diff --git a/docker_images/docker_tango_python/requirements.txt b/docker_images/docker_tango_python/requirements.txt
index 084c2114d646cf6216e9083aae4b72784c4206e5..70d4fad399affbd2faad24426948fa773d85536d 100644
--- a/docker_images/docker_tango_python/requirements.txt
+++ b/docker_images/docker_tango_python/requirements.txt
@@ -6,3 +6,4 @@ pyfiglet
 colorama
 unitgrade>=0.1.23
 unitgrade-devel>=0.1.37 # Required to run automatic evaluation (load tokens etc.)
+requests # For unitgrade, may remove later.
diff --git a/docker_images/unitgrade-docker/requirements.txt b/docker_images/unitgrade-docker/requirements.txt
index f415be306d4ff87b4943add66860a81f1cca01a3..cb32e1584ee5c69345f21bda8b1135bd342f9009 100644
--- a/docker_images/unitgrade-docker/requirements.txt
+++ b/docker_images/unitgrade-docker/requirements.txt
@@ -6,4 +6,4 @@ pyfiglet
 colorama
 importnb
 unitgrade # Perhaps just this and not the other.
-
+requests # For unitgrade, may remove later.
diff --git a/examples/02105/instructor/week2/StoneReport_handin_10_of_10.token b/examples/02105/instructor/week2/StoneReport_handin_10_of_10.token
index 14ff1bbd847dc4ba97e969f86d3429a1c4295f84..28772b965549f1c057b4c97903d798c7fe544775 100644
--- a/examples/02105/instructor/week2/StoneReport_handin_10_of_10.token
+++ b/examples/02105/instructor/week2/StoneReport_handin_10_of_10.token
@@ -1,180 +1,179 @@
 # This file contains your results. Do not edit its content. Simply upload it as it is.
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\ No newline at end of file
diff --git a/examples/02105/instructor/week2/stones_tests_grade.py b/examples/02105/instructor/week2/stones_tests_grade.py
index 50a90757f62400fc8f96e174999c81ce2d52a1bb..4ea35230b3640fc8049c34f102fc80f7fb3636b1 100644
--- a/examples/02105/instructor/week2/stones_tests_grade.py
+++ b/examples/02105/instructor/week2/stones_tests_grade.py
@@ -1,4 +1,4 @@
 # stones_tests.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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ioCUbii23sE7wT8SGQn00UZzWTU+ZzlgI8a5YWakmukb0dBK9gQ6/V/uEm8DgTDSdGKJu/fHHx3LRitBsWnvWzmFKUCMY0m0Z12HkXQgXbeb+Tx9c+LP2Nq70nR3vktVeUjqs5HoKusU8i7U+we2ymP+Lqs72+N3ZHrnisNNdZTlts+ywR2qs7pqPvntWc1dOzvetN9/y28fG+J21yqbFhMuj0415PrWdLPf78eO9dr4v0t646vlkLld77wa+1kfsg4ONvkO3ajEMAvvZsZnTHcKfIdfPvlJxeeU+6V03uwDLcSIDn+E/Jfb9N8dPV5sryap8uWM+quyj3bqjjmtrzpyw7J458n2xqmabvg9nS11/BQJQ44Q8I14pGLIXaJoEnVl1j35+ouwSsiMhWocDUAyIKVHlSNsrA+L8Nk1r7xkucG5giSKibabZIrz7JGepkfZ1/dqXfk7teN+Gz1Lo5PX69eW275HwwRkrV0f5fq3GXZji2To5kA7ZrNBGUwcBX3C/iwKKrNnYysbuUMRiac0SU0DpK3RME7j8af0IVgfE8eyXS7SCbFzUDNYxtbMr2azUWN/i1viWt5LMddZUQ3VirFR2fl5XNClvKldx0NrmLaUoifmIhI/G8E3cPBuSnRi9D/ZWY2oihnuP9t7iYeiblRbj3mKd5MCmB8NaqHIbezRx/OmWZSmBtFpp9QdmMjhCj+/KSh7APAo+49P6HEsYFJ9hiUnj9nh6/wA8NXpJh7PVfEU4QB5mcMNUQkDDxd8UJ5DBhU9cvcWm3yea1CEqqqxA52QNu3XYU7s81ROgZQyLFVVkNuLAOEOONsQzu8HMDQs+BUUgofDGSvNUrMbbLbKtsYhVjJKrJWVYgFQUK/ntMMzICh18j9bmZXEHER1FTRzC1EZPb+yG5iAxpafvNLQMhskiKxSIyTQh22x1KaTfvG6YRrHOJdichpGmp181UU1+C9vhZ17bTbUuf8a6aTuqfeyVG8ZJt2nFMjU1CSEbCzwZCLBZq9SdA25W5YOzbHj7bD5Wu1bsdWXPTqpUzFbflQt1cFFvjCvyeTBdzP9uXMZzDJRnJDLKItVTrVXBMPDvFy6SuXft9DUf2GLFviruy7UQ0H6MP7ui0nzrEWRmZZjiJgTZDUSRf4mkWceFkWYPrCJbgQeXGDRkfDVY7vdFKDmMPiJcSqD3FgiTymbyhk1TAzkOYRmkN7jcrEpYcPQxKypDAuxtyPALEO8yG4d3bcunyZvQ9Z8fhcEmaaB0aNN2Q8XBAQcZGkObxtdCLaTTUDRv3cBQ2O2ROWOIfs2XbP91rKOnSLq/iX90Wa83sx+Wul5tngLY1Neg0LTCwVhgQVJfoEYBeyF47nZeBYTscDycLo9GIYxTB4uP3NguDgQ8hUTeHYy8rEvD3Tvlj4t8SciRgR3PgZ9zccGXdn7ahpRPtiFJy9XxR/3dv1/qkdZku5FkCc79Nrs6GWT2EJy2JlTHEs9N6LxgtMX5Vmmx7039J3TTipEPnESgn7ac+fInaoV/CY7rXfGi2muFRQORq45wXXRA+S6FjvUCIPgQV8BfTptel00jptPo/AclkdkPbUt+/p+S2ZrSss8qFFL96cq5ZV42T75OS0rF7vyXj6HKvj33eFOffSBaLth+Mn0SlJW8loqKseNCRMmnXc9JilChfi/ptlZf9sYPabR2SdML4E6JB+GT8l1R3wtMo/240kfBnjjhb22lyr34XQ8yxjkQ/BSLIo4XvSmtIKdjnSm5rhD2Iy69bzLHXk8OlYh0wUR8BZLN1u4B4yuJ+K8VxMJ4D9fv5MOVlky5y6bNzVKbIh54JNF+2cw/Z4Pm/y6e/WIdELiX58VBpT2RkzEBPtm+OE30ea9atulCQpvK+Sv1d+WWutlrWK/U7ZGoYlakkbJJiEnHZwgl6ZaZ0irOnccxsg7SZEo3T7bHqG5hBuN/AhttXICC2Kpom7GN3C0780Ky8u8JUj5aS/JiT8if3uvLxjXPFy3Bedzwin+D0dPxG7ecPPX2T8aH6t+h77zNo2r5oUMRDskh3RTkzOJGjzQ8iGdyI5MzXSXhrcuTS9dxc4WHqIxUKHaPiqsr0121Ld0P9XJet8syCDsepHPVI3/j9brd+yTx7+vUusqq4d82/8sYPfm18JdL5vnEpLDnuoinl3jt6fm+qMaCsZlZXdfVb+I+cZcc17q8FRSU/e5C0uo0+5zXnbl/Ds+pSPkp37YPXltl3LhcOkZ1N3n0xrKst6ex1KN/ZcQdFlkRk91MZwlfKbxD6y7VBk91HdK2GsXap4WXbqzvXFS73nx8/dGmPf6clR28fYYKyscy5UxWamYf64mV2qV5PxxfbmPumz2adgcVfd6xXSuyup9x55tbh4y93EDdprxk+pQqcX2qod0QJ/ThHe/XhWMFTesKT57p87HmnVE//HqvI7v4COZw8a43d39SIjETU1RCdvLExR7vpxJxfyxx2e87itVPgRL/TpzKBVj3b+Fk8ItKId0hIIv6+uCh6eTcNt1L8glq7MQS3H0EmY9i9VlWHQWiDBNUUcQlJv7rAnBk1GCzQQiMDnhPulr31iiXmiRAV4T56fJ1sFzDcZCP2YDXokJ0Bv4OmZM3rx5TOENevnnzuSLW+von48j5FjBBDlljrCZRJMee/k1iuE2cly5FmHL5XwXuP2lvl3lT/KhM69eCx/9vulwut1c4HR2N7EXJ7sNmOah6cO7erbZdKts90NOjzGvujzoie+oEpb6lJdgT9twU0yMifXZX4W2ZzfFjBc8nMbKlleB79LJVxkohleSYmpT92prSnF3QjTjp126ck28/X4sZkb6Ceo36k+USpBx2FXDsywxxqIeyDowz8JGF04Din8j+2LML8cMbCnelYcbE537339+D0BG8vzgdjtVnQT26h629EyeRpqiuGOMiXTUMeU8VpRvnerDSdBZx2DAnnpUqXrK5yXfhk30uZTPzHfR45bmGohWMJ0OnLHqonh02bLr7Kl9g/KOTYSLCWEztsnT352Yp7tKHa1cLS6rj7+RjKd13h1Kmsreqy2/Ofdz+I6Ctvk1e+8duxF5h1X0mbcMNcVjyZuqd3RdflkRYWWkijk8CzdJpIJD74z8H4aYO/WWrPJAcnvzokT/UW0t7fVHy4k0jxw4bQ0Iubrzs3k3spv17KNgbt8Ny19THqQB/HIgTHsk5gUQGvqZP91044h4yLCR1HIwfr0l3lxsY82j1nMrcBz533BajsoNsTkFoi28x+lU6nmpRLEkOOJ346mfsIv7t3jOUKnddynboeSCVH9qDifwp03Q2GUJVd3jBemc2UXxUaUIfwi/Zryh5z1D4oomHLjE+c5PxyqEh/O3r9AkO58/vDE9Jz35hqI2EDbIaGFANV23togrJ5kCmk/F42Uue9+idfSnn6MmjCdXBd81dafOaMIzrE418s9fheuG65xWOd2/h0aY0rj5GFQT5miKKqwKMjVHYTm2hsr7DT9vcwMSzCMZsG70ZxFwEpWyuMblJXPjxxGwxgbM6FtBMSYkMOLYhxuoWbsm9sNJIdRTdwZoph7O6cHABbeOY/EECiwGZTgl1+AZ3qHIuY6Yqkw2+8elLxwijGEiGIKyJH9/l8cyzEZvxB2wA9DtKOzVkXHEKGqIMDYTsYTkZOR9UMDVvKNCZhBNH9mpEzenxFRCFgL4ME+w3BDNzzalw1IZHpeeC4BCYFdZqmy58rtmBn0Mm8p3jKloPrZKO4wHrOAVqGcz0pQRQ8DOZw7McRjuaODrDSqmCG/TjIEJY1G5EyRYfe+LOOuDOgMHRsKNi4QpKQn9R0zHSx6ovbGc7D3M+bd0l88dvvrCtkmBYC/0ufE9w+rIQWOdPBRaiUnOrnhBghbVYZpBSb/IFtm+/6uOCOns+gy+eDGp65QJCFguG+Ims9rFwyKKnZxgCUappY1fkaHn21jKDWvIxhksp3giZuvalATIFIRiIZCN3S57cjf2gd+pvOvQKZHyjGAdh16gKAcH4NS4oEBwcaAe7qayR7cveFthYEHkDc0B+cLeAXM3wbiv4n1clzmf3Lus+wmqRrbXL60ZfIzepbsYNJnz+rm/uH13wCwRIk27NZppzRWKiIoxRYgeXNsy3w0rbDbgOQGOm2qXJplJ396d06uKQ+kd/EoFv1j0exM33JkmGqKeA0B5urceA+78tnf57Hm7RtOlKqYPzPeX+OFjEV2LL04hP+51+ztRSQlw5w3vn0bwGc/RYIkURfNaDGNymRBUZ+CnuCQxhTHE5Zrjkby3CauZ32q9MhwORleRl9BRYkGN1DWcDsznEM/89d/K1s6q91zLRVF/bPrqgvWg9TdpRW3nN+zZtt1DTu+P0ncLJ7guelh6G9b7+/vfAUQ9lUKjFFUY+sysLRkUvFJwreIxCJ6dPLETCQbnCW/j2t3CfNu5uFgNp35ua8TaUNV952BS4JGh2K/aIWqcx9gaXEWZxs+Fxde7xEoy+bFfheFx+fbe9prk1y8waeeCOKxLkrmEbh3H1rMTWqdZrMk4jOMOVmwyyQaSZITu6eJkWs51eagV5mIjIpHlzCIZCbBDZpRNXlPVTncEYRnCnWd4kxV4mqRMVqE4ni2qcuobEPMmNxnT3hFBeFEQmMRpQrrEPCm9SOsyASqdGczd50sXp4xOql8vKu40auNKy7epeMl3l4qTCelNxz7Pay8woMjIN9zzb09M0G3TjrlhoVUUYKKJpqYQ1ZbDMRERRWJ0yGs0WQMkm3Z3DPLN813EzBnFca5HWgkJD6ahMceByRbbNqiIKDBVFFZ6edx9VKCJ3IQ6ImMO3PdSx303misuGD3e5KprGVji7o4efGqRefhzOHqcZJWXfJqsvqDd+PFYSHRKhXer70Si9VaJN0o41hRMO1iSZN8WJ4pJKoK1mUkrfJUDrPvDtkqlnG5xVqNUoxnJdcFTtgpm08eTLNhmOYeM8TDcbXEsYtyqz1rWtQjnvsvFtaSSW/1n8KJY5EAgNOXnAAaJhdY5MVxenvp4ZjdDGNY82z7PGNThmTMkJrXyd02k6JGnRXOArDCFIydMa8gsqurGOy8UDR4cdGDRddzekN7iDJH71sMdMhq+kcZ0NrshkyCcLqCKl8IbMnr58irtBBmOcK1zKOTrxGdmhX6hYcDNttDIH2/HmFMNSYrnnNcCko1qYnSlBpDbBldn1hz/FfBJHyP+mPoulb+R7Uf6fU/stwVJJ6r64+iLin1KBsOlEXyJUdSb2Q4BeOetEJHSOQ/xkH3H7PL4Hxdurv2MfnnxVrZ5w3/pfmFIQ3OJwS16okrfHv3Xwqf6B/qGb5D6CJkJHymfoROySdzJuZOXHYWV41O9PDTXwx3albNS7niyTDbFVEV8eCXucWmG4OmLAtA9SQ22Uo6qlcaaqKZ4ueWPLLG5HF89abKM5dMVNnLRw+dN+tocJ4r4GZpKJVrU82+OW6mdnPNsKmp/BMSKaE6t3SU9fmxJesfknU1V8Pdk+MeEh5la18yl9VPH9FtOXupYspyiVyYlhKFSTxiOcez71+4EXsTz7nN5Tx+Ifp+fFCKEfnsRrIskrJ9pTSH+EuXpRuBehZFRkRqC3hGEKwWEFg40AFIQqChjAxSYxtCCjBJUdscwKAq0B6TjoHxeKTSE2f1UrToqZp2wcjm9Rmi66xpCYoZanZXwtVl+lb5msGbDNhz/BXmixTouEeKIkb48VGMTUpFORLy1YLmnqCK/CPEvODFrD4wXCqUPgyiHmY9NzOsXChPGG57Oe1cY08cNyJjjjF4gwxWOgnx/A1ysLOOBkdnPybWCbEaqvUujAm267ctbN1In2262TvtW3dk2YXuhnM7CLEoy/suMG6Z2GlhbW+CS1LzriiU9/zEWTFN2MXLjxd2U+XOpjO2DQh915GmRhym4rENd3GZ7aJgU3hbxPh3AHPZ+ti2P3FyKZCHIpAkb1v62tmVWImt/tO+vGDX2/vgn0cx+kDA+X/o+v/594+bv4h1FCnQdjVVHR8lPE7ZUv7rDI+Bgzxo/CqmqdISJLr6VDkCzaYsjlG9t/V/ET9C5rD6vP5x9d1VIKq+RnxIcOoLnkZwcaG9RifyR/E9vS4fYkt/9b6h0d325aAS0IHaD3nhnAMwYCbcp7cWiCQQD8w9h3lCFFfhLhydho/y/z/Jl4/4btp/gGHPGwS5IdrVRJ2aTyyQQHWadwkNOqZJkx4GpEBwANsRObYf4B54kWH++w1Lh2ZSa1tg8DzEgnRgHHXnOZgMQZyijyLmhz+CnOGAL4LIhIkIBEAL+Dh3bSMJd2LB9J5e/mO451+2lmIm+8WHIHBtQg4wkxpBU6efMVHO/o8NxrE6cQResmQjJz964yWoMR8uZ1tBIdkx4+rvDLbMztbtQfIjkAiQc2TGvolCbe7PakCfw8zN7pYmh4EzKygY4bL7/rb+pmKqaOYX2G2mI2QyOee8NIBnGJjem+pQRCtjCIzGiYfCrzNGhVH0FEhGE9XnKpg+65aqqszYL2QnrMMk6Ucr3BAQNce0iPTPtJMWHxtKntubn+wdnFyZEL8KGtiiG8N1AE2vVizS+pkw8iX5JTPXaVKL6kKcLRQVeCdRvXkm1PB/I+PgFlHxiGD8HHiCDeYkdj9oh6evTCEkkykfqskUGJLP4JjMlPznBnmTT2JP/A5nirV+rpuly6ar9KSTuO8mzXijIQQrLLIjonBMwBGeJJSthO898oj3c5Gc/Qax81zf30/bf0szc8OBw8OrSCWl5K5n53B0mDif9bQ/ncL95Ty66z5+fMMs9XUO2pUc1JOWv16sB9wJgQludxGCB0IaRscTy4XMB+X8pRVHN8zMp1IZ7GpVFG6nq7PkDISygQg0H8E8Dvop3C9leT6k5Khw9E28H3yYqQrBPz+VzVDtf2OVKSQhJJhAKTdvoqKk0YF+FbnV7UrNw+v5d+WZ+4jE4Bafn8t3eamxeUvdOO7lkqzw+GTF14wb1EeMdQ9i4IeMqk6JX6oKg68bT8zSSDlFoen8bvMv9qz2Tk86qpI6e5MxFF2lvA91e6YJSxrxiTOHvVROlDQOPCHynl3UxAl3xAVxHbEEy3n6fxb1T8Q6ShS5pS4gpUtrpMjs7OjhUCgQ6M949ZeM7lvu13wzrb0JN85iHVLHo5Pu+yMF1CwjsQ/I49GojCt/B47IqjrlSGuXvK4vjDyOrZaIhsII6poTW7gm6d0rufdPbtj2IkTGc1PS/VfQoEk9p4viI9zsXDPPEENNRrqoaHE7cPBkfBG5e/S7l1/E8TWbZwQ75qR7eXytSlLlTHUOqfCSM+HvIoF0PuEh1inP055LkUbg6SnSg1vEdb3glYccflyI+FS2I+PeeWxVVR96+WVFFnfb2FLCvTbNe3+OnXuXhIiKR/RavbbNrSY+LDqZwzZHL/PhvcJhSPqazT6kvror4c9W51KfBhS7WnUSc+NuWjT+hqeEDsdOcIuhHlVG/PIPJObmp95Oh4ZUiCs7uVhuQFMCZUtTahpfqvqN4KzW8ZUT1cJCWyoIEyWXfCZxdnHGEKLN2ou444o9mWS8az2m82ojs0PBJUFTp25y1V8uPe8evYNW9OKrHshZ3FKw8jf6QUBRHHATRxrdDSPW0YgiptmWQ5PM6qTKltTrQ1wobzpPPud2n1P4Lcjx+NM9JskriGlH1eT+abkSMuJTniVLNk+B68V8LYwiULcR+j28wcY6zmrQWvU7Ygm/7kcy4lL6gS80PNamV1VB5p3wwYJFtz4mvFzzEKrcU34prb3t0eUP4rd09Nk7NfC9drjbpl7uNwzceLQYQxdRpoUyZSH5H6bpc092xDNzTMzeRHSp9ibHhbOEt2UpzJxSJrdEfmmQU8HqlY/L0PReeyJ0nLCJ787mrADsr/R6MevbgqxicyZ8sV9A+tXw2sNJJ8PV2Py/5/nHzh8LCrURPW/34LbfPQrsu3gXXhWrG1SzWX/C+dR79lO666dpfMHaSiDjDQIgcuI1NJtOHCze6TbL8fxq3ERIv4uerI36Uit7+VFnTz/tu331rdy58q019POwmbJqIeW6V650M6HWeB/RbjeRaPWbik6CClzCjKAFp/H4UlaQj/R7/fwVXRNIPKtMf2Z9mWXoAfMwhXGTsi04kxDEK4pUtrcWMaxi00fGChzj5J9tKn2vF2DIyKwAdUiMl4fY8jUmoT1HrIMC4UAUGYK8T/vDER7cyGQ+RJ/DoKQdt8CjlMWmCmTNY7XEJqhh2dMOBQKH1pqGTNepeYegIHhWQ6bQWQUeBNge0P0ycd8OwyD6DGIdxhYqCoG1hOAfYBclosm4/Acsw4kPQm0OnGuwV6wKH2hBuf1n+eTzDM2eq1ci6Gdwl3AhDYHy0iah+LuI7xyNUdA6g1dlUcD5kh1pxzXNYmvAkNDCmmWNw8BycFdZCBFdy63Xx6STEKLFEY7h06w8jAZChQ/a5hLOc507Q5daqKd4hnnnJwKnuuB1cCgTQ3RLAKJGh7M532IHaHgZBsDLJyTqlaUcQIMCyQLTQJYOo1HMGA4kReQP0EAKRzLA9gkDOuSaHVn6Qva3TkNGRxCzuGPXy3BkNePLoEydNopezrOfiTlWpKJE3J50ZzoVnSZA7gzIlgpGYkoPjCvbGaoLDnzCHd8K4y15zQLosYIIoKOpzkREh4AdAFC4gdgcW43NnSlByI8thyhjfE/YFBgFzZRostJEjsL0o9cCzdK9RS4CMREK82I4Wvo68obE0UfVJDm5ii3rhRrgh4tWNowDEO2Q0HWp+WEICsIIBwCWborDxffIUaF9q+jy29Gg8huIE/XKNNXYYCxSLEEFBYBv4KoB0kIZJMCwRAZE6Zl8R0IV6GgIMEVwhS7JFVYFEBAYy0rC/y7BtO0FUQFVRYfcVCa9qmASlJDdckC0nPgdEl1Bmjm29AmlfUP34eP42YSDREHxkARNmUMXMwopQMwweZ8XevRQ6Z1I9+Ory8iyLMomZWh8hRvEU3wblyZGDuO0O2CAN04ApDgnKpO0psMeSZxNj8Ci5ECiCxSRYjGJCFKFCgccEnbLIwYxj2lyWKTcjrMFX6SBCSKHonW2wxbUEQILGx/dtMTYWtqguEga7iJqyQrhdKU9AhLMtzPBdK9Ka1LwF1kPKne7ATG2BhEDjOFnwEQTvPiDwP7FQED2MrBcYySMSbyGIBO3VPwS3SsLu8Nqp+4IKbkiEQkQapKHRkQHAy1ByoDsRAlrEzS3okyCT5rnbqnAGJO0KYFxWjZEIlggO4Emp2HtgDGAoiAKAICBBANOtF/odvIN5LYq++KWD8X0YaAvQ0O2NBCQA7w1tgmwagh3UXPUYuFpMFEjlfoL9BY8LPoJ24eK4XLMPS2EBgMj5C5tsMGCWRtN713JeTZnJQHvJ4IskAUh93GQqahuNiu/atQqysmbsl1RXgWRCsyGJMjuBcaA84Z0Lcft6iiJXxC559nSOmot9ofnCLsUPmgPmtINVE3whZZp2m72+Q9+lU5bz7CmfAmWoTR/EOumlutGVx68ApMDAhXjufaBf+Ppr84dYf4/jJmTdiPPTa93YP2t9g8xMzxZVfwmWnhfso09ZPcjHQ2UgSgoX/awVjOXuov8oFQic7sbcep7ksI/Yk0RHEuAUGwhv6p/HlgpqH4jZDPM9DSKpDfdlkUiAZz0rQMvMPXJMcA+r8nx39cyhukIeZ1mSCbRyAyo4shkHIpGeP0fObEzncVBgosWG/PUD1zWMh/fEH6/6l/yszfcwyPzMfvhZ3cvrJ3PZQ7zA83zIeYa+MtlA/NZUXKslBEgKjpAxIYyD6SRoIwGaaizaWYjMBi5cDRDNRA3NcoVeZq6oVVFzDDP3fPX7aBl911antIGp8YdEtJ4RFkysKD1stpJjk365P25JNzaG4iigN+cZAfTwPB1sDVnDmkJLhoAEIv08UK9+IedWbAV4HYG0oDQVm6gqDIIIAxsK0f9I7OYD+EHOOjTrPEw3bMaLAJW2HbDU655mLgohyO9u5w7WEPf+YGDr4ffsBlmYZBrG8UQlBY31eRCqXM9E2EMNQJwUogdb8nAZxLjg/UZAlEBxH3WKIQIYYwrhLkDFEOSlLuD/QMrQPLR/591Z0ZIaRKgbytjDbADdPMMRklfhRPbQkURYRAVgh5FEh2ApRJcJftC6wfIF3GWAPt4PI7xfwNZUB8kw6bk7tUCUNIQU3FBikkgUJlwxwYNJqMuoZphtShp0ouqGO+9hbQWS62cBENIXWq4AmZK7P6e0ljFmrdmgyGe48LvbCPDiYmm7QqxoWg0qI3TtqVXfPoum2hhaO3DlFy40R38UazCg8KMtfDFJBcRR1M3Hx+M0UGP+MP0w93ubPdBh/QYxbh2AcqQaWBY852FEsg5MJkGdap2oGABg4i2IpQQaaX5ksvLuPFH3+W3YHhhPhioZC0rFW+uBiDP2RmB4dkId9h60qjMylFyIVAYSswERqGRwBLIJUmOSYCFImwdh90SjGH1HXiro7SQ0yTw+u5iJmRVG5cUcxyY1GW1tbmFXKVG2SWtn1NT7j8gntdvDOhQbWxgvi1nkItQSeYbvMG6joOPSf8C5zPya4cX/FVULcMJvICC5dYXPkO7oEjnbMvccJTgFHYHyHScXjyIVajEf0+MofWQDsmkJOkW1d1JnBuGc+wIHf+x/DgaE09lcpYO4KokAQsYsBOvts0E9gSR6vErUmdHxHcIidPxBQLYjKKJ05Ob6ywsT8YnlkGwohswCZmaQkhoNCNFlMfbz9B8fWPGfWP6u6eP5ljKVWL3Q5mbMBvRlq2iLHV+ATX3RrWNaOl6EjBwO8k/gnLcRiyx+V1hyzGIlNhEI3l2JMvSSBCOmfRn37zSwycwR2jgZsWLl3Td4+ag2ZbnkzBAijHGPniFrxcjLPlto0udD9LlGU245OeS7OWTWp3yDmG1OQdDWDqkEmK2yP2pvvrdulhKsPlBGjG5KeOOhVxSC11na9+ZbUyaxiQwiBJLCLtoxFHHO/A096PBE9eY4xw2vLM9zpHBjSQoMc476cNBg8YFI4wbqcdbyKioOJfJtEtDq7OWREkYcnhzankOIbSZvBBgNtoy8NiOen1RYiHzXG/HeHZFFj4F4rZqCQ5QgvjazA7DtxE2xmEjxrHhxREAgMmKtsSp3UHvdXkaM2e05GatxdnqzPkKFa2fyzozfEOyy9NAd4RRJ5cWzXKYccdU5ApJgdbFI+owjHDtLxBNypNEKtCKbdxZmCC8DwFkwWSUJsO9EsgkgJpdy7z1vGZ520FuFMcPI06KJHTVEaum4xn5LJq3xqCDGQ7WlKE5tPn031rcuuQQjK6RyOamrKTTBKyUlcLiMZ3zzm0yo4ndcc73qqUIgd8ojBlEEXWpxi4Lj4blsqkCNOwhCfs78Stb7RpwejKvDkj0ohsqBqT4qtBFuCgpjeIWAWUXYtxEomKgeXFZDNQrd61h4EnP0izF+t3nntV1J59jRPde0aVsDYhMW4s5IEKLLwnVyeHfp6oYqgsCPNtljZBUzeIWzaAm8N+WTGAa2ZbzQOOobJD6xk7gmpLkMpp7nyQ7SdqNaMonfONa6WpN3dNM1yXS6klowsqUJkmZYTq0Yp/HBlRabAtPwKkS6lZOPCcL2DnHGeod7cdwRMP1D8sUQoTo0jGHZtCE1te5zOjDN6scjhsPBsC1QIR0ja6Z+UcwTO+ZpFioeUI+DcYR4YvMPmghakdiMJd6lZundybzE5mlfNRl5dcTcZoVUUWryjWqPNE6l3STf8ZyoEmTAhgQmZFuG5xTMlBqC4GKaoMIlGtyHAAuMVhIIbQoI7jMuSYhmDIEsDdLBuYgUCIIHJTQRB99Mw6GwqjcGcC2KDU59oWDC0R6YUSLVC4xTNh/zJtdImD+jEoLGAZFvcTbOQEXYaDWA5LiKfsiH+eMGKJBEUGJZt0/r6hmEEVISGgDjYcsmMO6NCBVa+1svOLsscu27RZWQ420oEYZTLExjGocYVA81QUF6Bx2S5J2YmJpFCOXW4iV5wlYF4GpA3Mk3XBhXEmk3w7TYorxPxpSZwzGcc1iQdbvK0hFxd5vsWjnIJ8sPz2FOWGyawVUv7zNmeWo06zrEP7wg50JWSJ+2I+80I6V/pOgzwdBohxYiX7Ha8S5ZuvKKEg674QM5M8gFE9/XkzRjrZnqvWFBMGlElBEklGFREsAqAF88eZ8J9w3gHCPzdhPsNb5U2yH0B/bpdah40Iazn4/OlBRxm4wKC5buoA0LzYVLmG8RdBxhfiCYvCbKuDSGxE7Q2dkQjfVhcwuDAnagsBGBJFCBWGxVwHUPmDFciJl4E7dJ9Pnw4491EDm6+RRRJaVKpTrVb4gRKrECYcvDoIUDlwUPbKEQc6Rnlcc2a86AMHG2gODAQxBWYKxeOSsVa6azSFiLrFelNHQEcCRurgAZEM6Uf3ZGzEuqdxDo2hIQdo2LPx+qphXhAgUyRk5jXwKCTNKE0r/EiKawU3s3tkvCvD2+nrhV7Jlvw6xN2ZzUoe1BZJOowIsQ47n9YDP7BIUK7OFrW2fAH1sqTOyY2MsJI1bhysU+i4cgt/m8Kd41Pxi1aHc0DaMDsxguG8kN9ZGteV43ziy4Um26rQonN5LuZts3Z8dume2jKzunzSIMZswQoSBtSGSKApERQA0JUJYHvRUYHEiFKwBYARYLJFYJFTxeirETYqBm1g2QsF2hq4eQCMJEYq4Zn7ycGEH2f2YGQEGQ8Y2bjZHZCZgjAoy94pR4Qsu/Czwsp8SSEFgu0C7h0U/v7y4huAA3xWOAXLAe7WcYMIeePDxU4vCF1P3R3AXeBAxP1Tzh+QK16u1+/8MNA+w0tk0B6yQJIlb6YUUNQrqQfEixcCyUJ1o//SIh/Qcu/ljbyec9QHtOiIZwAtcaYRpohYIxWlKwrYIVkGgTMsOsxukANCjBEqUYAVRCUQKWUBRLYUFjCRgxFUZEZba2Sw/LglKDGIomCRyyjDEsYU9W3yG2YuRFQt+kcfsDZ2hyjTu5CSBTZXpkAwiptIACWipCKpoMDFbKAdtdkqxn+qP6H8iMCwWxBM7MTRuLO2fmhvI93z0yJ1yIaEo0h9v5nvNYvQPXAhJGARXpX5QvH+m+F7LT6vg3p6kUGGmI2QWwDezu95A7i6MM6fC4Ukvjl8mGn0Js8JozU0N0esoxnQZZeVgxWaMMl7jABZkCJEYzY0aF1HSSiIwfoponueYzj+4bGKsRWRIuhOCbh1Z35RjyInNnJ8x5WUVL9FPo/BsWeMbmofzfJNmbMr+XeasG40hho5WsyQB7HbUEXoNRJMx086xh+97rGlGMDOZ1gjpPWOxvTSW8/am2N7yk7glvVTyWhvGs3lFzfBkB8PmPfPYdpPfiiZS/E1MtJO0YFFMLCsCejhJLIxASKpzojPpYfMah0BchswoblVCDiTEuRjtsIBReXXn8hUz0SQOUcBcgiMYqNayecbZxsPNEweMEGDxu0YhYFUIFjD1eWZkc5Ok2G9m6aiy7UMh5DAsYDotrsIU0DOl7ua1p2kDhAoaQgQIO22wKRHWYF85qgQIJFkgiCYqEN3UYTYz2dNy01q7J7hhjAZMKkC1hSSxhF8oNQUkIzTGxqLtHFRpAwii6lsGI6aQlmz4apXX2OBRbqUQEsRZR9WwP3GT4IFo5EonSQZFgGmVFFhS0QLWIDGEFCoUQESIi0FkJ7YIAWKxRz5zHOP+OCSMIhIfiNQGAGAzNpgRcajFbWKojJAibELxCtfqO0chy5pwmdS+Ye2Bfq66yZ6ejt81ze4tf35UHUmlkhBhIDGMRkWI3sNeY0gISGtNIQwCfOxkGCrWMHbwSBiHVnTDIuemJ/cmsoqU0dpdgnsDB+Px2AUD6AH6qVuILITKji0QfUcx2n4xvm+Ir+MDNEiRA7Tn5HN14HpuWFkQucT3azgkbnm38RPkc6bv6ZzZuHhVjt8VjyE+wzcyyyuV6b+kwpXhGoT172vBqNtzf7cTLSRWcVM/od0leGzI03MNBeKYnKmC4cHTiSh7zMQk47q7qJw46VvpEe1y6BYHHLCsUWFHZ4erVZpNkgt31007XZ3HHEpMSdYp6DvoNxwX4jYfd644YDS9i53030BpE94aiCHcB744gJIg+aAfwIIrhDSEQd3gDnmQYjaBIrw851BuwUE/rnp+GiAafX85+ejEvpNJtsh6WYPDCdUlpSDjlSthS2W0rKL79lMsUFFC27CHrLuiFlT8yVuiISAeaAJISBII+uD0pC8PEe1tESQczRIYSokSAnzeQ7TsB7BAcGqDFewohtMAmJxzfrKXmQzmADnEzRFoVdAe4w0Zuqx5jl2Uc1mg4d5a003Epnu2+V/jnGJ9yf8jPKhZa2nBFFZfWFjG8KGFoKe/vykFQ0BoYka3MCpM1EteXu7QXcav4pvxGLyYHNKg2jqQgZn6A1Z4sIkuQSEmxCOJFCQUkSCSHuJbg2NfhLQNInUFutT0CQow7z0yGx5Req9qVyM7cFZwnMwIgkVgsRIiqqJCSLGAyQIIEUiQYoRIAxOWr4kVP1J/Mg0PS+2w5i3UkMEA60A9ukgFIHWCGsQOaMWMBhIvspCiRBJIsgxJGSEGdYexO56xe8JS4ocw9QlL6PIHkIBTu7EKR3YuyUQIS4QJiBhB543vYoI3IhwZzI0mal/tE9nnzG4D+qVVEyziHMCn1EQ9JB2atm/eXTsUQ4Id208DZodgLoCjKgpM5nUZ+maRLh3HrhnzEIQA+f4cttHrkSL0Au084YGrm5evVcumBcosQJJFyMrzArA3Bi2U8QagsqvhY+qSLDkFA3AxkkDY0fZO+JQ9nXWRVET6ohyLyaDUJWFqyN4fOdchmaRRsMXCGsA/FmIoNGm244WTqjxhUI3y+FcqSJlB2uHJDydCPGOcy6s5XjQn1bMENRKJRN0DES/AQVBrfIvbMoLhMkUm+05t6XvuGork08zCxBUeFZDBnqcxCrgqNvBjbI2PX53PT1oj8VCidOF81k6wwS86dmtE7BLNCDhG120n3inNbGh+KdlD/ltAqBYhzzIECBse6zFjyDEXxg4cY63l/V0qwgEYEgRkkCDEgIQIh09Jj/Lqv7vD6cf5QML2s7nUBW82CmdZT4Nl3NN7MKkVHl73fTZNBmHjIaIwZbRKrLSrUmja+jW2BF4yoaot+qNk4TdTC7ZQiiwR0JKuipbWIokowilVLEijbCtWbpQeAoMmpTcRYl1kipRKFaWDUqWnLjc32oyYIs3AECkiBN4E2DD8RRBGRgFEebz5XNQ6UAeK6UAQm5AguEyDVIbIhCJthsCDbcDwHWYDhQKqcD5nMQYcGjHBdIm88xR3++vYXCBdKC0Gvs7cQzm8Fhs6gNF02XIqCgs6n3N18dXxITx2PElg6R53JEWRTzgw0jqhD0A3dUqAo0s6v1uRWeYL4sCiYVXuKGLS7n3vrDSLAo3cdfSUDgr0IarGwfO/X2XG8O9i0od5tTkqHIoDh93P75u1atGcuQstSN6QkNVTlcKJfDUJGIERSABEdXWoEWBoypFuIViqUI5K7RozcurrNhV4Vqh3F6JDtJnZ2gO1TSjDZdgg3N6dHYy7LH13vtvugsboBOm68cpWw1MpoGKjIpHbRjUQ6Hm1NKUQ6crCojSV6vIdmfQu/OYFg2l9YMJtFcDFqDN9VUCQKnUu37FSA2RDT9jEMUC4HbFsQeGDKl8nrOYscx0UE8dL8JgQ3pzPAiyJx6wvuEXvEsRLS1EKI2RWMgiUQUGkFAqsIpEYkgtRtGClbBAgnHmMlPdZr1c4cwCktB85WIDEMW5yYtmG51Hql1BGHb8qO88dRam26U66ToUnO8e+2Zl4mcObmTOiWXLCiGg1FBeFyR7jrLO+HfVGBeunod9kfBso80XkdBAdxkEcBYNkQ/siikgLQ4GODYFspzGJbHmO/h5pw9z0M7ahRpdXLqSew7KyVOaCFlXqnbrzbv3qAqFjnM9Bow4WUvwpvfyXy14ZFYMGDfc4wKElDgDKQWLA2jMR3pwGKtGWHsZCvdaRuaDX9bIXjcVMPcaSu8JAa4XMe+tGoASJb6xLNaKm0sNK6GMwJAaWmDVtCBCCGlYETY2xDRq0rG2zGQcbmGZoy8GGBmzNR4Bm0DRpDZOw2KTJE4wgA07kQEuGRhG9MxN6GgFFmDIYIBiojFYJiEowS5pzUURLNZgjWDpcvI8wbOzeATM4onvkeRcLEYhxFI2yC2BDCCjCmtqFGsyIE2dAH6z4Gh2G2bE8iqBZ2Jg0BJrulkuBCUwzZCvRhKIaZ0SAaSEhb4l9hraChMh2i2DkBgqQRAYsBERAIQbBi4hGt8/UP8UfIyGBDJBR5CASy46P37LkpeSkgqsRT1WUTzk5XxhOaQyL86egPa5bk9QhVniLcE7C4Wz4AYkiyAYwp0FIlGNI3YpdjcuN2IQhUY3RpYQLiKJwILGUNhCqShpQQzTo0oJmICkgi/kaKCkUFAWRSKCEBSDEkBMigEjENgOCU3IgSKwFRUWAIjOMyA6xheCICbmR0ARELRFkVQ0LmpAhL4nf5aCMsKmkTkkMfp1hX8iI7iiKhqLalCX10m3p2dmBwIR713aiRVk1MGMBgVqOrhSz0Tv8KPcNj3pZe4LoUEknaMEZABHsQ70OWXLKWY9+QVorLATNFtpHypqpJy2NDvE7Tp6HtYcrFPEpqRKgSK4lsYl7yhCiKlJ+/FQsrYCEBgosARASALAiMFgIwiwLRGShoaCsQQRpKFLCtBLJkQ9vWjC8auMUbQqIjEQGIgyG1O/weg9jRyHQMuewOSayG/aDCg8TKn3nT6ZRZ4sNveuJeVPvMBGaKXqdb7Zx+4NDgUENLEJht37jLi+6t95Z2ZIwWd0PJwUGG24Ox50B+0jFiMjqhoOdNTG7zX8c7ydF+kot5DYWHz4v7XFxNmcssNvP2MRDjJMipAsD8LzwZBG50fB6SgCmJISMogUpAuhnpV+cM6GQKc5pU4jkKP5f3ivq+k29ZGIAyAbVIMJIQhGBGCOk+5ubi6YB3kC+6VddQpYtQWCnwkSIe/NgWFfsiIeJbhBkUgxcXUVaC1QUjAqA1RQklBEQgVJ5HtFJoIk2BEcQTbBf2q5OrPZS1s7YASiLa9KWUHIDcYPpTZADE5xJwGBcNTE94+s5HSHTmMjYWbGsA58AHt2AaCLUTBxwTtALjmUTrhypQyJF/cGBjDMC1CHCKGkJgyMGYyppDNKArtSSiPNhRsO+rhCDg2J6OCL+nilObrJ0CiWJMw1p6QDAMAxCJQYOsykgyAHSoHUQUHaQRAoCIoX1QYbD0T1fhR5ZeTzFFJSpbIUNsUFpJyh2SbRAYQNnJANxxiD90UO+EIqWIgFQStxAYk86O32oGLgDceghEMYKEOd6zNz6z/wYxgVoHrgYPR1BIwIDnoyRekVeoHwDfuPUfsffuKSYRGHcfMVf8LVjTAUUINAD1H0+Vyk8dSqft4kDo9j4oXJ7mLFJK6joOkpjRA9lKUIuTago3+swqLGyZFvh9Xw+TMopLPXCF/bUzNbchEzSkaM9SGYqChGhkwQZCW0AkBpjKGkgIyaAy5oS4wMQaMRmKhZruYHR2EA6x5H6qeoELASB9YVxHD56T74iAxEOc9YCB6yhAhi5heRHj9zPBl4No98TPlvH8iSFE+XnWI15meETJmNHYbAiDQLMrBctzxpWu86Wue9rG6FBoQm2dCPMD1EAj0O9Q/sRKbnWodtgTmJmEkIlwN46Ns9/17iz0yTCNg/5hKG44hexfobb7CyodGEJuXErIyF9s1bATRUNnA5qSQLhBOW0RursTNifdCTADhmbGU3FUVIpBQEEIJEIskQSAoCxigQBFRiyCREASCkWIwRgutdB8OSd+Hynhpy+Cfu5g4o1MGP5ex4cilCiSEKNdFuF9zkTnKN4w27qDEl8MWJmML6MvwH7R7tZttE2P8Lj3ijDaf9KBJW7VDiSfVvNJtEoT3inRFBTsnJJxNkez01u162FeNnG8s5kHvhZ7FOj2OVpVuUjazTwiqT8NxMFYUcge4pwSAQ3gRYLQjX+RzcOB8hLCWQ4gwDMFNAwIRCiJYHDJI4162s6EBuC6Fi5qUgxDwNvOJnoeMBaD3ejXpDSI9eoX8Fp7VMJ2ukBIwWRT6KPdOujDtdt6ZI9hkftBQ7YqoMCDfL/UKhbMvmS3qlRPivRooR9rJc5rd0bXKd06x+4gQkCdC+goLjltpTaVqtISJoIzbtLVo8RdvahkHQLY5Hb2BIN2l/VIHzvG/sE0ENEdwQ1ID+QtaZZBNgkSIw2MsAxgMEsbosASQSVhRG0ixRxCyp1zJJd/aLgcfDgaMYoTCoRlhjCOMbW5QLdntijwkLhyMhTNrlW0y3SMlNFx1aYaQxBBgmRQG2OEG9BoxYshswoYSLQzQrwKYukhhGadOWUo4PcYRmuQohM+gjCHmR/GQFuK8tJw7K9HRRgdpv1ho2PALSTQ3wZ9kAqTIFOSUgRVFE+QNm/d6w70HUtLdJchJKhyBpyOVjj+YeZq0hVCuaZYUbicVPEmXrg2rQ08qRBB9HWp2U4QsPxOsOtTB4+l6bbIu/tkXYQNs3Esy1HtN24U2mpkTwHok6PnuoKfKjRQeVSo9xR1Zq6zoSj1ZBSEHwqkmeBrOJCciqDMGjf1+9cgHWzMk7AUDBAZDm7pV1ZoHYooODMgTsgSwIxmMXWHIIHxfVN1wz9KTUvrvPwL1mjo5ytNSCwQnu8HpuDQ7KN+PehVUFRDamIsY9x085g1310Mn2JU8U5u3vkm4EkBLzDiqbuijVDCFDTJzeWL6tWv38hhjgyEhBxN+21/keOxwbccXElrVUkOiW5z28735neB5mHQeB5AoPEop8IOnVEn3bNsgerLs4Y0FWCMksQHJRRvSL6EA9Yh+thO4/TkBoANB7IAkSRTYMlh39tQnAIhgpkgCgPmR2JZ+JoDKI6YRgIe1U+1huO3E647JO3pLWmd8yCfVt8wcjae8zc4j8Y5IcjiSyXCREVSRGGZREV1Mwr6HSMKtwwkkqQSkS4MBaFHVgCGCl29AVEoyRSSMGFtksBkgIkFkRWVJaDSLCRQkgosUCkljKFECwQEEoFiFkBIgIyAxgI09AdgQWKEiyKZzVH5QXYEH1BVUmJm4eq8+ZhGSBz51VhgwmASFIfT6DU+XSuxlvBD6Dz502h836U+viRwcnVVAe3dtk5X23ztKnlslvMeyHV6waHHMXC6C1B+jkwM7MaU6d5A8+t1gn327VhiPoPv8SjLNP6mwYbT81dDbvJDHyd8uUBf7pMMwYsC+Cobcs5PjXabQb4K4cca4FPaEOJXWgrDmW8ndEcSSVIFsccVDI3Y6IJCAWF0mO8Owa/LiOcjs6eHr9RR2nwVK2w/K0uqbUFcRJRLlZpf5D8hbOdV4t7uJdaeMydOmHfEzyOzloqcJxzFq8OmVODiU42sGJ8dO82o94mzJ104huSTYsieKSe5d6KhoJX3EO3vnqyWTFvrQswUsRFO6vFKtM6CrSFiMPSiqeLrE2Yci5ZJH4+2ILdzZgB80qdajcNG7xqg+/GKwjdtmKNbqriYrJndgbnTYbyHZzDg8xpa4qVWGgbA+L6959k3aLNkicBJogYD2muvMbjAnIOjKhInaFCGZQ5F3PUzohLEjxNiG5vCgQeHx1U3zYYxOWVCkwhOlHTpMYsXqGKjiYsfwcISFToclUvGPLVZ8g0m1CJhjMf/MPc2SSlqnDBDOO43qaMmLbpWkqTJJxNrI9Q08abG1wPOIMze08+3JYGMepJFx6edRRS408ijNRKWIWWUUp9CwYHGEIwtca8es+c+TCacQzHWECJ9RewpA8FrTusC39bDVDD0ffzmQacsnaTtn0QHTpUKNOBROR19wwnTrKS6JOSYaVNFKWCNxvwTRSZCw88xKUOBCioxjBVIb2xaEygMYxQDWiAKRFBawUZpLQFyUEYannHiILJw5qLl1OqezZw4Jdjl9p4lTIyDZLEhAUiHw6aFvpuxQsbGVVkH9XVEdtShtCo1BYMZGMmkLhCNDGSTCoUKzD1p5WYpWPUK3kIpCacpM1mamh2WihYaunZWUzEGq8qrVGrQjWSukcIpGY3AwGl55hSR4PLe++D5cK5Ds20KX7A3wJBAzxDRAL2iwIzRXR7KIdN3CXlSl1LCdb6/IKmlTuIyTg3lCTgwFH3JEh4KqIrFWPVW/IhXjl+RtTDmOWJl+DMRHYdEIHTBk14VDvDO0UGIIYZA8oSCTewPEvqgfbwmGR1TZoSq6r2hqaDxSBB2v3hrzGpwzNSKdUCxx8dHQcKxpowhSPfV5Yh2OY0oFt2oSbb2q7zZkcadK30GeCBiRVEBYsRUERFRHcVjmBgfGJhkKRZUpaFQIISIJEAUhBE9FhRh6IIIlUDQ0r3t1qF7gmmdjCJWES1B5vkKzcdJCixis1kpgtUREMtS0LCYWuDIREJmYOAALKiQ2iSk3GRAOGdO4ydkaItS9dj7Vnamkdievjg2PMTnBhucb0qDLyLMWG8SWuiZzFRVxUTjN4MlzEQwfXtgEKmrkeNLB8eKLN9iSnsT4wHXDHzqycdps89so4Fh2s2D6GvnpyDMbUDErQUS3SRo2Gcg0DnRCMAvQO2jwjvHYEbDh1YyjlqRXy2gWxTbRQRdScWAnzPckY3flDHVGOFmEQDoZ2QejsPJp3cd08zRqPQlHcSrDzdGo51Wb3gce0+NULSuH+Ss1inzNP84oJTN7INSeS3nBa19wFnLAyZkLu4o365ZWFsGcIk/GnQYa0mi23Q5T5MvhEVqHKc8DDkVguSARk0w5HGIzWr8WRKiZxyCGa0e9iMsYxxpPPGeOuMxhhGnnMjyYRQUzTENDtzDmnZxDQsiY4EF4d0WCDMoNQDuHMFafdK5tDOaOlqOIBq2GUw4UFN+Kumq90MkwjRzU5jxhgafNhyTbyTisNoQrMOThre39fijW7aHZ685Q0rIIkgG4kI0JNclyGzhTaHVFZNYzYgq4BQhtd9WQ4OCwJRghspwYThld9ygbw1Ug4ziI3ju71cw0aTSI+GQa4Hpopo0/U4nzivO7jIh8zHE1NFEJ6UipPOnH5w+LfDauSSLehCqYCS5kmMOxxkHZmwPZ7Lok2jZvCuRlxggp0bfqW5eKkcZka5TkzHBvk2GCRGKIw4MNqQ1qS4F4QUYhNCRlKGZgic5TRg1A5lodREA3BojpBuR77umWRZohubPM4yXReXXMVo2sVrWczlYxsZmxLCTMQyOCgcKAaQqjY0JpXQVQaIhchcbV6MZie8y2MoSz0PKNIdGMEjkGMVKqiaQlrz9u9tpoyGgVDUENWQYxFgzW+aMYkxLuCalsoYRBJsYTUMKaPBCj0BD3fR8Bg9gbhijO2zMMabGdnR24QTHeiJCMk0xSRZU86icRscADUgfe7Kc+4pLkBZFcg5FKLXhlR7weK7ULDBJbjEBdPoMgyHiQrLB2FLs7kSiGMaGJjMCkQwGLBZFZmYihoKFIaZbZdQQiZClDsDraHtTt4OXEK6qVFWlKJihWNDG7ZKBIdhyNmAqNHpDxNHU23/XoJEGMwEWgc2Jjo6R9bplNHFhlEmwSfUKPDQ/Bt2liE1gnIEYiJYRaKet87M1d5aMZnt2iGiR1E9tWTEv6BTVhMCGzAmF3PaAuEzEUHkNVppI4amzTOAhpGI/KKtKlQQaIdsUpDMiAObSJFA4P35grrwxCW1BIohHWsDbmgob5YyJB0vkuLia+ujF6ghj1Hk6goMFAoHDjZkgQgJ2BWCqHFhpzx683IknYUzWkmG8ALjQuAWo1coW0wgKZKiiY6kooJYbUIMGsCIpiFE8IsiiS85dd3nCPv69SFRlqmcmSUJxIX9ktlCJ0CkEMDNamwIDtAE6QiG+9Tn86YGQYx6prgk62SG4BOxVVXpEOIOAM/GWtIjCuz8Zz2MNjlfs08+S2wN8qqKsOohSiMOgSwN5AqHyyUHp6kYoosDByGg133uXrrjFcNpmazfITYCBcA20WB3aGxNes7yGpJywWbYyCggMIwD0LiVE/KQLwRNYERTfjQcBaDlw2vs+3r8OmmMFLzyeo9XrNprYE2Kee5rUKrDgGlgq92nEOZdqqkVk0rIEAjBstQMqwNGFqsXIdI7uPZrqTzN09WIwUlQJRTvEpV9AdmsDpDEW5uBoEDVFcgINBmBtkxBgVWSZhHD8okIRQcp2PIUHPcwHSnkBNwnKl6BDlxcp2EVymG0IiZxhnsUTYEksEgjGIiE2jRA1ax6iUN/9mxCKEiA39uYgMCWQwA9I+y4GpTSK5icQyB6ooRge8gLCDHYj+nLnCHqA0TqBkP8DsdxGSNLUKWkS0ImpgEQcDivevl9dg7O2mJ45QSDh6a8/juYHyXYZnIVLTVz83d3wQma7ih7pJadSBcgdAOBQ+NYWxReUFWh68e8LJQzphRtB4LEd3m83S9ROsi7oEhSoa6HAIQw1o26aukI9JkdgYkSGrTXCA7Rg9QcHs+l9LfV3SQ2Ri/5WXKszAKKQWEBQRMKRjeAb2BcIAREuy0gzvOc08+/7iCEJmFvProKni41LB0nz/ALD7RfqCA9R3hpsDmFBEifPDUicaar2tXKZQCwWgoGghz6C4ri/XuK7oaJvYd9gpHlI1TITZMI93vf2yCbENikY5xAOMIgcNJX5D2GvJcxGRZl8QsGOWNH1l0xYZDSZDYUaHSfAHJD0TzmRkHeZGAvSTYx9RjCEViODFUTEM0C6Gucbity/Z2v9Pf2qkkkun9dKUnRZg7kokXkm1XcUlo7awyoMOBFqmMX9pDC1EfZ8KMpzHeGk49felqAj3MhfJsXQ8tLFYAyQQFlghCpIUZ3MjFEiwgKBPgiggbnqPe0Ru4asNz2UKkHyX5x9BLffO/fne91l0femK0PnUFr84mvUhajb5PwO0Q2To6GhlnQpQ1v226QQIdMpewyJ7gyJilfLY2pbNabZ1tNl3NKwmgohRjds3kXQFBmSLuIHhZE7nbMEE26RTfi5oaAyUDQZGnERLBzgYkV0d/ko7uw+W56IvKBtMFvrrNkoT/h+dmrB+P4BZmfB/uFRFiAmvELwHGCUjsEfP4ntTHFH8Nh38p+Np9R+bxb1l1x4eX/EpVs4MUfxLT+2vovyYscNRqpl/+cf9dXp/nP/4u5IpwoSFcFilwA')))
\ No newline at end of file
diff --git a/examples/02105/instructor/week2/unitgrade_data/Stones.pkl b/examples/02105/instructor/week2/unitgrade_data/Stones.pkl
index 070b083e581b9052718352ac872d777848661905..1bf38a4fd917fe69b27254e950aac0678e0a28ed 100644
Binary files a/examples/02105/instructor/week2/unitgrade_data/Stones.pkl and b/examples/02105/instructor/week2/unitgrade_data/Stones.pkl differ
diff --git a/examples/02105/students/week2/unitgrade_data/Stones.pkl b/examples/02105/students/week2/unitgrade_data/Stones.pkl
index 070b083e581b9052718352ac872d777848661905..1bf38a4fd917fe69b27254e950aac0678e0a28ed 100644
Binary files a/examples/02105/students/week2/unitgrade_data/Stones.pkl and b/examples/02105/students/week2/unitgrade_data/Stones.pkl differ
diff --git a/examples/02631/instructor/week5/Report1Flat_handin_40_of_40.token b/examples/02631/instructor/week5/Report1Flat_handin_40_of_40.token
new file mode 100644
index 0000000000000000000000000000000000000000..2ea703ab9cb00105b3bf3d8f79befcc923868252
--- /dev/null
+++ b/examples/02631/instructor/week5/Report1Flat_handin_40_of_40.token
@@ -0,0 +1,202 @@
+# 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/02631/instructor/week5/__pycache__/report1intro.cpython-38.pyc b/examples/02631/instructor/week5/__pycache__/report1intro.cpython-38.pyc
deleted file mode 100644
index ba16d7002f51dee562fcff1bb147d4600de3fb07..0000000000000000000000000000000000000000
Binary files a/examples/02631/instructor/week5/__pycache__/report1intro.cpython-38.pyc and /dev/null differ
diff --git a/examples/02631/instructor/week5/deploy.py b/examples/02631/instructor/week5/deploy.py
index 3457b7fd1275185e0c91b0d3b78182db7b768f0d..e6759e5b9e985639cfd394b7f4cff9415fd33dfa 100644
--- a/examples/02631/instructor/week5/deploy.py
+++ b/examples/02631/instructor/week5/deploy.py
@@ -1,4 +1,4 @@
-from report1intro import Report1Flat
+from looping_tests import Report1Flat
 from unitgrade_private.hidden_create_files import setup_grade_file_report
 from snipper import snip_dir
 
diff --git a/examples/02631/instructor/week5/report1intro.py b/examples/02631/instructor/week5/looping_tests.py
similarity index 100%
rename from examples/02631/instructor/week5/report1intro.py
rename to examples/02631/instructor/week5/looping_tests.py
diff --git a/examples/02631/instructor/week5/looping_tests_grade.py b/examples/02631/instructor/week5/looping_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e88d8efa8f18f1bb256bda6ab57e41f2702665e
--- /dev/null
+++ b/examples/02631/instructor/week5/looping_tests_grade.py
@@ -0,0 +1,4 @@
+# looping_tests.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/02631/instructor/week5/report1intro_grade.py b/examples/02631/instructor/week5/report1intro_grade.py
deleted file mode 100644
index 335212aa926b93e9c43ae8dbbeb52007d296cab4..0000000000000000000000000000000000000000
--- a/examples/02631/instructor/week5/report1intro_grade.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# report1intro.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/02631/instructor/week5/unitgrade_data/Bacteria.pkl b/examples/02631/instructor/week5/unitgrade_data/Bacteria.pkl
index 703d7a9b626c810bf555748f8a5de1c5886575c6..5fd7927c81b07caaef98db8a9e8111b12d62019b 100644
Binary files a/examples/02631/instructor/week5/unitgrade_data/Bacteria.pkl and b/examples/02631/instructor/week5/unitgrade_data/Bacteria.pkl differ
diff --git a/examples/02631/instructor/week5/unitgrade_data/ClusterAnalysis.pkl b/examples/02631/instructor/week5/unitgrade_data/ClusterAnalysis.pkl
index 9069a502a63c321f995ded8c9a84212b92cdeb5d..2f11291cbbf7032f654afea9023684431328a1ce 100644
Binary files a/examples/02631/instructor/week5/unitgrade_data/ClusterAnalysis.pkl and b/examples/02631/instructor/week5/unitgrade_data/ClusterAnalysis.pkl differ
diff --git a/examples/02631/instructor/week5/unitgrade_data/FermentationRate.pkl b/examples/02631/instructor/week5/unitgrade_data/FermentationRate.pkl
index 3d0646ebc545b5e45a3adf481ab44ff0231b59bf..0174a699f6daaebd098ec177240e48b8c3293a44 100644
Binary files a/examples/02631/instructor/week5/unitgrade_data/FermentationRate.pkl and b/examples/02631/instructor/week5/unitgrade_data/FermentationRate.pkl differ
diff --git a/examples/02631/instructor/week5/unitgrade_data/RemoveIncomplete.pkl b/examples/02631/instructor/week5/unitgrade_data/RemoveIncomplete.pkl
index 3e0852344f326a5cd96be0db968882489bc67637..c6aef837cef8ea1f347292519cc37296cb025d45 100644
Binary files a/examples/02631/instructor/week5/unitgrade_data/RemoveIncomplete.pkl and b/examples/02631/instructor/week5/unitgrade_data/RemoveIncomplete.pkl differ
diff --git a/examples/02631/students/week5/report1intro.py b/examples/02631/students/week5/looping_tests.py
similarity index 100%
rename from examples/02631/students/week5/report1intro.py
rename to examples/02631/students/week5/looping_tests.py
diff --git a/examples/02631/students/week5/unitgrade_data/Bacteria.pkl b/examples/02631/students/week5/unitgrade_data/Bacteria.pkl
index 703d7a9b626c810bf555748f8a5de1c5886575c6..5fd7927c81b07caaef98db8a9e8111b12d62019b 100644
Binary files a/examples/02631/students/week5/unitgrade_data/Bacteria.pkl and b/examples/02631/students/week5/unitgrade_data/Bacteria.pkl differ
diff --git a/examples/02631/students/week5/unitgrade_data/ClusterAnalysis.pkl b/examples/02631/students/week5/unitgrade_data/ClusterAnalysis.pkl
index 9069a502a63c321f995ded8c9a84212b92cdeb5d..2f11291cbbf7032f654afea9023684431328a1ce 100644
Binary files a/examples/02631/students/week5/unitgrade_data/ClusterAnalysis.pkl and b/examples/02631/students/week5/unitgrade_data/ClusterAnalysis.pkl differ
diff --git a/examples/02631/students/week5/unitgrade_data/FermentationRate.pkl b/examples/02631/students/week5/unitgrade_data/FermentationRate.pkl
index 3d0646ebc545b5e45a3adf481ab44ff0231b59bf..0174a699f6daaebd098ec177240e48b8c3293a44 100644
Binary files a/examples/02631/students/week5/unitgrade_data/FermentationRate.pkl and b/examples/02631/students/week5/unitgrade_data/FermentationRate.pkl differ
diff --git a/examples/02631/students/week5/unitgrade_data/RemoveIncomplete.pkl b/examples/02631/students/week5/unitgrade_data/RemoveIncomplete.pkl
index 3e0852344f326a5cd96be0db968882489bc67637..c6aef837cef8ea1f347292519cc37296cb025d45 100644
Binary files a/examples/02631/students/week5/unitgrade_data/RemoveIncomplete.pkl and b/examples/02631/students/week5/unitgrade_data/RemoveIncomplete.pkl differ
diff --git a/examples/example_autolab_deploy/autolab_courses.py b/examples/example_autolab_deploy/autolab_courses.py
index b73df36951980c5b4445bc74d4361409d8a1b3c7..b24fc83e5085a7385a68ec957500e8ce59122424 100644
--- a/examples/example_autolab_deploy/autolab_courses.py
+++ b/examples/example_autolab_deploy/autolab_courses.py
@@ -5,7 +5,7 @@ from unitgrade_private.docker_helpers import compile_docker_image
 if __name__ == "__main__":
     ## Step 1. Deploy the report file.
     # from report2_test import Report2
-    from report1intro import Report1Flat
+    from looping_tests import Report1Flat
     from stones_tests import StoneReport
     from unitgrade_private.hidden_create_files import setup_grade_file_report
     from snipper.snip_dir import snip_dir
@@ -26,12 +26,12 @@ if __name__ == "__main__":
 
     # Step 2: Create the cs102.tar file from the grade scripts. #!s=b
     instructor_base = f"../02105/instructor/week2"
-    student_base = "../02631/instructor/week5"
+    student_base = "../02105/students/week2"
 
-    from report2_test import Report2
     # INSTRUCTOR_GRADE_FILE =
-    description = """ Hand in the file 'stones.py'. You can find the full example, including solution, here <a href="https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/tree/master/examples/02631/instructor/week5">here</a>"""
-    output_tar = new_deploy_assignment("02105week2",  # Autolab name of assignment (and name of .tar file)
+    description = """ Hand in the file stones.py. You can find the full example, including solution, at https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/tree/master/examples/02105/instructor/week2 """
+    # description = "This is the stones-problem"
+    output_tar = new_deploy_assignment("c02105week2",  # Autolab name of assignment (and name of .tar file)
                                    INSTRUCTOR_BASE=instructor_base,
                                    INSTRUCTOR_GRADE_FILE=f"{instructor_base}/stones_tests_grade.py",
                                    STUDENT_BASE=student_base,
@@ -39,6 +39,19 @@ if __name__ == "__main__":
                                    homework_file="stones.py",
                                    description=description)
 
+    instructor_base = f"../02631/instructor/week5"
+    student_base = "../02631/students/week5"
+
+    # INSTRUCTOR_GRADE_FILE =
+    description = """ Hand in the file stones.py. You can find the full example, including solution, at https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/tree/master/examples/02631/instructor/week5 """
+    # description = "This is the stones-problem"
+    output_tar = new_deploy_assignment("c02631week5",  # Autolab name of assignment (and name of .tar file)
+                                       INSTRUCTOR_BASE=instructor_base,
+                                       INSTRUCTOR_GRADE_FILE=f"{instructor_base}/looping_tests_grade.py",
+                                       STUDENT_BASE=student_base,
+                                       autograde_image_tag=autograde_image,
+                                       homework_file="looping.py",
+                                       description=description)
 
     # STUDENT_GRADE_FILE=f"{instructor_base}/stones_tests_grade.py",
     # What can you do? Get a report class from the .token file?
diff --git a/examples/example_autolab_deploy/c02105week2.tar b/examples/example_autolab_deploy/c02105week2.tar
new file mode 100644
index 0000000000000000000000000000000000000000..02fa3fc1ff05b8c693fa3b91cda74eebec442a60
Binary files /dev/null and b/examples/example_autolab_deploy/c02105week2.tar differ
diff --git a/examples/example_autolab_deploy/c02631week5.tar b/examples/example_autolab_deploy/c02631week5.tar
new file mode 100644
index 0000000000000000000000000000000000000000..e8d5aef89dd8107bd1609ab7f798273e1310e9e5
Binary files /dev/null and b/examples/example_autolab_deploy/c02631week5.tar differ
diff --git a/examples/tmp/02105week2/02105week2-autograde/StoneReport_handin.token b/examples/tmp/02105week2/02105week2-autograde/StoneReport_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..37becd782259655b9e8516a08abe63ab3d3f2183
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/StoneReport_handin.token
@@ -0,0 +1,179 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+af74d9e2eea101854f07fd64951aafb1fbd062916c869b330e535271178c5ce49be3fc7eda177a383e7971a004abf73b787b543843a89e0b7959c0081a44e87a 31368
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/tmp/02105week2/02105week2-autograde/StoneReport_handin_10_of_10.token b/examples/tmp/02105week2/02105week2-autograde/StoneReport_handin_10_of_10.token
new file mode 100644
index 0000000000000000000000000000000000000000..37becd782259655b9e8516a08abe63ab3d3f2183
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/StoneReport_handin_10_of_10.token
@@ -0,0 +1,179 @@
+# 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/tmp/02105week2/02105week2-autograde/autograde-Makefile b/examples/tmp/02105week2/02105week2-autograde/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..688d7b8965001447eff8999d9a880613d13f87cb
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp stones.py 02105week2-handout
+	(cd 02105week2-handout; python3 driver_python.py)
+
+clean:
+	rm -rf *~ 02105week2-handout
\ No newline at end of file
diff --git a/examples/tmp/02105week2/02105week2-autograde/deploy.py b/examples/tmp/02105week2/02105week2-autograde/deploy.py
new file mode 100644
index 0000000000000000000000000000000000000000..a59af502aada3549c16dedd0d03a11f8b215c3cf
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/deploy.py
@@ -0,0 +1,9 @@
+from stones_tests import StoneReport
+from unitgrade_private.hidden_create_files import setup_grade_file_report
+from snipper import snip_dir
+
+if __name__ == "__main__":
+    setup_grade_file_report(StoneReport, minify=False, obfuscate=False, execute=False, with_coverage=True)
+
+    # Deploy the files using snipper: https://gitlab.compute.dtu.dk/tuhe/snipper
+    snip_dir(source_dir="", dest_dir="../../students/week2", exclude=['*.token', 'deploy.py'])
diff --git a/examples/tmp/02105week2/02105week2-autograde/driver_python.py b/examples/tmp/02105week2/02105week2-autograde/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..4375e8e376e0cf02b727b6bf9138ebcde6dd42fb
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/driver_python.py
@@ -0,0 +1,92 @@
+import os
+import glob
+import shutil
+import sys
+import subprocess
+from unitgrade_private.autolab.autolab import format_autolab_json
+from unitgrade_private.docker_helpers import student_token_file_runner
+from unitgrade_private import load_token
+import time
+import unitgrade_private
+
+verbose = False
+tag = "[driver_python.py]"
+
+if not verbose:
+    print("="*10)
+    print(tag, "Starting unitgrade evaluation...")
+import unitgrade
+print(tag, "Unitgrade version", unitgrade.version.__version__)
+print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
+
+
+sys.stderr = sys.stdout
+wdir = os.getcwd()
+
+def pfiles():
+    print("> Files in dir:")
+    for f in glob.glob(wdir + "/*"):
+        print(f)
+    print("---")
+
+handin_filename = "stones.py"
+student_token_file = 'StoneReport_handin.token'
+instructor_grade_script = 'stones_tests_grade.py'
+grade_file_relative_destination = "stones_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "stones.py"
+# homework_file = "stones.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/02105week2/02105week2-autograde/stones.py b/examples/tmp/02105week2/02105week2-autograde/stones.py
new file mode 100644
index 0000000000000000000000000000000000000000..96c9cf5eaeba7da59ecc9db55ada75b06cd093b0
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/stones.py
@@ -0,0 +1,15 @@
+def maximum_stones(W, stone_weights):
+    stone_weights.sort()
+    T = 0
+    s = 0
+    for k, we in enumerate(stone_weights):
+        T += we
+        if T <= W:
+            s = s + 1
+        else:
+            break
+    return s
+
+if __name__ == "__main__":
+    print("The following call using maximum weight of W=15 should return 5.")
+    print(maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7]))
diff --git a/examples/tmp/02105week2/02105week2-autograde/stones_tests.py b/examples/tmp/02105week2/02105week2-autograde/stones_tests.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f61cfd3822b0d2f526c318e6b380e8d0c5d6ef1
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/stones_tests.py
@@ -0,0 +1,44 @@
+from unitgrade.framework import Report, UTestCase
+from unitgrade.evaluate import evaluate_report_student
+import stones
+from stones import maximum_stones
+
+# A fancy helper function to generate nicer-looking titles.
+def trlist(x):
+    s = str(list(x))
+    if len(s) > 30:
+        s = s[:30] + "...]"
+    return s
+
+
+class Stones(UTestCase):
+    """ Test of the Stones function """
+    def stest(self, W, stone_weights): # Helper function.
+        N = maximum_stones(W, stone_weights)
+        self.title = f"stones({W}, {trlist(stone_weights)}) = {N} ?"
+        self.assertEqualC(N)
+
+    def test_basecase(self):
+        """ Test the stones-example given in the homework """
+        N = maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7])
+        self.assertEqual(N, 5) # Test that we can collect 5 stones.
+
+    def test_stones1(self):
+        self.stest(4, [4]) # One stone weighing 4 kg.
