .")
+    cmd = f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} ."
+    os.system(cmd)
     return tag
 
 
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver.sh
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver.sh
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver.sh-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver.sh-handout
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..e627a7473b7c94be7380bc9cd86ed3d653539af9
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver_python.py
@@ -0,0 +1,92 @@
+import os
+import glob
+import shutil
+import sys
+import subprocess
+from unitgrade_private.autolab.autolab import format_autolab_json
+from unitgrade_private.docker_helpers import student_token_file_runner
+from unitgrade_private import load_token
+import time
+import unitgrade_private
+
+verbose = False
+tag = "[driver_python.py]"
+
+if not verbose:
+    print("="*10)
+    print(tag, "Starting unitgrade evaluation...")
+import unitgrade
+print(tag, "Unitgrade version", unitgrade.version.__version__)
+print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
+
+
+sys.stderr = sys.stdout
+wdir = os.getcwd()
+
+def pfiles():
+    print("> Files in dir:")
+    for f in glob.glob(wdir + "/*"):
+        print(f)
+    print("---")
+
+handin_filename = "homework1.py"
+student_token_file = 'Report2_handin.token'
+instructor_grade_script = 'report2_test_grade.py'
+grade_file_relative_destination = "report2_test_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "homework1.py"
+# homework_file = "homework1.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver_python.py-handout
new file mode 100644
index 0000000000000000000000000000000000000000..e627a7473b7c94be7380bc9cd86ed3d653539af9
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/driver_python.py-handout
@@ -0,0 +1,92 @@
+import os
+import glob
+import shutil
+import sys
+import subprocess
+from unitgrade_private.autolab.autolab import format_autolab_json
+from unitgrade_private.docker_helpers import student_token_file_runner
+from unitgrade_private import load_token
+import time
+import unitgrade_private
+
+verbose = False
+tag = "[driver_python.py]"
+
+if not verbose:
+    print("="*10)
+    print(tag, "Starting unitgrade evaluation...")
+import unitgrade
+print(tag, "Unitgrade version", unitgrade.version.__version__)
+print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
+
+
+sys.stderr = sys.stdout
+wdir = os.getcwd()
+
+def pfiles():
+    print("> Files in dir:")
+    for f in glob.glob(wdir + "/*"):
+        print(f)
+    print("---")
+
+handin_filename = "homework1.py"
+student_token_file = 'Report2_handin.token'
+instructor_grade_script = 'report2_test_grade.py'
+grade_file_relative_destination = "report2_test_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "homework1.py"
+# homework_file = "homework1.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/homework1.py
new file mode 100644
index 0000000000000000000000000000000000000000..379766ca8efbf72b3380fa54fa7150d2ecd7839f
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/homework1.py
@@ -0,0 +1,327 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+47655d0753e025d6b3b20db676ecc36fe8124fb1af5d2933b475e0e5ff511d76e94036b02cf3e5949bcc17d82112f1f73e0e2e0ad97945d989a56f7943e40f39 58044
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/report2_test_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/report2_test_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..d35d464081aea7fee536c44ebc291e882d67be65
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/report2_test_grade.py
@@ -0,0 +1,4 @@
+# report2_test.py
+''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
+import bz2, base64
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/student_sources.zip
new file mode 100644
index 0000000000000000000000000000000000000000..923416694a5d0aeed427d324405a01930fa42b09
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105h/src/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105h/writeup/writeup.html b/examples/autolab_example_py_upload/instructor/tmp/cs105h/writeup/writeup.html
new file mode 100644
index 0000000000000000000000000000000000000000..143cf421951567e72125afac9d98c62d74cb3b57
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105h/writeup/writeup.html
@@ -0,0 +1,5 @@
+
+    <html><body>
+    To hand in this assignment, upload the file <b>homework1.py</b>
+    </body></html>    
+    
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/writeup/writeup.html b/examples/autolab_example_py_upload/instructor/tmp/writeup/writeup.html
new file mode 100644
index 0000000000000000000000000000000000000000..143cf421951567e72125afac9d98c62d74cb3b57
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/writeup/writeup.html
@@ -0,0 +1,5 @@
+
+    <html><body>
+    To hand in this assignment, upload the file <b>homework1.py</b>
+    </body></html>    
+    
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/report2_test.py b/examples/autolab_example_py_upload/students/cs102_autolab/report2_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..039ade86a6d8886ed0a17f87637047907a4f3fbb
--- /dev/null
+++ b/examples/autolab_example_py_upload/students/cs102_autolab/report2_test.py
@@ -0,0 +1,69 @@
+from unitgrade.framework import Report
+from unitgrade.evaluate import evaluate_report_student
+from homework1 import add, reverse_list
+from unitgrade import UTestCase, cache  
+import homework1
+import unittest
+
+
+class Week1(UTestCase):
+    def test_add(self):
+        self.assertEqualC(add(2,2))
+        self.assertEqualC(add(-100, 5))
+
