Unpacking & Multiple Assignment

Syntax

a, b, *rest = iterable

Examples

coordinates = (10, 20, 30)
x, y, z = coordinates
print(x, y, z)  # 10 20 30

first, second = ["Fola", "Zain"]
print(first, second)

numbers = [1, 2, 3, 4, 5]

first, *middle, last = numbers
print(first)   # 1
print(middle)  # [2, 3, 4]
print(last)    # 5

head, *tail = numbers
print(head, tail)  # 1 [2, 3, 4, 5]

def add(a, b, c):
    return a + b + c

numbers = [1, 2, 3]
print(add(*numbers))  # 6, same as add(1, 2, 3)

def greet(name, greeting):
    print(f"{greeting}, {name}!")

info = {"name": "Fola", "greeting": "Hi"}
greet(**info)  # unpacks dict into keyword arguments

point = (("x", 3), ("y", 4))

(x_label, x_val), (y_label, y_val) = point
print(f"{x_label}={x_val}, {y_label}={y_val}")  # x=3, y=4

# Common pattern: unpacking while iterating
pairs = [(1, "one"), (2, "two"), (3, "three")]
for number, word in pairs:
    print(f"{number}: {word}")

Best practices

• Use unpacking instead of manual indexing when you know exactly how many items an iterable contains
• Use *rest to flexibly capture 'everything else' without knowing the exact length in advance
• Use *args-style unpacking (*numbers) to spread a list into a function call rather than passing the list itself when separate arguments are expected
• Unpacking raises a ValueError if the number of variables does not match the number of items - use * to handle variable-length iterables safely

At a glance

Purpose

Scripting and general-purpose applications

File extension

.py

Runs in

Python interpreter

Usually used with

Python standard library and packages

Specifications & further reading

• Python language reference

Related Python documentation