hashable

In Python, an object is considered hashable if it has a hash value that remains constant during the object’s lifetime.

Hashable objects can be used as a key in a dictionary or as an element in a set, since both data structures rely on hashing to efficiently look up and store elements.

To be hashable, an object must implement the .__hash__() method and the .__eq__() method. Immutable built-in types like integers, strings, and tuples containing only hashable elements are hashable. Mutable types like lists and dictionaries have .__hash__() set to None by design, making them unhashable. This prevents silent data corruption that would occur if a key’s hash changed after insertion into a dictionary or set.

>>> # Hashable
>>> hash(42)
42
>>> hash("Real Python")
3074007028937194714  # Varies per session

>>> numbers = (1, 2, 3)
>>> hash(numbers)
529344067295497451  # Varies per session

>>> # Not hashable
>>> hash([1, 2, 3])
Traceback (most recent call last):
    ...
TypeError: unhashable type: 'list'

>>> hash((1, [2, 3]))
Traceback (most recent call last):
    ...
TypeError: unhashable type: 'list'

Related Resources

Tutorial

Build a Hash Table in Python With TDD

In this step-by-step tutorial, you'll implement the classic hash table data structure using Python. Along the way, you'll learn how to cope with various challenges such as hash code collisions while practicing test-driven development (TDD).

intermediate algorithms data-structures

For additional information on related topics, take a look at the following resources:

• Python's Built-in Functions: A Complete Exploration (Tutorial)
• Build a Hash Table in Python With TDD (Quiz)
• Python's Built-in Functions: A Complete Exploration (Quiz)