+    def test_reverse(self):
+        self.assertEqualC(reverse_list([1, 2, 3])) 
+
+    def test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+class Week1Titles(UTestCase): 
+    """ The same problem as before with nicer titles """
+    def test_add(self):
+        """ Test the addition method add(a,b) """
+        self.assertEqualC(add(2,2))
+        print("output generated by test")
+        self.assertEqualC(add(-100, 5))
+        # self.assertEqual(2,3, msg="This test automatically fails.")
+
+    def test_reverse(self):
+        ls = [1, 2, 3]
+        reverse = reverse_list(ls)
+        self.assertEqualC(reverse)
+        # Although the title is set after the test potentially fails, it will *always* show correctly for the student.
+        self.title = f"Checking if reverse_list({ls}) = {reverse}"  # Programmatically set the title 
+
+    def ex_test_output_capture(self):
+        with self.capture() as out:
+            print("hello world 42")                     # Genereate some output (i.e. in a homework script)
+        self.assertEqual(out.numbers[0], 42)            # out.numbers is a list of all numbers generated
+        self.assertEqual(out.output, "hello world 42")  # you can also access the raw output.
+
+
+class Question2(UTestCase): 
+    @cache
+    def my_reversal(self, ls):
+        # The '@cache' decorator ensures the function is not run on the *students* computer
+        # Instead the code is run on the teachers computer and the result is passed on with the
+        # other pre-computed results -- i.e. this function will run regardless of how the student happens to have
+        # implemented reverse_list.
+        return reverse_list(ls)
+
+    def test_reverse_tricky(self):
+        ls = (2,4,8)
+        ls2 = self.my_reversal(tuple(ls))                   # This will always produce the right result, [8, 4, 2]
+        print("The correct answer is supposed to be", ls2)  # Show students the correct answer
+        self.assertEqualC(reverse_list(ls))                 # This will actually test the students code.
+        return "Buy world!"                                 # This value will be stored in the .token file  
+
+
+class Report2(Report):
+    title = "CS 106a"
+    questions = [(Week1, 10), (Week1Titles, 6), (Question2, 10)]
+    pack_imports = [homework1]
+
+if __name__ == "__main__":
+    evaluate_report_student(Report2(), unmute=True)
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Question2.pkl b/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Question2.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..bcfd4d4c0ec3b7fa90b9d5945812dfd05623770b
Binary files /dev/null and b/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Question2.pkl differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1.pkl b/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1.pkl
index ad7ddfc809f5bda52c1d7e563ee22f36ab221123..d7e897ace5ae661bbe6e4d3d29bff2c3dbbea55a 100644
Binary files a/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1.pkl and b/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1.pkl differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1Titles.pkl b/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1Titles.pkl
index f0cd99c72858c45d52215386019e7a4ed35e3342..3f846dd3e070d58ba594674b8ac74ebd84837781 100644
Binary files a/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1Titles.pkl and b/examples/autolab_example_py_upload/students/cs102_autolab/unitgrade_data/Week1Titles.pkl differ
diff --git a/examples/autolab_example_py_upload/tmp/cs105_pyfile/src/report2_grade.py b/examples/autolab_example_py_upload/tmp/cs105_pyfile/src/report2_grade.py
index ed7227f24103a00dfc8b261b6795896bd2a4f4d2..cb89f5a40b86e7388e579a0696d75b02fc26b199 100644
--- a/examples/autolab_example_py_upload/tmp/cs105_pyfile/src/report2_grade.py
+++ b/examples/autolab_example_py_upload/tmp/cs105_pyfile/src/report2_grade.py
@@ -1,4 +1,4 @@
-# cs102/report2.py
+# cs102/report2_test.py
 ''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
 import bz2, base64
 exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/twosumlab.png b/examples/autolab_example_py_upload/twosumlab.png
new file mode 100644
index 0000000000000000000000000000000000000000..b192f20fd894abe4306de0c1fa7b1f9f1f6f12d7
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diff --git a/examples/autolab_example_py_upload/twosumlab.tar b/examples/autolab_example_py_upload/twosumlab.tar
new file mode 100644
index 0000000000000000000000000000000000000000..b0ce70794d1577eb3206c5fe298d53ef5e13af6c
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diff --git a/examples/example_framework/instructor/cs102/report2_grade.py b/examples/example_framework/instructor/cs102/report2_grade.py
index ed7227f24103a00dfc8b261b6795896bd2a4f4d2..cb89f5a40b86e7388e579a0696d75b02fc26b199 100644
--- a/examples/example_framework/instructor/cs102/report2_grade.py
+++ b/examples/example_framework/instructor/cs102/report2_grade.py
@@ -1,4 +1,4 @@
-# cs102/report2.py
+# cs102/report2_test.py
 ''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
 import bz2, base64
 exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/examples/example_framework/instructor/output/report2.py b/examples/example_framework/instructor/output/report2.py
index aa50d37bf51fc03215fc5872d4877289d60abe2b..16d830f1c05d60ea9656adc73f504c5dab5dd1b0 100644
--- a/examples/example_framework/instructor/output/report2.py
+++ b/examples/example_framework/instructor/output/report2.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 from unitgrade import UTestCase, cache  
 
