How Does Python Implement Its Lists Internally?

Python List Implementation: Unraveling the Enigma

Python lists, an integral aspect of the language, store collections of elements of any type. Many developers have speculated about their underlying implementation, but definitive answers have remained elusive. This article delves into the depths of Python's C code to uncover the truth behind list realization.

Examining the header file listobject.h, we discover the fundamental structure of a Python list:

typedef struct {
    PyObject_HEAD
    Py_ssize_t ob_size;

    /* Vector of pointers to list elements.  list[0] is ob_item[0], etc. */
    PyObject **ob_item;

    /* ob_item contains space for 'allocated' elements.  The number
     * currently in use is ob_size.
     * Invariants:
     *     0 ≤ ob_size ≤ allocated
     *     len(list) == ob_size
     *     ob_item == NULL implies ob_size == allocated == 0
     */
    Py_ssize_t allocated;
} PyListObject;

This code reveals that Python lists are indeed implemented as vectors or arrays. Specifically, they utilize an overallocation strategy, which means that memory is allocated in advance for potential additions to the list.

If the list reaches its allocated limit, the resize code in listobject.c expands the array by allocating:

new_allocated = (newsize >> 3) + (newsize < 9 ? 3 : 6);
new_allocated += newsize;

where newsize represents the requested size, whether for extending by an arbitrary number of elements or simply appending one.

Furthermore, the Python FAQ provides additional insights into the list implementation, highlighting its dynamic and efficient nature, capable of resizing as needed while preserving performance.

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