How Does Python Implement Its List Object, Including Memory Management and Resizing?

Implementation Details of Python's List Object

The Python programming language implements its lists as an overallocated vector of pointers to object references. Unlike a linked list, Python's list is a continuous array in memory.

To understand this further, let's delve into the Python source code:

typedef struct {
    PyObject_HEAD
    Py_ssize_t ob_size;
    PyObject **ob_item;
    Py_ssize_t allocated;
} PyListObject;

Here, ob_item is a vector of pointers to object references, representing the elements of the list. ob_size indicates the number of elements currently stored in the list, while allocated represents the current capacity of the vector.

Python's list implementation employs a strategy of incremental resizing. When the list reaches its capacity, the code in listobject.c reallocates the vector to accommodate more elements. This reallocation occurs not by doubling the size but by growing it according to the following formula:

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

where newsize is the requested size. This formula balances the need for efficiency with the potential for memory fragmentation.

It's worth noting that this implementation differs from a true dynamic array in that it doesn't shrink when elements are removed from the list. As a result, lists in Python can contain empty slots, which may have implications for performance and memory usage.

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