How Does Python Handle Memory Allocation for Identical Strings?

When Does Python Allocate New Memory for Identical Strings?

Python's approach to memory allocation for identical strings is an intriguing topic that has captured the attention of programmers. As you have observed, strings that appear identical (i.e., a == b) may or may not share memory space (id(a) == id(b)). This behavior stems from the fact that Python implementations handle string allocation differently.

Each Python implementation has the flexibility to allocate immutable objects like strings in various ways. One such strategy is to maintain a cache (also known as a "Ucache") of unique strings. This Ucache serves to conserve memory by storing a single copy of each unique string. If a new identical string is encountered, rather than creating a new object, the implementation may simply reference the existing object in the Ucache.

However, when it comes to allocating strings from files or across separate functions, real-world implementations often adopt a different strategy. Searching for and identifying identical existing objects can be a time-consuming task. To avoid this overhead, implementations may opt to create new objects instead of attempting to locate and reuse existing ones.

In your specific example, loading a list of state names from a file and then reading it back in resulted in a significant increase in memory consumption. This is because the Python implementation did not attempt to identify and reuse identical strings that were already in memory. Instead, it created new objects for each string, even if the strings were identical.

It is important to note that Python's approach to string allocation can vary across implementations. Some implementations may adopt more aggressive caching strategies, while others may prioritize runtime performance over memory conservation. If you encounter situations where you suspect that excessive memory is being allocated due to identical strings, you can consider implementing your own "constants pool" mechanism to manage immutable objects and avoid potential memory bloat.

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