Do these 3 things before closing this tab:
1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesIf a Python condition compares integer values, use ==, not is. The is operator checks whether two expressions refer to the same object; == checks whether their values compare equal. An integer identity test may appear to work in one case, but Python does not guarantee that equal integers are the same object.
What the operators test
Python’s expressions reference defines is and is not as object-identity comparisons: x is y is true only when x and y are the same object. The value-comparison operators include == and !=; their result depends on how the objects implement comparison.
So these expressions ask different questions:
a == b: do the values compare equal?a is b: are these references to the very same object?
Why an integer identity test can fail
Python does not guarantee that integer objects are singletons. Two expressions can produce equal integer values without referring to the same object. An is test may happen to be true in a particular expression or environment, but that observation is not a portable guarantee. The Python programming FAQ specifically advises against using identity tests for integers when you mean numeric equality.
Do not depend on a presumed integer cache range or on what a particular run happens to show. The reliable rule is to use == for numeric value comparisons.
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Repair the comparison
Change the operator when the condition is asking whether an integer has a particular value:
# Bug: asks whether result and the literal are the same object
if result is 1000:
...
# Fix: asks whether their values compare equal
if result == 1000:
...The same correction applies when comparing two integer variables, a variable and a computed result, or an integer with a literal. Choose the operator based on the question the code needs to answer, not on whether the old condition happened to pass.
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Debug the unexpected branch
- Reproduce the failure. Run the input or execution path that makes the condition choose the unexpected branch.
- Inspect the operands at the comparison. Check their runtime values and types immediately before the condition. Python’s FAQ documents
breakpoint()as a built-in entry point for pausing execution in a debugger. - Check the intended meaning. If the condition asks whether numeric values are equal, replace
iswith==. If it genuinely asks whether two references identify one object, retain an identity check. - Run the relevant checks. Test the repaired path and search nearby code for other integer comparisons written with
is. Review each match by intent rather than replacing identity checks indiscriminately.
The Python FAQ names Ruff, Pylint, and Pyflakes as tools for basic code checking. A tool can help find issues, but the FAQ does not guarantee that every tool or configuration will flag every integer identity comparison.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When is is appropriate
Identity checks are useful when identity itself is the requirement. The familiar example is checking Python’s None singleton:
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if value is None:
...A private sentinel is another suitable case:
sentinel = object()
if default is sentinel:
...The expressions reference notes that None and NotImplemented are singletons. For ordinary integer values, use equality instead. The FAQ’s concise rule is: “In most other circumstances, identity tests are inadvisable and equality tests are preferred.”
Quick Recap
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