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Deep Reads › CPython Internals › 8. Performance Internals ›

79. Memory Locality

79. Memory Locality Memory locality is the degree to which a program accesses memory that is close together in time and space. CPython is a dynamic object runtime. Most Python values are heap-allocated objects, accessed through pointers. This gives Python flexibility, but it also means execution often follows chains of references through memory. Example: total += obj.value At the machine level, this may touch: current frame evaluation stack local variable...
cpython python internals performance memory
Deep Reads › CPython Internals › 10. Advanced Topics ›

93. Immortal Objects

93. Immortal Objects Immortal objects are objects whose lifetime is treated as effectively permanent by the CPython runtime. Their reference counts no longer behave like ordinary objects, and the interpreter avoids many normal reference counting operations on them. Immortal objects were introduced as part of larger runtime optimization work, especially in support of free-threaded CPython and multicore scalability. The main idea is simple: some objects exist for the entire interpreter...
cpython python internals memory
Wiki › Algorithms › 02. Data Structures › 1. Core Data Structures and Operations › 1.1 Arrays and Dynamic Arrays ›

Array Copying

Array Copying Array copying creates another array with the same elements. The copy may duplicate only the element references, or it may recursively duplicate the objects stored inside the array. You use it when a later mutation should not change the original array storage. Problem Given an array $A$ of length $n$, create a new array $B$ such that: $$ B[i] = A[i] $$ for every valid index $i$. Algorithm...
data-structures arrays copying memory
Deep Reads › CPython Internals › 7. C API and Extensions ›

62. Reference Ownership Rules

62. Reference Ownership Rules Reference ownership is the core memory discipline of the Python C API. Every PyObject * points to a Python object whose lifetime is controlled by a reference count. Native extension code must follow ownership rules exactly. A single missing Py_DECREF can leak memory. A single extra Py_DECREF can free a live object and corrupt the interpreter. 62.1 Why Ownership Rules Exist CPython stores a reference count...
cpython python internals c-api memory
Deep Reads › CPython Internals › 6. Standard Library Interfaces to the Core ›

55. `gc`

55. gc The gc module exposes CPython’s cyclic garbage collector. It gives Python code a way to inspect, configure, disable, enable, and manually run the collector that handles unreachable reference cycles. CPython’s main memory management mechanism is reference counting. Most objects are destroyed as soon as their reference count reaches zero. The cyclic garbage collector exists for the cases reference counting cannot solve: groups of objects that keep each other...
cpython python internals memory