diff --git a/docker_images/docker_tango_python/Dockerfile b/docker_images/docker_tango_python/Dockerfile
index bc05f666f81280d1aac298f1da2d3ac03a37a080..e081c74465e0b3f3a0e933f16f5a1f180c8740c3 100644
--- a/docker_images/docker_tango_python/Dockerfile
+++ b/docker_images/docker_tango_python/Dockerfile
@@ -29,7 +29,7 @@ RUN chmod +s /usr/bin/autodriver
 
 # Do the python stuff.
 COPY requirements.txt requirements.txt
-RUN pip3 install -r requirements_pip.txt
+RUN pip3 install -r requirements.txt
 
 # Clean up
 WORKDIR /home
diff --git a/docker_images/docker_tango_python/requirements.txt b/docker_images/docker_tango_python/requirements.txt
index d54dd8e080c8d149c26b762a2f7376367c679c1c..084c2114d646cf6216e9083aae4b72784c4206e5 100644
--- a/docker_images/docker_tango_python/requirements.txt
+++ b/docker_images/docker_tango_python/requirements.txt
@@ -4,4 +4,5 @@ jinja2
 tabulate
 pyfiglet
 colorama
-unitgrade-devel>=0.1.26 # Required to run automatic evaluation (load tokens etc.)
+unitgrade>=0.1.23
+unitgrade-devel>=0.1.37 # Required to run automatic evaluation (load tokens etc.)
diff --git a/docker_images/unitgrade-docker/Dockerfile b/docker_images/unitgrade-docker/Dockerfile
index c52ab6f4ea333affedd36b0fb78dbeeeac206f1d..0ba4b77a284c02a8d364d63d1da9505e09ffc63c 100644
--- a/docker_images/unitgrade-docker/Dockerfile
+++ b/docker_images/unitgrade-docker/Dockerfile
@@ -9,7 +9,7 @@ WORKDIR /home
 
 # Remember to include requirements.
 COPY requirements.txt requirements.txt
-RUN pip3 install -r requirements_pip.txt
+RUN pip3 install -r requirements.txt
 
 # Not required.
 # RUN pip install git+https://git@gitlab.compute.dtu.dk/tuhe/unitgrade.git
diff --git a/examples/autolab_example/cs102.tar b/examples/autolab_example/cs102.tar
index 5087f6edb70f36a48a8310e5ed1a96dd163740a6..46c9f415daf0e036b9dc5db9d6d64f88454836c0 100644
Binary files a/examples/autolab_example/cs102.tar and b/examples/autolab_example/cs102.tar differ
diff --git a/examples/autolab_example/tmp/cs102/autograde.tar b/examples/autolab_example/tmp/cs102/autograde.tar
index f69ca9f83fbe5bb8e566e8d74b9d5376eaa73215..a1c603b811ed5be1b9e3859dca39473006d40110 100644
Binary files a/examples/autolab_example/tmp/cs102/autograde.tar and b/examples/autolab_example/tmp/cs102/autograde.tar differ
diff --git a/examples/autolab_example/tmp/cs102/cs102-handout.tar b/examples/autolab_example/tmp/cs102/cs102-handout.tar
index f69ca9f83fbe5bb8e566e8d74b9d5376eaa73215..a1c603b811ed5be1b9e3859dca39473006d40110 100644
Binary files a/examples/autolab_example/tmp/cs102/cs102-handout.tar and b/examples/autolab_example/tmp/cs102/cs102-handout.tar differ
diff --git a/examples/autolab_example/tmp/cs102/cs102-handout/docker_helpers.py b/examples/autolab_example/tmp/cs102/cs102-handout/docker_helpers.py
index 1e77a6aa1061c2ded4df8efed4af4b9df5779c78..38cf3134cc1b5b032dc1e9088a7025e824862dd1 100644
--- a/examples/autolab_example/tmp/cs102/cs102-handout/docker_helpers.py
+++ b/examples/autolab_example/tmp/cs102/cs102-handout/docker_helpers.py
@@ -7,7 +7,6 @@ import io
 import subprocess
 import urllib.request
 
-
 def download_docker_images(destination=None):
     if destination is None:
         destination = os.getcwd()
@@ -32,8 +31,6 @@ def download_docker_images(destination=None):
             else:
                 print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
                 shutil.copytree(tmp_dir, dest)
-        # zf.extract(f, path=destination)
-    a = 234
 
 
 def compile_docker_image(Dockerfile, tag=None):
@@ -47,9 +44,12 @@ def compile_docker_image(Dockerfile, tag=None):
 
 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:
@@ -59,50 +59,46 @@ def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade
     """
     assert os.path.exists(student_token_file)
     assert os.path.exists(instructor_grade_script)
-    start = time.time()
     from unitgrade_private import load_token
+    start = time.time()
     results, _ = load_token(student_token_file)
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
     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.
 
+    # 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 # pycom[:-3]
+    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, token_location
+    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):
+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:
@@ -113,6 +109,10 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
     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)
@@ -138,8 +138,19 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
     # Done extracting the zip file! Now time to move the (good) report test class into the location.
     gscript = instructor_grade_script
 
-    student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    instructor_grade_script = os.path.dirname(student_grade_script) + "/"+os.path.basename(gscript)
+    # 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)
 
     """
@@ -151,14 +162,20 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
         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( 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)}"
@@ -167,11 +184,14 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
     print(fcom)
     init = time.time() - start
     # thtools.execute_command(fcom.split())
-    subprocess.check_output(fcom, shell=True).decode("utf-8")
+    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/tmp/cs102/cs102-handout/driver_python.py b/examples/autolab_example/tmp/cs102/cs102-handout/driver_python.py
index dc9aaa659551702eed60208d404c8c31b610c368..7e5dfc87253beea6b6ab26307fc5c7eb63ea2ec0 100644
--- a/examples/autolab_example/tmp/cs102/cs102-handout/driver_python.py
+++ b/examples/autolab_example/tmp/cs102/cs102-handout/driver_python.py
@@ -1,5 +1,6 @@
 import os
 import glob
+import shutil
 import sys
 import subprocess
 from unitgrade_private.autolab.autolab import format_autolab_json
@@ -23,10 +24,14 @@ def pfiles():
         print(f)
     print("---")
 
+handin_filename = "Report2_handin.token"
 student_token_file = 'Report2_handin.token'
 instructor_grade_script = 'report2_grade.py'
 grade_file_relative_destination = "cs102/report2_grade.py"
 host_tmp_dir = wdir + "/tmp"
+homework_file = ""
+# homework_file = ""
+student_should_upload_token =  # Add these from template.
 
 if not verbose:
     pfiles()
@@ -34,7 +39,17 @@ if not verbose:
     print(f"{student_token_file=}")
     print(f"{instructor_grade_script=}")
 
-command, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
+
+
+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):
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 1d854fcf648874f8dfbe9ae3413612904da2955c..ed7227f24103a00dfc8b261b6795896bd2a4f4d2 100644
--- a/examples/autolab_example/tmp/cs102/cs102-handout/report2_grade.py
+++ b/examples/autolab_example/tmp/cs102/cs102-handout/report2_grade.py
@@ -1,3 +1,4 @@
+# cs102/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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')))
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')))
\ No newline at end of file
diff --git a/examples/autolab_example/tmp/cs102/cs102-handout/student_sources.zip b/examples/autolab_example/tmp/cs102/cs102-handout/student_sources.zip
index c3a864fb570486f750958bc57e8c223a151e3f1f..f29b4caddf48034e22b6e375d7798a41d324194d 100644
Binary files a/examples/autolab_example/tmp/cs102/cs102-handout/student_sources.zip and b/examples/autolab_example/tmp/cs102/cs102-handout/student_sources.zip differ
diff --git a/examples/autolab_example/tmp/cs102/src/docker_helpers.py b/examples/autolab_example/tmp/cs102/src/docker_helpers.py
index 1e77a6aa1061c2ded4df8efed4af4b9df5779c78..38cf3134cc1b5b032dc1e9088a7025e824862dd1 100644
--- a/examples/autolab_example/tmp/cs102/src/docker_helpers.py
+++ b/examples/autolab_example/tmp/cs102/src/docker_helpers.py
@@ -7,7 +7,6 @@ import io
 import subprocess
 import urllib.request
 
-
 def download_docker_images(destination=None):
     if destination is None:
         destination = os.getcwd()
@@ -32,8 +31,6 @@ def download_docker_images(destination=None):
             else:
                 print("> Extracting docker image", os.path.basename(f[:-1]), "to", dest)
                 shutil.copytree(tmp_dir, dest)
-        # zf.extract(f, path=destination)
-    a = 234
 
 
 def compile_docker_image(Dockerfile, tag=None):
@@ -47,9 +44,12 @@ def compile_docker_image(Dockerfile, tag=None):
 
 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:
@@ -59,50 +59,46 @@ def student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade
     """
     assert os.path.exists(student_token_file)
     assert os.path.exists(instructor_grade_script)
-    start = time.time()
     from unitgrade_private import load_token
+    start = time.time()
     results, _ = load_token(student_token_file)
-    # with open(student_token_file, 'rb') as f:
-    #     results = pickle.load(f)
     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.
 
+    # 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 # pycom[:-3]
+    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, token_location
+    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):
+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:
@@ -113,6 +109,10 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
     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)
@@ -138,8 +138,19 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
     # Done extracting the zip file! Now time to move the (good) report test class into the location.
     gscript = instructor_grade_script
 
-    student_grade_script = host_tmp_dir + "/" + sources['report_relative_location']
-    instructor_grade_script = os.path.dirname(student_grade_script) + "/"+os.path.basename(gscript)
+    # 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)
 
     """
@@ -151,14 +162,20 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
         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( 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)}"
@@ -167,11 +184,14 @@ def docker_run_token_file(Dockerfile_location, host_tmp_dir, student_token_file,
     print(fcom)
     init = time.time() - start
     # thtools.execute_command(fcom.split())
-    subprocess.check_output(fcom, shell=True).decode("utf-8")
+    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/tmp/cs102/src/driver_python.py b/examples/autolab_example/tmp/cs102/src/driver_python.py
index dc9aaa659551702eed60208d404c8c31b610c368..7e5dfc87253beea6b6ab26307fc5c7eb63ea2ec0 100644
--- a/examples/autolab_example/tmp/cs102/src/driver_python.py
+++ b/examples/autolab_example/tmp/cs102/src/driver_python.py
@@ -1,5 +1,6 @@
 import os
 import glob
+import shutil
 import sys
 import subprocess
 from unitgrade_private.autolab.autolab import format_autolab_json
@@ -23,10 +24,14 @@ def pfiles():
         print(f)
     print("---")
 
+handin_filename = "Report2_handin.token"
 student_token_file = 'Report2_handin.token'
 instructor_grade_script = 'report2_grade.py'
 grade_file_relative_destination = "cs102/report2_grade.py"
 host_tmp_dir = wdir + "/tmp"
+homework_file = ""
+# homework_file = ""
+student_should_upload_token =  # Add these from template.
 
 if not verbose:
     pfiles()
@@ -34,7 +39,17 @@ if not verbose:
     print(f"{student_token_file=}")
     print(f"{instructor_grade_script=}")
 
-command, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
+
+
+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):
diff --git a/examples/autolab_example/tmp/cs102/src/driver_python.py-handout b/examples/autolab_example/tmp/cs102/src/driver_python.py-handout
index dc9aaa659551702eed60208d404c8c31b610c368..7e5dfc87253beea6b6ab26307fc5c7eb63ea2ec0 100644
--- a/examples/autolab_example/tmp/cs102/src/driver_python.py-handout
+++ b/examples/autolab_example/tmp/cs102/src/driver_python.py-handout
@@ -1,5 +1,6 @@
 import os
 import glob
+import shutil
 import sys
 import subprocess
 from unitgrade_private.autolab.autolab import format_autolab_json
@@ -23,10 +24,14 @@ def pfiles():
         print(f)
     print("---")
 
+handin_filename = "Report2_handin.token"
 student_token_file = 'Report2_handin.token'
 instructor_grade_script = 'report2_grade.py'
 grade_file_relative_destination = "cs102/report2_grade.py"
 host_tmp_dir = wdir + "/tmp"
+homework_file = ""
+# homework_file = ""
+student_should_upload_token =  # Add these from template.
 
 if not verbose:
     pfiles()
@@ -34,7 +39,17 @@ if not verbose:
     print(f"{student_token_file=}")
     print(f"{instructor_grade_script=}")
 
-command, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script, grade_file_relative_destination)
+
+
+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):
diff --git a/examples/autolab_example/tmp/cs102/src/report2_grade.py b/examples/autolab_example/tmp/cs102/src/report2_grade.py
index 1d854fcf648874f8dfbe9ae3413612904da2955c..ed7227f24103a00dfc8b261b6795896bd2a4f4d2 100644
--- a/examples/autolab_example/tmp/cs102/src/report2_grade.py
+++ b/examples/autolab_example/tmp/cs102/src/report2_grade.py
@@ -1,3 +1,4 @@
+# cs102/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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')))
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\ No newline at end of file
diff --git a/examples/autolab_example/tmp/cs102/src/student_sources.zip b/examples/autolab_example/tmp/cs102/src/student_sources.zip
index c3a864fb570486f750958bc57e8c223a151e3f1f..f29b4caddf48034e22b6e375d7798a41d324194d 100644
Binary files a/examples/autolab_example/tmp/cs102/src/student_sources.zip and b/examples/autolab_example/tmp/cs102/src/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_16_of_16.token b/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_16_of_16.token
index d1cc89f47b8026336d54ea9a744b5054d7576e4e..77a978252351241192fdfe7c24ee07f3e7d8191e 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_16_of_16.token
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/Report2_handin_16_of_16.token
@@ -1,540 +1,178 @@
 # 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/cs105_pyfile.tar b/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105_pyfile.tar
deleted file mode 100644
index e159d0587428fcef010410b511cbdb0645606d2d..0000000000000000000000000000000000000000
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diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105b.tar b/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105b.tar
new file mode 100644
index 0000000000000000000000000000000000000000..a52f0ba0471f27e68343b19e8812799658aef457
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diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105d.tar b/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105d.tar
new file mode 100644
index 0000000000000000000000000000000000000000..964da30cec68ef068731ddfea6fe7f2413b005f1
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/cs102_autolab/cs105d.tar differ
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 36c24bdba72dda48bc6a383d8b1b0d57c9aac60f..5f9dc9514e160898d68c3aa93fc8d10ff3c89459 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
@@ -7,17 +7,17 @@ if __name__ == "__main__":
     from report2 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.py', '*_grade.py'])
-
+    snip_dir("./", "../../students/cs102_autolab", clean_destination_dir=True, exclude=['*.token', 'deploy_autolab.py', '*_grade.py', 'tmp'])
 
     # 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).
     dockerfile = f"../docker/docker_tango_python/Dockerfile"
-    autograde_image = 'tango_python_tue'  # Tag given to the image in case you have multiple images.
-    compile_docker_image(Dockerfile=dockerfile, tag=autograde_image)  # Compile docker image. #!s
+    autograde_image = 'tango_python_tue2'  # Tag given to the image in case you have multiple images.
+    compile_docker_image(Dockerfile=dockerfile, tag=autograde_image, no_cache=False)  # Compile docker image. #!s
 
     # Step 2: Create the cs102.tar file from the grade scripts. #!s=b
     instructor_base = f"."
@@ -25,7 +25,7 @@ if __name__ == "__main__":
 
     from report2 import Report2
     # INSTRUCTOR_GRADE_FILE =
-    output_tar = new_deploy_assignment("cs105_pyfile",  # Autolab name of assignment (and name of .tar file)
+    output_tar = new_deploy_assignment("cs105d",  # 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",
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/report2.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2.py
index e128e2f308dcfa756c479d130324a681cab38be1..3bbcbbaa0daa564af5d04a15ba8f095bdff0f397 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/report2.py
+++ b/examples/autolab_example_py_upload/instructor/cs102_autolab/report2.py
@@ -1,6 +1,6 @@
 from unitgrade.framework import Report
 from unitgrade.evaluate import evaluate_report_student
-from cs102.homework1 import add, reverse_list
+from homework1 import add, reverse_list
 from unitgrade import UTestCase, cache  # !s
 import homework1
 
@@ -59,9 +59,8 @@ class Question2(UTestCase): #!s=c
         return "Buy world!"                                 # This value will be stored in the .token file  #!s=c
 
 
-import cs102
 class Report2(Report):
-    title = "CS 102 Report 2 (Scored using autolab)"
+    title = "CS 105 Report autolab v2"
     questions = [(Week1, 10), (Week1Titles, 6)]
     pack_imports = [homework1]
 
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 2b103752549d1ab716f7b6c48eb578fd6837f2a8..d52adecef721df29022bb284524df9472feb6c55 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
 ''' 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/tmp/cs105_pyfile/autograde-Makefile b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/autograde-Makefile
deleted file mode 100644
index cfd3cff716e59ce47bd4a2c9bf9cb54475b164cf..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/autograde-Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-all:
-	tar xf autograde.tar
-	cp homework1.py cs105_pyfile-handout
-	(cd cs105_pyfile-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/cs102_autolab/tmp/cs105_pyfile/autograde.tar b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/autograde.tar
deleted file mode 100644
index fa015f767ed7a30b2e059bd12d5aab797c18c453..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/autograde.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout.tar b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout.tar
deleted file mode 100644
index fa015f767ed7a30b2e059bd12d5aab797c18c453..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/homework1.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/homework1.py
deleted file mode 100644
index d1cc89f47b8026336d54ea9a744b5054d7576e4e..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/homework1.py
+++ /dev/null
@@ -1,540 +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/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/report2_grade.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/report2_grade.py
deleted file mode 100644
index 2b103752549d1ab716f7b6c48eb578fd6837f2a8..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-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/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/student_sources.zip
deleted file mode 100644
index 7017ea3793c96587c540e38f5cf1ef3e0a0e8b7f..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/student_sources.zip and /dev/null differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/homework1.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/homework1.py
deleted file mode 100644
index d1cc89f47b8026336d54ea9a744b5054d7576e4e..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/homework1.py
+++ /dev/null
@@ -1,540 +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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-l3MCWfOJ39QeGA6E7GspdAAAAAFauLhfu/THzAAGttASjuQkCoRebscRn+wIAAAAABFla.
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/report2_grade.py
deleted file mode 100644
index 2b103752549d1ab716f7b6c48eb578fd6837f2a8..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/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('QlpoOTFBWSZTWbHJ20cAVud/gH/25FZ7/////+//vv////5gZt73j3nvX2PG8PTpBe19895aZAAUOxg6D06o3t1SqoDm1GXsd7feMr1e+WltitRJNaAX0AGjW7fd96+Pr7UC82exNvjyJHeenHoKO++t6c91vl7z2Ou++96uRbu7vuNLH0Cvumb33N2Pu999vdu9mqcmUzabZJXWs7Vu4XdNdvB3dDeru3nwoiqW++5p9hfMPu3bb2+dzzyfYwn133vbnHemDd267x3PZe7157KFXt3vHuDPW3JenHvdbd5Uu8nDGrD24DpEs2l7OnnuL7ed3MfK93Zt10glK3yPlGNuvMfTzjr68p2U774Dpp77dr3vs8btx3clcZa0k2y+zqnuxrwlNEEAJkCaaCaCaYIBoIo9MU8Q0T1HlGnpNNPUaHqG1NqDTIEEQg0QEypvQ0Sn6kDymgNDR6npPUNNA0NAAAGCUxEQiE1FP0m1TTynqeoPKeU2mKPUaeU9QB6hoHqANADTIACTSSIImmVPxRiBhJ6m1PSMk9QNlBk2o000aaPJPSMgANBoIkiCaaEBoRimmaCeptRqZoIyKekNPamp5I9I08oDRmoAAk1EhACaAmTEU2KT9JqbUflR6myI2k00yAA0GQAAB0of1wX3fOygVAlFKv8SKfCAoj80AUkFAJCknoUWKqKn6/R5cLqoaT8P+lwpffQ6P6VfPSPqs0fh/wf9YrGJi7/gna+tXD/H78LFa8GF9XUVJCpV5/3897/yWhewxrvw997yvLFbio+463Bloaoi1PXhxbV6lJehXvv1Y3UXLuDcFa/04D81lwx2kR4aQnu+I48UzQXMEouCLocyRehyGTlLScyuX4QfyPwJTj7/435IEv8ub6az15TiKf95zpOTulovyK+VvfYwTHltuMtzDGbEUBEP++eWXQYICIJ1ggHkxFkCQgsFBEihIsikkn3SSiosBCST8oNlURt/hAKU4EBFKSKqVQ1AIiBA1IGmjBwaWkgNbHwdivGr1Jtzb6G7NL2nXga5k9pOknkqBZQVYJBVlkaKqCin3mFBiKgKpBUGRFVILlpI/7d36uXXzOzlzh+PsF8HWfBnf/0sYwWOiM+91zCdqIBcMqT7wBHgnNnkO7gdhYTvHSelZG/W34OArfBdEh09pgoTEwknZP5kI0XLMHHzdOwHTqQOSjra+qXYxm7eGFMtLS0pKYc8VoiOWXI/zORZmOcO44ftPO1haQz+hz/bd/P0fossry83vjrqOPHA4Sa6MZBybCjfqjBIr/GbNP+rKJ87Ebbr8JQmPejZPx+COvsdfydu5F4zfMmYwLi45nsg+FnbB9EJ6ViyXrrw9i8OVL5CL1epAmsEOmz9UGEytj//r4hM/vuyvukfO71Zw+a3A7uAibqFw9ngRtvPnwevWtnvIEQg1Gp6PVHw3kP54RJyv12xiQUB3SHnKUQi1ecEQi9FPVb8Ob9pfuOMmj6vLylkJoaj2eLz9kNOEz+vx7WaGXn+FunGj3f5+iXng/QLoihfZHSIKK6rw/+rvlCx2sjHVDs9Pu3HDE3djigpR/bR6ZaE4FUnXKdbsCmU2+pe0wfT7Odhjrdnu1Kc7r4DR9Mn/j0IylWV5oJcN+OeFscLJTrHYvdjNVhY5atBb79Y87iG33K8hHbnw898jqNe+OS9oPXb2S45r1rNd5GsdnJ+yePhi6M/Ci+JJG6iO79hQb/ZHu9BUkdRle3JnxoKu/SBd4uBXOfZoWc27DeW67gO3fLuckjK3h36EHq9jNCogWeIKEGI8VR0evl/MfmWyS5SVm30R54G6wWtcTwWEhe9OLLdTwRS8RWy2Bcm8ZeYjz/HyKEm0KaoUUW60lDSPaPNImGga8ylOwDqAzORNM+HQYybvp34ZUMlezuQIB91V/OsMhpiCGIKWW2K4qQCCT08MuBcbmY5EbK0ZSaRSLuczZnRo0yHibDUduvsWeMLOLJEIhxPm0cdi9o7Cy99l4QVRQZxeorhN0me/lyqsyVk69uykdTRgactEdO+70oA4s/V2+ZfXpCFDJMM3Mh8Pfd9WToRqUNUMaceMPiu1pwzgW5YLK2YFrO7MsppLfMBUj9TNjhwLAubqfeQEykz5NHt2KgdWbHy1nbXLtoFQHAQSEOhHKoX/yofL1OtDkCF20CPoo7eBHKDfX/GRITfyBboL2K3j6GsxO646tt3HsazU9AyCaCfUWG739oFELOBKOH0SloTodmd2Cfk2tBs6K2/Sh8tus53mAmq0h3XtnjezU2yHsfLtpPzcR9ncFMeAi+KNJx2LyC7TN8dXmMvzzoQNjxEv4Zfphx+Kx68bisnI6Athyw0EHP/5uUvChvFgUVEM4GAghVI56veECPjsX2m0Z3qXIidK/bSES4PBni7TODnTk7Z2GQTzOfB67bWQIsVBfu2sF8lxbSwccoUfn9+Er5115sXqjb7zNNFgjYt9TlCCW15H+NpghUlrKzXLjAdlka4RHLZ6w5dFv43+Qs/wwwnhpoKwEc88L7sgOXIpo9OLZfHT96ghXfIO3j9YnEi4tG3GcYM201LIJGNGJkB1JsaQFs9jg4m9BeWQbiMbcD6M2eLiyrO0HJA4WFrM2MTyKVKW3Y47s5pV82tDQta4oEioTw7ZVsqRiwi0sLCpNgzkdhDSFirj8CTXIVjm+jB07p7RksbKvR8TibyjjtDlrLjuPqNNo3AqUW1wofgZaT0g0CbVhx+4kRfoPqOClWcaiz2pS8SEhWmFR8WL0XVaouRbla68Z1LC45xflcZl5ke+29JIZkJIN6addE9g9CTIpmLDKm9rUFbutvOJIz8sMjLq+2qLbdwLNXspnw+aYVRnu6b97skIhz+gH1Lw0MWhxCHSAIiXCddh8t0KDy+tgZqYioSRN9r8/wyrZrd57CRvXtiabsrZRp4RpKTFpxH38D1wcbMjXIw7Gq7J7nIJY+BP75SKZWeLYEaTD7WtJn4ej58MhzIO8XzmRjZiVaiasFv4Gmuto86H3vSjraCvZ5pZXV53kOVdpN2hA68yacEzfIHa6YaGN13jvpXdy7wZ+jDsT5gmvS7BRNs9PB3pY1Xf6I7u9+vS/V4wa2Uw3FnDoA9RqhQ82RbDh7+WB6TB729whiYbYwQPnxM3Ei80wyKsQO/21eGFO3rkvqBiH++XAn7/294KS5/KuTjIfOkwRef91IiAC2tJVC3uVj60v6konqWubkegIZ9vmePls3G6+Ztpd3brzO2zZ8I7RyhaKRe+NuMRPFsqL7JJkTLpjXRrHO0uKS0lSeVhju7IL/l569picgyMdxwNiL1gVduXN2YtqvrF9t+F1/A5FzXUd6vVSPajpZT6NC22nSqWXTYK5WF5lOvSZkwNgnY7JKJExyPkIoTmYkAjOZXgeeKMhEQwMj1ucz2hv4HcZ0djO18UeybG/I3U2Zty601yzz7nyjgXlN94Ge3F+03O0jKhYmFSRuVa6Fhuv74kYMwmkcgwPxdHafh6z5M0E31NjkixD4SUkO0gIHDpOkteFOJFRHIptfaWYfOcpmOEygWhywfMcC+txW4uJKnCUGStFFcpXiIZSKcXKyuJkMdQfqR/eqppUipzu0NdKBWxR7gqqLEfbsoowbSVFNDpMEEmSE6dlFPVZbaXb9phV50uWK9QUQ3e4XBAT4GI/hrdYNrkZFTcCqrmnYXSoUDJFsZmhgWDXqtto6Dg0/ImeG+glsDFZePC3DuCN7wecO2X1eZOtoWAmEMTmIqWUIDbFQRQ3HGQV3luHu+vG2Eihkks02NyFgdaGg2de4cvkQ6pe7M+hBItHFjjOfCY2dHYXZWml+GMJ3RgKevaalQ3b4MFIi68KSw3mmRLNzNsypKqlo6SmTe2wMcCV0h7Oca6WhodRF2V5ZlIkwao+Bl8hXTChrrh0qLZ03cuSO9o5LZ23uyc07BNIm01w17pg8Ss9udJLFiMoRLoJIUr8Zb7Emh6camd9U6bekqKwiMzsszpfYOadY7sMg7FURUViAJa+kJvUT2qO36QhkPRHqNqRiJFYVE+FDwoUjZ3YuTi7u2vOd8jSvW/jpbXodl41bLSDfa2WWNKWZ8dQ95a+JaGIYEDHZz5agJGHnkSvyOvQhb8ue8lKOOrg6G7aWReiiZFo7qCMROG6IxCojCp6nMJg9ofVmcJ3YgubLpn0uvtJW8FWlNlhOIsJ3N5iwnIQQFMLgWF1gYUTDjjp44v3b2u79MAX9JVxkjd5Qwb+ON5Y+dLd0qkJgcNomqvJzXNp1ioFN0GM3IXiZXl2w0XVYE5SjN908gRQ2woWPLEPzdDQh0V7ESB3reOkGZdKDmiwJsJbnqYEuRfkOuzm3U42+MtsdGrWO3arrGfhLYaRKHAtsZTbGZEaiLhzHhdcVyNcM7K3sUeEYW0PMPNMXY2qpJjxKnK6VpL8WUtjrhqjtW5NS7zw5w0rt22otelsTuupTphLdiep4pJxI4L8k2lD6umU33GWjCMm7AXhMsseh2XXdWc3CnS4xb2yJ7zgVDEQgICrYIWFd4oLWRccs/TTI9EFTtEeszYdgN/PpL/UtUvED4/bIr5adGLN/d42bt/CIbxX47PWezUdgQ5gOQoXYI8AR9yCYm9zjlGuGsPg50b1UzvrqSa1dedCmcwEr/H+KL757BsHh23YJu/hHHs3LRitBsWnv2zmFKUCopFg68Fp4Z0FDKtX1+H5L7o91OX2tl+6TvfueB7xgg+o+glHkqBrwPuHtspj/g6rPwa1Pcrc8ol/1+3dts+qw73tnhNR+XWspWPhnP7Sxd354T1uo6qPxXE5zxj5xnHjhY+36Zsnk+yurjP2sj0g4ONtIdvBECxDAL72bGZ08ZT4jr5toEJ474t9T3YBnqSIDs/PPz2fZdh29fVleTxevzRjPWvv3aWUnxv7sMuL650TNN3vevRrbt6hoccIeF3cUhMkzD7DoE5Zb4b7ymoFYRRai1DgWyGRilR41QbYHwfz6w1fwmS5wMg8KYRWJIUW5O6PkQ60TGeukG+cfbfrlj7Xt8yL1ajh/D3ZnL0b95wpN7cZwbZd1Y3BYzrGhVZhxa1je8sMiadEiZHLbqGCdR+ZIsh7/llxWVgK8KhXSV0mvos0/VtfofqGG/G3V4OOt5YaRViDt8nLM0L+j6vz9O5u8h4DXjos5Lv+YSzj9yrEUimoRyRdZC+k41D5sTbOWu/vba1ZrVqGmPWM0LWDusWRkOuCfeVrBWVF0jJ7oe14IYf4ako+0B5inzn2P5puYbFJ+oxKT1+Pq/Z/sA9Wvzkw+j33xEOaAVgcLI5EIhCr2fto1ggbtD8mPgazp+Hv1oiqqqxA5JA2bNWsp255ionMZQyKKqrIZaVANENNMrQvj0N2GBZ8qopBQ+1GSnYqVmNtltlW2MQqxkKrJWVYySoKFf12mGZgCh0/LyPk6DWNgcrDwGRhtC7Afn/FNDBJhkyehJkCTJCIqSaQ8NroppN+waAoPHW5rkMhsy9XOZBxP7H8fV1zVKpeP/MPumML951AFkJBKvAYcQlOW0qhnspMQNXknRDZWF02x3/fYfdamVIw61yjMGIedLgudTTiRSuzXkoFiqiP2QzfHEpKcM3xU0sxrnGTJJpJLUb8faDRo+liooOPBvBFzVPuxtHnN/1SlzVxlbmQIcCTIaiSJW/eRi5+wLDHdQipaecIlgbY1LSwepUVHphihrw3lsSyHsmgRZ693rhFKsuVUVcRFewag1BNIDuLg7MAWD0GkH8AKBCURp0k2rafBxrkecet9nULOKyoHJyeKHNQgQ3KTKOlxjsQk2VaaAs8stGg2EPGqRcYhdGwmx+poHNkipr4CvwehnyVC/xnnybGxsAi2HgN3Q0LTG0VhiQVJf1iMQvZHp1hl5FhOxw0sa9YXQhFOxXXH3dBLEwZ5Eoe2fZryZfUxNXCWWHwb4CMAkWCOw94x3bexjCXV3aCI9Vgts7ui7sR7Rst8ChSHbnr9nShGduMByhl6Ew+4aW8D1qu0Yhq7lvikWjUwCFi3iPlsFNDmPSH6303yaq9dYYEJzqdtms7kHwaN+LLIewQ49gXqz4kaVS0BEDP5w4diOixQj9X+j8sSPDjEdOaFGP85RVyyrxsn3yclrWL3f5F5vU5V8e+7wpz9VIFou+H5SfQmIOfU9jRt/zVAkSUfkqkEqEf4l9cxjf9h+FkeT90nTC5ky8+kewUOEv1ZxzmdvOfiUxi76WeOUqYVLlXwvuh5lhyIfgpDzsC96aTefVzom574i/LruvMsd3F4dK1DpiiyF9Is1DrXoHlK4n5LyV8rx+vv4sPUcsX919moT4Ee+HnYkZF94y65TjS+z3LgX7POU88np7zQ2YycDDu0mFzxCMfxL85xoaqCT4qZG/FLPK/dusttWG475GoZlakkW7OkxIcdnCRP1yzm9GdO45RzvJEbS760ijGrCbU4jm7NyAgtiiZ5TDevPncAyJtJyZI+WCfuuB9xXoj27PniXA0N41DRv3KRypnU4Myn5+kQDuVyp6KIojRjcgyiR0qbQjLu94VPNDtCQ2Sdji874N8ZdB5PfNP2NwrMwm9kTU+OOmYbnrw4j7HF63yzEEFpzIwxa79nKdl1N8jdywh0Rpe72zf+Fsis13w6Xk917ZRKSdH2TLqZd4PTz/D5veAJrEHB6n40vALF4QQz6z2iTH4oOclY/h6bnVedoV78vBHy7a9YH2cN5n8D6bCJHWxoHh/wUV53Hco3D9/loOLte7otVzLk7iU7rwj5l+ik6Jy4wfnPGNfO52fQx+0p9d8fGRL76eQuRlO67XiIderw8cLtO92Nr6v9fW87PfAniO4uTn8yfEvzHZx8S5ruvHZdIhwUfx4XzXv4t+CvO+Kr18Z9cqcu9lPiPa4jouoIqLT41nzqvhh8RFRMurSgenvqBuvjeuirGnnOOoc+/SGCAaz6760I2RR/jeUndISCWPXrBQ+Xi3DfO7II3bQAk0iex8STD7582zJKgZkC6GcISXVqGvZYE3RcyIk1RAyEMd+E/CW7xrFEvREiArwn2ae/uYLgaOKR9mA16YkJ0Bd0dMyZuy/WUqoKW+Vm1JEUu7pEdt49RUHHcnm4sJlqA9Kv5NYmuEZyV3BWwfvjM9ep2GP/bsz2X/1Ps+xb0b5UST7782OCh6bd2qttlyr7oJTe4a+70yInuqBKW6pTlPoFPbeFd2RLpWn1WVzm+LHHJzWtCuXE9/HdbOzKSiGWBIaan79TWc7XdCLHHTrLFyRe8u/cxZIboSxi7oS1iUgQ7HG+9XzEPODstx6yMM5wHBXKPB/dFs78cMbCno+h1acbU5ppTTnU3gi/GhDGcpmQSzxh52vMlsWtKk+GER0oGBywolnRvoerDKzlqF5LLO6petrnJaQQ1JRDkZoVKzIJMgdMga4urCscRp2Wart61L7B+McW4gYER9jx0nZV9ZHwbtgcUgvHuOInOfn7TXaM+3Gd9J8OXxHRiIsc9HlrjjiO3VGJl240mb+F9/Jm+fruu6XX5ZEWllxIo5PAs3yaSCQ/GM/J+VrBnjY07MCAwOllpIT95RpNx5o8L5FqN1XC5DQi5u7OzeTeym/d34upzdFnu5fantiv/DeWIk+a9ixNSxAftp95DpqHnEzISbA4k2++8k3FOa2+w5lgHOtQqjumN2EwBYI1oe39w0YL++OBAQQKW/fEfaFEwR+lLqKvDVktT54cXZ9pNV6q7+EO7h8DO2aKkQ/yJ167XFD2iaSYxLTA7Ti++jQY+g9npEh3Pn+AYnqOW3EOgST5UlQemE0qdU5IaYrIsclprnfPt+ziPjQse9JCZ3Ekyc3Aoi8TFY+WvzzjTRredLwmGfPVQT1NBRVUCnM4I9ROnlC/AafV2oF1V2OsDSwvbrkHCJETQnGU1PzoojSTZDoBmzDGYcGXhuoU3Sb2w0kTYUYyxG5RY8N7kZAFuA5nvCNFgM0Til18g2HWOG2IEiPPtKvptLYpRSUY6lz+Pq9PAz1UjoHgnAouUNwoaogwNSexhN52NkfFEy+6xFomYlM+ycxMbdBTIQvTYFaktlFLz8G4bUN57HnguAQmBXmNs33PhdswNm2LuKdwygtB8GSiw8DcFaBlMkM1QQkHmLDoHSlAE2jYBcAxDBpdRIEKC84wckWH2eRqsyoDQ6NZRrXCFJD8xzl84ZWsVraHFnrR3SXlXHlOqoyTAqhRHM3j5shBVzlsosRKTnPhfBehUYZpxL2BZXW7rd1Ixeh0LHsvK2yxwQJCFUpA0zexOGQm4YszIcqign72oeXF5TYT2bEPBuuakwJDl4mEI3c3PbibdWO/Q2OmJ8GLw/GdugKAcHqSDzpSg913AMf9YT3BRvpbVfefGTGr7UP2LrT7h3Emoi36mHpki2ANESICfN6PubIbesLQqTMo1V8QwnGItPBlNCQTdnu9q7M2VmsNy7JTRSVGKm3U81WGA8yB5+aPKuUB9Is6GB19wa2qD50yTBQvZB5vu1PMP9/fyo6Z92Pz0U5yoep62P21Vaxlq4GWezUI/Tv+3m3hRdZusvcPb1oqoqCxBERYsZzqkWMpqIgjHtO6+pwMVjBU+dqsVYihsUoljpD2OOgmamMr97bzc85stSfEskkyi8cgSGTSGDFm1Li43hf/NYy87PRHtg3Uthyd/cHD1x6/vilBBXB9hN0UmRIzg0jG7KXUHoGlZeXUPk+TT0+fLwl0s75eAhRFFFGCoqogqsUViIfyUlip5mr1ylQUVRVRVRVUVkWbI0CrU1kN3p7d4wUOdB07Ovz9U8BrLMGty4uuoceHeFGsO5JLBL2BdvOnEv1n05EjBylhouMV2t7iYlqDxh8iPriIiRfuhYzRSQxvciZFLNrA0+cXurETpafKUFFQTMqzYjL0VlzkzAM6SVXrAOsy+ARGJdYdRUVMGSi7qrOGMNISpISQq6VSb3OOcnMmsx4aOpqZMLOKRS6nKuPUxodLnVq74dpanGVglSTGFKzEuEaKmc4fAMy5YucwMQ9DMYVGFQmwYRzZmsYkFPGMTMOXtS6krJGQbImre1IqZZIOrwA4BBYsRQlZwo91O1RUCo1KWnmdNqWM5W4wQISjFWGlabsVPEJ5bTLWau0lwbkwkLzrlZs1OObs78BgtugTjFZoaD5Z5mnR1jCznIrL3dzRu5kKKi3qShmEcTNQMziazOKrAxTviUiYqlUSYp3qomaloiZqmd6e7NybKm81Ob08du/oiEvICNjfg50Gzdgl5bgaoN8pRBiCCqiIwGIqwZ8PK5ERFgpGagYbVDU0sWDEYMFevJrU0Ko0kwLqzqgpR5swynSVkYl5eWhoWEFhUOtpoSeV9WHEKyKsRFgqxjFRGIiqxURU5nPfRoViDFiJFWKKDsU8FrBiYXlEDpIbFCGG+TPJ0RvBFaCGGHHfv4JbHTDZHTcieahcLhnxzUw8GVLU92szY4UUs16LdOTS3tS97zuL1FU2JQp07vPeraThZrDwZcrWZeupGai5L6VMEKkqVbvjLwTayc7HURbo1cTmqosSWBBZSuJk1l51msyLtytad2UZoEkkgEgFvYw3MZOa2lnSk3uA4MXDgnDrc3GIxQoEypCQQFMioOcQN+IDzejrWQ+ZnG4MRuioc607mKFQL0SH6HBwFOTnJkYnNicOK3ZwKFWMsM6j4aBSc2zOCRnTs4S4znXVp5i7LcNErNrBF6sTzBKkIEoFhCi5TWnT7znFI4wMHnpsLNzv/jx+sdoDdEyASYxcSTa2UDIDMh04EZPUtGRq+h5obt0Dsy9+TWwz5zMTzqbAwGYbPxScZCK2QHABBa4Q6SMFjdKdHQosp+QpK/T9dGGLBMhEwyqH7IHmO3t5T9eS8rFgQDp+opKgGoju5hptCCiNFw3Pf35VV1i1esG06NTqL7E1cBakS0c+8MdqCdoGiwrSrCY1Tswp27XS8q7URJRJ6PJhiEmCwMbsvOGf7V8UkfS/6I+66Xd73tR+D9R/b57rVp7X0z6J0a+hQrv76J2svTV18UYB2HPeiEjtHIf8UmPyn9Po8j8bt11MPjLhY2WUm/vX5xSENyicGspknEnfuzko/iH/wLPaN6hMVYR5FvFhjvQmxJ079RZT5M8E9Onp547tRWvUXc8kkw2xYrF8t6XtcWmG4OlAUk9CQ2WVFdSoXRIsSMQ7fOPnMbIMdjeUJ7Aw5YkjXmmjgoMRpL0EloYmhtpYNuV12d6Wqx+KosUSCjSCMb+rzP0e4jHmpnsnr6J/36x5/lNHtMPGCJjXixzxV9JR09/4n98EXenTmbHo9j+19dogRfvoVAWSVX5ylA/O6NUCaA1YRSSSpJpIFYKEFg40kikgVkxJjJAlDV01gLCFsAx6TltDz9SzAzj9WerPsrmrVDPjBLm9gzRffa0hMUMNx218LVZfpW+Zug0qqO/s/Uux6F4Jo6EDh5z3FO8xXZjJbus0avHkJnxT0GuNm9Lb3s1FloezhEd3PXk41kUKem3yh3Oryn02wWG93VuLYTfAEx3I/fHbo4xwwMjr89DVsKK5S5Xk23W7lpZupE+63Syd9q178mzC90M5nYRYlGX6bjBuc7DSwtrfBJbi86RRKfb8xFkxTdjFy48ndlPlzqYztg0IfW8jTInxWg9Axk1FbexyKmEvznl4wlB9MQo/KdgxiJReSCl1t3i1GZToIlO74K3d5/0Ar7X/MwQH0/+z4f5/rPryqNcMEzoRhBipWfEzzA8KaJ/PAw+M3hvD7t05w5UWJYr6JA6QkbUMuzTS3w/9D+izmn5vD1j5MtqCqu3gIdPcGTzyhSZPUdJ/en6D7XjofUr0/+bdA8vu7+JA7+RZUs5ODGoEwMgNXPZImOwwOB0PWbyGccc/cpB7WyLv4d9PBH7M8j+4MBQWUnhKmo1Uh3h3m/xFJlqSMPM4F2agGmInP/P+gel4Kn7am4tHZpNo2oeJ6CQUowFFTQSGRRR6FxnN2qcwYCPasiEiQgEVXZz09vLc1vpqh9h6f6Okqijs8sdxsf1k16Adm3BB4Qkw5TnHy8hO54a+ncaROm8EXrFkYw5vkjMGI+bI6NBIdkzcPN6+8MtszO46oPajkCQI1DqyY29LtK1IE/h52aMDM8CRLCrluy/4fc3+hiQkJMZiFuo2VGEspgb3yDJA5MmmOGsYiAKFffLLOZ7Vd0wYFUeuQlBP4e0LMH23LVVVmbBTwwnmMMJ0+UMDIcVS495KO4qfbUke6xuz+kdnFzZEL89DSxRDeO6gCbh27lu/exq5f4+OumJhP0Qmy0g3yHQxqNtDln9859AVKHnELHy06QZDiKcD9AunJy6tEVVjAXM4DyBdD7HrECv7Y7spkrBK/j9gwSf1+3Ment+i/QITybNeSMhBCsssiOycEzAEZ4klK2E7z3yiPdzkZz9Ruj5rm/fT9d/RmbnhwOHmzcjO4laz8rexMi9xP+podBdqT9Gec+PpyDHLR1DtoVHNCTlr9NGA+8DARfvVQjBJzTSNjievfcwH+H/ZRVHy6NNuCClqcdxy91w5eTTFDggBJw/s713HVx1gJc38V2vJP6IDimvsPlkWQ0rCPL1WSnMdqehyclURQmGAUm7XvsuKgasqDHnWbqe9Ksxfx/DirH9Ui4wAdLP4VVYmKPlCqUEkKEGh2+GBMTYzjwfwfl1YNgrBkoiT+yY5g+FFcRRJA4IohSvCqc/ebdA7vpMDk04KMiEcyFMZgAgJeYnWY+NuZTHwQbY+U7Q7kEvLcCea6B5by8/4NZlbdElzCGTCBAwZOjyWI6JkRJkAuCER1XvdPh2/C+tMjhSD9sJ0ZN+aEeqqYc0R0DroEFIw732t+SI42XAz9yzhBbNbtOEZY5DvZAfmWcsSC1JAzPPrPTpfciAQMYmH5X7K5BcElTaeLS9Uw5qA/PDh2in3cuzoFNpPgjgEKUfOciOKVVVQj/Anic0wKxMQ9PjOolGXc8Y1j2kjfo9kmAvEfUSGrQfKh7y/BMWXGsrjMhzKCC2g7+7rDW/7dDzkIkko+7e/Kiinht6ylCvRtmvF9NOncvBgjAfNpeDMroDUzNlo3X8lm1wmFI97WafsJnsUvyeG472VBHj7nDRpfRZe+hTptnj5Zgr46ZlHV+BnRqogrPH3YHJkU0JtVoJ7l3GJFRiu5eOMuSOJdwWJBLE8pAlwWQPMpmWvV5JIhIDsQiRnpbwT438vPEgRtdMIks74VOJRTDqN/ugoCiOOAmjh1XY0j8U5IZCSLiamIngdaTKlDuQ1ovXenn4oJ9X9MfD78N/DBknGk7+aueO4kZlMphx1vLjhGuykuRBBt3/R3y4rV3EkE8kn2Hi1HS/nHMowdOCfEhROojdlx90oNfuz06j4+qH3BzgepyR/lLLaz2XWX86u137SDgjnd3xhipYUsp6t0M0IM0FkOyd2dE2Unaz7V+G7Bt6Cp5Id75snWwh6WaeVVMa74vVwh5KMqnk+bv/ZkOK2rwvYfrS+/DzUxxPl6a9TcABMePr9enx8/UzdxiBjyufiM5rbZpoEDj2ph9/8P0f6OrNmcu8ca/ycFP0E+B+WAO1UwUiukd4oLHY5zmMAawHVqQ9eVCCOSeJ4ZWRhx5tKvQvr+vdEOvWZ7cTXOkVucmivHl/XPW6tbd/DhWr8vXysKGqvQ8t0uWNqHWdp9FreMWjxOUoeoipcmURqf3fTSWiEP9d8Jk5xgHXNI/DfhuXOZA9SFMbaaemRIIEvEq5M7xLRlpMmewCGyPJPoSk+zmmAWCASQFl6GEWsp6pmbV1E9h7iFILBgDDgPpDCivVsDCvMs+rYYg8OehzoYbsDaMm5ZvmM2yFKwcCgUPXMPMaB0gByVFNuCSKSE3DoHoD8R37k4mAXcO0tYqCsmtCbg+gC5LRZNh9s6cwxGPIa4NpWWiS4AODQf0H76NuGVbHL95BaXl03B8NonvH6XkI8o6msdB1DXzcx4hDGjaJt7CQ2MKaZY4Dyjk4K6kIEV4Lud3R8BcwoqKIxzDb00DIbwoPp2ElQ4BnuZISHaQLru3Uu4p8LIahiUAaAtD58zysQ9IeZoG8NNJpDtaTuhMwEiFQQt0EsHWanOGA4kQeIP1kAKQzWB7hIGxdcuq410BQ+bp4mbiNuW28SzpglciYEg8hImid6M40KziGiJsCkZklnlChugsPL37hDu9K4y175oF0WMEEUFJd0WEIQ7wOIFK4gc7zljfxTn3nPDC5+4KC4Ym6jZZaYQNxekHsgWbhXtKZAyEYiM/nv2IPyDWalfo5w2JqUfgeITo6CjD2wo4pA+xuztiBRmepTaemQ+tFCSJFAOglm6Kw9P8JCjNfevyeFj3aHqP38tBKuzbiwLBRSKMEFAPQGnkJ0qoA74SZSTMWCIDInXMHSdSHvNAQYIriFXZIqrAogIDGWlYX8m4bTriqgKqiKh9BYChxPaNAlUiUqFQaDYhoWuZkwBi29RPNR2fzuQYh7igEYcB2ZwyuBoFFKBoYPcaeS8qFyxpZ336PDqLDI4MMSsjqKNTdRUZuS7S4ljrOIg2TlVCP+/mTiW7iiwx4psA4B+4poYSiCxYRYjGIEKUKFgcOEOEpBiz04LGHRId+QSfSIIqQOZDTAIeYgZPNYjs4ZjmSA58SOV4TMXYlHUgSrNcrop1pqpregWiHpT0O4I3zEuBv3WfERBPScg8TuVIMh4pWUmbFWMHtEzAHv3P8sL8JEwdAcSB+UEkOUEBgSIMSJpkQHAy1iHYkRKiVOVesF91n35dm8Iw7FbBLSlgMKSDMgF39iAxkURCKSIIQGAau1F/K7esN4BaMkn0sSwfd9mC6DviJwbBNw1FO6vkPdRpxMZgrLmchy09J1k4JqnqbyCAqFg7yajBgmkDYZ02MzLIwA4vdJFVkE/1epSnNO81ru2LcLLoLJDmbiQKzgaGh5hJnQHgGa2/XOxao9fNxTZVUu4/pDcIeMA8LyDVJjMGIIDiXebxF2Ud1P6G/INKvzSdgqvxCsk61raN2Lx+kZvz/YL7OgR9zMr2M8BtnIf5ssRa12Gd9U1V/EZadn28aesnijHQ2UQaFJP/MC7vs++i++BUIHQcrbrPOlCn4JNkEwLoFG4h1/E/5d+0h0E+MmQOTypLBVIdOYYRSIBifhV/WHmVtuD80+psmaieo5zCBDMmAGFF6GmGo6E3X2+wtRZZdE4Kkygqt7pwPPCwPyiH55D1gnyFIe25N2X2k8t1cLsOBgOfxQ5jT18XMlA/9sqOVoFBEgKjshpB1SGkg+2SNBGAzj0FMjMhZQ4M2HC1Ej3QvQcOFC2ngk383pv4EDj+TLinve0MA5dkokxFh7lQoPSy2wmO/zQJoyGhUWSG/qAUJzPGbom3UHPAawCAnwqefy3Mwkm06Q2U5MYqsKFaP41T7eYD/XAzggtu7PIWc0ODB1YocW847FA3nVRF/NMMez1Bc6NfGwxsYheiBcu0i0F5Nd6Ng0O6sRI4UFZlijsDycBnOYDgn2mQJREMR+W6EQTPMrmhmSB4QP6Ush0B/yGloeyj+7+daoyQ1IUhuK2QNEA1fWFiK19UhDzIkURSCArEPMUkPFCkmQmecG3BVSJmB7dR0HDvM9WqeYKwpm03zKxbwEO2lgWNpF27Gm2DKTUxl4g1CViYxK2GtMAkVrLBggFdtQpElNWvzMGlWOniHEwVUT1LaWm6KW1Iy39IaBW1SgNgmNCI8d6ymkty3abYWSJOzl1zxsan1tVdkBWQROLfCKbdCEnSMiZ/yMAt+77/zH/IojIyYO0DGhJRSFMzdpRGyFyYTIMOap0oGwBsbkmDIUKjJ74XJ0954s+1677jB7YqFQqqYq16Zc+MZ0SaBJDqesPt5UZmJclqAkKzAUamRwCkKW0MbgUlNg6T5RKIrDzOuxXR4IflSTZAOz4nMRMyK2luXFHMcmNRC2trcwq5So2wjbPLqfn+krq4GUdSUHJTgPfvPQRagk9I3egOWj1nHsP0kjZvpZ9eT/7lVQtRj83jDfeCDBeAYPoO7oFNLmtFBYvBo7w+I6nF49Rai1UYj+3hQ+JAO1XglzZiH7nG7rga+8/GCCX9reWpcYdr+ZQHeFUKAhYyJ2d1mgnmEkTg6Eyo49wqdl6wwFospQ7dnd8hgYJ98Tz8hIcjFgaoSILS0o0mPT5+p29kbpdkfXdN4/yVbEp0YlaSaASlyCxUT9yOyVSKuKrHwczRy3ZfwJmt6NDO2PDWpaNIi5QlUNu0kCEdqfAv0ziTbGwuI0AJF7KA5f5l20MNsWhwCJF7v52+f3Xc2NEYPGOXbHGxvY4oDhjR1wBQy9gIhpZGCBAnLt/gI/eI1CvnqwWeOgtAwBjjK/TyM0MDN3AFlwSclThHGJGt76A5HQjXkNN4P1GycHjTM615dHjB8h0ed0sHQNYucFbGpW0adHFDoxDwHtCJyHDlttpSQOxagMtjatPciQQ6puceWaECQqB8DkdXHMggVva1LBXtDwq+3HFOBAbowy3kIr5UFyiuGbyfUDZw/V3tmXIouPenJxnUdLbyoD8cLPW60V3N4oPUhghLsKD6nCNebLchc1Z0RZyIyuzw42Q1scDRe7NmUTTwukFkC8Xkcd+s1ffrmlswL1uA0OIElpd91LbvHyOBmleXDiCEPAsycD6VLrtvM2TOQdNERBptPHktKrlrgxFVt8Vha44zZBkbjc541qIKLZODYwQhFS9VkMnq5utrELh0hJ+K6tc9eMQKzSzTseKStqFYnzmchpAmZR1uLQcM1oXUlouZBQgaDs0g0lObTglD9QPVj+tKevpag/AUWeTnOgbEVdi9kSBCihTBOoos8sHnMCdAH1bQwHIJgvIGI7AhqGuGEYrnhgGS/XF7Amoln4QxZk8HqQ3k3I00MoeLpjHCqSZuREFoweD2gQz2cGCCCWY2UaIuV6WMF6LWMnZkiEYOBvtFn0CG945dKkEgCIdcuoCNSoZwxxpcyEcXHZfXFetNSg2ByhlrgFEbkjJ5ZbI4cRGsRJFAyFBBHvbmzg9sXl4fKZ+bkQwjBPWYOalJCKy8Zma5nBdHiaeBiZGxvq78U5ctztTWPBWf264uCxIkBGRYXDc4pA1CwGCmsSjc4jgrcYrCQQ4BQR5DFc1iYhiCUDZMwyLoMQ3MwCkPJubTEbpkEMcxbmfAMC9qoTshYkWqBwimf8sYTebR/LAxSxgGRb6CcV5jYdIG8nVCT9NYIKJBEUGJZr6eIMoCpAV2JQcB2pUabRwIV5+Ubl71NaJa1gxeDv29YQWt6rkIgZjdIQhUznRAL4UDQ5tFMnGUjgRuYluPnojfU6L5htX+gsFutj4BYw7uk1OWHccEVcjByHGyGryFAchyBRlHMgn1Yf02FOnqx1EBT6DPN48pt7A3kEP7Ag7gyRP9ER+g0R2j9ZxMtDphIiPvHI7W4zGvnRBUWKQDs0bIjylNN3PeDsjBpRJUSSUQGAVAC948z4D5Tp4AGcJ9th+qVK56PoxzD2j+91d6h6UMaN5093xTX2DzMF7bAIVBOq7Bw6IC3DPdBPFg0lRqQqQ4h3+KIR279LuZB8bIRYEIkGRRw3IOA7R9YYLl6Cd20+32YdOPfy2Krj0lXJPLQ9Fu57csRmioKhnYPURQZzRo+3cJLjhrGuIF+MgAUM4ZwMhMEIw4isWdbNYWGCYG0LEXUV606g2jgSN1cELGRsYYm/MuSHiJ18AUScCWXPH7lOVeTBCorF5nDf0WKC62UQ3SAb4QnKOksjx6uZ25uXr3fwd93rRxxloelDRZfMMEbGz5iuPfsMEVQ2cabVgD5MZLJijoNaJGaQHBqVkU6ERT/NCdZ9uIIxkBsigmYYEyzAVDsUUcK6e1LhthHdVoUTm8V3N3GdG/Vz256p4p8EiDGcdAUYBySGycLKApERQA4EqNwPKEg7xpoEYgRYLJFYpFTv8KsRNyAGewGwF2DZPShEhIjAA1x7E/lKUR8/04GAoIMnbGzcbI7ITMEYFG9ZIULJ16w7MkPiFRJEkxAkT4v+7rJgMwANEDJphKAPb5jghkI9EebBWmPLCwn9keAN3lIGKbM+t/Z/0wyH2mbY9gewkCSJXrphRQ1CuoU7lWJgWShOtH/6REPnOjt806bej3Hge1aOuIbFW1wpgMaWCMVpSsKlghWQoEy0xngNNxgTQMERiAFUQUlECllkURBirEhGCIqjIstqSh/jiIUTBJjKMxLGFPb29Ztmd+pVFfxJX0Eo3hsZRwBDWjCSVZAvEHnIqIWipCKpoYGIWUHuolH4/s/YfpjCVKxANUczX0Fzg/WnITy+FCyelYD1h1/XPObiTtHzQIQkYBAo/WUB2L9IbT46lfPp9n1Hj3QyYYmI2TWwHt8fQQJ+zCV/mTkDx3RnBJK8U5C0XmDMjEI7CITICpJVtUYl+KWAQwESIxnJpwLqapKKMH5jRO01v9Q2MVYisiRfATQmYa+VYGOojsZqekYiS+hH0fu2R+w0njP5PkekaRF8G3kGFMMG0Q7jPV20ZFyDRkzdnKsX/2vhYM5lSCOw9w7GyaS2b+pNqbSlJwS7lU85aGw1mxRc3wZM36fieR6DqJ54Myl9VplpJ1DJRTChWE9LphMIxASKp1ojJ9k4B2BgTZDAt3LKFLJSTiaczKUDCdni6ixPaVDvZyJOAMIxkhNxYewl6yXDmhlOpEF4XaMQsNURTs9GJc5B5nYa7a1LLwQ6c7GA6W32QKKCds8enFvgMEnMBhxvgFQhN5es3IIJJFkgiCXUIdZbD1dOst0q7J7WGNBhhUAb9bKMhkQi90GoKSQZsxtZZ9YbMGQELL1TcNQ1CTNnizDHH2XQouWUgJgiynycQ/iSFNEoHKQT9lhWQqSopWNoyJYyCgpUKJFkRKQAYqSE48TbiTX9iIe+H5TUDEDEdugRM6QL2KoktTuQqIVu9p3DVCuy3K1mJFgEc+x6Ms+HTzyNGoz/tq4cr0kJlVIkVUGtxjmYQEJDGE5PswQhkJIfqkYRb0Kts4PmMkmAea+JY9kT+tN5S0o08ZcBPMGj8HvcoFB9MD76XoILIOFG6UQfcc53H4hn8BXL6wJEiRA7js5vP1CGZJgc3nS83MJpZbDH0NuDL6VTLufU6OdqJnfHHE4rS+QshFY1TH7vuyKxNJPfu7yDzje7v420t1wwmXKhmsovauGowadKPSSUG1mcS0JLHyiKrsFjFHQ1SQlTLfDx1WadmC3fXPTtdnc2LDYfHCHviHUdcnxjYfZcuPzr1jm+vYGgeT6SIHnA+mOiAQgB6YP8SAi4Q2hAHk7xdmQYgVAkAOfyHrDllJIH4X2/PkUBkvzHuhQHwMCqUeNpodGFRvRhRjla2FLZbSpZ57KZYoKLLbsQMjJD5y9TIQ9CQBRQUkP0mHbBMM8z4S2EFDVKFiwJ83rO46g9RAdWqDHUb3XhAnHNuMpehDOXsBiyhBV2B5F9mXZY8Dj56aY8neWtoYVeNdOL+ou717DuWEH7j3ytc6Toqwh9jXDdEDKr7S0IUx2mAWWGNLhzc/KLxOS4xelhzSoOiwN5y62RGDhSARYQN7ZS0ltklt+2XM0KM/CWgaROQXWp3CQow6jxyHA7Yuut6U3GdmCs+EYCwBGRBCKqkGQFJIkSDFCRE6dekip+1P/xBoYOHHikLoB1AB7dCDQvUCGogcwMFk91EohBEYKqLFYwfdDv7gPAJQ4Lyj1IU9y9xEPSQ4diFgeGJulECEHEC8Hnja9iggXIJys5gaTKl/eJ7PlzOQD8ZVUTLYjzgJ9xEPIicmu/hyw8yiH3HOh5ch8hw0eCjoFGVBWwR/q3aiXDuPdDZnBEA+Pz9vGj3rBk7gk9oYPfuOqyyixjFg8xheYFYPWEKU+U0DNBfRY++SCmYUYwLZJAyMHxOESg+bdTIqiJ8olF7TJDMLDE2+g6yGZrWvwcKtiB+xhoozRptqLaVEeBcro0+rLfjgYmhCyWYczL6FXpyqx4wbMbDKJsyYl+wZA3yz13bAnTEqFjLw3vNfZRblybWoXPRmw34TcivsPnUOa5FfxM/E9WE+LaibNF6ak2hYlcaN+ME3iVAwINkapt6hxh6TkfxNRuvp1AaAaqCbvPTbPURhJ5hMupm6df3e0ARIxiiCgkYgAgscuRT+fOXw7/sp/4QTlENo2AD7jIZiWJB0DpXgI4M1qQ1O37LnuuNu4ap47TasSpSqy0q1ho2zWpBXfMQ9ml9Q0DZSl1lBRthRgrhUtrEUYUQilVKxRtCtWbJQdwoMmpTYRYl1kipRKFaWDUqWnHjub7UQm4AgaJECZwJR+YzDibzNPb7tZnmeDCfI+CAWncCGwYhyhwo4ICJSsCvl5BOZOo3kzKIApznvUvYdocp6ynQoIECoPo/Dt+AYvICw19QGi6a7kVBQWHVsCh9WLs3kJy5RYyOkedwERFJMRyhDuLULZAoi9gX1/TmWhzBYCiBToUFm7zT0Vws3Mgo3h28i6qGoxoH1PI62GoeLEpm7FjYANhwNPz6t8FnhbYQIw4ixQ5J0xR2BKsyFwmDiruEhECKhFWI+7f8ioRYGzL+2yLiIbVSImwA5h1sG3q7PA5Srwo7uFFF6LkJDs4d6mTz4reIMG20djLrY+7g+3C6CljeQJtpP29U+jkw2FukUkBNiD1l5bNNIQ0zqKi0leryHZn0Lv6DAsY0vrBhNorgTGb8KIEgXWnh+VUhtkQ0/cQxa2DYBKUgKOzeXsNSDUXLycb7jsJ2Q8Ugd/kDOsResSxEqotKCUisSCJRBY0goVWEWCMQgtRtGClbBJATfsMlmdpxAPcJaCdJTEBkEmZqSZoaG09lXlRDBy98Oox1U4WyDIjGt1FcVJzvR3WzZeBsDm702G2AEgvMCoXI7joO25He7lhJ+fJtfBsoZuJyEDaYhHBLUMRD+qIo0OBjg2UbKc5dtF4np3+1OH2XmzuqFGl1cugDyO2sleIy5JPRWUdcrdH/4sMwzAI3tc4XztgYlq7Sl5SrhOpCBBBe5rAwLcnECiTJupgep9iOAhapotDNLdZRswM99DJrhFQgLVCpm1BVVKUauwLx5YZTwQiwbBVWIMZmBoKUggIIokGGtZiK6pRqOy8mjWrq4jCwL0wvKTPA0WO26TVOgM1ZAlwyMBvLMTehqRRSSjCVURisExCUQS5pzQxLNZkrCr2djuHY8K8gk3njwOC7LU1GKuqVDEUlRmZZ2WYxcCKbZH5D0MGw2TYnqKoFnYmMmBntbJZESQExim2I3gXjtijeKKVXwK8C+CSA7x2CFBBwBKSgKKFBJqovXs3eRXh5moNBkyOkQFRT8GRlg1vNkgqoJ32UTprfCcJDBfyU9UOeWxO4AuEmBDxmBnHeTdZInIoQuxYQyYYThEBErGZCWRENEMI0NYYG8CZJKa2mEG4UlBMSKQERQUigoCyKRQQZCCgsk3LJAQYG0W6FIj4NwOggY3GLDSSOwCKDaCobFzpAhL4nb8tBGWBTanQkMfs3BX95FeBREkRa2qFuHHXs5D/iQj3Dw2kiyLziAxka2ndzqTw8LPcNj3pZewLoUIi9REhEVhxoPNA58Oej4WC+UkbAQwRbaR86aqL1+6UToIek9HbPTE6uzBQhcKYsJuYTMaEowDfIfmd4Q1JKIkSARARAYSLAiMFgjCFoiBQ2GgrEEFpLClCtBKBkTxa0Zw1rGKJbWCIgiAxEEhtTr7G9ck4hbDj1CekAb0WMxaCDvJOvmNpMd7KGPGraQPvDETR55537fwDQaCgzCB8gbcus2UT147eS7SyGRickKubXLEI60FJtET9ZGLFdYaHSmrG5z3+Wd5Oq/WUW9JsLB43t+eXsw2YtiwacnVGEDeBhShYD7EOiCN+r4EAYRSBZDMpByXBAOY2Kc44ij/aC+z4mvURgiO5SDCSEIRgRgJof5XeWS554GP2yu/BdRS5egsFN5AiHlmmBYR/CAh3gXCJIpBgkiOtBSIFlVZIFBEQArDt7yyaCcgpBxBOEU/gjnFM82kRKtQN10t5QzEbvIQdSLvs/QTsOjnDA3HUmZuAOhwVPNvXQQrDab7Q9ABomZROkONKGRBfvY2BWFBxgHBFDTIYMjBmOspUM0oCu1IUR5sKKHfk4kgcTcvts+nhymHOWhW0LK2utFG5PYqYBg4hAoMB3GUkWQA60A7CIKcCIAFAQVb6wYdR9d+x/XTzuj0FKlcYFHGLFqTuh7MnMQGEDX1M5HWwJ+FgHkiIQsQIMI+iHL3wEmRgEETWbpeZ9JI9M9DOzuFEIO/FR6hR6wfkDbodh/j+ezILeEInWe4q3424NZE0FoqKEHABO4+Gnl+W0Q2L0fJmVU+/gIc3fEpfZGRkFridh1lMSonjSlCL8rAnMfMXqLMbpkX+n4elwPzFQsdqQz92zc447CJulRvEhsKhoTmRgYbC65ASA4o2irIE5OQODhJFlMNBVGI4qHe2Dr7SAdg8T9tPYECwEEPqCt8vPDJ8gYHIecCAeJiWIhokfD0NeB8vDSrnz7CvsKjeV+7advNOyolYww3mgBQkhdIOWRRUec0tVqo6YUGSE3Ti8oPYQCPE4C/5kSm52K9tkTJSQiWA847N88vv4Fnqkk00B/vCUNvwC9i/M12sLKnPCE3DgVkZC/CatgJoqGuxowpA7NwzGGkzGTFlD8yEpga2EEU3FVWBEGQEGBEGALIoMJJEVGLIIQSExjaPRqTlZ8Tow3XQn13Y2o05RD7/ec+wqQKFRKN9F88cppOoegiceVBiSedTETCFv2MV3l1jFRR8Mvx4wxZ/ylV1aLeP3LnFmy75UyHoy/qdCpg7rDBGC5IxSdbZCoCX4stmht3E0hJGjiU5MsmqS8neB3GKBQYdAyJJRCV+cefM+CdLZDiDAMwpoCI0RLAGGMcWvmaNiEELqOixc6EoizHzDDvloA3D4d+3vBtCu3vkT4JmJ37wKRkFPXT0z2aaeTd4IPoIH90BBNUy4bO17wYByLVwKUyZEdj4s+Qnsi7dV1ZU4PcT8AgkUg9knuKDBNOFAcCttqLDYMeHAutniYmLoihsks6jv9ALDUsfitD4XS+4XYKbFc0QQtH0mZjG0igxIiGxmYSLFIiWN0NAKSCSsKyoojFHELKnTMALv7BcDfvQLLVDHcoouMtA00JVslBJpaumrGyWPkuFl6lytO3lEdmEtQxBlCQKIRGjSi7Bsampqm6GBotmwmFTgHddmy6arFDm4QTFsQNGclOiofEjCHpQ/OQQuK8dpzeai2/QNrwCouzE1wZ+tAKkzBUYsCKoolnGBpNRiSdhITA3BBbcK+sc2uxTJTLNjBtq0czV7Z0TC9wqWspQh8ekDjThCw/mOk6VOTaeB8+zleuEXfN8eFWzIY5k6DQOUsvYTNeb33UFPajRQeNSpPQUefYFe1zQ5HROkqgzNcvcaE6mycwlEBgckVyzAcsso0RjB9mDjBoRa+KlRwCD3Pl1FCe+F0/bfPzFw5t4WnSQZPHwPJcGg+wnTrqQtoWIaQuyBGdXAsZba5IP3Qp7Yb+PmV0CChDN4eBinR2WcUNIUaydXZZ8d2cfr6po00SlpRsX1Zj8bpytFaBuOZaqew54z7PQ5cgHIZQ3uiV3epxOo7z1BQfIip7Aha5F/PTpjdDuvWMtaUEkiQitMAc0VS9IvrQD3IH+dhO4/LINBD5gIm0gc26lNwMC7URAkSeCm9LP0mxyhpFJCMBDxVP0sOHdidsd8nZ5i1psfARPu4esN55GWXOJPjZwgd8O4choFgirJEYZlEYLHRXvuIkq3DCSltUJRBJGTQSUCxE1wBDAS7elqJRFZFGJArIgIQEYCxFSpLQbBSEWSEFFigUCWMoUQLBAQoDIFIESBCKxgxKfOecWCEiyKczxp9xJPCCC+WKcA9Gc+ZoraHOyoYg4A2QZ8ntGP38qaGPYz4/UrOuOYfCvl4bVwch4h0p7fXD3X23ztKnoslsY90OjBkIxcLYLEH9nIBnBtKYO8mDbCVCOc76sP3Hy6Eyxml+lqltrvOd5wyJaZsDXzjqq3qjNjEIdIfo7zxQc6GoanQkekQaqycYFo6GzVJqiqaQdDp2Ui+ugusDAW+468YwOPe3O6ODlvQZeRztx8jdrByayE0azAkQhjR/YPtCTbRJpLTO5qHbe3HViH8hbgURXYEomjBZEUKZCrpfCzyLa9AjFVI9FGEO+hcCmXq28MlQj7g7t6xzUMWOcgwLgSad6TnFORGWRAmkQre0FMJ6t7FoPdSxhcuP0d4cYSGxbMFGJR0+3bb1eZA/C8YoapsPIzqZp4ecDGqAGoy1jUdnKu1s4dW30lOqgUAY/TgfFr6hazYjjVQHmLLMy8kIsC9EDMD7ggHlKAsIqeSLmGaTMcig5UxAfHyTYFpGEze9IEhpoY2QrNi7gl6aMne5ofDCJCxoZeL1uJvzDhVxEQ7D/m3lH8mFcWIEE6lAJiMIN7hqDgW7dDRJliqllNbU2dMUWcR1xomuGYeTflNBpBlQHp+9+dR0FXxCzDvYyxmJ7igAAgwIYNC1x+XefE/awm3AMx86fWXsNyAFB6FrSgW3uYbZf2fl0mQY4u8ndPsgOmihRpgUOe/jvIE6RJrNAcU0bKmyMEbjfTNFMh3yphZwEKiMY1KCqQ3ZWEcAQKBtsWSFsMCbaJU2JsBhZGCEQdR7Y8BBZOKVGdc89XTu3mMDn9J6ijIyDXLEkgJ+x20XO3MFlGZbIPr1RHbUobCWMZGMmkLhSpFEKyXRkJQxNH5dK4i6cQsZErY6bHicHeXePBEchTIzJijiIXYGRXKiqCqKVbig0xtVC8lBexRI8xxfKD4XrpHXdQpfmDhAB64ukG4lgjNK4+NEOq7hLypS6rDTsPH1KpqpwGK5mbQLmWCQi8kkkISRkWPTW7BCvPL+9tTDmOWJl8+YiOo5wgdMEc8pI8A3XjGBAsWXkBIOPKTtQ/xGGOuaWtAeDJCG/pC2h0DeMckFDf4ucTSiIJodh7avLEOxzNoNu3UR0tpJNTZgcaymtBjdQ1IqiCorFiKxFiI7io5gYH2hMMhSLUpaVIAhIgkQBYIw4wTiiFhsBEjbpktGnoDCkmBV0dbZU0rpJYDE1kpgtUREMtS0LCYWskrCFwaQAUxDCG0SUDgIJJozbxLm+NCLSVuqPbU4JhHKHflkYHOOiRMTLGioEazKbSJiwaqZQxb0ySXphpuEs3b/Xoohe0jXeLT6p5AS+jHrVk03mTvyuhwF0ckzD9Nnz2awxhZQXbQLAxclTAxIYpvBgNGLH2w7ybSZgy2vPfBmGagHqtAtifhHhYoInQnUxU+B4MIRI+pFMUycLMYgHQzsg9vn7z0a+PPfPQ3NSoBfMPbqER4hDpjFasIKirqQcmnUjNQt3nZ4EVV6YcWea3quPhAs7UFIpLxSYpZ6sDKDWkWfMutAq0kTRzg9vEdr6jFiPI5ZsxnzyqiloOiUS73dcqiVSnAM17uei6LjVB34W+vHrJoOWcTObHZwjAy5K7M8IMRUXIg0cjDaNAg4iDmBqd4a5biOqO3jDKOWA3wZL4plPjmVbWhDUGqOqfQsujlBxSttxdyIs2oXi/Q26beeGuKNpIGEFHEiVEWOjsJDNqGuTaqwvDEpgDBmptWqNmx0FMVCDEjZKN0kqa1oYGraGJo4dG2oW4bMMpFDFWxWgPAwulvMeMy9ghXD6iYkSHMvAMrkTk8YWMPiutXBWXodiFlwLrV2XOXR24B1VbHo9OsLDk50sspd9EMaF4Q7OXY6KRx0ndkrdnjAmQwQRiiMNDBigMYksHRBRlCkRCUQuYInKU0YWgchDkRFVsFQ1bO6k4GuFC43V6GcGld825hNecPORs3Oc4xGDd6Zma4YEsGDsRsSAgJAJoMlUYRiwzYMlElhOROO+OxpNQ2od3bBxyFBGSERdgoU7mYiyElny9NaAysByDIsmYQGEpjCRI524MYwbtpiYqUFkRJkWSjEEowckLjtBD3dnvMH1GJtXYZg02M7OzxwgmO9ESEZppikiGZj3KJ0jY5gDVX8nfTsiWICyC4hmWLDfjScOp5Eci4rkQQLYRhDqIFFQowt0GhBESJoMMggMWCyKy1HQUhjFmQlgnSb9t4B7M6uJy4ynVdsSoq0tE2lMRgi5MtwC00czdAmDD3Q5EzBFxb99HTqYgstedXCZAmMTFHndMpTNuYakwaxJ8RR36Hw2bCxIdQIxESoRaU9b3szVUY3xWiG5I6jPEqYgt8hRypAIO8DAOvnpWpQ4OySHA5i5yI5sF+yCNClQRKIdsUpDIUGdVsrUpduflV0th03AMbApYRN29wDLaJkc9997pk/FxNfTRi5QQx7jy6BQAoFA58LGMRM07A0s0Sh3ce3f4JV1CsHK5D1gZ20FWS7tHfRrCaCKZKijMbJSTDWBRBmpYYahLHRYxhO3lyPKd2f0+11mO4PWymxpxKH9nHNtMswzsuBHiQ4AhOJIQrk0+2HrMwNqBPQwmsBOxVVXoN1Ag4Az85a1EYV2fjPBsYbHG/t07cltgb5VUVYayFFCMOQlgbglQ98lBXIe2abb2L01vZJeWhiet1BChDSjQDqyNkM/OedM1TouWNCKSBAIjED1lmFK25aETcBEUoXAOnk3Pj8/X3dVVCmElUHnPP3l2+5hgSjtzNahVYcAbYiCRy7ZMkMTUsDEFMyAmRMW2yHYdHV38eEPQc54tDBSURp3JZV6zcpdH17JwALACYgRNobgOekLM9u9kE6vqFETMoz8KwNnIk7vUSTiJ0WsvSIdHOZTsIrmTBEyQhnvKMJQsgkEYisIY0eRKTf9RgoApFCBfxzIDpLriB6x+a4GA7QHMmIvXESMD6Iiwg7kD9uOxE84FxzCKf7jWYkISNLUKWglhOgA2O2T5/P68Dx+Sxh5UoKTb033/LowPiuwzOIqWmrn/3X1yMma8Nnkgw2S5OKN2h+RhbFASB6cE7wslDOqFiEE6S6XIAJHFHLqq6Qj1HQecxIkOvsrkhNxEO4OM8PuPprx4zIQgoxRjVLP04BRQERYIgQUEJvYRmkDskBLql5GWkGdx1G3k+JAYTJU0vX4UFTsO/ptLhc+PwCw+Iv6AgPWZ+cM6XgMPHMeEbfK3IMiwQoUJQeWEk2nzeEvtpyeuJuqqM9plemJPwoZiR12kBlHtMsgXx2H1guMk3EKgE+AUGGONH4F1xHIMksKOp5C5Pum4MTEPUZGCnRH1uEIQAgUgYwwMkt65ronS9D+Tvr6PR6c8Kvw/HWwcPGB3woUeIcBeQoLQDKhLcxFqmMH+BDK1Efd5Vtek+gNp19/lC6AZ4qY0lmAH1oxWAwCKURAqClEeEGMhAkVCQU5fW1AgGR3HfcZWQXpPZEz+NN30bAs/N5bddm3bfK5HsROr2W0UL3lsgoq3VPYZzhvjcZGQ1twoQ1nE8uzSCCGqWPYW6XQIdKhxb0akjzFItYl21FXohRhds3kXYHAzS68xA9VgT5HkwQTk1FM8XOGgTNQNDI24iJYOK5EV09PhR5+w+az7YSdCGhctO6hhD/Ce+JlnSP5fUEFT6XmrEzegLgHGCKHiI+r0HwTHBH92pVeBm4fcfprxJmd/+0wdaLQ/kY+nLRNaDcOEZ/7oefm+h//F3JFOFCQscnbRwA==')))
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/student_sources.zip
deleted file mode 100644
index 7017ea3793c96587c540e38f5cf1ef3e0a0e8b7f..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/student_sources.zip and /dev/null 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 88d27fe22ab6b3e1f9f01592b6fe48693f235f99..b5d4dfac0e7bedd5d862a80da7987e7e74fdcbdd 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 dfad953c979edce489b1fad0368eba4530aa8d98..15fc0f6b47c26ddaabe6c9f65fffe605a6b8ef62 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/docker/docker_tango_python/Dockerfile b/examples/autolab_example_py_upload/instructor/docker/docker_tango_python/Dockerfile
index bc05f666f81280d1aac298f1da2d3ac03a37a080..e081c74465e0b3f3a0e933f16f5a1f180c8740c3 100644
--- a/examples/autolab_example_py_upload/instructor/docker/docker_tango_python/Dockerfile
+++ b/examples/autolab_example_py_upload/instructor/docker/docker_tango_python/Dockerfile
@@ -29,7 +29,7 @@ RUN chmod +s /usr/bin/autodriver
 
