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Advanced Python

Python decorators, metaprogramming, descriptors, GIL mechanics, asyncio asynchronous event loop, and C extension modules.

1Decorators, Closures & Function Metaprogramming

Lexical closures, closure cell internals, decorator desugaring, functools.wraps, and class-based decorators.

Decorators, Closures & Function Metaprogramming

Master first-class function mechanics, lexical closures, decorator factories, and metadata preservation.

Decorators, Closures & Function Metaprogramming

Master Python function metaprogramming foundations, analyzing lexical closures, closure cell heap storage, decorator syntactic desugaring, and functools.wraps metadata preservation.

2Descriptors, Metaclasses & Dynamic Object Creation

Descriptor protocol, data vs non-data descriptors, attribute lookup order, metaclasses, and __init_subclass__.

Descriptors, Metaclasses & Dynamic Object Creation

Understand CPython attribute lookup order, the descriptor protocol (__get__, __set__), and class creation via metaclasses.

Descriptors, Metaclasses & Dynamic Object Creation

Explore CPython attribute resolution order, master data versus non-data descriptors, customize class allocation with metaclasses, and construct declarative ORM-style schemas.

3GIL Mechanics, Concurrency & Asyncio Event Loops

Global Interpreter Lock (GIL), thread switching intervals, generators to coroutines, and asyncio event loop internals.

GIL Mechanics, Concurrency & Asyncio Event Loops

Master CPython GIL mechanics, evaluate threading versus multiprocessing, and understand cooperative asyncio event loops.

GIL Mechanics, Concurrency & Asyncio Event Loops

Analyze CPython GIL internals, evaluate reference counting protection, understand preemptive thread switching, and implement cooperative single-threaded asyncio event loops.

4Memory Profiling, C-Extensions & Performance

PyMalloc arena/pool/block memory architecture, __slots__ optimization, cyclic GC tri-color marking, and C extensions.

Memory Profiling, C-Extensions & Performance

Master CPython PyMalloc architecture, __slots__ memory reduction, generational garbage collection, and native C extension acceleration.

Memory Profiling, C-Extensions & Performance

Inspect CPython PyMalloc memory pools, optimize object footprint with __slots__, diagnose generational cyclic garbage collection leaks, and compile native C-extension accelerators.