+
+    def test_stones2(self):
+        self.stest(4, [1, 4]) # should also give 1
+
+    def test_stones3(self):
+        self.stest(4, [4, 1]) # should also give 1
+
+    def test_stones4(self):
+        self.stest(13, [2, 5, 3, 1, 8, 4, 5, 7])
+
+class StoneReport(Report):
+    title = "02105 week 2: Stone collection"
+    questions = [(Stones, 10),]
+    pack_imports = [stones]
+
+if __name__ == "__main__":
+    evaluate_report_student(StoneReport())
diff --git a/examples/tmp/02105week2/02105week2-autograde/stones_tests_grade.py b/examples/tmp/02105week2/02105week2-autograde/stones_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..d8065998b6dd1a1400ae7910febf59d4c6330f40
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-autograde/stones_tests_grade.py
@@ -0,0 +1,4 @@
+# stones_tests.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/tmp/02105week2/02105week2-autograde/unitgrade_data/Stones.pkl b/examples/tmp/02105week2/02105week2-autograde/unitgrade_data/Stones.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..125aa648ecdcca1ead793e5533eb67870d27f11d
Binary files /dev/null and b/examples/tmp/02105week2/02105week2-autograde/unitgrade_data/Stones.pkl differ
diff --git a/examples/tmp/02105week2/02105week2-handout.zip b/examples/tmp/02105week2/02105week2-handout.zip
new file mode 100644
index 0000000000000000000000000000000000000000..6ab227e83a06450246d3f3fca59413b7729fe7ad
Binary files /dev/null and b/examples/tmp/02105week2/02105week2-handout.zip differ
diff --git a/examples/tmp/02105week2/02105week2-handout/StoneReport_handin_10_of_10.token b/examples/tmp/02105week2/02105week2-handout/StoneReport_handin_10_of_10.token
new file mode 100644
index 0000000000000000000000000000000000000000..37becd782259655b9e8516a08abe63ab3d3f2183
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-handout/StoneReport_handin_10_of_10.token
@@ -0,0 +1,179 @@
+# 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/tmp/02105week2/02105week2-handout/deploy.py b/examples/tmp/02105week2/02105week2-handout/deploy.py
new file mode 100644
index 0000000000000000000000000000000000000000..a59af502aada3549c16dedd0d03a11f8b215c3cf
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-handout/deploy.py
@@ -0,0 +1,9 @@
+from stones_tests import StoneReport
+from unitgrade_private.hidden_create_files import setup_grade_file_report
+from snipper import snip_dir
+
+if __name__ == "__main__":
+    setup_grade_file_report(StoneReport, minify=False, obfuscate=False, execute=False, with_coverage=True)
+
+    # Deploy the files using snipper: https://gitlab.compute.dtu.dk/tuhe/snipper
+    snip_dir(source_dir="", dest_dir="../../students/week2", exclude=['*.token', 'deploy.py'])
diff --git a/examples/tmp/02105week2/02105week2-handout/stones.py b/examples/tmp/02105week2/02105week2-handout/stones.py
new file mode 100644
index 0000000000000000000000000000000000000000..96c9cf5eaeba7da59ecc9db55ada75b06cd093b0
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-handout/stones.py
@@ -0,0 +1,15 @@
+def maximum_stones(W, stone_weights):
+    stone_weights.sort()
+    T = 0
+    s = 0
+    for k, we in enumerate(stone_weights):
+        T += we
+        if T <= W:
+            s = s + 1
+        else:
+            break
+    return s
+
+if __name__ == "__main__":
+    print("The following call using maximum weight of W=15 should return 5.")
+    print(maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7]))
diff --git a/examples/tmp/02105week2/02105week2-handout/stones_tests.py b/examples/tmp/02105week2/02105week2-handout/stones_tests.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f61cfd3822b0d2f526c318e6b380e8d0c5d6ef1
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-handout/stones_tests.py
@@ -0,0 +1,44 @@
+from unitgrade.framework import Report, UTestCase
+from unitgrade.evaluate import evaluate_report_student
+import stones
+from stones import maximum_stones
+
+# A fancy helper function to generate nicer-looking titles.
+def trlist(x):
+    s = str(list(x))
+    if len(s) > 30:
+        s = s[:30] + "...]"
+    return s
+
+
+class Stones(UTestCase):
+    """ Test of the Stones function """
+    def stest(self, W, stone_weights): # Helper function.
+        N = maximum_stones(W, stone_weights)
+        self.title = f"stones({W}, {trlist(stone_weights)}) = {N} ?"
+        self.assertEqualC(N)
+
+    def test_basecase(self):
+        """ Test the stones-example given in the homework """
+        N = maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7])
+        self.assertEqual(N, 5) # Test that we can collect 5 stones.
+
+    def test_stones1(self):
+        self.stest(4, [4]) # One stone weighing 4 kg.
+
+    def test_stones2(self):
+        self.stest(4, [1, 4]) # should also give 1
+
+    def test_stones3(self):
+        self.stest(4, [4, 1]) # should also give 1
+
+    def test_stones4(self):
+        self.stest(13, [2, 5, 3, 1, 8, 4, 5, 7])
+
+class StoneReport(Report):
+    title = "02105 week 2: Stone collection"
+    questions = [(Stones, 10),]
+    pack_imports = [stones]
+
+if __name__ == "__main__":
+    evaluate_report_student(StoneReport())
diff --git a/examples/tmp/02105week2/02105week2-handout/stones_tests_grade.py b/examples/tmp/02105week2/02105week2-handout/stones_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..d8065998b6dd1a1400ae7910febf59d4c6330f40
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2-handout/stones_tests_grade.py
@@ -0,0 +1,4 @@
+# stones_tests.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/tmp/02105week2/02105week2-handout/unitgrade_data/Stones.pkl b/examples/tmp/02105week2/02105week2-handout/unitgrade_data/Stones.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..125aa648ecdcca1ead793e5533eb67870d27f11d
Binary files /dev/null and b/examples/tmp/02105week2/02105week2-handout/unitgrade_data/Stones.pkl differ
diff --git a/examples/tmp/02105week2/02105week2.rb b/examples/tmp/02105week2/02105week2.rb
new file mode 100644
index 0000000000000000000000000000000000000000..860cca7ae1696f9f33544c9104de6c66b4cff9e8
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2.rb
@@ -0,0 +1,11 @@
+require "AssessmentBase.rb"
+
+module 02105week2
+  include AssessmentBase
+
+  def assessmentInitialize(course)
+    super("02105week2",course)
+    @problems = []
+  end
+
+end
\ No newline at end of file
diff --git a/examples/tmp/02105week2/02105week2.yml b/examples/tmp/02105week2/02105week2.yml
new file mode 100644
index 0000000000000000000000000000000000000000..0b65d2aef2370d8b7385aa5192ff811327518460
--- /dev/null
+++ b/examples/tmp/02105week2/02105week2.yml
@@ -0,0 +1,38 @@
+---
+
+general:
+  name: 02105week2
+  description: 'This is the stones-problem'
+  display_name: '02105 week 2: Stone collection'
+  handin_filename: stones.py
+  handin_directory: handin
+  max_grace_days: 0
+  handout: 02105week2-handout.zip
+  writeup: writeup/writeup.html
+  max_submissions: -1
+  disable_handins: false
+  max_size: 2
+  has_svn: false
+  category_name: Lab
+problems:
+
+  - name: Unitgrade score
+    description: 'Score obtained by automatic grading'
+    max_score: 10
+    optional: false
+
+  - name: Written feedback
+    description: 'Written (TA) feedback'
+    max_score: 0
+    optional: true
+
+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/tmp/02105week2/Makefile b/examples/tmp/02105week2/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..5d8022ac0430b53c43badb1055cbbff5d00148d0
--- /dev/null
+++ b/examples/tmp/02105week2/Makefile
@@ -0,0 +1,55 @@
+#
+# 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 02105week2-handout; mkdir 02105week2-handout)
+	cp -p src/Makefile-handout 02105week2-handout/Makefile
+	cp -p src/README-handout 02105week2-handout/README
+	cp -p src/driver_python.py 02105week2-handout
+
+	cp -p src/student_sources.zip 02105week2-handout
+
+	cp -p src/stones.py 02105week2-handout
+
+	cp -p src/docker_helpers.py 02105week2-handout
+
+	cp -p src/stones_tests_grade.py 02105week2-handout
+
+	cp -p src/StoneReport_handin.token 02105week2-handout
+
+
+handout-tarfile: handout
+	# Build *-handout.tar and autograde.tar
+	# tar cvf 02105week2-handout.tar 02105week2-handout
+	# cp -p 02105week2-handout.tar autograde.tar
+	tar cvf 02105week2-handout.tar autograde.tar
+	# cp -p 02105week2-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 02105week2-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/tmp/02105week2/autograde-Makefile b/examples/tmp/02105week2/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..e8498f170fbf69a5102df356074d23df518a39f1
--- /dev/null
+++ b/examples/tmp/02105week2/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp stones.py 02105week2-autograde
+	(cd 02105week2-autograde; python3 driver_python.py)
+
+clean:
+	rm -rf *~ 02105week2-autograde
\ No newline at end of file
diff --git a/examples/tmp/02105week2/autograde.tar b/examples/tmp/02105week2/autograde.tar
new file mode 100644
index 0000000000000000000000000000000000000000..225f8fbfba0a1844805a06e9db0301b68616f71c
Binary files /dev/null and b/examples/tmp/02105week2/autograde.tar differ
diff --git a/examples/tmp/02105week2/src/Makefile b/examples/tmp/02105week2/src/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/tmp/02105week2/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/tmp/02105week2/src/Makefile-handout b/examples/tmp/02105week2/src/Makefile-handout
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/tmp/02105week2/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/tmp/02105week2/src/README b/examples/tmp/02105week2/src/README
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/tmp/02105week2/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/tmp/02105week2/src/README-handout b/examples/tmp/02105week2/src/README-handout
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/tmp/02105week2/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/tmp/02105week2/src/StoneReport_handin.token b/examples/tmp/02105week2/src/StoneReport_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..37becd782259655b9e8516a08abe63ab3d3f2183
--- /dev/null
+++ b/examples/tmp/02105week2/src/StoneReport_handin.token
@@ -0,0 +1,179 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+af74d9e2eea101854f07fd64951aafb1fbd062916c869b330e535271178c5ce49be3fc7eda177a383e7971a004abf73b787b543843a89e0b7959c0081a44e87a 31368
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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+XQkvmSitbJOzOX4u18v9GpqvC8Grq1YmN2Ll0RbM/jZRHfUhZmUK9Hh9G62UbgcFOEaBcmo74na9d7P2S5Y+mEdUR5s+k8/FSl6isiVmbgHiUoye15WszVj6cXPYUyRAZLY8/TU72rbtE4mgEyetr2oYQNV9xPb4Cii5GUW7AIhXzNPLYOwZ
+9ul0mpUV3FiTQAgDsODQARPz6lUCEyYTQcPgBBZTubkMQNCDfnXkQENMUj0T/BFJ2FjhOuhrNwlNaY/G5rbjSwxRrschZ36iD322U/UwDU0xR6RbslLrRHoMf7Se9kKcGfviDw4PHCvRTZu5to0XWIGfhNa+baQ+3DA4nZChiQKdJlu08tEP
+d0d8cH6tNWGs/mq+U7qnm13rz2lndZWtcLMYy/9wPMgQmzCVft1g3MuTVz31uMWNHyeAERuJug+vl1olTJzWc/qVgq4/azEBhpyc86x8Tgucn0Y8bubdztgoIA+hB5+CiRWLibVQZfTC5c3n4aBzZH10AiIdjNlR2VjyYE96eTCsANJ4yxSa
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+1cN94iDDNwJfXouKqV/jo1Cifx4AAco6N8P05R6hrna4WlP0Av3Xlr4LjQ6F2LRZv6lGoW9RNeFLm4tAyDjTNGNP+YY8oo3lAWpMBLilOAekRVTqrHg3yEZsNe7ztiTjz+H9xtouJRP3fg6S11Yhhr2ex/cdNo+mY+eZItCI/Ddf5axyM1Tg
+bAACKczjXvRrrVgABwLcB2osCQumBfrHEZ/sCAAAAAARZWg==.
\ No newline at end of file
diff --git a/examples/tmp/02105week2/src/docker_helpers.py b/examples/tmp/02105week2/src/docker_helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..0b82a931c0268a356ee54f777fbc7ed0ef095e3f
--- /dev/null
+++ b/examples/tmp/02105week2/src/docker_helpers.py
@@ -0,0 +1,198 @@
+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)
+    cmd = f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} ."
+    os.system(cmd)
+    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):$(id -g)" '
+    else:
+        user_cmd = ''
+
+    if xvfb:
+        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
+
+    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
+    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
+    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
+    fcom = f"{cdcom}  && {dcom}"
+    print("> Running docker command")
+    print(fcom)
+    init = time.time() - start
+    # thtools.execute_command(fcom.split())
+    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
+    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
+    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
+    for t in tokens:
+        print("Source image produced token", t)
+    elapsed = time.time() - start
+    print("Elapsed time is", elapsed, f"({init=} seconds)")
+    if len(tokens) != 1:
+        print("Wrong number of tokens produced:", len(tokens))
+        print(out)
+    return tokens[0]
diff --git a/examples/tmp/02105week2/src/driver.sh b/examples/tmp/02105week2/src/driver.sh
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/tmp/02105week2/src/driver.sh
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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 ${status}"
+#    echo "{\"scores\": {\"Correctness\": 0}}"
+#fi
+
+exit
diff --git a/examples/tmp/02105week2/src/driver.sh-handout b/examples/tmp/02105week2/src/driver.sh-handout
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/tmp/02105week2/src/driver.sh-handout
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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/tmp/02105week2/src/driver_python.py b/examples/tmp/02105week2/src/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..4375e8e376e0cf02b727b6bf9138ebcde6dd42fb
--- /dev/null
+++ b/examples/tmp/02105week2/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 = "stones.py"
+student_token_file = 'StoneReport_handin.token'
+instructor_grade_script = 'stones_tests_grade.py'
+grade_file_relative_destination = "stones_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "stones.py"
+# homework_file = "stones.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/02105week2/src/driver_python.py-handout b/examples/tmp/02105week2/src/driver_python.py-handout
new file mode 100644
index 0000000000000000000000000000000000000000..4375e8e376e0cf02b727b6bf9138ebcde6dd42fb
--- /dev/null
+++ b/examples/tmp/02105week2/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 = "stones.py"
+student_token_file = 'StoneReport_handin.token'
+instructor_grade_script = 'stones_tests_grade.py'
+grade_file_relative_destination = "stones_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "stones.py"
+# homework_file = "stones.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/02105week2/src/stones.py b/examples/tmp/02105week2/src/stones.py
new file mode 100644
index 0000000000000000000000000000000000000000..37becd782259655b9e8516a08abe63ab3d3f2183
--- /dev/null
+++ b/examples/tmp/02105week2/src/stones.py
@@ -0,0 +1,179 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+af74d9e2eea101854f07fd64951aafb1fbd062916c869b330e535271178c5ce49be3fc7eda177a383e7971a004abf73b787b543843a89e0b7959c0081a44e87a 31368
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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\ No newline at end of file
diff --git a/examples/tmp/02105week2/src/stones_tests_grade.py b/examples/tmp/02105week2/src/stones_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..d8065998b6dd1a1400ae7910febf59d4c6330f40
--- /dev/null
+++ b/examples/tmp/02105week2/src/stones_tests_grade.py
@@ -0,0 +1,4 @@
+# stones_tests.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/tmp/02105week2/writeup/writeup.html b/examples/tmp/02105week2/writeup/writeup.html
new file mode 100644
index 0000000000000000000000000000000000000000..08a6eeee8e4a05dcd058e6e03156862d1d5e01b4
--- /dev/null
+++ b/examples/tmp/02105week2/writeup/writeup.html
@@ -0,0 +1,5 @@
+
+    <html><body>
+    To hand in this assignment, upload the file <b>stones.py</b>
+    </body></html>    
+    
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/Makefile b/examples/tmp/c02105week2/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..d6fd3f7dbfc705dbfd095fff519dd9dda7043a1c
--- /dev/null
+++ b/examples/tmp/c02105week2/Makefile
@@ -0,0 +1,53 @@
+#
+# 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 c02105week2-handout; mkdir c02105week2-handout)
+	cp -p src/Makefile-handout c02105week2-handout/Makefile
+	cp -p src/README-handout c02105week2-handout/README
+	cp -p src/driver_python.py c02105week2-handout
+
+	cp -p src/stones.py c02105week2-handout
+
+	cp -p src/docker_helpers.py c02105week2-handout
+
+	cp -p src/stones_tests_grade.py c02105week2-handout
+
+	cp -p src/StoneReport_handin.token c02105week2-handout
+
+
+handout-tarfile: handout
+	# Build *-handout.tar and autograde.tar
+	# tar cvf c02105week2-handout.tar c02105week2-handout
+	# cp -p c02105week2-handout.tar autograde.tar
+	tar cvf autograde.tar c02105week2-handout
+	# cp -p c02105week2-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 c02105week2-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/tmp/c02105week2/autograde-Makefile b/examples/tmp/c02105week2/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..8225e82a17329397b97b543e785f96afd210562d
--- /dev/null
+++ b/examples/tmp/c02105week2/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp stones.py c02105week2-autograde
+	(cd c02105week2-autograde; python3 driver_python.py)
+
+clean:
+	rm -rf *~ c02105week2-autograde
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/autograde.tar b/examples/tmp/c02105week2/autograde.tar
new file mode 100644
index 0000000000000000000000000000000000000000..ced3d8e9aba10f3114d7572d5229cce2ce7f6fcd
Binary files /dev/null and b/examples/tmp/c02105week2/autograde.tar differ
diff --git a/examples/tmp/c02105week2/c02105week2-autograde/StoneReport_handin.token b/examples/tmp/c02105week2/c02105week2-autograde/StoneReport_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..28772b965549f1c057b4c97903d798c7fe544775
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-autograde/StoneReport_handin.token
@@ -0,0 +1,179 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+9852caeff7982dd3966eafc68abd871290dda63b0dd8198cd87e9dc122c6bbe9b6784a54580d42861a21abc5724bd4017c18c36e38c9840cb3cfb6e46a5084c3 31400
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4IXpW7xdAEABDnvvn8N61cV3uyv9rA3VXYLFhUioEJM45nedEKdqnO19PvW/YXoHmDkQocrblVLERQOzdoe2zfnvVikcsMGzEktlVOe3W3XUOr+/vL7QSGinStr49f86RE5jY5bPLOoCeppsRkj
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\ No newline at end of file
diff --git a/examples/tmp/c02105week2/c02105week2-autograde/autograde-Makefile b/examples/tmp/c02105week2/c02105week2-autograde/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..c5737b290bd8d79d61eefbb597c5f7edab2872fd
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-autograde/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp stones.py c02105week2-handout
+	(cd c02105week2-handout; python3 driver_python.py)
+
+clean:
+	rm -rf *~ c02105week2-handout
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/c02105week2-autograde/driver_python.py b/examples/tmp/c02105week2/c02105week2-autograde/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..4375e8e376e0cf02b727b6bf9138ebcde6dd42fb
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-autograde/driver_python.py
@@ -0,0 +1,92 @@
+import os
+import glob
+import shutil
+import sys
+import subprocess
+from unitgrade_private.autolab.autolab import format_autolab_json
+from unitgrade_private.docker_helpers import student_token_file_runner
+from unitgrade_private import load_token
+import time
+import unitgrade_private
+
+verbose = False
+tag = "[driver_python.py]"
+
+if not verbose:
+    print("="*10)
+    print(tag, "Starting unitgrade evaluation...")
