Contributing to Core Python

Contributing to Core Python: An Opinionated Guide for Scientists and Data Scientists

Presented to Data Umbrella Meetup on November 10, 2020.

Transcript

1. Contributing to Core Python
   An Opinionated Guide for Scientists and Data Scientists
   1
   Carol Willing
   Twitter: @WillingCarol
   
   GitHub: @willingc
   Data Umbrella Meetup
   November 10, 2020
   

   View Slide

2. Core Python = CPython
   

   View Slide

3. Data and Science
   • Primary Audience
   
   • Data scientists
   
   • Scientists
   
   • Data Engineers
   
   • Folks who may get value but are not the
   focus of this talk
   
   • Computer scientists
   
   • Compiler engineers
   
   • Operating system experts
   Contributing to CPython
   Climate Change
   ECMWF
   

   View Slide

4. Contributing to Core Python
   An opinionated approach for scientists and data scientists
   Core Python Today
   
   Comparing Core Python to Data / Science Projects
   
   Getting Started
   
   

   View Slide

5. Beyond BDFL
   

   View Slide

6. Steering Council
   Barry Warsaw
   Brett Cannon
   Carol Willing
   Thomas Wouters
   Victor Stinner
   

   View Slide

7. PEP 13: Python Language Governance
   ‣ Quality and Stability
   ‣ Contributing accessible, inclusive, sustainable
   ‣ Core team and PSF relationship
   ‣ Decision making processes for PEPs
   ‣ Seek consensus
   

   View Slide

8. Which contributions are needed
   

   View Slide

9. Python Software Foundation (python.org)
   The mission of the Python Software Foundation is to promote,
   protect, and advance the Python programming language,
   and to support and facilitate the growth of a diverse and
   international community of Python programmers.
   

   View Slide

10. Ways to Contribute
    More ways than writing new code
    • Add new code with backward compatibility
    
    • Maintain security and improve core development workflow
    
    • Writing and running tests
    
    • Writing and editing documentation
    
    • Triaging bugs for reproducibility
    
    • Reviewing PRs
    
    • Share your knowledge with the community (talks, blog posts, and meetups)
    

    View Slide

11. Comparing
    Projects
    

    View Slide

12. CPython and Data/Scientific Projects
    • GitHub workflow
    
    • Pull requests
    
    • Code Review
    
    • Automated Testing / CI
    What's similar
    

    View Slide

13. CPython and Data/Scientific Projects
    • New feature velocity
    
    • Use beyond data / science
    
    • Project Age and Lifecycle (30
    years vs <10 years)
    
    • Stability and backward
    compatibility
    
    • Context of use: CPython is a
    foundation for projects to be built
    upon
    What differs
    

    View Slide

14. Getting
    Started
    and continuing to contribute
    

    View Slide

15. First time contributors to open source
    Consider Python projects in the Scientific / Data community
    

    View Slide

16. Mindset
    Getting set for success
    • Check your intent or why you want to contribute
    
    • Set a goal
    
    • Limit scope of your initial impact
    
    • Practice patience
    
    • Be persistent
    

    View Slide

17. Common reasons for contributing
    These are just a few of the many reasons.
    • Fix a possible bug
    
    • Improve the documentation for the next person
    
    • Thought it would be cool
    
    • Wanted to understand more about how things work
    
    • Strengthen development skills
    

    View Slide

18. Dev Guide
    devguide.python.org
    devguide.python.org
    

    View Slide

19. Helpful prerequisites
    This will improve your contribution experience.
    • Take time to understand CPython's culture
    
    • Understand difference between core language and standard library
    
    • Remember most core developers are volunteers
    
    • Understand Git and GitHub workflow
    
    • Familiarity with Python (C is not necessary)
    

    View Slide

20. Build CPython
    Dev Guide Quick Reference Steps 1 - 3
    • Fork and clone source code from https://github.com/python/cpython
    
    • Use the C compiler to configure and build Python
    
    • Unix/Linux/macOS
    
    • Windows
    https://devguide.python.org/#quick-reference
    ./configure --with-pydebug && make -j
    PCbuild\build.bat -e -d
    

    View Slide

21. Run the tests
    Dev Guide Quick Reference Step 4
    • From the command line, run the tests
    
    • Unix/Linux
    
    • Mac
    
    • Windows
    https://devguide.python.org/#quick-reference
    python.exe -m test
    python.bat -m test
    python -m test
    

    View Slide

22. Congrats on building and testing
    Dev Guide will help answer additional questions on contributing
    • Changes are submitted as GitHub pull requests
    
    • CI will run the automated tests
    
    • Wait for review
    
    • Address feedback
    
    • Core dev review and hopefully merge
    

    View Slide

23. Learn about CPython Internals
    23
    

    View Slide

24. Resources
    • Anthony Shaw's blog post and/
    or book on CPython internals
    
    • Core developer websites
    
    • Guido
    
    • Victor Stinner
    
    • Brett Cannon
    
    • CPython sprints
    
    • PyCon talks by core developers
    
    • My PyCon 2015 talk
    
    • Mariatta
    
    • Victor
    
    • AsyncIO: Lukasz on YouTube
    
    

    View Slide

25. Our time is limited so...
    25
    

    View Slide

26. Community is key
    26
    Python Brasil official photo.
    The sign represents Python in BSL (Brazilian Sign Language),
    made by Amanda and Sávio at Python Sul 2018
    https://pyfound.blogspot.com/2019/02/python-brasil-people-technology.html
    PyLadiesBRConf official photo
    PyLadiesBRConf official photo
    

    View Slide

27. Happy contributing!
    Join the discussion:
    discuss.python.org
    

    View Slide

28. 28
    Thank you
    

    View Slide