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News & links about Python programming.
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How We Made Jupyter Notebooks Load 10 Times Faster

When we received feedback our Notebooks UI was taking too long too load, our engineers dove into ways to improve the developer experience — bringing some load times from 30 seconds down to less than one.

https://www.singlestore.com/blog/how-we-made-notebooks-load-10-times-faster/
LightAPI

LightApi is a lightweight API framework designed for rapid development of RESTful APIs in Python. It provides a simple and intuitive interface for defining endpoints and handling HTTP requests without the need for complex configuration or dependencies.

https://github.com/iklobato/LightAPI
Injecting syscall faults in Python and Ruby

The post introduces a Python and Ruby library called Cirron that allows developers to inject syscall faults for testing purposes. It demonstrates how to use Cirron to simulate various error conditions, such as disk space issues and network timeouts, by modifying syscall behavior, enabling more robust testing of error handling in software.

https://blog.mattstuchlik.com/2024/09/08/injecting-syscall-faults.html
Avoid These 7 Common OOP Mistakes in Python

The video discusses common bad practices in Python object-oriented programming and how to avoid them. It covers issues like using classes unnecessarily instead of functions, overusing mixins, and excessive encapsulation, while providing practical examples and alternatives to improve code structure and readability.

https://www.youtube.com/watch?v=yFLY0SVutgM
Deep learning compilers and how the sausage is made

A series of discussions focused on deep learning compilers and machine learning. It covers how deep learning models are optimized and deployed for practical use cases. The content dives into topics relevant for developers and engineers working with AI frameworks and model performance optimization.

https://www.youtube.com/playlist?list=PLaMu-SDt_RB7ImARcTT_Wjypwx2vBIBen
Some tricks with UV

UV can be seen as an alternative to pip, but that might be a limiting way to think about the tool. Instead of looking at faster builds, which are still super nice, it might also make sense to rethink the stuff that we might be able to do from Python going forward.

https://www.youtube.com/watch?v=jXWIxk2brfk