+import unitgrade
+print(tag, "Unitgrade version", unitgrade.version.__version__)
+print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
+
+
+sys.stderr = sys.stdout
+wdir = os.getcwd()
+
+def pfiles():
+    print("> Files in dir:")
+    for f in glob.glob(wdir + "/*"):
+        print(f)
+    print("---")
+
+handin_filename = "stones.py"
+student_token_file = 'StoneReport_handin.token'
+instructor_grade_script = 'stones_tests_grade.py'
+grade_file_relative_destination = "stones_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "stones.py"
+# homework_file = "stones.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/c02105week2-autograde/stones.py b/examples/tmp/c02105week2/c02105week2-autograde/stones.py
new file mode 100644
index 0000000000000000000000000000000000000000..96c9cf5eaeba7da59ecc9db55ada75b06cd093b0
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-autograde/stones.py
@@ -0,0 +1,15 @@
+def maximum_stones(W, stone_weights):
+    stone_weights.sort()
+    T = 0
+    s = 0
+    for k, we in enumerate(stone_weights):
+        T += we
+        if T <= W:
+            s = s + 1
+        else:
+            break
+    return s
+
+if __name__ == "__main__":
+    print("The following call using maximum weight of W=15 should return 5.")
+    print(maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7]))
diff --git a/examples/tmp/c02105week2/c02105week2-autograde/stones_tests.py b/examples/tmp/c02105week2/c02105week2-autograde/stones_tests.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f61cfd3822b0d2f526c318e6b380e8d0c5d6ef1
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-autograde/stones_tests.py
@@ -0,0 +1,44 @@
+from unitgrade.framework import Report, UTestCase
+from unitgrade.evaluate import evaluate_report_student
+import stones
+from stones import maximum_stones
+
+# A fancy helper function to generate nicer-looking titles.
+def trlist(x):
+    s = str(list(x))
+    if len(s) > 30:
+        s = s[:30] + "...]"
+    return s
+
+
+class Stones(UTestCase):
+    """ Test of the Stones function """
+    def stest(self, W, stone_weights): # Helper function.
+        N = maximum_stones(W, stone_weights)
+        self.title = f"stones({W}, {trlist(stone_weights)}) = {N} ?"
+        self.assertEqualC(N)
+
+    def test_basecase(self):
+        """ Test the stones-example given in the homework """
+        N = maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7])
+        self.assertEqual(N, 5) # Test that we can collect 5 stones.
+
+    def test_stones1(self):
+        self.stest(4, [4]) # One stone weighing 4 kg.
+
+    def test_stones2(self):
+        self.stest(4, [1, 4]) # should also give 1
+
+    def test_stones3(self):
+        self.stest(4, [4, 1]) # should also give 1
+
+    def test_stones4(self):
+        self.stest(13, [2, 5, 3, 1, 8, 4, 5, 7])
+
+class StoneReport(Report):
+    title = "02105 week 2: Stone collection"
+    questions = [(Stones, 10),]
+    pack_imports = [stones]
+
+if __name__ == "__main__":
+    evaluate_report_student(StoneReport())
diff --git a/examples/tmp/c02105week2/c02105week2-autograde/stones_tests_grade.py b/examples/tmp/c02105week2/c02105week2-autograde/stones_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ea35230b3640fc8049c34f102fc80f7fb3636b1
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-autograde/stones_tests_grade.py
@@ -0,0 +1,4 @@
+# stones_tests.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/tmp/c02105week2/c02105week2-autograde/unitgrade_data/Stones.pkl b/examples/tmp/c02105week2/c02105week2-autograde/unitgrade_data/Stones.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..1bf38a4fd917fe69b27254e950aac0678e0a28ed
Binary files /dev/null and b/examples/tmp/c02105week2/c02105week2-autograde/unitgrade_data/Stones.pkl differ
diff --git a/examples/tmp/c02105week2/c02105week2-handout.zip b/examples/tmp/c02105week2/c02105week2-handout.zip
new file mode 100644
index 0000000000000000000000000000000000000000..78f0781cfd261377ba61c688e6fab6823801cf2c
Binary files /dev/null and b/examples/tmp/c02105week2/c02105week2-handout.zip differ
diff --git a/examples/tmp/c02105week2/c02105week2-handout/stones.py b/examples/tmp/c02105week2/c02105week2-handout/stones.py
new file mode 100644
index 0000000000000000000000000000000000000000..96c9cf5eaeba7da59ecc9db55ada75b06cd093b0
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-handout/stones.py
@@ -0,0 +1,15 @@
+def maximum_stones(W, stone_weights):
+    stone_weights.sort()
+    T = 0
+    s = 0
+    for k, we in enumerate(stone_weights):
+        T += we
+        if T <= W:
+            s = s + 1
+        else:
+            break
+    return s
+
+if __name__ == "__main__":
+    print("The following call using maximum weight of W=15 should return 5.")
+    print(maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7]))
diff --git a/examples/tmp/c02105week2/c02105week2-handout/stones_tests.py b/examples/tmp/c02105week2/c02105week2-handout/stones_tests.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f61cfd3822b0d2f526c318e6b380e8d0c5d6ef1
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2-handout/stones_tests.py
@@ -0,0 +1,44 @@
+from unitgrade.framework import Report, UTestCase
+from unitgrade.evaluate import evaluate_report_student
+import stones
+from stones import maximum_stones
+
+# A fancy helper function to generate nicer-looking titles.
+def trlist(x):
+    s = str(list(x))
+    if len(s) > 30:
+        s = s[:30] + "...]"
+    return s
+
+
+class Stones(UTestCase):
+    """ Test of the Stones function """
+    def stest(self, W, stone_weights): # Helper function.
+        N = maximum_stones(W, stone_weights)
+        self.title = f"stones({W}, {trlist(stone_weights)}) = {N} ?"
+        self.assertEqualC(N)
+
+    def test_basecase(self):
+        """ Test the stones-example given in the homework """
+        N = maximum_stones(15, [2, 5, 3, 1, 8, 4, 5, 7])
+        self.assertEqual(N, 5) # Test that we can collect 5 stones.
+
+    def test_stones1(self):
+        self.stest(4, [4]) # One stone weighing 4 kg.
+
+    def test_stones2(self):
+        self.stest(4, [1, 4]) # should also give 1
+
+    def test_stones3(self):
+        self.stest(4, [4, 1]) # should also give 1
+
+    def test_stones4(self):
+        self.stest(13, [2, 5, 3, 1, 8, 4, 5, 7])
+
+class StoneReport(Report):
+    title = "02105 week 2: Stone collection"
+    questions = [(Stones, 10),]
+    pack_imports = [stones]
+
+if __name__ == "__main__":
+    evaluate_report_student(StoneReport())
diff --git a/examples/tmp/c02105week2/c02105week2-handout/unitgrade_data/Stones.pkl b/examples/tmp/c02105week2/c02105week2-handout/unitgrade_data/Stones.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..1bf38a4fd917fe69b27254e950aac0678e0a28ed
Binary files /dev/null and b/examples/tmp/c02105week2/c02105week2-handout/unitgrade_data/Stones.pkl differ
diff --git a/examples/tmp/c02105week2/c02105week2.rb b/examples/tmp/c02105week2/c02105week2.rb
new file mode 100644
index 0000000000000000000000000000000000000000..8a4aac3f5cfc2b0c8ba22a6438bcc436410cec1b
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2.rb
@@ -0,0 +1,11 @@
+require "AssessmentBase.rb"
+
+module C02105week2
+  include AssessmentBase
+
+  def assessmentInitialize(course)
+    super("c02105week2",course)
+    @problems = []
+  end
+
+end
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/c02105week2.yml b/examples/tmp/c02105week2/c02105week2.yml
new file mode 100644
index 0000000000000000000000000000000000000000..3b0fef8549da4fcee84af2839c2a1b3ab74c8651
--- /dev/null
+++ b/examples/tmp/c02105week2/c02105week2.yml
@@ -0,0 +1,38 @@
+---
+
+general:
+  name: c02105week2
+  description: ' Hand in the file stones.py. You can find the full example, including solution, at https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/tree/master/examples/02105/instructor/week2 '
+  display_name: '02105 week 2: Stone collection'
+  handin_filename: stones.py
+  handin_directory: handin
+  max_grace_days: 0
+  handout: c02105week2-handout.zip
+  writeup: writeup/writeup.html
+  max_submissions: -1
+  disable_handins: false
+  max_size: 2
+  has_svn: false
+  category_name: Lab
+problems:
+
+  - name: Unitgrade score
+    description: 'Score obtained by automatic grading'
+    max_score: 10
+    optional: false
+
+  - name: Written feedback
+    description: 'Written (TA) feedback'
+    max_score: 0
+    optional: true
+
+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/tmp/c02105week2/src/Makefile b/examples/tmp/c02105week2/src/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/tmp/c02105week2/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/tmp/c02105week2/src/Makefile-handout b/examples/tmp/c02105week2/src/Makefile-handout
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/tmp/c02105week2/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/tmp/c02105week2/src/README b/examples/tmp/c02105week2/src/README
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/tmp/c02105week2/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/tmp/c02105week2/src/README-handout b/examples/tmp/c02105week2/src/README-handout
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/tmp/c02105week2/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/tmp/c02105week2/src/StoneReport_handin.token b/examples/tmp/c02105week2/src/StoneReport_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..28772b965549f1c057b4c97903d798c7fe544775
--- /dev/null
+++ b/examples/tmp/c02105week2/src/StoneReport_handin.token
@@ -0,0 +1,179 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+9852caeff7982dd3966eafc68abd871290dda63b0dd8198cd87e9dc122c6bbe9b6784a54580d42861a21abc5724bd4017c18c36e38c9840cb3cfb6e46a5084c3 31400
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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+Y0eLPfoJ0rHX005TpZmBdwBZghdBd0RlHAADZQVhwq86tcAAB2LcB6osCJIxvtbHEZ/sCAAAAAARZWg==.
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/src/docker_helpers.py b/examples/tmp/c02105week2/src/docker_helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..0b82a931c0268a356ee54f777fbc7ed0ef095e3f
--- /dev/null
+++ b/examples/tmp/c02105week2/src/docker_helpers.py
@@ -0,0 +1,198 @@
+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)
+    cmd = f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} ."
+    os.system(cmd)
+    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):$(id -g)" '
+    else:
+        user_cmd = ''
+
+    if xvfb:
+        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
+
+    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
+    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
+    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
+    fcom = f"{cdcom}  && {dcom}"
+    print("> Running docker command")
+    print(fcom)
+    init = time.time() - start
+    # thtools.execute_command(fcom.split())
+    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
+    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
+    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
+    for t in tokens:
+        print("Source image produced token", t)
+    elapsed = time.time() - start
+    print("Elapsed time is", elapsed, f"({init=} seconds)")
+    if len(tokens) != 1:
+        print("Wrong number of tokens produced:", len(tokens))
+        print(out)
+    return tokens[0]
diff --git a/examples/tmp/c02105week2/src/driver.sh b/examples/tmp/c02105week2/src/driver.sh
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/tmp/c02105week2/src/driver.sh
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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 ${status}"
+#    echo "{\"scores\": {\"Correctness\": 0}}"
+#fi
+
+exit
diff --git a/examples/tmp/c02105week2/src/driver.sh-handout b/examples/tmp/c02105week2/src/driver.sh-handout
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/tmp/c02105week2/src/driver.sh-handout
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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/tmp/c02105week2/src/driver_python.py b/examples/tmp/c02105week2/src/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..4375e8e376e0cf02b727b6bf9138ebcde6dd42fb
--- /dev/null
+++ b/examples/tmp/c02105week2/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 = "stones.py"
+student_token_file = 'StoneReport_handin.token'
+instructor_grade_script = 'stones_tests_grade.py'
+grade_file_relative_destination = "stones_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "stones.py"
+# homework_file = "stones.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/src/driver_python.py-handout b/examples/tmp/c02105week2/src/driver_python.py-handout
new file mode 100644
index 0000000000000000000000000000000000000000..4375e8e376e0cf02b727b6bf9138ebcde6dd42fb
--- /dev/null
+++ b/examples/tmp/c02105week2/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 = "stones.py"
+student_token_file = 'StoneReport_handin.token'
+instructor_grade_script = 'stones_tests_grade.py'
+grade_file_relative_destination = "stones_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "stones.py"
+# homework_file = "stones.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/c02105week2/src/stones.py b/examples/tmp/c02105week2/src/stones.py
new file mode 100644
index 0000000000000000000000000000000000000000..28772b965549f1c057b4c97903d798c7fe544775
--- /dev/null
+++ b/examples/tmp/c02105week2/src/stones.py
@@ -0,0 +1,179 @@
+# 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/tmp/c02105week2/src/stones_tests_grade.py b/examples/tmp/c02105week2/src/stones_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ea35230b3640fc8049c34f102fc80f7fb3636b1
--- /dev/null
+++ b/examples/tmp/c02105week2/src/stones_tests_grade.py
@@ -0,0 +1,4 @@
+# stones_tests.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/tmp/c02105week2/writeup/writeup.html b/examples/tmp/c02105week2/writeup/writeup.html
new file mode 100644
index 0000000000000000000000000000000000000000..08a6eeee8e4a05dcd058e6e03156862d1d5e01b4
--- /dev/null
+++ b/examples/tmp/c02105week2/writeup/writeup.html
@@ -0,0 +1,5 @@
+
+    <html><body>
+    To hand in this assignment, upload the file <b>stones.py</b>
+    </body></html>    
+    
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/Makefile b/examples/tmp/c02631week5/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..315a17b0b162a8f382a97133a51277225c0f0f67
--- /dev/null
+++ b/examples/tmp/c02631week5/Makefile
@@ -0,0 +1,53 @@
+#
+# 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 c02631week5-handout; mkdir c02631week5-handout)
+	cp -p src/Makefile-handout c02631week5-handout/Makefile
+	cp -p src/README-handout c02631week5-handout/README
+	cp -p src/driver_python.py c02631week5-handout
+
+	cp -p src/looping.py c02631week5-handout
+
+	cp -p src/docker_helpers.py c02631week5-handout
+
+	cp -p src/looping_tests_grade.py c02631week5-handout
+
+	cp -p src/Report1Flat_handin.token c02631week5-handout
+
+
+handout-tarfile: handout
+	# Build *-handout.tar and autograde.tar
+	# tar cvf c02631week5-handout.tar c02631week5-handout
+	# cp -p c02631week5-handout.tar autograde.tar
+	tar cvf autograde.tar c02631week5-handout
+	# cp -p c02631week5-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 c02631week5-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/tmp/c02631week5/autograde-Makefile b/examples/tmp/c02631week5/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..dc896c7748f55a06288022bb6f3a89a43d31bff4
--- /dev/null
+++ b/examples/tmp/c02631week5/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp looping.py c02631week5-autograde
+	(cd c02631week5-autograde; python3 driver_python.py)
+
+clean:
+	rm -rf *~ c02631week5-autograde
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/autograde.tar b/examples/tmp/c02631week5/autograde.tar
new file mode 100644
index 0000000000000000000000000000000000000000..d12f04a6e83a78effe31f775d3ca8d420c7e512e
Binary files /dev/null and b/examples/tmp/c02631week5/autograde.tar differ
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/Report1Flat_handin.token b/examples/tmp/c02631week5/c02631week5-autograde/Report1Flat_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..2ea703ab9cb00105b3bf3d8f79befcc923868252
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-autograde/Report1Flat_handin.token
@@ -0,0 +1,202 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+ba426da415e8071cc74bec270089fe6b6181c69b47ada4ab4f361248ffb4348064ab706575dd29f9b74a52694aba493fd9f3e745269c55683abfd2b20e870c9c 35488
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4LMLZ7ZdAEABDm0lO6BLPJD6X7ENapNZv7rYMKri6UIrIRnmROSK5M5SCcD8zluru0cupNVcTngHjXQurbpNyj43fOZFHRcJtpFhJzoaR7iqNEAerLGAbeI/U8AOAbAOwb/PQpU3Rbi9UiA+TV7
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\ No newline at end of file
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/autograde-Makefile b/examples/tmp/c02631week5/c02631week5-autograde/autograde-Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..4640cce8e90097573b60ac218e49c145caa63b73
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-autograde/autograde-Makefile
@@ -0,0 +1,7 @@
+all:
+	tar xf autograde.tar
+	cp looping.py c02631week5-handout
+	(cd c02631week5-handout; python3 driver_python.py)
+
+clean:
+	rm -rf *~ c02631week5-handout
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/driver_python.py b/examples/tmp/c02631week5/c02631week5-autograde/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..286f74612cf1a77248e066f52be1ec0b739ec485
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-autograde/driver_python.py
@@ -0,0 +1,92 @@
+import os
+import glob
+import shutil
+import sys
+import subprocess
+from unitgrade_private.autolab.autolab import format_autolab_json
+from unitgrade_private.docker_helpers import student_token_file_runner
+from unitgrade_private import load_token
+import time
+import unitgrade_private
+
+verbose = False
+tag = "[driver_python.py]"
+
+if not verbose:
+    print("="*10)
+    print(tag, "Starting unitgrade evaluation...")
