


CPython's Intriguing Equivalence in Object Identification
In CPython, the enigmatic behavior of id({}) == id({}) and id([]) == id([]) often puzzles developers. While immutability may explain the equivalence in the case of tuples, the rationale for mutable objects like dictionaries and lists is less evident.
Unveiling the Mystery
According to experts, CPython's memory allocation mechanism plays a significant role in this behavior. When id({}) is invoked, a new dictionary is created and passed to the id function. However, the id function merely captures the dictionary's memory location before discarding the object itself. If a second id({}) is called shortly after, the newly created dictionary may happen to reside in the same memory location as the first one. Since id in CPython uses the memory location as the object identifier, the two dictionaries end up with the same id.
Mutability and Object Lifetime
Mutability does not directly impact this phenomenon. Rather, the caching of literal objects within code objects is the key factor. Code objects in the same scope (e.g., a function body) reuse the same integer, string, and tuple literals throughout their lifetime. However, mutable objects are dynamically created and modified at runtime, preventing reuse.
Ephemeral Identity
In essence, an object's id is unique only during its lifetime. Once the object is destroyed or before it is created, its id may be reused by subsequent objects. This behavior is not peculiar to mutable objects but applies to all objects in general.
Practical Implications
This understanding has important practical implications. When comparing objects, it is crucial to recognize the transient nature of object identity. Relying solely on id comparisons can lead to erroneous conclusions, especially in code involving object creation and destruction.
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