 # Do the python stuff.
 COPY requirements.txt requirements.txt
-RUN pip3 install -r requirements_pip.txt
+RUN pip3 install -r requirements.txt
 
 # Clean up
 WORKDIR /home
diff --git a/examples/autolab_example_py_upload/instructor/output/deploy_autolab_a.py b/examples/autolab_example_py_upload/instructor/output/deploy_autolab_a.py
deleted file mode 100644
index 10874b224b7ffc88b37fb502a5d39ae61e6c09cc..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/output/deploy_autolab_a.py
+++ /dev/null
@@ -1,6 +0,0 @@
-# deploy_autolab.py
-    # Step 1: Download and compile docker grading image. You only need to do this once.  
-    download_docker_images("../docker") # Download docker images from gitlab (only do this once).
-    dockerfile = f"../docker/docker_tango_python/Dockerfile"
-    autograde_image = 'tango_python_tue'  # Tag given to the image in case you have multiple images.
-    compile_docker_image(Dockerfile=dockerfile, tag=autograde_image)  # Compile docker image. 
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/output/deploy_autolab_b.py b/examples/autolab_example_py_upload/instructor/output/deploy_autolab_b.py
deleted file mode 100644
index 119cd80f2a54ed23e4e2b8b16df5e207d1419df1..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/instructor/output/deploy_autolab_b.py
+++ /dev/null
@@ -1,16 +0,0 @@
-# deploy_autolab.py
-    # Step 2: Create the cs102.tar file from the grade scripts. 
-    instructor_base = f"."
-    student_base = f"../../students/cs102_autolab"
-
-    from report2 import Report2
-    # INSTRUCTOR_GRADE_FILE =
-    output_tar = new_deploy_assignment("cs105_pyfile",  # 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",
-                                   STUDENT_BASE=student_base,
-                                   STUDENT_GRADE_FILE=f"{instructor_base}/report2.py",
-                                   autograde_image_tag=autograde_image,
-                                   student_should_upload_token=False,
-                                    homework_file="homework1.py") 
\ 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
new file mode 100644
index 0000000000000000000000000000000000000000..e511c68d3823b53c626fd1b1bd7e448b36cae9fd
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/Makefile
@@ -0,0 +1,51 @@
+#
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..d768a52ad4b14903ca2d3d0cea8745d16ceff387
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/autograde-Makefile
@@ -0,0 +1,7 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..e3f6068795cb9e02815d639fba64fe4d3ae7edca
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/autograde.tar 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
new file mode 100644
index 0000000000000000000000000000000000000000..e3f6068795cb9e02815d639fba64fe4d3ae7edca
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout.tar differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/Makefile
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/Makefile
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/README b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/README
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/README
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/README
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/docker_helpers.py
similarity index 99%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/docker_helpers.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/docker_helpers.py
index 38cf3134cc1b5b032dc1e9088a7025e824862dd1..b4b885526bfe90b86900afb241496de2c7c84aea 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/docker_helpers.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/docker_helpers.py
@@ -38,7 +38,7 @@ def compile_docker_image(Dockerfile, tag=None):
     base = os.path.dirname(Dockerfile)
     if tag == None:
         tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --tag {tag} .")
+    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
     return tag
 
