in operator

Updated March 16, 2026 · Keywords

keyword membership operator iteration

The in keyword is a membership operator in Python. It checks whether a value exists within a sequence such as a string, list, tuple, set, or dictionary.

Syntax

value in sequence

Returns True if the value is found, False otherwise.

Checking Membership in Different Types

Lists

fruits = ["apple", "banana", "cherry"]

print("apple" in fruits)
# True

print("orange" in fruits)
# False

Tuples

colors = ("red", "green", "blue")

print("red" in colors)
# True

print("yellow" in colors)
# False

Sets

vowels = {"a", "e", "i", "o", "u"}

print("a" in vowels)
# True

print("b" in vowels)
# False

Strings

The in operator checks for substrings:

text = "Hello, World!"

print("Hello" in text)
# True

print("Python" in text)
# False

print("o" in text)
# True

Dictionaries

By default, in checks for keys, not values:

person = {"name": "Alice", "age": 30, "city": "NYC"}

print("name" in person)
# True

print("Alice" in person)
# False

print("age" in person)
# True

To check for values, use .values():

print("Alice" in person.values())
# True

To check for key-value pairs, use .items():

print(("name", "Alice") in person.items())
# True

Using in Conditional Statements

Basic If Statement

user_permissions = ["read", "write", "delete"]

if "delete" in user_permissions:
    print("Can delete files")
# Can delete files

Not In

Use not in to check absence:

banned_users = ["alice", "bob", "charlie"]

user = "dave"

if user not in banned_users:
    print("Access granted")
# Access granted

Checking Environment Variables

import os

if "PYTHONPATH" in os.environ:
    print(f"Python path: {os.environ['PYTHONPATH']}")

Performance Characteristics

Sets and Dictionaries: O(1) Average

Looking up membership in sets and dictionaries is very fast:

allowed_ids = {1, 2, 3, 4, 5}

# Fast - O(1) average case
print(3 in allowed_ids)
# True

Lists and Tuples: O(n)

Linear search through lists is slower for large collections:

names = ["alice", "bob", "charlie", "dave"]

# Slower for large lists - O(n)
print("charlie" in names)
# True

When to Convert List to Set

If you’re checking membership multiple times, convert to a set first:

# Slow - converts on every check
while user_input:
    if user_input in user_list:  # O(n) each time
        process(user_input)

# Fast - convert once, O(1) each check
user_set = set(user_list)
while user_input:
    if user_input in user_set:  # O(1) each time
        process(user_input)

in with Range

The in keyword also works with range() objects:

print(5 in range(10))
# True

print(10 in range(10))
# False

print(0 in range(-5, 5))
# True

in with Generators and Iterators

You can check membership in any iterable using a generator expression:

import itertools

# Check if any number greater than 10 exists
numbers = [1, 5, 8, 3, 9]

has_large = any(n > 10 for n in numbers)
print(has_large)
# False

# But note: in doesn't work with generators directly
# gen = (n for n in numbers)
# print(5 in gen)  # This would consume the generator

Comparison with Other Languages

Python’s in is similar to .includes() in JavaScript:

# Python
"a" in "abc"    # True
"a" in ["a", "b", "c"]  # True

// JavaScript
"abc".includes("a")    // true
["a", "b", "c"].includes("a")  // true

In SQL, similar functionality uses IN and LIKE:

-- SQL equivalent
SELECT * FROM users WHERE role IN ('admin', 'moderator');

Common Patterns

Validate User Input

valid_choices = {"yes", "no", "maybe"}

choice = input("Enter choice: ").lower()
if choice in valid_choices:
    print(f"You chose: {choice}")
else:
    print("Invalid choice")

Check Feature Flags

enabled_features = {"dark-mode", "notifications", "beta"}

if "beta" in enabled_features:
    enable_beta_ui()

Safe Dictionary Access

config = {"host": "localhost", "port": 8080}

# Use in to avoid KeyError
if "timeout" in config:
    print(f"Timeout: {config['timeout']}")
else:
    print("Using default timeout")