Upgrade to Python3 #1014
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Upgrade to Python3 #1014
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- Created test suite for parsing module #986 -> tests Validator -> tests Digestor -> tests utils - Updated schools mappers to use new directory structure -> looks for courses.py, evals.py, textbooks.py -> Moved school settings to school local config files - Restructured logging infrastructure -> Use logging config yaml files instead of Python dicts -> Removed custom loggers written in parsing module -> Use pythong logging module -> load loggers in __init__.py -> Incorporated updates into makeschool command -> TODO - email notification logger on parsing error #552 - Minor API changes to parsing module -> pass year_and_terms_filter dictionary to start method of parse -> Load sensitive.py information inside __new__ -> moved and refactored much of extractor into utils -> Parsing command arguments use composable actions -> Iterated on parsing inline documentation -> removed yet iterated on extract_info - (partially) added uoft to parsing infrastructure - Added sensitive.py to .gitignore - fixed absolute file import errors to pass doc build ++ many more things that I dont want to enumerate :-)
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Version Python 3.5 The heavy lifting was done by: `2to3 -w -n -f all -f idiom .` Then some fixes were made to coerce float/into conversion. As well as updated all packages (except Django) to latest version. NOTE: some packages were removed and replaced if they did not support Py3 -> due to pip not resolving all dependencies some pip installs were added manually to travisCI Python3 initializes django modules in different order, issues arose in school_mappers in relation to importing parsers. Thus parser import was moved into the ingest command.
In Python3 all classes are __new style__ classes
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Version Python 3.5
The heavy lifting was done by:
2to3 -w -n -f all -f idioms .Then some fixes were made to coerce float/into conversion.
As well as updated all packages (except Django) to latest version.
NOTE: some packages were removed and replaced if they did not support Py3
-> SciPy and Numpy are capatilized in order to come before sckitlearn
FIXME
@alexahn917 there is a conflict with string/bytes in a numpy operation in the vectorizer. I couldn't easily fix so Im leaving it to you. Let me know if you wanna talk.
@alexahn917 the update to Numpy 1.13.1 created a minor error with some de-pickling. We shouldnt have any static pickle files. On deploy we can pickle what we need so its cached instead of hardcoding pickle objects.
For now I
return 0on the problem function (see FIXME in code)Testing
Test coverage is not exhaustive and this version should be internally poked and prodded before release. From what I can see, however, everything I have tested works.