Pop the champagne, Python 3.15 is here!
InfoWorld ·
The best Python yet isn’t just faster than before. It’s also smarter at telling you what’s wrong, better at letting you profile applications, and loaded with new language features to give you a better programming experience. Top picks for Python readers on InfoWorld The best new features in Python 3.15 Python 3.15 is now GA, and it’s the best Python yet. Get your hands on its improved JIT compilation, lazy imports, more detailed errors, and all-new profiling superpowers. Python’s new frozendict type, demonstrated Ever wanted to use a Python dictionary where you needed an immutable type, like a dictionary key? The new frozendict type lets you do exactly that. This video demonstrates its powers and usefulness, along with its quirks and eccentricities. Speed-boost Python with lazy imports If you rely on imports with slow startup times, you can quit drumming your fingers or coming up with clumsy workarounds. Python’s new lazy import feature defers the delays. Get started with Python’s new native JIT Although still in its early stages, Python’s native JIT is yielding bigger performance gains with each passing revision. Learn how your Python code can speed up by as much as 20% with this feature, without your needing to change anything. More good reads and Python updates elsewhere What we learned about Rust for CPython at the Python Language Summing 2026 Rust is becoming part of the CPython codebase, chiefly for rewriting specific components like the zlib module. This article explains how that project is going (slowly and carefully), and what its goals are. Making np.searchsorted up to 25× faster in NumPy 2.5 A fascinating deep dive into how NumPy’s binary search algorithm got a major performance boost. The bigger the array, the bigger the payoffs, especially when working with inputs bigger than your L2 cache. Lifeguard: Static analysis for lazy imports in Python Lazy imports are a great new feature, but they behave strangely in some corner-case scenarios. This tool scans codebases to determine if your code is fully lazy-import safe. Polars 2.0 is here This top-class dataframes library for Python just notched a major point release, which brings A-list support for SQL queries and tons of performance improvements overall.