 class Week1(UTestCase):
diff --git a/examples/example_framework/instructor/output/report2_b.py b/examples/example_framework/instructor/output/report2_b.py
index e5dc8fe9178b7ec1199e0f74700381379af011cc..e14f75cf25d8da29f86a70d6cff1a0b0511646e0 100644
--- a/examples/example_framework/instructor/output/report2_b.py
+++ b/examples/example_framework/instructor/output/report2_b.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 class Week1Titles(UTestCase): 
     """ The same problem as before with nicer titles """
     def test_add(self):
diff --git a/examples/example_framework/instructor/output/report2_c.py b/examples/example_framework/instructor/output/report2_c.py
index 8b386384e5672619f390c1cb458986fed8409a3a..c47fa0b31b2d016e4ae11ef4544fdfb960167834 100644
--- a/examples/example_framework/instructor/output/report2_c.py
+++ b/examples/example_framework/instructor/output/report2_c.py
@@ -1,4 +1,4 @@
-# report2.py
+# report2_test.py
 class Question2(UTestCase): 
     @cache
     def my_reversal(self, ls):
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..50fd70cae5e15aa30e95150c5054ac51e504f089
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,5 @@
+mosspy
+jinja2
+#unitgrade
+setuptools==57 # This is because of pyminifier (mumble, grumble)
+pyminifier
diff --git a/src/unitgrade_private/autolab/autolab.py b/src/unitgrade_private/autolab/autolab.py
index ce1313809525b13d2aaa5e4a8c306de6cf465cc1..25230471d8d59489fc139be1c73198e09fb820f9 100644
--- a/src/unitgrade_private/autolab/autolab.py
+++ b/src/unitgrade_private/autolab/autolab.py
@@ -73,7 +73,14 @@ def paths2report(base_path, report_file):
 def run_relative(file, base):
     relative = os.path.relpath(file, base)
     mod = os.path.normpath(relative)[:-3].split(os.sep)
-    os.system(f"cd {base} && python -m {'.'.join(mod)}")
+    for pyver in ["python", "python3", "python3.9"]:
+        code = os.system(f"cd {base} && {pyver} -m {'.'.join(mod)}")
+        if code == 0:
+            return code
+    raise Exception("Could not run the file", file, "in dir", dir)
+
+
+
 
 
 def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STUDENT_BASE, STUDENT_GRADE_FILE,
@@ -111,6 +118,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     # Now we have the instructor token file. Let's get the student token file.
     total_ = res['total'][1]
     problems = []
+<<<<<<< HEAD
     problems.append(dict(name='Unitgrade score', description='Score obtained by automatic grading', max_score=total_, optional='false'))
     problems.append(dict(name='Written feedback', description='Written (TA) feedback', max_score=0, optional='true'))
     # print(problems)
@@ -120,6 +128,20 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
 
     run_relative(STUDENT_GRADE_FILE, STUDENT_BASE)
 