+import unitgrade
+print(tag, "Unitgrade version", unitgrade.version.__version__)
+print(tag, "Unitgrade-devel version", unitgrade_private.version.__version__)
+
+
+sys.stderr = sys.stdout
+wdir = os.getcwd()
+
+def pfiles():
+    print("> Files in dir:")
+    for f in glob.glob(wdir + "/*"):
+        print(f)
+    print("---")
+
+handin_filename = "looping.py"
+student_token_file = 'Report1Flat_handin.token'
+instructor_grade_script = 'looping_tests_grade.py'
+grade_file_relative_destination = "looping_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "looping.py"
+# homework_file = "looping.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/looping.py b/examples/tmp/c02631week5/c02631week5-autograde/looping.py
new file mode 100644
index 0000000000000000000000000000000000000000..64db4f21b1aa35baa2ad7650bebee649c2581309
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-autograde/looping.py
@@ -0,0 +1,51 @@
+import numpy as np
+import itertools
+
+def bacteriaGrowth(n0, alpha, K, N): 
+    """
+    Calculate time until bacteria growth exceed N starting from a population of n0 bacteria.
+    hints:
+        * You need to update the number of bacteria n0 within a loop
+    """
+    # TODO: 7 lines missing.
+    raise NotImplementedError("Implement function body")
+    return t
+
+def clusterAnalysis(reflectance):
+    reflectance = np.asarray(reflectance)
+    I1 = np.arange(len(reflectance)) % 2 == 1
+    while True:
+        m = np.asarray( [np.mean( reflectance[~I1] ),  np.mean( reflectance[I1] ) ] )
+        I1_ = np.argmin( np.abs( reflectance[:, np.newaxis] - m[np.newaxis, :] ), axis=1) == 1
+        if all(I1_ == I1):
+            break
+        I1 = I1_
+    return I1 + 1
+
+def fermentationRate(measuredRate, lowerBound, upperBound):
+    """
+    Compute and return the mean value of the rates in 'measuredRate'
+    which falls within lowerBound and upperBound.
+    """
+    mean_value = np.mean( [r for r in measuredRate if lowerBound < r < upperBound] )
+    return mean_value
+
+def removeIncomplete(id):
+    """
+    Hints:
+        * Take a look at the example in the exercise.
+    """
+    id = np.asarray(id)
+    id2 = []
+    for i, v in enumerate(id):
+        if len( [x for x in id if int(x) == int(v) ] ) == 3:
+            id2.append(v)
+    return np.asarray(id2)
+
+if __name__ == "__main__":
+    # I = clusterAnalysis([1.7, 1.6, 1.3, 1.3, 2.8, 1.4, 2.8, 2.6, 1.6, 2.7])
+    # print(I)
+    print(fermentationRate(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 15, 25))
+    # print(removeIncomplete(np.array([1.3, 2.2, 2.3, 4.2, 5.1, 3.2, 5.3, 3.3, 2.1, 1.1, 5.2, 3.1])))
+    # Problem 1: Write a function which add two numbers
+    # clusterAnalysis([2, 1, 2, 4, 5])
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/looping_tests.py b/examples/tmp/c02631week5/c02631week5-autograde/looping_tests.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8076c26210356404b46a61e660ba7ee4617a51b
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-autograde/looping_tests.py
@@ -0,0 +1,138 @@
+from unitgrade.framework import Report, UTestCase
+from unitgrade import cache
+from unitgrade.evaluate import evaluate_report_student
+import numpy as np
+import looping
+from looping import bacteriaGrowth, clusterAnalysis, removeIncomplete, fermentationRate
+
+def trlist(x):
+    s = str(list(x))
+    if len(s) > 30:
+        s = s[:30] + "...]"
+    return s
+
+class Bacteria(UTestCase):
+    """ Bacteria growth rates """
+
+    def stest(self, n0, alpha, K, N):
+        g = bacteriaGrowth(n0=n0, alpha=alpha, K=K, N=N)
+        self.title = f"bacteriaGrowth({n0}, {alpha}, {K}, {N}) = {g} ?"
+        self.assertEqualC(g)
+
+    def test_growth1(self):
+        """ Hints:
+        * Make sure to frobulate the frobulator.
+        """
+        self.stest(100, 0.4, 1000, 500)
+
+    def test_growth2(self):
+        self.stest(10, 0.4, 1000, 500)
+
+    def test_growth3(self):
+        self.stest(100, 1.4, 1000, 500)
+
+    def test_growth4(self):
+        self.stest(100, 0.0004, 1000, 500)
+
+    def test_growth5(self):
+        """
+        hints:
+        * What happens when n0 > N? (in this case return t=0) """
+        self.stest(100, 0.4, 1000, 99)
+
+class ClusterAnalysis(UTestCase):
+    """ Cluster analysis """
+
+    def stest(self, n, seed):
+        np.random.seed(seed)
+        x = np.round(np.random.rand(n), 1)
+        I = clusterAnalysis(x)
+        self.title = f"clusterAnalysis({list(x)}) = {list(I)} ?"
+        self.assertEqualC(list(I))
+
+    def test_cluster1(self):
+        """ Hints:
+        * Make sure to frobulate the frobulator.
+        * Just try harder
+        """
+        self.stest(3, 10)
+
+    def test_cluster2(self):
+        self.stest(4, 146)
+
+    def test_cluster3(self):
+        self.stest(5, 12)
+
+    def test_cluster4(self):
+        """
+        Cluster analysis for tied lists
+        Hints:
+        * It may be that an observations has the same distance to the two clusters. Where do you assign it in this case?
+        """
+        x = np.array([10.0, 12.0, 10.0, 12.0, 9.0, 11.0, 11.0, 13.0])
+        self.assertEqualC(list(clusterAnalysis(x) ) )
+
+
+class RemoveIncomplete(UTestCase):
+    """ Remove incomplete IDs """
+
+    def stest(self, x):
+        I = list( removeIncomplete(x) )
+        self.title = f"removeId({trlist(x)}) = {trlist(I)} ?"
+        self.assertEqualC(I)
+
+    @cache
+    def rseq(self, max, n):
+        np.random.seed(42)
+        return np.random.randint(max, size=(n,) ) + (np.random.randint(2, size=(n,) )+1)/10
+
+    def test_incomplete1(self):
+        self.stest( np.array([1.3, 2.2, 2.3, 4.2, 5.1, 3.2, 5.3, 3.3, 2.1, 1.1, 5.2, 3.1]) )
+
+    def test_incomplete2(self):
+        self.stest( np.array([1.1, 1.2, 1.3, 2.1, 2.2, 2.3]) )
+
+    def test_incomplete3(self):
+        self.stest(np.array([5.1, 5.2, 4.1, 4.3, 4.2, 8.1, 8.2, 8.3]) )
+
+    def test_incomplete4(self):
+        self.stest(np.array([1.1, 1.3, 2.1, 2.2, 3.1, 3.3, 4.1, 4.2, 4.3]) )
+
+    def test_incomplete5(self):
+        self.stest(self.rseq(10, 40))
+
+
+class FermentationRate(UTestCase):
+    """ Fermentation rate """
+
+    def stest(self, x, lower, upper):
+        I =  fermentationRate(x, lower, upper)
+        s = trlist(x)
+        self.title = f"fermentationRate({s}, {lower}, {upper}) = {I:.3f} ?"
+        self.assertEqualC(I)
+
+    @cache
+    def rseq(self, max, n):
+        np.random.seed(42)
+        return np.random.randint(max, size=(n,) ) + (np.random.randint(3, size=(n,) )+1)/n
+
+    def test_rate1(self):
+        self.stest(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 15, 25)
+
+    def test_rate2(self):
+        self.stest(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 1, 200)
+
+    def test_rate3(self):
+        self.stest(np.array([1.75]), 1, 2)
+
+    def test_rate4(self):
+        self.stest(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 18.2, 20)
+
+
+class Report1Flat(Report):
+    title = "02531 week 5: Looping"
+    questions = [(ClusterAnalysis, 10), (RemoveIncomplete, 10), (Bacteria, 10),  (FermentationRate, 10),]
+    pack_imports = [looping]
+
+if __name__ == "__main__":
+    evaluate_report_student(Report1Flat())
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/looping_tests_grade.py b/examples/tmp/c02631week5/c02631week5-autograde/looping_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e88d8efa8f18f1bb256bda6ab57e41f2702665e
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-autograde/looping_tests_grade.py
@@ -0,0 +1,4 @@
+# looping_tests.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/tmp/c02631week5/c02631week5-autograde/unitgrade_data/Bacteria.pkl b/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/Bacteria.pkl
new file mode 100644
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Binary files /dev/null and b/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/Bacteria.pkl differ
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/ClusterAnalysis.pkl b/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/ClusterAnalysis.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..2f11291cbbf7032f654afea9023684431328a1ce
Binary files /dev/null and b/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/ClusterAnalysis.pkl differ
diff --git a/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/FermentationRate.pkl b/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/FermentationRate.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..0174a699f6daaebd098ec177240e48b8c3293a44
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diff --git a/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/RemoveIncomplete.pkl b/examples/tmp/c02631week5/c02631week5-autograde/unitgrade_data/RemoveIncomplete.pkl
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index 0000000000000000000000000000000000000000..c6aef837cef8ea1f347292519cc37296cb025d45
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diff --git a/examples/tmp/c02631week5/c02631week5-handout.zip b/examples/tmp/c02631week5/c02631week5-handout.zip
new file mode 100644
index 0000000000000000000000000000000000000000..6af76da24433b9788d99f1264c7c6657a71df26d
Binary files /dev/null and b/examples/tmp/c02631week5/c02631week5-handout.zip differ
diff --git a/examples/tmp/c02631week5/c02631week5-handout/looping.py b/examples/tmp/c02631week5/c02631week5-handout/looping.py
new file mode 100644
index 0000000000000000000000000000000000000000..64db4f21b1aa35baa2ad7650bebee649c2581309
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-handout/looping.py
@@ -0,0 +1,51 @@
+import numpy as np
+import itertools
+
+def bacteriaGrowth(n0, alpha, K, N): 
+    """
+    Calculate time until bacteria growth exceed N starting from a population of n0 bacteria.
+    hints:
+        * You need to update the number of bacteria n0 within a loop
+    """
+    # TODO: 7 lines missing.
+    raise NotImplementedError("Implement function body")
+    return t
+
+def clusterAnalysis(reflectance):
+    reflectance = np.asarray(reflectance)
+    I1 = np.arange(len(reflectance)) % 2 == 1
+    while True:
+        m = np.asarray( [np.mean( reflectance[~I1] ),  np.mean( reflectance[I1] ) ] )
+        I1_ = np.argmin( np.abs( reflectance[:, np.newaxis] - m[np.newaxis, :] ), axis=1) == 1
+        if all(I1_ == I1):
+            break
+        I1 = I1_
+    return I1 + 1
+
+def fermentationRate(measuredRate, lowerBound, upperBound):
+    """
+    Compute and return the mean value of the rates in 'measuredRate'
+    which falls within lowerBound and upperBound.
+    """
+    mean_value = np.mean( [r for r in measuredRate if lowerBound < r < upperBound] )
+    return mean_value
+
+def removeIncomplete(id):
+    """
+    Hints:
+        * Take a look at the example in the exercise.
+    """
+    id = np.asarray(id)
+    id2 = []
+    for i, v in enumerate(id):
+        if len( [x for x in id if int(x) == int(v) ] ) == 3:
+            id2.append(v)
+    return np.asarray(id2)
+
+if __name__ == "__main__":
+    # I = clusterAnalysis([1.7, 1.6, 1.3, 1.3, 2.8, 1.4, 2.8, 2.6, 1.6, 2.7])
+    # print(I)
+    print(fermentationRate(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 15, 25))
+    # print(removeIncomplete(np.array([1.3, 2.2, 2.3, 4.2, 5.1, 3.2, 5.3, 3.3, 2.1, 1.1, 5.2, 3.1])))
+    # Problem 1: Write a function which add two numbers
+    # clusterAnalysis([2, 1, 2, 4, 5])
diff --git a/examples/tmp/c02631week5/c02631week5-handout/looping_tests.py b/examples/tmp/c02631week5/c02631week5-handout/looping_tests.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8076c26210356404b46a61e660ba7ee4617a51b
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5-handout/looping_tests.py
@@ -0,0 +1,138 @@
+from unitgrade.framework import Report, UTestCase
+from unitgrade import cache
+from unitgrade.evaluate import evaluate_report_student
+import numpy as np
+import looping
+from looping import bacteriaGrowth, clusterAnalysis, removeIncomplete, fermentationRate
+
+def trlist(x):
+    s = str(list(x))
+    if len(s) > 30:
+        s = s[:30] + "...]"
+    return s
+
+class Bacteria(UTestCase):
+    """ Bacteria growth rates """
+
+    def stest(self, n0, alpha, K, N):
+        g = bacteriaGrowth(n0=n0, alpha=alpha, K=K, N=N)
+        self.title = f"bacteriaGrowth({n0}, {alpha}, {K}, {N}) = {g} ?"
+        self.assertEqualC(g)
+
+    def test_growth1(self):
+        """ Hints:
+        * Make sure to frobulate the frobulator.
+        """
+        self.stest(100, 0.4, 1000, 500)
+
+    def test_growth2(self):
+        self.stest(10, 0.4, 1000, 500)
+
+    def test_growth3(self):
+        self.stest(100, 1.4, 1000, 500)
+
+    def test_growth4(self):
+        self.stest(100, 0.0004, 1000, 500)
+
+    def test_growth5(self):
+        """
+        hints:
+        * What happens when n0 > N? (in this case return t=0) """
+        self.stest(100, 0.4, 1000, 99)
+
+class ClusterAnalysis(UTestCase):
+    """ Cluster analysis """
+
+    def stest(self, n, seed):
+        np.random.seed(seed)
+        x = np.round(np.random.rand(n), 1)
+        I = clusterAnalysis(x)
+        self.title = f"clusterAnalysis({list(x)}) = {list(I)} ?"
+        self.assertEqualC(list(I))
+
+    def test_cluster1(self):
+        """ Hints:
+        * Make sure to frobulate the frobulator.
+        * Just try harder
+        """
+        self.stest(3, 10)
+
+    def test_cluster2(self):
+        self.stest(4, 146)
+
+    def test_cluster3(self):
+        self.stest(5, 12)
+
+    def test_cluster4(self):
+        """
+        Cluster analysis for tied lists
+        Hints:
+        * It may be that an observations has the same distance to the two clusters. Where do you assign it in this case?
+        """
+        x = np.array([10.0, 12.0, 10.0, 12.0, 9.0, 11.0, 11.0, 13.0])
+        self.assertEqualC(list(clusterAnalysis(x) ) )
+
+
+class RemoveIncomplete(UTestCase):
+    """ Remove incomplete IDs """
+
+    def stest(self, x):
+        I = list( removeIncomplete(x) )
+        self.title = f"removeId({trlist(x)}) = {trlist(I)} ?"
+        self.assertEqualC(I)
+
+    @cache
+    def rseq(self, max, n):
+        np.random.seed(42)
+        return np.random.randint(max, size=(n,) ) + (np.random.randint(2, size=(n,) )+1)/10
+
+    def test_incomplete1(self):
+        self.stest( np.array([1.3, 2.2, 2.3, 4.2, 5.1, 3.2, 5.3, 3.3, 2.1, 1.1, 5.2, 3.1]) )
+
+    def test_incomplete2(self):
+        self.stest( np.array([1.1, 1.2, 1.3, 2.1, 2.2, 2.3]) )
+
+    def test_incomplete3(self):
+        self.stest(np.array([5.1, 5.2, 4.1, 4.3, 4.2, 8.1, 8.2, 8.3]) )
+
+    def test_incomplete4(self):
+        self.stest(np.array([1.1, 1.3, 2.1, 2.2, 3.1, 3.3, 4.1, 4.2, 4.3]) )
+
+    def test_incomplete5(self):
+        self.stest(self.rseq(10, 40))
+
+
+class FermentationRate(UTestCase):
+    """ Fermentation rate """
+
+    def stest(self, x, lower, upper):
+        I =  fermentationRate(x, lower, upper)
+        s = trlist(x)
+        self.title = f"fermentationRate({s}, {lower}, {upper}) = {I:.3f} ?"
