Python keywords are reserved words that have special meaning in the language. These keywords define the syntax and structure of Python and cannot be used as identifiers (names for variables, functions, classes, etc.).

In this article, we’ll explore all Python keywords (as of Python 3.11+), explain what each does, and provide examples for every keyword.

Getting All Keywords in Python

To view all keywords programmatically:

import keyword
print(keyword.kwlist)

Python Keywords (with Examples)

Below is the complete list of Python keywords and a short example for each.

✅ 1. False

Boolean false value.

x = False
if not x:
    print("It is false")

✅ 2. True

Boolean true value.

x = True
if x:
    print("It is true")

✅ 3. None

Represents the absence of a value.

x = None
if x is None:
    print("No value")

✅ 4. and

Logical AND.

a = True
b = False
print(a and b)  # False

✅ 5. or

Logical OR.

a = True
b = False
print(a or b)  # True

✅ 6. not

Logical NOT.

a = False
print(not a)  # True

✅ 7. if

Used for conditional execution.

x = 10
if x > 5:
    print("Greater than 5")

✅ 8. elif

Else-if condition in branching.

x = 5
if x > 5:
    print("Greater")
elif x == 5:
    print("Equal")

✅ 9. else

Final fallback block.

x = 3
if x > 5:
    print("Greater")
else:
    print("Smaller or equal")

✅ 10. while

Used for loops with a condition.

x = 0
while x < 3:
    print(x)
    x += 1

✅ 11. for

Looping over sequences.

for i in range(3):
    print(i)

✅ 12. break

Breaks out of a loop.

for i in range(5):
    if i == 3:
        break
    print(i)

✅ 13. continue

Skips current iteration.

for i in range(5):
    if i == 2:
        continue
    print(i)

✅ 14. pass

Does nothing (used as a placeholder).

def my_func():
    pass

✅ 15. def

Defines a function.

def greet():
    print("Hello")
greet()

✅ 16. return

Returns a value from a function.

def add(x, y):
    return x + y
print(add(2, 3))

✅ 17. yield

Used with generators.

def count_up_to(n):
    for i in range(n):
        yield i
print(list(count_up_to(3)))

✅ 18. import

Imports a module.

import math
print(math.sqrt(16))

✅ 19. from

Used with import.

from math import pi
print(pi)

✅ 20. as

Gives an alias to modules or context managers.

import math as m
print(m.pi)

✅ 21. class

Defines a class.

class Dog:
    def bark(self):
        print("Woof")

✅ 22. global

Declares a global variable.

x = 0
def set_global():
    global x
    x = 5
set_global()
print(x)

✅ 23. nonlocal

Declares a non-local variable in nested functions.

def outer():
    x = 5
    def inner():
        nonlocal x
        x = 10
    inner()
    print(x)
outer()

✅ 24. lambda

Creates an anonymous function.

square = lambda x: x * x
print(square(4))

✅ 25. try

Start of a try-except block.

try:
    print(1 / 0)
except ZeroDivisionError:
    print("Cannot divide by zero")

✅ 26. except

Handles exceptions.

(See above)

✅ 27. finally

Always executes after try/except.

try:
    x = 1 / 1
finally:
    print("Cleaning up...")

✅ 28. raise

Raises an exception.

raise ValueError("Invalid value")

✅ 29. assert

Debugging aid to check conditions.

assert 2 + 2 == 4

✅ 30. del

Deletes an object.

x = [1, 2, 3]
del x[1]
print(x)

✅ 31. with

Context manager (automatically handles resources).

with open("example.txt", "w") as f:
    f.write("Hello")

✅ 32. async

Defines an asynchronous function.

async def greet():
    return "Hi"

✅ 33. await

Waits for an asynchronous result.

import asyncio

async def say_hello():
    return "Hello"

async def main():
    greeting = await say_hello()
    print(greeting)

asyncio.run(main())

✅ 34. in

Checks membership.

print(2 in [1, 2, 3])  # True

✅ 35. is

Checks object identity.

x = None
print(x is None)  # True

✅ 36. match

Structural pattern matching (Python 3.10+).

def http_status(code):
    match code:
        case 200:
            return "OK"
        case 404:
            return "Not Found"
print(http_status(200))

✅ 37. case

Used inside match.

(See above)

Summary Table

Final Thoughts

Python keywords are the backbone of the language’s syntax. Mastering them helps you read and write Python code more effectively and allows you to understand how Python logic is constructed.