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Check whether a list contains a value
Python’s in and not in operators test membership. For built-in sequences such as lists and tuples, a match is found when an element is identical to the searched value or equal to it.
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values = [10, 42, 99]
if 42 in values:
print("found")The condition is True, so the example prints found. To test for absence, write 42 not in values.
See the Python language reference for the membership operators and their semantics.
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How membership differs by container
The same syntax can ask different membership questions depending on the container. In a dictionary, in checks keys, not values:
record = {"name": "Ada", "role": "engineer"}
"name" in record # True: checks keys
"Ada" in record.values() # True: checks valuesIf you need to perform repeated membership checks, a set or dictionary may be a more suitable structure when its membership semantics fit your task. Choose based on what you need to store and check; the syntax alone does not make these containers interchangeable.
Python arrays and elementwise conditions
For a NumPy array, value in array_values asks whether the scalar is a member. NumPy documents ndarray.__contains__ as returning bool(key in self).
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(array_values > 10).any() # True if at least one element is greater than 10
(array_values > 10).all() # True if every element is greater than 10NumPy warns that testing the truth value of a multi-element array is ambiguous and raises an error; use .any() or .all() to express which result you want. For an elementwise equality question, use (array_values == value).any().
See NumPy’s ndarray reference for membership and array truth-value behavior.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What happens with a custom container
A custom Python object can define its membership behavior with __contains__(). If it has no such method, Python tries iteration, then the legacy indexed-sequence protocol. The Python data model documentation describes this fallback order.
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