+        self.assertEqualC(I)
+
+    @cache
+    def rseq(self, max, n):
+        np.random.seed(42)
+        return np.random.randint(max, size=(n,) ) + (np.random.randint(3, size=(n,) )+1)/n
+
+    def test_rate1(self):
+        self.stest(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 15, 25)
+
+    def test_rate2(self):
+        self.stest(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 1, 200)
+
+    def test_rate3(self):
+        self.stest(np.array([1.75]), 1, 2)
+
+    def test_rate4(self):
+        self.stest(np.array([20.1, 19.3, 1.1, 18.2, 19.7, 121.1, 20.3, 20.0]), 18.2, 20)
+
+
+class Report1Flat(Report):
+    title = "02531 week 5: Looping"
+    questions = [(ClusterAnalysis, 10), (RemoveIncomplete, 10), (Bacteria, 10),  (FermentationRate, 10),]
+    pack_imports = [looping]
+
+if __name__ == "__main__":
+    evaluate_report_student(Report1Flat())
diff --git a/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/Bacteria.pkl b/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/Bacteria.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..5fd7927c81b07caaef98db8a9e8111b12d62019b
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diff --git a/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/ClusterAnalysis.pkl b/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/ClusterAnalysis.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..2f11291cbbf7032f654afea9023684431328a1ce
Binary files /dev/null and b/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/ClusterAnalysis.pkl differ
diff --git a/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/FermentationRate.pkl b/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/FermentationRate.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..0174a699f6daaebd098ec177240e48b8c3293a44
Binary files /dev/null and b/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/FermentationRate.pkl differ
diff --git a/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/RemoveIncomplete.pkl b/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/RemoveIncomplete.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..c6aef837cef8ea1f347292519cc37296cb025d45
Binary files /dev/null and b/examples/tmp/c02631week5/c02631week5-handout/unitgrade_data/RemoveIncomplete.pkl differ
diff --git a/examples/tmp/c02631week5/c02631week5.rb b/examples/tmp/c02631week5/c02631week5.rb
new file mode 100644
index 0000000000000000000000000000000000000000..7fb4d2cca4f73d960a75f8648b093970002a8bd0
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5.rb
@@ -0,0 +1,11 @@
+require "AssessmentBase.rb"
+
+module C02631week5
+  include AssessmentBase
+
+  def assessmentInitialize(course)
+    super("c02631week5",course)
+    @problems = []
+  end
+
+end
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/c02631week5.yml b/examples/tmp/c02631week5/c02631week5.yml
new file mode 100644
index 0000000000000000000000000000000000000000..353bf07c1c88032a0e6144477161e152fa10bd1a
--- /dev/null
+++ b/examples/tmp/c02631week5/c02631week5.yml
@@ -0,0 +1,38 @@
+---
+
+general:
+  name: c02631week5
+  description: ' Hand in the file stones.py. You can find the full example, including solution, at https://gitlab.compute.dtu.dk/tuhe/unitgrade_private/-/tree/master/examples/02631/instructor/week5 '
+  display_name: '02531 week 5: Looping'
+  handin_filename: looping.py
+  handin_directory: handin
+  max_grace_days: 0
+  handout: c02631week5-handout.zip
+  writeup: writeup/writeup.html
+  max_submissions: -1
+  disable_handins: false
+  max_size: 2
+  has_svn: false
+  category_name: Lab
+problems:
+
+  - name: Unitgrade score
+    description: 'Score obtained by automatic grading'
+    max_score: 40
+    optional: false
+
+  - name: Written feedback
+    description: 'Written (TA) feedback'
+    max_score: 0
+    optional: true
+
+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/tmp/c02631week5/src/Makefile b/examples/tmp/c02631week5/src/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/tmp/c02631week5/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/tmp/c02631week5/src/Makefile-handout b/examples/tmp/c02631week5/src/Makefile-handout
new file mode 100644
index 0000000000000000000000000000000000000000..6d094e3a3869dfe9ee9e51a06150c6999c402286
--- /dev/null
+++ b/examples/tmp/c02631week5/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/tmp/c02631week5/src/README b/examples/tmp/c02631week5/src/README
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/tmp/c02631week5/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/tmp/c02631week5/src/README-handout b/examples/tmp/c02631week5/src/README-handout
new file mode 100644
index 0000000000000000000000000000000000000000..8eea4bef3abb4665581173c4843b6155b3dc59d2
--- /dev/null
+++ b/examples/tmp/c02631week5/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/tmp/c02631week5/src/Report1Flat_handin.token b/examples/tmp/c02631week5/src/Report1Flat_handin.token
new file mode 100644
index 0000000000000000000000000000000000000000..2ea703ab9cb00105b3bf3d8f79befcc923868252
--- /dev/null
+++ b/examples/tmp/c02631week5/src/Report1Flat_handin.token
@@ -0,0 +1,202 @@
+# This file contains your results. Do not edit its content. Simply upload it as it is.
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
+ba426da415e8071cc74bec270089fe6b6181c69b47ada4ab4f361248ffb4348064ab706575dd29f9b74a52694aba493fd9f3e745269c55683abfd2b20e870c9c 35488
+---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
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+rm76Ib1pzaPf2ylAj5JuhAnFO2rLveOhTtP9eGleAwTWHZnwtEzrblWeKH3IX5QxpOfYVwysG05mJ2sb77PfZyyxtKA2upUzNB9pp5MD9F0yDm7zMCqiKfdOrQ2+/WeBecVOgCdXKFP3agYe/Seq5MguQaoxg7BAFcZuznxG4PFmiIs/OfFF
+czhetdBIgd+Amt4F2bqZO8VkdtEnmSC28peTDGu8GKQs0S23TH5/obu7E3uFOSarYlxqXIcFekdN3Vr7ed/fn7r5Cbq/LFwdqzYcG4hyWZIA0IycoveGfouseEoZt0BBOJKn2LOn36CWVvi9PnKQDpD2JbX2Wrlu1JhQUxqi7ULmBPfSA/PI
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+7Jc8dXoxVdwMgY0R5SIOXsd0tjsxK4Jx6f4AUcoypoIgzkO5qEaqWEhDeM/i3xZ5E/74tj5CTIRo5wj7tOX07FXG7ZUh51sH6ldvsnAT1J7dzD1zFyeC1wE7i9yLFwHv2T+pVQyAGvM2YP/b7yuYl3gm4Y5RlL8457j9dgyFqW6nP948RFfO
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+PTmQKLgMt85Q/RzpMVD2fNkfUwcQf006cLYcElBGN2nw5X9wExuope63gf8ZoAUsIVbqYBUGDM0hRT13Ibtk0tlJahGm3NwFsc2CL3l1IbgH1R/ykM3zAz6zauro1eII3rUGEWEXSw9WHPFLC5ocjmlhvKhflZeapLjbmdChQGnIDu/p8EPn
+cEhRNBjvhXpSqbILXY205CMFJnNCFRTOpPsFYvvAtujKy295CseWG83e3PfzBFsXn+Xz0VITcMN9A6HMM3Z/VTbPPFDqUDS424DN9Az6UoLApZwAmHK5L0puc0hZE1VvLwgB5RLBWQhWU6ubyKJ5nMPIgTfwzNkIHAAAAAOwjdoEkWotYAAH
+SzwGM5gI0pl9BscRn+wIAAAAABFla.
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/src/docker_helpers.py b/examples/tmp/c02631week5/src/docker_helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..0b82a931c0268a356ee54f777fbc7ed0ef095e3f
--- /dev/null
+++ b/examples/tmp/c02631week5/src/docker_helpers.py
@@ -0,0 +1,198 @@
+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)
+    cmd = f"cd {base} && docker build {'--no-cache' if no_cache else ''} --tag {tag} ."
+    os.system(cmd)
+    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):$(id -g)" '
+    else:
+        user_cmd = ''
+
+    if xvfb:
+        user_cmd = " -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix " + user_cmd
+
+    tmp_path = os.path.abspath(host_tmp_dir).replace("\\", "/")
+    dcom = f"docker run {user_cmd} -v {tmp_path}:/home {dockname} {pycom}"
+    cdcom = f"cd {os.path.dirname(Dockerfile_location)}"
+    fcom = f"{cdcom}  && {dcom}"
+    print("> Running docker command")
+    print(fcom)
+    init = time.time() - start
+    # thtools.execute_command(fcom.split())
+    out = subprocess.check_output(fcom, shell=True).decode("utf-8")
+    host_tmp_dir +"/" + os.path.dirname(tmp_grade_file) + "/"
+    tokens = glob.glob( os.path.dirname(instructor_grade_script) + "/*.token" )
+    for t in tokens:
+        print("Source image produced token", t)
+    elapsed = time.time() - start
+    print("Elapsed time is", elapsed, f"({init=} seconds)")
+    if len(tokens) != 1:
+        print("Wrong number of tokens produced:", len(tokens))
+        print(out)
+    return tokens[0]
diff --git a/examples/tmp/c02631week5/src/driver.sh b/examples/tmp/c02631week5/src/driver.sh
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/tmp/c02631week5/src/driver.sh
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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 ${status}"
+#    echo "{\"scores\": {\"Correctness\": 0}}"
+#fi
+
+exit
diff --git a/examples/tmp/c02631week5/src/driver.sh-handout b/examples/tmp/c02631week5/src/driver.sh-handout
new file mode 100644
index 0000000000000000000000000000000000000000..05a006e95e416fa5d5088f1d61479f73901588c2
--- /dev/null
+++ b/examples/tmp/c02631week5/src/driver.sh-handout
@@ -0,0 +1,33 @@
+#!/bin/bash
+# driver.sh - The simplest autograder we could think of. It checks
+#   that students can write a C program that compiles, and then
+#   executes with an exit status of zero.
+#   Usage: ./driver.sh
+
+# Compile the code
+# echo "Compiling hello3.c"
+# python3 -c "print('Hello world from python 2')"
+# python3 --version
+python3 driver_python.py
+
+#(make clean; make)
+#status=$?
+#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/tmp/c02631week5/src/driver_python.py b/examples/tmp/c02631week5/src/driver_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..286f74612cf1a77248e066f52be1ec0b739ec485
--- /dev/null
+++ b/examples/tmp/c02631week5/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 = "looping.py"
+student_token_file = 'Report1Flat_handin.token'
+instructor_grade_script = 'looping_tests_grade.py'
+grade_file_relative_destination = "looping_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "looping.py"
+# homework_file = "looping.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/src/driver_python.py-handout b/examples/tmp/c02631week5/src/driver_python.py-handout
new file mode 100644
index 0000000000000000000000000000000000000000..286f74612cf1a77248e066f52be1ec0b739ec485
--- /dev/null
+++ b/examples/tmp/c02631week5/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 = "looping.py"
+student_token_file = 'Report1Flat_handin.token'
+instructor_grade_script = 'looping_tests_grade.py'
+grade_file_relative_destination = "looping_tests_grade.py"
+host_tmp_dir = wdir + "/tmp"
+homework_file = "looping.py"
+# homework_file = "looping.py"
+student_should_upload_token = False # Add these from template.
+
+if not verbose:
+    pfiles()
+    print(f"{host_tmp_dir=}")
+    print(f"{student_token_file=}")
+    print(f"{instructor_grade_script=}")
+
+print("Current directory", os.getcwd())
+print("student_token_file", student_token_file)
+for f in glob.glob(os.getcwd() + "/*"):
+    print(f)
+try:
+    # This is how we get the student file structure.
+    command, host_tmp_dir, token = student_token_file_runner(host_tmp_dir, student_token_file, instructor_grade_script,
+                                                             grade_file_relative_destination)
+    # run the stuff.
+    if not student_should_upload_token:
+        """ Add the student homework to the right location. """
+        print("Moving uploaded file from", os.path.basename(handin_filename), "to", handin_filename)
+        # print("file exists?", os.path.isfile(os.path.basename(handin_filename)))
+        shutil.move(os.path.basename(handin_filename), host_tmp_dir + "/" + handin_filename)
+
+    command = f"cd tmp && {command} --noprogress --autolab"
+    def rcom(cm):
+        rs = subprocess.run(cm, capture_output=True, text=True, shell=True)
+        print(rs.stdout)
+        if len(rs.stderr) > 0:
+            print(tag, "There were errors in executing the file:")
+            print(rs.stderr)
+
+    start = time.time()
+    rcom(command)
+    ls = glob.glob(token)
+    f = ls[0]
+    results, _ = load_token(ls[0])
+
+except Exception as e:
+    if not student_should_upload_token:
+        print(tag, "A major error occured while starting unitgrade.")
+        print(tag, "This can mean the grader itself is badly configured, or (more likely) that you submitted a completely wrong file.")
+        print(tag, "The following is the content of the file you uploaded; is it what you expect?")
+        with open(host_tmp_dir + "/" + handin_filename, 'r') as f:
+            print( f.read() )
+        print(" ")
+        print(tag, "If you cannot resolve the problem, please contact the teacher and include details such as this log, as well as the file you submitted.")
+
+    raise e
+
+if verbose:
+    print(tag, f"{token=}")
+    print(tag, results['total'])
+
+format_autolab_json(results)
\ No newline at end of file
diff --git a/examples/tmp/c02631week5/src/looping.py b/examples/tmp/c02631week5/src/looping.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ea703ab9cb00105b3bf3d8f79befcc923868252
--- /dev/null
+++ b/examples/tmp/c02631week5/src/looping.py
@@ -0,0 +1,202 @@
+# 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/tmp/c02631week5/src/looping_tests_grade.py b/examples/tmp/c02631week5/src/looping_tests_grade.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e88d8efa8f18f1bb256bda6ab57e41f2702665e
--- /dev/null
+++ b/examples/tmp/c02631week5/src/looping_tests_grade.py
@@ -0,0 +1,4 @@
+# looping_tests.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/tmp/c02631week5/writeup/writeup.html b/examples/tmp/c02631week5/writeup/writeup.html
new file mode 100644
index 0000000000000000000000000000000000000000..d81ace4b8563a838e174c23b501294628c389eb0
--- /dev/null
+++ b/examples/tmp/c02631week5/writeup/writeup.html
@@ -0,0 +1,5 @@
+
+    <html><body>
+    To hand in this assignment, upload the file <b>looping.py</b>
+    </body></html>    
+    
\ No newline at end of file
diff --git a/src/unitgrade_private/autolab/autolab.py b/src/unitgrade_private/autolab/autolab.py
index dee673b593ac0aed3234fe77d3079104c3ab564c..2de93dfce12df28dbe2d19680f07c8a415b5b732 100644
--- a/src/unitgrade_private/autolab/autolab.py
+++ b/src/unitgrade_private/autolab/autolab.py
@@ -73,11 +73,13 @@ def paths2report(base_path, report_file):
 def run_relative(file, base):
     relative = os.path.relpath(file, base)
     mod = os.path.normpath(relative)[:-3].split(os.sep)
+    print(mod)
     for pyver in ["python", "python3", "python3.9"]:
-        code = os.system(f"cd {base} && {pyver} -m {'.'.join(mod)}")
+        cmd = f"cd {base} && {pyver} -m {'.'.join(mod)}"
+        code = os.system(cmd)
         if code == 0:
             return code
-    raise Exception("Could not run the file", file, "in dir", dir)
+    raise Exception("Could not run the file", file, "in dir", base, "using code", cmd)
 
 def new_deploy_assignment(base_name, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STUDENT_BASE,
                           STUDENT_GRADE_FILE = None, # Defaults to instructor grade file.
@@ -89,6 +91,9 @@ def new_deploy_assignment(base_name, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STU
                           description=None):
     if STUDENT_GRADE_FILE is None:
         STUDENT_GRADE_FILE = INSTRUCTOR_GRADE_FILE
+        run_relative(STUDENT_GRADE_FILE, INSTRUCTOR_BASE) # Generate token in the instructor-directory. The student directory will not work.
+    else:
+        run_relative(STUDENT_GRADE_FILE, STUDENT_BASE)
 
     """ Check we got correct paths. """
     assert os.path.isfile(INSTRUCTOR_GRADE_FILE)
@@ -128,7 +133,6 @@ def new_deploy_assignment(base_name, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STU
     ss = ", ".join([f'"{t}": {s}' for t, s in sc])
     scores = '{"scores": {' + ss + '}}'
 
-    run_relative(STUDENT_GRADE_FILE, STUDENT_BASE)
 
     # =======
     #     problems.append(dict(name='Unitgrade score', description='Automatic score as computed using the _grade.py script', max_score=total_, optional='false'))
@@ -172,7 +176,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STU
         '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,
+        'src_files_to_handout': ['driver_python.py', handin_filename, # 'student_sources.zip',
                                  os.path.basename(docker_helpers.__file__),
                                  os.path.basename(INSTRUCTOR_GRADE_FILE),
                                  student_token_src_filename],  # Remove tname later; it is the upload.
@@ -208,7 +212,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STU
     # zip_base_dir = pathlib.Path(os.path.relpath(STUDENT_GRADE_FILE, STUDENT_BASE)).parent
     zip_base_dir = pathlib.Path(os.path.relpath(INSTRUCTOR_GRADE_FILE, INSTRUCTOR_BASE)).parent
     # Alternatively: Unzip the sources directory and hand it out.
-    shutil.make_archive(LAB_DEST + '/src/student_sources', 'zip', root_dir=STUDENT_BASE, base_dir=str(zip_base_dir))
+    # shutil.make_archive(LAB_DEST + '/src/student_sources', 'zip', root_dir=STUDENT_BASE, base_dir=str(zip_base_dir))
     print("We made it")
 
     shutil.copyfile(docker_helpers.__file__, f"{LAB_DEST}/src/{os.path.basename(docker_helpers.__file__)}")
@@ -237,7 +241,7 @@ def new_deploy_assignment(base_name, INSTRUCTOR_BASE, INSTRUCTOR_GRADE_FILE, STU
     with open(LAB_DEST + "/writeup/writeup.html", 'w') as f:
         f.write(writeup)
 
-    shutil.make_archive(output_tar[:-4], 'tar', root_dir=COURSES_BASE, base_dir=base_name)
+    # shutil.make_archive(output_tar[:-4], 'tar', root_dir=COURSES_BASE, base_dir=base_name)
     print("Log in to autolab, go to 'install assessment', upload the tar file", output_tar)
     # Lets try an alternative creation procedure.
     if os.path.exists(f"{LAB_DEST}/{base_name}-handout"):
diff --git a/src/unitgrade_private/autolab/lab_template/Makefile b/src/unitgrade_private/autolab/lab_template/Makefile
index 2e2158af2ed5e96f1412a880288e75c5d7a0f1df..e2228540a42b779831c7345fc123372fc32ef7ac 100644
--- a/src/unitgrade_private/autolab/lab_template/Makefile
+++ b/src/unitgrade_private/autolab/lab_template/Makefile
@@ -18,8 +18,10 @@ handout:
 
 handout-tarfile: handout
 	# Build *-handout.tar and autograde.tar
-	tar cvf {{ base_name }}-handout.tar {{ base_name }}-handout
-	cp -p {{ base_name }}-handout.tar autograde.tar
+	# tar cvf {{ base_name }}-handout.tar {{ base_name }}-handout
+	# cp -p {{ base_name }}-handout.tar autograde.tar
+	tar cvf autograde.tar {{ base_name }}-handout
+	# cp -p {{ base_name }}-handout.tar autograde.tar
 
 clean:
 	# Clean the entire lab directory tree.  Note that you can run
diff --git a/src/unitgrade_private/autolab/lab_template/hello.yml b/src/unitgrade_private/autolab/lab_template/hello.yml
index a2e18477b8336fb537dfa2c8a84ef839ba4d45a9..333e36393d021ba13629a68899532a4f770ad75b 100644
--- a/src/unitgrade_private/autolab/lab_template/hello.yml
+++ b/src/unitgrade_private/autolab/lab_template/hello.yml
@@ -3,11 +3,11 @@
 general:
   name: {{ base_name }}
   description: '{{description}}'
-  display_name: {{ display_name }}
+  display_name: '{{ display_name }}'
   handin_filename: {{ handin_filename }}
   handin_directory: handin
   max_grace_days: 0
-  handout: {{ base_name }}-handout.tar
+  handout: {{ base_name }}-handout.zip
   writeup: writeup/writeup.html
   max_submissions: -1
   disable_handins: false