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CPython A Complete Guide to CPython's Architecture and Performance [#990906]
Free Download CPython: A Complete Guide to CPython's Architecture and Performance
English | 2025 | ISBN: 9798868817687 | 313 pages | PDF | 9.97 MB
Deep Dive CPython explores the internal mechanics of CPython, the widely used Python interpreter written in C. Starting with a practical guide on downloading and compiling the CPython source, this book is perfect for developers eager to understand Python's behaviour at a fundamental level.
The book takes readers from basic concepts to complex details with a systematic breakdown of core components. It covers everything from CPython's data structures like PyObject and PyTypeObject to object lifecycle management, giving insight into memory allocation and object reference counting. Each chapter illustrates CPython's architecture, such as Python's "everything is an object" philosophy, list handling, string manipulation, and dictionary operations. Readers will explore Python's REPL modifications, string internals, and custom type creation with practical examples, like crafting a "backflipping" PyKitty_Type. Detailed sections on Python's virtual machine operations, bytecode generation, and exception handling enrich readers' understanding of how Python code is parsed, compiled, and executed.
This book is a thorough guide for readers who want to go beyond basic Python use and understand how it works internally. Covering complex concepts like generators, iterators, descriptors, and metaclasses, this book equips readers with a thorough grasp of Python's performance optimization and design complexities.
What you will learn:
How to download, compile, and modify CPython's source code
Gain insight into fundamental structures like PyObject and PyTypeObject,
Understand Python's detailed handling of lists, strings, dictionaries, and the REPL environment.
What are bytecode generation, custom types, and the inner workings of Python's virtual machine.
Who this book is for:
Python programmers aiming to gain a deeper understanding of Python's internals and move beyond standard usage, as well as software professionals interested in CPython's C-based implementation and core architecture.
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