+=======
+    problems.append(dict(name='Unitgrade score', description='Automatic score as computed using the _grade.py script', max_score=total_, optional='false'))
+    print(problems)
+    sc = [('Total', res['total'][0])] + [(q['title'], q['obtained']) for k, q in res['details'].items()]
+    ss = ", ".join([f'"{t}": {s}' for t, s in sc])
+    scores = '{"scores": {' + ss + '}}'
+    print(scores)
+    # Quickly make student .token file to upload:
+    # os.system(f"cd {os.path.dirname(STUDENT_HANDOUT_DIR)} && python -m programs.{os.path.basename(INSTRUCTOR_GRADE_FILE)[:-3]}")
+    # os.system(f"cd {STUDENT_HANDOUT_DIR} && python {os.path.basename(INSTRUCTOR_GRADE_FILE)}")
+    # handin_filename = os.path.basename(STUDENT_TOKEN_FILE)
+    run_relative(os.path.join(STUDENT_BASE, STUDENT_GRADE_FILE), STUDENT_BASE)
+    # if student_should_upload_token:
+>>>>>>> 0429c721315832077f7682929c6f3a40449d85fc
     STUDENT_TOKEN_FILE = glob.glob(os.path.dirname(STUDENT_GRADE_FILE) + "/*.token")[0]
     handin_filename = os.path.basename(STUDENT_TOKEN_FILE)
     for _ in range(3):
@@ -140,7 +162,6 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     INSTRUCTOR_REPORT_FILE = INSTRUCTOR_GRADE_FILE[:-9] + ".py"
 
     print("Making data...")
-
     # /home/tuhe/Documents/unitgrade_private_v1/examples/example_simplest/instructor/programs/report5.py"
     data = {
         'base_name': base_name,
@@ -158,7 +179,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
         'student_should_upload_token': student_should_upload_token,
         'homework_file': homework_file,
         'student_token_src_filename': student_token_src_filename,
-        # 'homework_file_basename':
+        'description': f'Upload the file {homework_file}' if homework_file is not None else handin_filename
     }
     print("> Running jinja2")
     # shutil.copyfile(TEMPLATE_BASE + "/hello.yml", f"{LAB_DEST}/{base_name}.yml")
@@ -191,7 +212,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     os.mkdir(LAB_DEST + "/handin")
     os.mkdir(LAB_DEST + "/test-autograder")  # Otherwise make clean will screw up.
     print(f"cd {LAB_DEST} && make && cd {CURDIR}")
-    cmd = f"cd {LAB_DEST} && make && cd {CURDIR}"
+    # cmd = f"cd {LAB_DEST} && make && cd {CURDIR}"
 
