WEEK 4: Updating Decorator, Exploring Lazy Loading, and Code Reviews

Hello everyone,

Welcome again to my Google summer of code 2024 (GSoC’ 2024) journey 2024!. This week, I focused on updating the warn_on_args_to_kwargs decorator, applying it across multiple modules, exploring lazy loading, and continuing with code reviews.

Updating the warn_on_args_to_kwargs decorator

Based on feedback from my mentor Serge Koudoro and peers Iñigo Tellaetxe Elorriaga, Robin Roy, Kaustav Deka, I refined the warn_on_args_to_kwargs decorator and its associated unit tests:

1. Improvements:

   • Added conditions to verify if the values of from_version, until_version, and the current version of FURY are respected. This includes handling cases where from_version is greater than the current version of FURY, until_version is less than the current version of FURY, and until_version is greater than or equal to the current version of FURY.

   • Ensured the decorator and tests cover a broader range of edge cases.

   • Enhanced the warning messages for better clarity and guidance.

2. Doctest Updates:

   • Updated the doctest considering the values of from_version and until_version.

   • Moved the doctest from the def decorator() function to the root function.

3. Unit Tests:

def test_warn_on_args_to_kwargs():
    @warn_on_args_to_kwargs()
    def func(a, b, *, c, d=4, e=5):
        return a + b + c + d + e

# if FURY_CURRENT_VERSION is less than from_version
fury.__version__ = "0.0.0"
npt.assert_equal(func(1, 2, 3, 4, 5), 15)
npt.assert_equal(func(1, 2, c=3, d=4, e=5), 15)
npt.assert_raises(TypeError, func, 1, 3)

• This ensures robust validation and helps catch potential issues early.

Applying the warn_on_args_to_kwargs Decorator

This week, I applied the warn_on_args_to_kwargs decorator to several modules, ensuring consistent usage and improved code quality. The modules updated include:

• actors

• ui

• animation

• shares

• data

For each module, I opened a pull request to track the changes and facilitate reviews:

• actors: fury-gl/fury#898

• animation: fury-gl/fury#899

• data: fury-gl/fury#900

• shares: fury-gl/fury#901

• ui: fury-gl/fury#902

Exploring lazy loading

In order to optimize performance, I’ve started exploring and implementing lazy loading. This week, the focus was on the following points:

• Getting to grips with how the lazy loader works

• Implementing some small script to understand how the lazy loader works

• I also read the SPEC1 document available at SPEC1

• Understanding the benefits of lazy loading and how it can be applied to the FURY code base

• Planning the integration of lazy loading into the FURY code base

Code sample: https://gist.github.com/WassCodeur/98297d7a59b27979d27945760e3ffb10

Peer Code Review

This week, I continued to dedicate time to reviewing the code of my peers. Specifically, I reviewed Kaustav Deka’s work, providing constructive feedback and suggestions for improvement. You can view the pull request here: dipy/dipy#3239.

Acknowledgements

I am deeply grateful to my classmates Iñigo Tellaetxe Elorriaga, Robin Roy, Kaustav Deka for their continuous support and insightful suggestions. Special thanks to my mentor, Serge Koudoro , whose expertise and guidance have been invaluable in navigating these technical challenges.

Did I get stuck?

Yes, I was a bit confused about understanding lazy loader, but thanks to the help of my mentor Serge Koudoro , I was able to understand it better.

What’s next?

For the upcoming week, I plan to:

• Implement lazy loading in the FURY code base

• Continue refining the warn_on_args_to_kwargs decorator based on feedback

• Engage in more code reviews to support my peers

• Prepare to working on the FURY website to improve the documentation and user experience

Thank you for following my progress. Your feedback is always welcome.

WEEK 3: Refinements and Further Enhancements   Week 4: Pipeline Improvements and Taking The Bot Public!