`hash()`

The built-in hash() function returns an integer hash value for a given object, which is used internally for fast lookups.

This hash value is used to quickly locate dictionary keys during lookups. Objects that compare equal must have the same hash value. Here’s how you can use the function:

>>> hash("Hello, world!")
-3907008302013813614

`hash()` Signature

hash(object)

Arguments

Argument	Description
`object`	The object to be hashed.

Return Value

Returns an integer representing the hash value of the given object. The hash value is consistent within a single Python session but may vary between sessions for security reasons.

`hash()` Examples

With a string as an argument:

>>> hash("Real Python")
-456543210987654321

With a number as an argument:

>>> hash(42)
42

With a floating-point number as an argument:

>>> hash(3.14)
322818021289917443

`hash()` Common Use Cases

The most common use cases for the hash() function include:

Creating hash values for dictionary keys
Implementing hash tables
Supporting custom objects in sets and dictionaries

`hash()` Real-World Example

Suppose you want to use custom objects as set members or dictionary keys. You can implement .__hash__() and .__eq__() to make your objects hashable:

class Employee:
    def __init__(self, emp_id, name):
        self.emp_id = emp_id
        self.name = name

    def __eq__(self, other):
        return isinstance(other, Employee) and self.emp_id == other.emp_id

    def __hash__(self):
        return hash(self.emp_id)

    def __repr__(self):
        return f"Employee({self.emp_id}, '{self.name}')"

>>> team_a = {Employee(1, "Alice"), Employee(2, "Bob")}
>>> team_b = {Employee(2, "Bob"), Employee(3, "Charlie")}
>>> team_a & team_b
{Employee(2, 'Bob')}

By delegating to hash() on the emp_id attribute, two employees with the same ID are treated as the same person in sets and dictionaries, even if their names differ.

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: