The difference is about object identity, not integer value: is asks whether two references point to the same object, while == asks whether their values are equal. Python may reuse integer objects, but the language does not guarantee that it will. The familiar 256/257 example is therefore not a rule to build code around.
What “256 is 256” means in Python
In an expression such as a is b, Python tests whether a and b refer to one and the same object. By contrast, a == b tests whether their values compare equal. Two different integer objects can represent the same number, so identity and equality are separate questions.
Integers are immutable. An implementation can reuse an existing integer object when the same value is requested again; when it does, separate references may be identical. The Python data model says such reuse of immutable objects depends on the implementation and must not be relied on. Python data model
Why the 256/257 example has a caveat
The Python FAQ uses a familiar example in which identity appears to behave differently for 256 and 257. It also warns that integer constants are not guaranteed to be singletons. That example illustrates a possible observation, not a language promise or a permanent cache boundary. Python FAQ
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For a version-specific illustration, the Python 3.15.0rc2 C API documentation says CPython keeps an array of integer objects from -5 through 1024, and that creating an integer in this range returns a reference to the existing object. The documentation explicitly calls this a CPython implementation detail. It does not establish behavior for every Python implementation or every version. CPython C API: Integer Objects
Those two documentation examples should not be collapsed into the claim that 256 is a universal upper limit, or that every value above 256 must be a distinct object. Results can also depend on details such as compilation and constant handling. If a particular identity result matters for debugging, identify the implementation and version and test that runtime; do not generalize from a one-line REPL observation.
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Use equality for integer values
When the question is whether two numbers have the same value, use ==:
a = 257
b = 257
print(a == b) # True: the values are equal
print(a is b) # Identity is not a portable value comparisonThe first comparison expresses the intended numeric test. The second asks an unrelated question about object reuse, whose answer is not guaranteed by Python’s language rules.
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When identity checks are appropriate
Use is when your logic is specifically about whether a reference is a particular object. Common cases include checking for None or comparing with a private sentinel object. The Python FAQ recommends identity checks for these kinds of known singleton objects, but cautions against using them for constants such as integers and strings. Python FAQ
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- Numeric values: use
==. - Absence represented by
None: useis None. - A private sentinel that your code deliberately creates and shares: use
isto check for that exact object.
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