Python Cheatsheet: 15 Must-Know Tips for Fast Learning

Python Cheatsheet is a quick reference guide to help you write clean and efficient Python code. Whether you’re a beginner or an experienced developer, this cheatsheet covers essential syntax, operations, and advanced concepts with practical examples.

Python Basics

Python is a high-level, interpreted language known for its simplicity and readability. It uses indentation instead of braces, making the code clean and beginner-friendly.

print("Hello, World!")

print("Hello, World!")

Variables don’t require explicit type declarations. Python dynamically assigns types.

age = 25
salary = 5000.50
name = "Alice"

age = 25
salary = 5000.50
name = "Alice"

Data Types in Python

Python supports multiple built-in data types, including numbers, strings, booleans, lists, tuples, sets, and dictionaries.

x = 10          # int
y = 3.14        # float
name = "John"   # str
is_valid = True # bool

x = 10          # int
y = 3.14        # float
name = "John"   # str
is_valid = True # bool

You can check a variable’s type with:

type(x)

type(x)

Control Flow and Conditional Statements

Control flow determines how code executes. Python supports if, elif, and else for decision-making.

if age >= 18:
    print("Adult")
elif age > 13:
    print("Teenager")
else:
    print("Child")

if age >= 18:
    print("Adult")
elif age > 13:
    print("Teenager")
else:
    print("Child")

Loops are used for iteration:

for i in range(5):
    print(i)

for i in range(5):
    print(i)

while age < 30:
    age += 1

while age < 30:
    age += 1

Functions and Modules

Functions improve reusability and readability.

def greet(name):
    return f"Hello, {name}"

def greet(name):
    return f"Hello, {name}"

Modules let you use external functionality.

import math
print(math.sqrt(25))

import math
print(math.sqrt(25))

You can also create custom modules by saving functions in .py files.

Python Data Structures

Python provides flexible data structures for storing collections.

• List (ordered, mutable):

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

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

• Tuple (ordered, immutable):

coordinates = (10, 20)

coordinates = (10, 20)

• Set (unordered, unique):

unique_nums = {1, 2, 3, 3}

unique_nums = {1, 2, 3, 3}

• Dictionary (key-value pairs):

person = {"name": "Alice", "age": 28}

person = {"name": "Alice", "age": 28}

String Operations

Strings are widely used in Python.

message = "Python Cheatsheet"
print(message.lower())   # lowercase
print(message.upper())   # uppercase
print(message.split())   # split

message = "Python Cheatsheet"
print(message.lower())   # lowercase
print(message.upper())   # uppercase
print(message.split())   # split

You can also use f-strings for formatting:

name = "Alice"
print(f"Hello, {name}")

name = "Alice"
print(f"Hello, {name}")

List Comprehensions

A concise way to create lists:

squares = [x**2 for x in range(5)]

squares = [x**2 for x in range(5)]

With condition:

even_squares = [x**2 for x in range(10) if x % 2 == 0]

even_squares = [x**2 for x in range(10) if x % 2 == 0]

File Handling

Python simplifies reading and writing files.

with open("data.txt", "w") as f:
    f.write("Hello, File!")

with open("data.txt", "w") as f:
    f.write("Hello, File!")

with open("data.txt", "r") as f:
    print(f.read())

with open("data.txt", "r") as f:
    print(f.read())

Always use with to handle file closing automatically.

Exception Handling

Errors are managed with try-except blocks.

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero")

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero")

You can add finally for cleanup actions.

Object-Oriented Programming (OOP)

Python supports OOP with classes and objects.

class Car:
    def __init__(self, brand, model):
        self.brand = brand
        self.model = model

car = Car("Tesla", "Model S")
print(car.brand)

class Car:
    def __init__(self, brand, model):
        self.brand = brand
        self.model = model

car = Car("Tesla", "Model S")
print(car.brand)

Inheritance allows code reuse.

class ElectricCar(Car):
    def battery(self):
        print("Battery powered")

class ElectricCar(Car):
    def battery(self):
        print("Battery powered")

Python Libraries and Packages

Python’s ecosystem includes thousands of libraries.

• NumPy: Numerical computing.
• Pandas: Data analysis.
• Matplotlib: Data visualization.
• Requests: HTTP requests.

Install libraries using pip:

pip install numpy

pip install numpy

Virtual Environments

Use virtual environments to manage dependencies.

python -m venv venv

python -m venv venv

Activate environment:

• Windows: venv\Scripts\activate
• Linux/macOS: source venv/bin/activate

Python Generators

Generators allow efficient iteration over large datasets.

def countdown(n):
    while n > 0:
        yield n
        n -= 1

def countdown(n):
    while n > 0:
        yield n
        n -= 1

for num in countdown(5):
    print(num)

for num in countdown(5):
    print(num)

Decorators

Decorators modify functions without changing their code.

def decorator(func):
    def wrapper():
        print("Before function")
        func()
        print("After function")
    return wrapper

@decorator
def hello():
    print("Hello!")

def decorator(func):
    def wrapper():
        print("Before function")
        func()
        print("After function")
    return wrapper

@decorator
def hello():
    print("Hello!")

Useful Python Shortcuts

• Swap values:

a, b = b, a

a, b = b, a

• Multiple assignment:

x, y, z = 1, 2, 3

x, y, z = 1, 2, 3

• Dictionary iteration:

for k, v in person.items():
    print(k, v)

for k, v in person.items():
    print(k, v)

Conclusion

This Python Cheatsheet provides a compact reference for Python basics, control flow, functions, data structures, file handling, OOP, decorators, and libraries. Keep it handy to speed up coding, debug effectively, and learn faster.

FAQs About Python Cheatsheet