When Does Python Allocate New Memory for Identical Strings?

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Release: 2024-10-19 11:56:02
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When Does Python Allocate New Memory for Identical Strings?

Python's String Memory Allocation: Unveiling the Mystery

Python's efficient handling of identical strings through memory optimization has been a topic of discussion among developers. However, understanding the precise circumstances under which Python allocates new memory for identical strings remains elusive.

The Python interpreter utilizes two distinct categories of strings: unique strings and ordinary strings. Unique strings are stored in a unique cache (Ucache), effectively saving memory and expediting string equality comparisons. On the other hand, ordinary strings, known as Ostrings, can be stored multiple times in memory.

String allocation in Python depends on implementation-specific optimizations, prioritizing efficiency. Creating a new object when locating an existing equal object appears to be a time-consuming operation. Consequently, implementations generally favor creating new objects or reusing existing ones based on the likelihood of finding a match quickly.

When multiple occurrences of the same string literal appear within a single function, Python typically employs the "new reference to same object" strategy. This approach is practical as it can identify and avoid duplicates within a function's constant pool. However, extending this strategy across separate functions becomes more challenging, prompting implementations to either abstain from the optimization altogether or limit its application to certain scenarios.

Reading data from files introduces another layer of complexity. Python implementations generally do not make the effort to identify potential duplicates when processing string input from files. This approach aims to maintain a reasonable tradeoff between runtime performance and memory consumption.

Developers can create their own "constants-pool" strategy to address memory optimization concerns in scenarios where they anticipate large, duplicate-prone immutable objects. Python's intern() function is useful for string interning, enabling developers to manually identify and reuse existing string objects.

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