 
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/driver_python.py
similarity index 93%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/driver_python.py
index 3542e09379b7aec9fa34126730ad9a5670160778..49a443dc051e8c745c096b613cb0ddf4ec262339 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/driver_python.py
@@ -7,6 +7,7 @@ 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]"
@@ -14,6 +15,10 @@ 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()
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
new file mode 100644
index 0000000000000000000000000000000000000000..bd5258f7f5597728f597306d5f0c9927be6dbca9
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/homework1.py
@@ -0,0 +1,178 @@
+# 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-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
new file mode 100644
index 0000000000000000000000000000000000000000..f74205d5b64eba088d62e54e7fb97267c1785733
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/report2_grade.py
@@ -0,0 +1,4 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..bb4071233d4b81173b73946b3f220c8b826d57fe
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version-handout/student_sources.zip 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
new file mode 100644
index 0000000000000000000000000000000000000000..6839a6381d5c9a0459273a3804f0888a10b476ef
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.rb
@@ -0,0 +1,11 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..91c6ac44dbc6297ed69997a00abb8c897b7dc890
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/cs105-new-version.yml
@@ -0,0 +1,33 @@
+---
+
+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/cs102_autolab/tmp/cs105_pyfile/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/Makefile-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/Makefile-handout
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/README b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/README
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/README-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/README-handout
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/docker_helpers.py
similarity index 99%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/docker_helpers.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/docker_helpers.py
index 38cf3134cc1b5b032dc1e9088a7025e824862dd1..b4b885526bfe90b86900afb241496de2c7c84aea 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/docker_helpers.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/docker_helpers.py
@@ -38,7 +38,7 @@ def compile_docker_image(Dockerfile, tag=None):
     base = os.path.dirname(Dockerfile)
     if tag == None:
         tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --tag {tag} .")
+    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
     return tag
 
 
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver.sh
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver.sh-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver.sh-handout
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
new file mode 100644
index 0000000000000000000000000000000000000000..49a443dc051e8c745c096b613cb0ddf4ec262339
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/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 = '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/students/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py-handout
similarity index 93%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py-handout
index 3542e09379b7aec9fa34126730ad9a5670160778..49a443dc051e8c745c096b613cb0ddf4ec262339 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py-handout
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/driver_python.py-handout
@@ -7,6 +7,7 @@ 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]"
@@ -14,6 +15,10 @@ 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()
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
new file mode 100644
index 0000000000000000000000000000000000000000..bd5258f7f5597728f597306d5f0c9927be6dbca9
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/homework1.py
@@ -0,0 +1,178 @@
+# 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-new-version/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/report2_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..f74205d5b64eba088d62e54e7fb97267c1785733
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/report2_grade.py
@@ -0,0 +1,4 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..bb4071233d4b81173b73946b3f220c8b826d57fe
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105-new-version/src/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105/Makefile
similarity index 63%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/Makefile
index 2625f4e99636100acb4adc78cce9291525311656..b9c752894264c4bac9843a2d1bc1fb171a8881d1 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/Makefile
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/Makefile
@@ -9,24 +9,24 @@ all: handout handout-tarfile
 
 handout: 
 	# Rebuild the handout directory that students download
-	(rm -rf cs105_pyfile-handout; mkdir cs105_pyfile-handout)
-	cp -p src/Makefile-handout cs105_pyfile-handout/Makefile
-	cp -p src/README-handout cs105_pyfile-handout/README
-	cp -p src/driver_python.py cs105_pyfile-handout
+	(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
 
-	cp -p src/student_sources.zip cs105_pyfile-handout
+	cp -p src/student_sources.zip cs105-handout
 
-	cp -p src/homework1.py cs105_pyfile-handout
+	cp -p src/homework1.py cs105-handout
 
-	cp -p src/docker_helpers.py cs105_pyfile-handout
+	cp -p src/docker_helpers.py cs105-handout
 
-	cp -p src/report2_grade.py cs105_pyfile-handout
+	cp -p src/report2_grade.py cs105-handout
 
 
 handout-tarfile: handout
 	# Build *-handout.tar and autograde.tar
-	tar cvf cs105_pyfile-handout.tar cs105_pyfile-handout
-	cp -p cs105_pyfile-handout.tar autograde.tar
+	tar cvf cs105-handout.tar cs105-handout
+	cp -p cs105-handout.tar autograde.tar
 
 clean:
 	# Clean the entire lab directory tree.  Note that you can run
@@ -35,7 +35,7 @@ clean:
 	rm -f *~ *.tar
 	(cd src; make clean)
 	(cd test-autograder; make clean)
-	rm -rf cs105_pyfile-handout
+	rm -rf cs105-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/cs105/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..dfcdcfda5aa8049ab3b62a997b374031687046b6
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde-Makefile
@@ -0,0 +1,7 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..5217159da449d47c709258f3089da0ed705afe90
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105/autograde.tar 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
new file mode 100644
index 0000000000000000000000000000000000000000..5217159da449d47c709258f3089da0ed705afe90
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout.tar differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/Makefile
similarity index 100%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/Makefile
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/README b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/README
similarity index 100%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/README
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/README
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/docker_helpers.py
similarity index 99%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/docker_helpers.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/docker_helpers.py
index 38cf3134cc1b5b032dc1e9088a7025e824862dd1..b4b885526bfe90b86900afb241496de2c7c84aea 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/docker_helpers.py
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/docker_helpers.py
@@ -38,7 +38,7 @@ def compile_docker_image(Dockerfile, tag=None):
     base = os.path.dirname(Dockerfile)
     if tag == None:
         tag = os.path.basename(base)
-    os.system(f"cd {base} && docker build --tag {tag} .")
+    os.system(f"cd {base} && docker build --no-cache --tag {tag} .")
     return tag
 
 
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/driver_python.py
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile-handout/driver_python.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/driver_python.py
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
new file mode 100644
index 0000000000000000000000000000000000000000..18576f18162b3e965b483dc0c9f2673d29b35a2f
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/homework1.py
@@ -0,0 +1,178 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+bf53f370e71e4336d4a54c09f106ff88be0c37385c9ba6d9558657c25640e0166ca05e546617c8619f4d20e975652285268341097c88a559c4bfb73c809f1037 31256
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4J7RW09dAEABDnplQAh68K1MW+XxsudM+mkbOKPi5w3bSR2iPjq/0bufDOoDgP0a59qm4zFsg5jT+dpVTKPcVl5qm7mS4tEVYjRnoojhRQVv3wGaY5hcXphHa9WW1K5WP/mCfYMIVHcd3l19Y5C
+v6O4HkDjBrJJ4eP8dqI5tODjzw1NVfJp6qj6I0xYoEn+fOufsyocvCn25vXY6oxcpamNSIdXAO0Ku27Zf+DyJMXwAuIB3/0yqZIDeDa0Fy5mTO9ozUmkJbv/eH1335YLOo5zo8RH2+xMSxvV1JskGNLNFJ6w6v2FOMz/KCSBI7dbNpwaIaaV
+stG1BgtNiHK+hEMuvGOrQ4pyVgbYSi0VzbXB6K/n0f+J+yfYCUkZPC71AD6Xo/LAM4t5qmd5VQAFVzDK0Tkyh67mTJX+WuWdihL1Orr7VEi7EyX7cmvhLGTE+9lLG8dE3N5ocu/H2LAeFZ1K/LZQpbfwTZbeE6qO9cGkhf37BBtlYn625gHZ
+5DGrYObZekUHKQQ9Q08U4a1CoPFG7EOod70Zhso/MZNEfI333Iy/OIjGD8HSdTM+OuoIfPa23lmNX5m3FTJQvdtlIvnd+gXTgQWDaakgRTZstTfmaBuIIpEohVIXOr1bgzH9WfMeSUzNIt6qiU4yKI9AsQo0weNXr79k4LSI03CnoaZCBY+C
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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
new file mode 100644
index 0000000000000000000000000000000000000000..7484d93eae4ad3d81e212ea0c2a5c8561c1761b8
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/report2_grade.py
@@ -0,0 +1,4 @@
+# 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/cs105-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/student_sources.zip
new file mode 100644
index 0000000000000000000000000000000000000000..1c7054920d7d9ebff314ff8df914324ae7c4103a
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105-handout/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.rb
similarity index 69%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.rb
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.rb
index 3c915906b125a87b96c1e6bef3ba4c7b046da469..b115a01143a9ecc95eda6fbb126244631c5a74fe 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.rb
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.rb
@@ -1,10 +1,10 @@
 require "AssessmentBase.rb"
 
-module Cs105_pyfile
+module Cs105
   include AssessmentBase
 
   def assessmentInitialize(course)
-    super("cs105_pyfile",course)
+    super("cs105",course)
     @problems = []
   end
 