     os.system(f"cd {LAB_DEST} && make && cd {CURDIR}")
     # os.system(f"cd {LAB_DEST} && make handout")
@@ -201,9 +222,52 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     print("Ran make command...")
     if output_tar is None:
         output_tar = os.getcwd() + "/" + base_name + ".tar"
-    print("Making archive")
+    # Making the writeup-directory.
+    os.mkdir(LAB_DEST + "/writeup")
+
+    writeup_template = f"""
+    <html><body>
+    To hand in this assignment, upload the file <b>{handin_filename}</b>
+    </body></html>    
+    """
+    writeup = Environment(loader=FileSystemLoader("./")).from_string(writeup_template).render(data)
+    with open(LAB_DEST + "/writeup/writeup.html", 'w') as f:
+        f.write(writeup)
+
     shutil.make_archive(output_tar[:-4], 'tar', root_dir=COURSES_BASE, base_dir=base_name)
     print("Log in to autolab, go to 'install assessment', upload the tar file", output_tar)
+    # Lets try an alternative creation procedure.
+    if os.path.exists(f"{LAB_DEST}/{base_name}-handout"):
+        shutil.rmtree(f"{LAB_DEST}/{base_name}-handout")
+    if os.path.exists(f"{LAB_DEST}/{base_name}-autograde"):
+        shutil.rmtree(f"{LAB_DEST}/{base_name}-autograde")
+    shutil.copytree(STUDENT_BASE, f"{LAB_DEST}/{base_name}-handout")
+    shutil.copytree(STUDENT_BASE, f"{LAB_DEST}/{base_name}-autograde")
+    shutil.copyfile(STUDENT_TOKEN_FILE, f"{LAB_DEST}/{base_name}-autograde/{student_token_src_filename}")
+
+    jj(TEMPLATE_BASE + "/src/driver_python.py", f"{LAB_DEST}/{base_name}-autograde/driver_python.py", data)
+    jj(TEMPLATE_BASE + "/autograde-Makefile", f"{LAB_DEST}/{base_name}-autograde/autograde-Makefile", data=data)
+    # shutil.copyfile(STUDENT_TOKEN_FILE, f"{LAB_DEST}/{base_name}-autograde/{student_token_src_filename}") # Why is this needed? TBH it is not needed, really.
+    shutil.copyfile(INSTRUCTOR_GRADE_FILE, f"{LAB_DEST}/{base_name}-autograde/{os.path.basename(INSTRUCTOR_GRADE_FILE)}")
+
+    autograde_makefile_template = f"""
+all:
+	tar xf autograde.tar
+	cp {handin_filename} {base_name}-autograde
+	(cd {base_name}-autograde; python3 driver_python.py)
+
+clean:
+	rm -rf *~ {base_name}-autograde  
+""".strip()
+    autograde_makefile = Environment(loader=FileSystemLoader("./")).from_string(autograde_makefile_template).render(data)
+    with open(f"{LAB_DEST}/autograde-Makefile", 'w') as f:
+        f.write(autograde_makefile)
+    # Check if you need to make the autograder...
+
+    # Make the autograder and the handouts...
+    shutil.make_archive(f"{LAB_DEST}/autograde", 'tar', root_dir=f"{LAB_DEST}", base_dir=f"{base_name}-autograde")
+    shutil.make_archive(f"{LAB_DEST}/cs105h-handout", 'tar', root_dir=f"{LAB_DEST}", base_dir=f"{base_name}-handout")
+    shutil.make_archive(output_tar[:-4], 'tar', root_dir=COURSES_BASE, base_dir=base_name)
     return output_tar
 
 def deploy_assignment(base_name, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STUDENT_BASE, STUDENT_GRADE_FILE,
diff --git a/src/unitgrade_private/autolab/lab_template/autograde-Makefile b/src/unitgrade_private/autolab/lab_template/autograde-Makefile
index 55d8a7d5b5059d6cd28c8c3a3e157019e175e8d5..6be4b0659ec23d15826c66d2e9e6c610624c176d 100644
--- a/src/unitgrade_private/autolab/lab_template/autograde-Makefile
+++ b/src/unitgrade_private/autolab/lab_template/autograde-Makefile
@@ -4,4 +4,4 @@ all:
 	(cd {{base_name}}-handout; python3 driver_python.py)
 
 clean:
-	rm -rf *~ hello3-handout
+	rm -rf *~ {{base_name}}-handout
diff --git a/src/unitgrade_private/autolab/lab_template/hello.yml b/src/unitgrade_private/autolab/lab_template/hello.yml
index f5df4d46cb62f783efef5694ddffc4ca139feaca..a2e18477b8336fb537dfa2c8a84ef839ba4d45a9 100644
--- a/src/unitgrade_private/autolab/lab_template/hello.yml
+++ b/src/unitgrade_private/autolab/lab_template/hello.yml
@@ -2,13 +2,13 @@
 
