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alexgaynor.net | ||
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ashvardanian.com
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| | | | | Python's not the fastest language out there. Developers often use tools like Boost.Python and SWIG to wrap faster native C/C++ code for Python. PyBind11 is the most popular tool for the job not the quickest. NanoBind offers improvements, but when speed really matters, we turn to pure CPython C API bindings. With StringZilla, I started with PyBind11 but switched to CPython to reduce latency. The switch did demand more coding effort, moving from modern C++17 to more basic C99, but the result is a 5x lower ... | |
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stefan-marr.de
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| | | | | A look into the implementation details of CPython's Global Interpreter Lock (GIL) and how they changed between Python 3.9 and the current development branch that will become Python 3.13. | |
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www.pypy.org
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| | | | | Last summer, Shriram Krishnamurthi asked on Twitter: "I'm curious what the current state of tracing JITs is. They used to be all the rage for a while, then I though I heard they weren't so effective, | |
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aaronluna.dev
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| | | Decorators can be a daunting topic when first encountered. While the Zen of Python states "There should be one- and preferably only one -obvious way to do it", there are many, equally valid ways to implement the same decorator. These different methods can be categorized as either function-based, class-based, or a hybrid of both. In this post I will explain the design and behavior of Python decorators and provide examples of decorators that I frequently use in my own code. | ||