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.yml
similarity index 85%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.yml
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.yml
index d388356ff57c52ee78e3d5c524d99020bb5f80f9..e13ff06a3ec4cf0051bbb98ec1b330e3c45ec35e 100644
--- a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.yml
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/cs105.yml
@@ -1,14 +1,14 @@
 ---
 
 general:
-  name: cs105_pyfile
+  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_pyfile-handout.tar
-  writeup: writeup/cs105_pyfile.html
+  handout: cs105-handout.tar
+  writeup: writeup/cs105.html
   max_submissions: -1
   disable_handins: false
   max_size: 2
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile
similarity index 100%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/Makefile-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile-handout
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/Makefile-handout
@@ -0,0 +1,7 @@
+# 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/students/cs102_autolab/tmp/cs105_pyfile/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README
similarity index 100%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/README-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/src/README
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README-handout
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/README-handout
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..b4b885526bfe90b86900afb241496de2c7c84aea
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/docker_helpers.py
@@ -0,0 +1,197 @@
+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/students/cs102_autolab/tmp/cs105_pyfile/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh
similarity index 100%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver.sh
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh-handout
similarity index 100%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/driver.sh-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver.sh-handout
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py
diff --git a/examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py-handout
similarity index 100%
rename from examples/autolab_example_py_upload/instructor/cs102_autolab/tmp/cs105_pyfile/src/driver_python.py-handout
rename to examples/autolab_example_py_upload/instructor/tmp/cs105/src/driver_python.py-handout
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
new file mode 100644
index 0000000000000000000000000000000000000000..18576f18162b3e965b483dc0c9f2673d29b35a2f
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/homework1.py
@@ -0,0 +1,178 @@
+# 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/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/report2_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..7484d93eae4ad3d81e212ea0c2a5c8561c1761b8
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/report2_grade.py
@@ -0,0 +1,4 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..1c7054920d7d9ebff314ff8df914324ae7c4103a
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105/src/student_sources.zip 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
new file mode 100644
index 0000000000000000000000000000000000000000..ea7c9d2e41f6b768d3fc89ab2f087c1bdcdecac3
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/Makefile
@@ -0,0 +1,51 @@
+#
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..132cbaf68c797bdeafa87c17fa6fab2e1c41bf78
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde-Makefile
@@ -0,0 +1,7 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..0b7539927b932f17726ef3659895ede0fbd31807
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/autograde.tar 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
new file mode 100644
index 0000000000000000000000000000000000000000..0b7539927b932f17726ef3659895ede0fbd31807
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-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/cs105_new_version/cs105_new_version-handout/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/Makefile
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/README
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..b4b885526bfe90b86900afb241496de2c7c84aea
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/docker_helpers.py
@@ -0,0 +1,197 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..49a443dc051e8c745c096b613cb0ddf4ec262339
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/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 = '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
new file mode 100644
index 0000000000000000000000000000000000000000..55f96f90371e3b69cde9e6abaebe2a6409993f3b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/homework1.py
@@ -0,0 +1,178 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..2f3e2d766a3dbd871523e373f4420ee5921da44b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/report2_grade.py
@@ -0,0 +1,4 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..9d307cc1b71b8470bf731a5ae210cc5d8471f22a
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version-handout/student_sources.zip 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
new file mode 100644
index 0000000000000000000000000000000000000000..7d5b5b88f6484d3cdfc01aaed8f758dbb2094e0d
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.rb
@@ -0,0 +1,11 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..25461e45d118a5da0610e1f7283d6f53d9ca1e33
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/cs105_new_version.yml
@@ -0,0 +1,33 @@
+---
+
+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
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/Makefile-handout
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/README-handout
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..b4b885526bfe90b86900afb241496de2c7c84aea
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/docker_helpers.py
@@ -0,0 +1,197 @@
+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):$(id -g)" '
+    else:
+        user_cmd = ''
+
+    if xvfb:
+        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
+
+    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
+    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
+    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
+    fcom = f"{cdcom}  && {dcom}"
+    print("> Running docker command")
+    print(fcom)
+    init = time.time() - start
+    # thtools.execute_command(fcom.split())
+    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
+    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
+    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
+    for t in tokens:
+        print("Source image produced token", t)
+    elapsed = time.time() - start
+    print("Elapsed time is", elapsed, f"({init=} seconds)")
+    if len(tokens) != 1:
+        print("Wrong number of tokens produced:", len(tokens))
+        print(out)
+    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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 ${status}"
+#    echo "{\"scores\": {\"Correctness\": 0}}"
+#fi
+
+exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh-handout
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/driver.sh-handout
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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
new file mode 100644
index 0000000000000000000000000000000000000000..49a443dc051e8c745c096b613cb0ddf4ec262339
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/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 = '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
new file mode 100644
index 0000000000000000000000000000000000000000..49a443dc051e8c745c096b613cb0ddf4ec262339
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/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 = '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
new file mode 100644
index 0000000000000000000000000000000000000000..55f96f90371e3b69cde9e6abaebe2a6409993f3b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/homework1.py
@@ -0,0 +1,178 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..2f3e2d766a3dbd871523e373f4420ee5921da44b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/report2_grade.py
@@ -0,0 +1,4 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..9d307cc1b71b8470bf731a5ae210cc5d8471f22a
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105_new_version/src/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105b/Makefile
similarity index 63%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/Makefile
rename to examples/autolab_example_py_upload/instructor/tmp/cs105b/Makefile
index 2625f4e99636100acb4adc78cce9291525311656..b12dc571349b4501f1e9bc7b1c45858ad52b484f 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/Makefile
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/Makefile
@@ -9,24 +9,24 @@ all: handout handout-tarfile
 
 handout: 
 	# Rebuild the handout directory that students download
-	(rm -rf cs105_pyfile-handout; mkdir cs105_pyfile-handout)
-	cp -p src/Makefile-handout cs105_pyfile-handout/Makefile
-	cp -p src/README-handout cs105_pyfile-handout/README
-	cp -p src/driver_python.py cs105_pyfile-handout
+	(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 cs105_pyfile-handout
+	cp -p src/student_sources.zip cs105b-handout
 
-	cp -p src/homework1.py cs105_pyfile-handout
+	cp -p src/homework1.py cs105b-handout
 
-	cp -p src/docker_helpers.py cs105_pyfile-handout
+	cp -p src/docker_helpers.py cs105b-handout
 
-	cp -p src/report2_grade.py cs105_pyfile-handout
+	cp -p src/report2_grade.py cs105b-handout
 
 
 handout-tarfile: handout
 	# Build *-handout.tar and autograde.tar
-	tar cvf cs105_pyfile-handout.tar cs105_pyfile-handout
-	cp -p cs105_pyfile-handout.tar 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
@@ -35,7 +35,7 @@ clean:
 	rm -f *~ *.tar
 	(cd src; make clean)
 	(cd test-autograder; make clean)
-	rm -rf cs105_pyfile-handout
+	rm -rf cs105b-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/cs105b/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..f07ac0d3757170e32ab3584241fddea0825b44b2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde-Makefile
@@ -0,0 +1,7 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..d918a132bd4f491b2df40f93a4a19b87efd9d7ee
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105b/autograde.tar 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
new file mode 100644
index 0000000000000000000000000000000000000000..d918a132bd4f491b2df40f93a4a19b87efd9d7ee
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout.tar 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
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/Makefile
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/README
@@ -0,0 +1,15 @@
+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/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/docker_helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..806c2b39c6782ed377ab0d4cf70a36d03940fd7b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/docker_helpers.py
@@ -0,0 +1,197 @@
+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/cs105b/cs105b-handout/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..78e248e085b8de1a55f12d412520bc828dafd5ac
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/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_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
new file mode 100644
index 0000000000000000000000000000000000000000..22d3556a6adf524702c6829e95415abcb0e5aaed
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/homework1.py
@@ -0,0 +1,178 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+2673de03a1dd2c7cce073a5f05532ee5a90d5af1632134c954b072b79e128692ee64f95183249b6e9750be00390bedc51d1e021825a6da9e2d0ddc6e5780534a 31232
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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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
new file mode 100644
index 0000000000000000000000000000000000000000..6a3e210416d3f1d38a3d87397ce71e63cdcc8c4c
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/report2_grade.py
@@ -0,0 +1,4 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..7256169a6f823cce5b36856a58c7d94cec8c8d79
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b-handout/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.rb
similarity index 69%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.rb
rename to examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.rb
index 3c915906b125a87b96c1e6bef3ba4c7b046da469..bc7d741ac450871b0062ea2121915feab1d1c057 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.rb
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.rb
@@ -1,10 +1,10 @@
 require "AssessmentBase.rb"
 
-module Cs105_pyfile
+module Cs105b
   include AssessmentBase
 
   def assessmentInitialize(course)
-    super("cs105_pyfile",course)
+    super("cs105b",course)
     @problems = []
   end
 
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.yml
similarity index 71%
rename from examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.yml
rename to examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.yml
index d388356ff57c52ee78e3d5c524d99020bb5f80f9..9c5d9f56c3165485281e508c4bd3367f56f5d91d 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/cs105_pyfile.yml
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/cs105b.yml
@@ -1,14 +1,14 @@
 ---
 
 general:
-  name: cs105_pyfile
+  name: cs105b
   description: ''
-  display_name: CS 102 Report 2 (Scored using autolab)
+  display_name: CS 105 Report autolab v2
   handin_filename: homework1.py
   handin_directory: handin
   max_grace_days: 0
-  handout: cs105_pyfile-handout.tar
-  writeup: writeup/cs105_pyfile.html
+  handout: cs105b-handout.tar
+  writeup: writeup/cs105b.html
   max_submissions: -1
   disable_handins: false
   max_size: 2
@@ -23,7 +23,7 @@ problems:
 
 autograder:
   autograde_timeout: 180
-  autograde_image: tango_python_tue
+  autograde_image: tango_python_tue2
   release_score: true
 
 # problems:
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Makefile-handout
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/README-handout
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..22d3556a6adf524702c6829e95415abcb0e5aaed
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/Report2_handin_16_of_16.token
@@ -0,0 +1,178 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+2673de03a1dd2c7cce073a5f05532ee5a90d5af1632134c954b072b79e128692ee64f95183249b6e9750be00390bedc51d1e021825a6da9e2d0ddc6e5780534a 31232
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4J7JWz9dAEABDnnhhAh68K1MW+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/cs105b/src/docker_helpers.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/docker_helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..806c2b39c6782ed377ab0d4cf70a36d03940fd7b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/docker_helpers.py
@@ -0,0 +1,197 @@
+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/cs105b/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh
@@ -0,0 +1,33 @@
+#!/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 ${status}"
+#    echo "{\"scores\": {\"Correctness\": 0}}"
+#fi
+
+exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh-handout
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/driver.sh-handout
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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
new file mode 100644
index 0000000000000000000000000000000000000000..78e248e085b8de1a55f12d412520bc828dafd5ac
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/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_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
new file mode 100644
index 0000000000000000000000000000000000000000..78e248e085b8de1a55f12d412520bc828dafd5ac
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/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_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
new file mode 100644
index 0000000000000000000000000000000000000000..22d3556a6adf524702c6829e95415abcb0e5aaed
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/homework1.py
@@ -0,0 +1,178 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+2673de03a1dd2c7cce073a5f05532ee5a90d5af1632134c954b072b79e128692ee64f95183249b6e9750be00390bedc51d1e021825a6da9e2d0ddc6e5780534a 31232
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4J7JWz9dAEABDnnhhAh68K1MW+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/cs105b/src/report2_grade.py b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/report2_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..6a3e210416d3f1d38a3d87397ce71e63cdcc8c4c
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/report2_grade.py
@@ -0,0 +1,4 @@
+# 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/src/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/student_sources.zip
new file mode 100644
index 0000000000000000000000000000000000000000..7256169a6f823cce5b36856a58c7d94cec8c8d79
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105b/src/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105d/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..45ec86c53510bab07263a227e5fa144b84aa5dc3
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/Makefile
@@ -0,0 +1,51 @@
+#
+# 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 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
+
+	cp -p src/student_sources.zip cs105d-handout
+
+	cp -p src/homework1.py cs105d-handout
+
+	cp -p src/docker_helpers.py cs105d-handout
+
+	cp -p src/report2_grade.py cs105d-handout
+
+
+handout-tarfile: handout
+	# Build *-handout.tar and autograde.tar
+	tar cvf cs105d-handout.tar cs105d-handout
+	cp -p cs105d-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 cs105d-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/cs105d/autograde-Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..c3596436ec9a956e5a3986977181b35860df0ed5
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde-Makefile
@@ -0,0 +1,7 @@
+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/autograde.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde.tar
new file mode 100644
index 0000000000000000000000000000000000000000..02da307fa4894beb490166ad6fa781828626c011
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105d/autograde.tar differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout.tar b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout.tar
new file mode 100644
index 0000000000000000000000000000000000000000..02da307fa4894beb490166ad6fa781828626c011
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout.tar differ
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
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/Makefile
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/README
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..806c2b39c6782ed377ab0d4cf70a36d03940fd7b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/docker_helpers.py
@@ -0,0 +1,197 @@
+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/driver_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..78e248e085b8de1a55f12d412520bc828dafd5ac
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/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_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/cs105d/cs105d-handout/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/homework1.py
new file mode 100644
index 0000000000000000000000000000000000000000..77a978252351241192fdfe7c24ee07f3e7d8191e
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/homework1.py
@@ -0,0 +1,178 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+531d216ee8525a094329d938de021b7d3ca09efb01b4b75971d3dcb13125e300b58be0fdce4af12e6bce97fc0c4e13710d773491d51234214ab598f7ab88081c 31260
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
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
new file mode 100644
index 0000000000000000000000000000000000000000..d52adecef721df29022bb284524df9472feb6c55
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/report2_grade.py
@@ -0,0 +1,4 @@
+# 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/cs105d-handout/student_sources.zip b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/student_sources.zip
new file mode 100644
index 0000000000000000000000000000000000000000..9b846859f70ba232d9273d91aeea1a3806f72612
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d-handout/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.rb b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.rb
new file mode 100644
index 0000000000000000000000000000000000000000..cf285db3bd5a91ba7023b67b4a39ba3cf18af258
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.rb
@@ -0,0 +1,11 @@
+require "AssessmentBase.rb"
+
+module Cs105d
+  include AssessmentBase
+
+  def assessmentInitialize(course)
+    super("cs105d",course)
+    @problems = []
+  end
+
+end
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.yml b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.yml
new file mode 100644
index 0000000000000000000000000000000000000000..7bf57bb054756d1c5aabb0dd43dd0577a576606f
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/cs105d.yml
@@ -0,0 +1,33 @@
+---
+
+general:
+  name: cs105d
+  description: ''
+  display_name: CS 105 Report autolab v2
+  handin_filename: homework1.py
+  handin_directory: handin
+  max_grace_days: 0
+  handout: cs105d-handout.tar
+  writeup: writeup/cs105d.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/cs105d/src/Makefile b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Makefile-handout
@@ -0,0 +1,7 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README
@@ -0,0 +1,15 @@
+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
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/README-handout
@@ -0,0 +1,15 @@
+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_16_of_16.token b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin_16_of_16.token
new file mode 100644
index 0000000000000000000000000000000000000000..77a978252351241192fdfe7c24ee07f3e7d8191e
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/Report2_handin_16_of_16.token
@@ -0,0 +1,178 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+531d216ee8525a094329d938de021b7d3ca09efb01b4b75971d3dcb13125e300b58be0fdce4af12e6bce97fc0c4e13710d773491d51234214ab598f7ab88081c 31260
+---------------------------------------------------------------------- ..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
new file mode 100644
index 0000000000000000000000000000000000000000..806c2b39c6782ed377ab0d4cf70a36d03940fd7b
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/docker_helpers.py
@@ -0,0 +1,197 @@
+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):$(id -g)" '
+    else:
+        user_cmd = ''
+
+    if xvfb:
+        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
+
+    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
+    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
+    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
+    fcom = f"{cdcom}  && {dcom}"
+    print("> Running docker command")
+    print(fcom)
+    init = time.time() - start
+    # thtools.execute_command(fcom.split())
+    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
+    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
+    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
+    for t in tokens:
+        print("Source image produced token", t)
+    elapsed = time.time() - start
+    print("Elapsed time is", elapsed, f"({init=} seconds)")
+    if len(tokens) != 1:
+        print("Wrong number of tokens produced:", len(tokens))
+        print(out)
+    return tokens[0]
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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 ${status}"
+#    echo "{\"scores\": {\"Correctness\": 0}}"
+#fi
+
+exit
diff --git a/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh-handout
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver.sh-handout
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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_python.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..78e248e085b8de1a55f12d412520bc828dafd5ac
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/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_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/cs105d/src/driver_python.py-handout b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/driver_python.py-handout
new file mode 100644
index 0000000000000000000000000000000000000000..78e248e085b8de1a55f12d412520bc828dafd5ac
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/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_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/cs105d/src/homework1.py b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/homework1.py
new file mode 100644
index 0000000000000000000000000000000000000000..77a978252351241192fdfe7c24ee07f3e7d8191e
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/homework1.py
@@ -0,0 +1,178 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+531d216ee8525a094329d938de021b7d3ca09efb01b4b75971d3dcb13125e300b58be0fdce4af12e6bce97fc0c4e13710d773491d51234214ab598f7ab88081c 31260
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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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
new file mode 100644
index 0000000000000000000000000000000000000000..d52adecef721df29022bb284524df9472feb6c55
--- /dev/null
+++ b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/report2_grade.py
@@ -0,0 +1,4 @@
+# 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
new file mode 100644
index 0000000000000000000000000000000000000000..9b846859f70ba232d9273d91aeea1a3806f72612
Binary files /dev/null and b/examples/autolab_example_py_upload/instructor/tmp/cs105d/src/student_sources.zip differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/cs105_pyfile.tar b/examples/autolab_example_py_upload/students/cs102_autolab/cs105_pyfile.tar
deleted file mode 100644
index e159d0587428fcef010410b511cbdb0645606d2d..0000000000000000000000000000000000000000
Binary files a/examples/autolab_example_py_upload/students/cs102_autolab/cs105_pyfile.tar and /dev/null differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/cs105b.tar b/examples/autolab_example_py_upload/students/cs102_autolab/cs105b.tar
new file mode 100644
index 0000000000000000000000000000000000000000..a52f0ba0471f27e68343b19e8812799658aef457
Binary files /dev/null and b/examples/autolab_example_py_upload/students/cs102_autolab/cs105b.tar differ
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/deploy.py b/examples/autolab_example_py_upload/students/cs102_autolab/deploy.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbfc07e836708a6c9560ec7a99c951c54cda8721
--- /dev/null
+++ b/examples/autolab_example_py_upload/students/cs102_autolab/deploy.py
@@ -0,0 +1,9 @@
+from cs102.report2 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/students/cs102_autolab/deploy_autolab.py b/examples/autolab_example_py_upload/students/cs102_autolab/deploy_autolab.py
deleted file mode 100644
index 7011e3e9456a33b0121c067cfea923dc3cb3fda6..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/students/cs102_autolab/deploy_autolab.py
+++ /dev/null
@@ -1,38 +0,0 @@
-from unitgrade_private.autolab.autolab import new_deploy_assignment
-from unitgrade_private.docker_helpers import download_docker_images
-from unitgrade_private.docker_helpers import compile_docker_image
-
-if __name__ == "__main__":
-    ## Step 1. Deploy the report file.
-    from report2 import Report2
-    from unitgrade_private.hidden_create_files import setup_grade_file_report
-    from snipper.snip_dir import snip_dir
-
-    # 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.py', '*_grade.py'])
-
-
-    # Step 1: Download and compile docker grading image. You only need to do this once.  
-    download_docker_images("../docker") # Download docker images from gitlab (only do this once).
-    dockerfile = f"../docker/docker_tango_python/Dockerfile"
-    autograde_image = 'tango_python_tue'  # Tag given to the image in case you have multiple images.
-    compile_docker_image(Dockerfile=dockerfile, tag=autograde_image)  # Compile docker image. 
-
-    # Step 2: Create the cs102.tar file from the grade scripts. 
-    instructor_base = f"."
-    student_base = f"../../students/cs102_autolab"
-
-    from report2 import Report2
-    # INSTRUCTOR_GRADE_FILE =
-    output_tar = new_deploy_assignment("cs105_pyfile",  # 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",
-                                   STUDENT_BASE=student_base,
-                                   STUDENT_GRADE_FILE=f"{instructor_base}/report2.py",
-                                   autograde_image_tag=autograde_image,
-                                   student_should_upload_token=False,
-                                    homework_file="homework1.py") 
-
-    # What can you do? Get a report class from the .token file?
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/report2.py b/examples/autolab_example_py_upload/students/cs102_autolab/report2.py
index 5b5631fd0dba4b51faeecb4ede4f510bf521a07b..f0c0566912ba71eafd24c72f840c0f8b821e68ab 100644
--- a/examples/autolab_example_py_upload/students/cs102_autolab/report2.py
+++ b/examples/autolab_example_py_upload/students/cs102_autolab/report2.py
@@ -1,6 +1,6 @@
 from unitgrade.framework import Report
 from unitgrade.evaluate import evaluate_report_student
-from cs102.homework1 import add, reverse_list
+from homework1 import add, reverse_list
 from unitgrade import UTestCase, cache  
 import homework1
 