 general:
   name: {{ base_name }}
-  description: ''
+  description: '{{description}}'
   display_name: {{ display_name }}
   handin_filename: {{ handin_filename }}
   handin_directory: handin
   max_grace_days: 0
   handout: {{ base_name }}-handout.tar
-  writeup: writeup/{{base_name}}.html
+  writeup: writeup/writeup.html
   max_submissions: -1
   disable_handins: false
   max_size: 2
diff --git a/src/unitgrade_private/autolab/lab_template/src/driver_python.py b/src/unitgrade_private/autolab/lab_template/src/driver_python.py
index e0554527f13653c439dbb17ecb95ab52d3a0cc57..5a21791060c91f01fe99996b8f85f84fd7b83539 100644
--- a/src/unitgrade_private/autolab/lab_template/src/driver_python.py
+++ b/src/unitgrade_private/autolab/lab_template/src/driver_python.py
@@ -44,54 +44,49 @@ if not verbose:
     print(f"{student_token_file=}")
     print(f"{instructor_grade_script=}")
 
-
 print("Current directory", os.getcwd())
 print("student_token_file", student_token_file)
 for f in glob.glob(os.getcwd() + "/*"):
     print(f)
-
-command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
-# Alternatively. Unzip the .token file of the student (true version). Overwrite the .py file with the one uploaded, then
-# run the stuff.
-if not student_should_upload_token:
-    """ Add the student homework to the right location. """
-    print("Moving from", os.path.basename(handin_filename), "to", handin_filename)
-    print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
-    shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
-
-command = f"cd tmp && {command} --noprogress --autolab"
-
-def rcom(cm):
-    rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
-    print(rs.stdout)
-    if len(rs.stderr) > 0:
-        print(tag, "There were errors in executing the file:")
-        print(rs.stderr)
-
-start = time.time()
-rcom(command)
-ls = glob.glob(token)
-f = ls[0]
-results, _ = load_token(ls[0])
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
 
 if verbose:
-    print(f"{token=}")
-    print(results['total'])
+    print(tag, f"{token=}")
+    print(tag, results['total'])
 
 format_autolab_json(results)
-
-# if os.path.exists(host_tmp_dir):
-#     shutil.rmtree(host_tmp_dir)
-# with io.BytesIO(sources['zipfile']) as zb:
-#     with zipfile.ZipFile(zb) as zip:
-#         zip.extractall(host_tmp_dir
-# print("="*10)
-# print('{"scores": {"Correctness": 100,  "Problem 1": 4}}')
-## Format the scores here.
-
-# sc = [('Total', results['total'][0])] + [(q['title'], q['obtained']) for k, q in results['details'].items()]
-# ss = ", ".join([f'"{t}": {s}' for t, s in sc])
-# scores = '{"scores": {' + ss + '}}'
-# print('{"_presentation": "semantic"}')
-# print(scores)
-
diff --git a/src/unitgrade_private/docker_helpers.py b/src/unitgrade_private/docker_helpers.py
index 806c2b39c6782ed377ab0d4cf70a36d03940fd7b..0b82a931c0268a356ee54f777fbc7ed0ef095e3f 100644
--- a/src/unitgrade_private/docker_helpers.py
+++ b/src/unitgrade_private/docker_helpers.py
@@ -38,7 +38,8 @@ def compile_docker_image(Dockerfile, tag=None, no_cache=False):
     base = os.path.dirname(Dockerfile)
     if tag == None:
         tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} .")
+    cmd = f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} ."
+    os.system(cmd)
     return tag
 
 
diff --git a/src/unitgrade_private/hidden_gather_upload.py b/src/unitgrade_private/hidden_gather_upload.py
index a044bf7e58744d620080a021222665a91d96e5f7..f83f278c0567db0e74a63c0d01727a9d53b5e4ee 100644
--- a/src/unitgrade_private/hidden_gather_upload.py
+++ b/src/unitgrade_private/hidden_gather_upload.py
@@ -218,7 +218,9 @@ def load_token(file_in):
 
 
 def source_instantiate(name, report1_source, payload):
+    # print("Executing sources", report1_source)
     eval("exec")(report1_source, globals())
+    # print("Loaind gpayload..")
     pl = pickle.loads(bytes.fromhex(payload))
     report = eval(name)(payload=pl, strict=True)
     return report