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From "Jarek Potiuk (Jira)" <>
Subject [jira] [Updated] (AIRFLOW-5373) Super fast pre-commit check for python2 compatibility (for cherry-picking)
Date Mon, 02 Sep 2019 01:10:00 GMT


Jarek Potiuk updated AIRFLOW-5373:
    Attachment: matches_python3.txt

> Super fast pre-commit check for python2 compatibility (for cherry-picking)
> --------------------------------------------------------------------------
>                 Key: AIRFLOW-5373
>                 URL:
>             Project: Apache Airflow
>          Issue Type: Improvement
>          Components: ci
>    Affects Versions: 1.10.5
>            Reporter: Jarek Potiuk
>            Priority: Major
>         Attachments: matches_python3.txt
> I thought about a super-fast way of protecting against bad python3 cherry-picks in our
v1-10-test branch. From the experience, it looks like we have two types of problems most often:
>  # super()
>  # python3 type annotations in definition of function parameters/return values
>  # python3 type annotations in variables
> I tried to find some good "proper" solution to check automatically if the code is python2-compliant
but surprisingly could not find anything fast and good (actually there are plenty of python3
compat checkers and auto-converters but I could not find good verification is some python3
constructs are used in python2 code).
> However it came to me that we can likely do a simple grep that should be able to catch
vast majority of those case with very limited (if at all) false positives. It turned out to
be a good idea for 1 and 2 (which is vast majority of cases I think) :
> Such simple and straigthforward regexp does the work beautifully:
> ".super\\(\\)|^\\s+def\\s*\\S*\\([^):]*:.*\\)|^\\sdef\\s*\\S*\\(.*\\):\\s*\\-\\>\\s*
> S*"
> I managed to find two actual problems - Python3 incompatibilitites in v1-10-test this
way (!!!). In master we have 830 matching lines (attached) so I think it's rather good.

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