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This article dissects the CPython implementation of three dictionary methods—get, setdefault, and popitem—showing example usage, walking through the C source code, explaining hash look‑ups, entry handling, and the subtle state changes that occur when keys are missing or removed.
This article dissects CPython's dictionary implementation, explaining how a PyDictObject and its PyDictKeysObject are allocated, how method groups map to Python magic methods, and the detailed C logic for inserting, updating, and retrieving key‑value pairs, including __missing__ handling.
This article explains the WSGI/ASGI ecosystem, compares uWSGI, Nginx, and uvicorn, and then introduces Granian—a Rust‑written ASGI server that supports WSGI, ASGI, and RSGI, offering superior performance, HTTP/2‑3 support, and easy integration for Python web applications.
This article dissects Python's dictionary implementation, explaining the PyDictObject layout, the combined and split hash‑table designs, memory‑optimisation techniques, insertion and lookup processes, ordered iteration, and precise memory‑size calculations with concrete code examples.
The article explains how Python maps a dict key to a hash‑table slot, the two classic collision‑resolution strategies (separate chaining and open addressing), why Python uses an iterative probing function, and walks through the core C functions that perform the lookup and slot‑finding logic.
An object is hashable in Python if it is immutable and implements __eq__, allowing it to serve as a dictionary key; the hash value is normally derived from the object's address unless __hash__ is overridden, and equal objects must share identical hash values, influencing dictionary indexing and collision handling.
The article explains how Python's dict uses a hash table to provide constant‑time insertion, deletion, and lookup, demonstrates its speed advantage over lists with benchmarks, and details the handling of collisions, resizing, and the underlying array‑based implementation.
This article explains Python tuples as immutable list subsets, details their C‑level struct layout, creation and deallocation processes, the internal freelist cache for lengths up to 20, performance advantages over lists, and the special handling of the empty tuple singleton.
This article walks through the CPython source code that defines list’s built‑in methods—append, insert, pop, index, count, remove, reverse, clear, and copy—explaining how each method is wired into the type object, the underlying C logic, time‑complexity characteristics, and common pitfalls such as reference‑count handling and shallow versus deep copying.
The article explains the various sequence‑type operations that Python lists provide—concatenation, repetition, indexing, slicing, and element assignment—detailing how each is realized in CPython through the tp_as_sequence and tp_as_mapping slots and the corresponding C functions such as list_concat, list_repeat, list_subscript, and list_ass_subscript.
