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Introduction

Python is renowned for its clean syntax, versatility, and a vast ecosystem of libraries, making it one of the most popular programming languages in the world. Whether you are a beginner or an advanced developer, having a well-structured cheat sheet is invaluable for quick reference and efficient learning. This comprehensive Python cheat sheet is designed to cover all major aspects of the language, from basic syntax to advanced features such as decorators, generators, context managers, and concurrency. Each section provides concise explanations, best practices, and well-commented code examples to facilitate rapid understanding and application.

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Python Syntax and REPL Basics

Python's syntax is designed to be readable and straightforward, closely resembling plain English. This section introduces the essential elements of Python syntax and how to interact with the Python interpreter.

• Starting the Python Interpreter
• Comments

Variables, Assignment, and Naming Conventions

Variables in Python are dynamically typed and created upon assignment. Python follows specific naming conventions to enhance code readability.

• Variable Assignment

Naming Conventions

• Variables and Functions: Use snake_case (lowercase with underscores).
• Classes: Use CamelCase (also called PascalCase).
• Constants: Use ALL_CAPS_WITH_UNDERSCORES.

Examples:

user_name = "Bob"
MAX_CONNECTIONS = 10

class MyClass:
    pass

PEP 8, the official Python style guide, recommends these conventions for clarity and consistency.

Data Types and Type System

Python supports several built-in data types, each with specific characteristics and methods.

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Core Data Types

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• Type Checking and Conversion </aside>

String Methods

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• String Formatting </aside>

Arithmetic Operators

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Operator precedence:** > *, /, //, % > +, - (right-to-left for **, left-to-right otherwise).

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Built-in Numeric Functions

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Type conversion

int("42")      # 42
float("3.14")  # 3.14
complex(2, 3)  # (2+3j)

For advanced math, use the math module:

import math
math.sqrt(16)  # 4.0
math.pi        # 3.141592653589793

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• Collections: Lists, Tuples, Sets, Dictionaries
• Control Flow: Conditionals and Boolean Logic
• Loops and Iteration Patterns
• Functions: Definition, Arguments, Return Values
• Comprehensions: List, Dict, Set, Generator Expressions
• Modules, Packages, and Imports </aside>

Python's standard library is extensive. Here are some essential modules:

Standard Library Highlights

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Example:

import os
print(os.getcwd())

For more, see the official documentation10.

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• File Handling and I/O (Text, Binary, CSV, JSON)
• Error Handling and Exceptions (EAFP vs LBYL)
• Classes and Object-Oriented Programming
• Advanced OOP: Metaclasses, Descriptors, Protocols
• Decorators: Function and Class Decorators
• Generators and Iterators
• Context Managers and the with Statement
• Concurrency: Threads, Asyncio, Multiprocessing (Overview) </aside>

Summary Table

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• Decorators, Generators, Context Managers (Combined Patterns)
• Functional Tools: map, filter, reduce, functools, itertools
• Type Hints and Static Typing
• Testing and Debugging
• Packaging, Virtual Environments, and Deployment </aside>

Common Built-in Functions Cheat Sheet