For seasoned Pythonists, library authors, and performance-minded engineers, this book goes far beyond idioms and into the mechanics that unlock real leverage. It distills hard-won practices from modern CPython to help you write systems that are faster, safer, and easier to evolve-without sacrificing clarity. If you build frameworks, data pipelines, services, or tooling and want to exploit Python's lesser-known capabilities with confidence, this guide is your map to the terrain professionals actually traverse. You'll ...
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For seasoned Pythonists, library authors, and performance-minded engineers, this book goes far beyond idioms and into the mechanics that unlock real leverage. It distills hard-won practices from modern CPython to help you write systems that are faster, safer, and easier to evolve-without sacrificing clarity. If you build frameworks, data pipelines, services, or tooling and want to exploit Python's lesser-known capabilities with confidence, this guide is your map to the terrain professionals actually traverse. You'll dissect the runtime-subinterpreters and the per-interpreter GIL, immortal objects, adaptive specialization, and vectorcall-then harness the modern typing core: parameterized aliases and type parameters (PEP 695), protocols (PEP 544), Self (PEP 673), variadic generics (PEP 646), and override checks (PEP 698). You'll master structural pattern matching for robust dispatch; exploit descriptors, __slots__, and metaclasses for high-performance, declarative object models; and architect asynchronous systems with precise task/cancellation semantics, context variables, async resource management, TaskGroup-based structured concurrency, and ExceptionGroup/except*. You'll turn the import system into a platform for plugins, use pyproject.toml and contemporary backends to ship reproducible wheels, and apply power patterns-single-dispatch and PEP 701 f-strings-for expressive, introspection-friendly APIs. Prerequisites: strong Python experience and familiarity with asyncio and type hints. The book favors verifiable techniques-type-checked, benchmarked, and tool-friendly-pairing deep explanations with pragmatic checklists, failure modes, and migration advice for real codebases.
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