@@ -59,9 +59,8 @@ class Question2(UTestCase):
         return "Buy world!"                                 # This value will be stored in the .token file  
 
 
-import cs102
 class Report2(Report):
-    title = "CS 102 Report 2 (Scored using autolab)"
+    title = "CS 105 Report autolab v2"
     questions = [(Week1, 10), (Week1Titles, 6)]
     pack_imports = [homework1]
 
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/autograde-Makefile b/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/autograde-Makefile
deleted file mode 100644
index cfd3cff716e59ce47bd4a2c9bf9cb54475b164cf..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/autograde-Makefile
+++ /dev/null
@@ -1,7 +0,0 @@
-all:
-	tar xf autograde.tar
-	cp homework1.py cs105_pyfile-handout
-	(cd cs105_pyfile-handout; python3 driver_python.py)
-
-clean:
-	rm -rf *~ hello3-handout
\ No newline at end of file
diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/homework1.py b/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/homework1.py
deleted file mode 100644
index b86df35fcddd43c2f4cd2917037dadae3341d7a8..0000000000000000000000000000000000000000
--- a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/homework1.py
+++ /dev/null
@@ -1,181 +0,0 @@
-# This file contains your results. Do not edit its content. Simply upload it as it is.
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-f4ba0f1c4bc6ceb0b7d4f6f73c8f652f66df5bedf31db06f2123c1d612f151928b83b9c4cf58aaccb1e1354d7045df1aefb44983894bd408cdf77edb03b38180 31680
----------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
-./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4J7eXI9dAEABDns7UYh68K1MW+XxsudM+mkbOKPi5w3bSR2iPjq/0bufDOoDgP0a59qm4zFsg5jT+dpVTKPcVl5qm7mS4tEVYjRnoojhRQVv3wGaY5hcXphHa9WW1K5WP/mCfYMIVHcd3l19Y5C
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-v9JrIzcT2OQwT67qdyt+CVbQwzxePgYBcSECEnlY0NqPJVc15Y6Sh3/8iSDrMxC02y3vIqPFMh/AT1FFJ9UPJlOZhVFG56MMvDeAc/IzgFgUg7e9v/t8NGyD8SkHdxavjOvakk/YwDhFllaXxLP//Vp7b6hcC41Ob+9xk/gmexyFnMVM19qc
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diff --git a/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/student_sources.zip b/examples/autolab_example_py_upload/students/cs102_autolab/tmp/cs105_pyfile/src/student_sources.zip
deleted file mode 100644
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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 88d27fe22ab6b3e1f9f01592b6fe48693f235f99..b5d4dfac0e7bedd5d862a80da7987e7e74fdcbdd 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 dfad953c979edce489b1fad0368eba4530aa8d98..15fc0f6b47c26ddaabe6c9f65fffe605a6b8ef62 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/example_framework/instructor/cs102/Report2_handin_16_of_16.token b/examples/example_framework/instructor/cs102/Report2_handin_16_of_16.token
index 88b3c45c9fe6f2e1fb92d6b86477ef01d105a367..1da90732870b6c63df1df6515bde40a76477f4e3 100644
--- a/examples/example_framework/instructor/cs102/Report2_handin_16_of_16.token
+++ b/examples/example_framework/instructor/cs102/Report2_handin_16_of_16.token
@@ -1,176 +1,174 @@
 # 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/example_framework/instructor/cs102/__pycache__/report2_grade.cpython-39.pyc b/examples/example_framework/instructor/cs102/__pycache__/report2_grade.cpython-39.pyc
index 9f83b8f6d0e4ba8170158ad5c8686e5cdd794cd5..989996fb05e8d4dff8b46b260753e90921ec8a51 100644
Binary files a/examples/example_framework/instructor/cs102/__pycache__/report2_grade.cpython-39.pyc and b/examples/example_framework/instructor/cs102/__pycache__/report2_grade.cpython-39.pyc differ
diff --git a/examples/example_framework/students/cs102/Report2_handin_3_of_16.token b/examples/example_framework/students/cs102/Report2_handin_3_of_16.token
index 23e96b88b5b86df15d7880ff02c5e70ca4881afa..d5fc9cff10ea529c942f24d12db19ecc312aac5f 100644
--- a/examples/example_framework/students/cs102/Report2_handin_3_of_16.token
+++ b/examples/example_framework/students/cs102/Report2_handin_3_of_16.token
@@ -1,27 +1,5 @@
 # This file contains your results. Do not edit its content. Simply upload it as it is. 
-### Content of cs102\homework1.py ###
-
-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])) 
-
-
-### Content of cs102\report2.py ###
+### Content of cs102/report2.py ###
 
 from unitgrade.framework import Report
 from unitgrade.evaluate import evaluate_report_student
@@ -90,165 +68,186 @@ class Report2(Report):
 
 if __name__ == "__main__":
     evaluate_report_student(Report2(), unmute=True)
+
+
+### Content of cs102/homework1.py ###
+
+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]))
 ---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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 ---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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+AAAAEWVo=.
\ No newline at end of file
diff --git a/src/unitgrade_private/__init__.py b/src/unitgrade_private/__init__.py
index d928c7ab2cc52d397f8abaf0a346f0d9ed8c0f9d..cd56efa2d9dc110ce754ae04fbbd9ff4f5b2ae1a 100644
--- a/src/unitgrade_private/__init__.py
+++ b/src/unitgrade_private/__init__.py
@@ -1,5 +1,5 @@
 import os
-# import compress_pickle
+from unitgrade_private.version import __version__
 from unitgrade_private.hidden_gather_upload import load_token, save_token
 from unitgrade_private.plagiarism.mossit import unpack_sources_from_token
 from unitgrade_private.hidden_create_files import setup_grade_file_report
diff --git a/src/unitgrade_private/autolab/autolab.py b/src/unitgrade_private/autolab/autolab.py
index e4a41c770747712bedf28c79c7d645b2b1bf9174..be85379abba7b708960a84a8322737f5fa61b552 100644
--- a/src/unitgrade_private/autolab/autolab.py
+++ b/src/unitgrade_private/autolab/autolab.py
@@ -104,7 +104,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     # deploy_assignment()
     # deploy_directly = COURSES_BASE != None
     if COURSES_BASE == None:
-        COURSES_BASE = os.getcwd() + "/tmp"
+        COURSES_BASE = os.getcwd() + "/../tmp"
         if not os.path.exists(COURSES_BASE):
             os.mkdir(COURSES_BASE)
 
@@ -124,9 +124,6 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     total_ = res['total'][1]
     problems = []
     problems.append(dict(name='Unitgrade score', description='', max_score=total_, optional='false'))
-    # for k, q in res['details'].items():
-    #     problems.append(dict(name=q['title'], description='', max_score=q['possible'], optional='true'))
-    # problems.append(dict(name="Autograding Total", description='The description (set in autolab.py)', 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])
@@ -157,11 +154,13 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     INSTRUCTOR_REPORT_FILE = INSTRUCTOR_GRADE_FILE[:-9] + ".py"
 
     print("Making data...")
+    student_token_src_filename = os.path.basename(STUDENT_TOKEN_FILE)
     # /home/tuhe/Documents/unitgrade_private_v1/examples/example_simplest/instructor/programs/report5.py"
     data = {
         'base_name': base_name,
         'display_name': paths2report(INSTRUCTOR_BASE, INSTRUCTOR_REPORT_FILE).title,
         'handin_filename': handin_filename,
+        # 'student_token_file': STUDENT_TOKEN_FILE,
         'autograde_image': autograde_image_tag,
         'src_files_to_handout': ['driver_python.py', 'student_sources.zip', handin_filename,
                                  os.path.basename(docker_helpers.__file__),
@@ -171,6 +170,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
         'problems': problems,
         'student_should_upload_token': student_should_upload_token,
         'homework_file': homework_file,
+        'student_token_src_filename': student_token_src_filename,
         # 'homework_file_basename':
     }
     print("> Running jinja2")
@@ -189,6 +189,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     # Copy the student grade file to remove.
     shutil.copyfile(INSTRUCTOR_GRADE_FILE, f"{LAB_DEST}/src/{os.path.basename(INSTRUCTOR_GRADE_FILE)}")
     shutil.copyfile(STUDENT_TOKEN_FILE, f"{LAB_DEST}/src/{handin_filename}")
+    shutil.copyfile(STUDENT_TOKEN_FILE, f"{LAB_DEST}/src/{student_token_src_filename}")
     import pathlib
     print("> Making archive..")
     # zip_base_dir = pathlib.Path(os.path.relpath(STUDENT_GRADE_FILE, STUDENT_BASE)).parent
@@ -202,14 +203,18 @@ def new_deploy_assignment(base_name, INSTRUCTOR_REPORT_CLASS, INSTRUCTOR_BASE, I
     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}"
+<<<<<<< HEAD
     # import os
 
+=======
+    print("Running make...")
+>>>>>>> 0143c936a578e836547abc69d4aaeb950e9d596d
     os.system(f"cd {LAB_DEST} && make && cd {CURDIR}")
-    os.system(f"cd {LAB_DEST} && make handout")
-    from slider.latexutils import latexmk
-    import subprocess
-    s = subprocess.check_output(cmd, shell=True)
-
+    # os.system(f"cd {LAB_DEST} && make handout")
+    # from slider.latexutils import latexmk
+    # import subprocess
+    # s = subprocess.check_output(cmd, shell=True)
+    print("Ran make command...")
     if output_tar is None:
         output_tar = os.getcwd() + "/" + base_name + ".tar"
     print("Making archive")
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 34b79419533f68a5cd9d4d5b4ecc47acd3d44020..8a54a020bd15b1b0f958e8783caa4e070d2d6eeb 100644
--- a/src/unitgrade_private/autolab/lab_template/src/driver_python.py
+++ b/src/unitgrade_private/autolab/lab_template/src/driver_python.py
@@ -7,6 +7,7 @@ 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]"
@@ -14,6 +15,10 @@ 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()
@@ -25,7 +30,7 @@ def pfiles():
     print("---")
 
 handin_filename = "{{handin_filename}}"
-student_token_file = '{{handin_filename}}'
+student_token_file = '{{handin_filename if student_should_upload_token else student_token_src_filename}}'
 instructor_grade_script = '{{instructor_grade_file}}'
 grade_file_relative_destination = "{{grade_file_relative_destination}}"
 host_tmp_dir = wdir + "/tmp"
diff --git a/src/unitgrade_private/docker_helpers.py b/src/unitgrade_private/docker_helpers.py
index 38cf3134cc1b5b032dc1e9088a7025e824862dd1..806c2b39c6782ed377ab0d4cf70a36d03940fd7b 100644
--- a/src/unitgrade_private/docker_helpers.py
+++ b/src/unitgrade_private/docker_helpers.py
@@ -33,12 +33,12 @@ def download_docker_images(destination=None):
                 shutil.copytree(tmp_dir, dest)
 
 
-def compile_docker_image(Dockerfile, tag=None):
+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 --tag {tag} .")
+    os.system(f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} .")
     return tag
 
 
diff --git a/src/unitgrade_private/version.py b/src/unitgrade_private/version.py
index 95c1f747104f59378bddddaa7fd9ab823b1d0e6d..c0a8133867b198d104d272bb3ab44310837bfbbd 100644
--- a/src/unitgrade_private/version.py
+++ b/src/unitgrade_private/version.py
@@ -1 +1,5 @@
+<<<<<<< HEAD
 version = "0.1.37"
+=======
+__version__ = "0.1.38"
+>>>>>>> 0143c936a578e836547abc69d4aaeb950e9d596d