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Programming in Python

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You can buy the complete book with detailed explanations, code examples on:
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What to Expect

This book is meticulously structured to guide you through the intricacies of Python programming, ensuring a balanced blend of theoretical concepts and practical applications. Here’s a glimpse of what you’ll explore:

Foundations of Python: Grasp the core syntax, data types, and control structures that form the backbone of Python programming.
Advanced Concepts: Delve into object-oriented programming, modules, packages, and error handling to build robust and maintainable code.
Data Structures: Master lists, tuples, dictionaries, and sets to efficiently manage and manipulate data.
Networking with Python: Learn how to create networked applications, handle protocols, and interact with web services using Python’s networking libraries.
Working with Databases: Understand how to connect to, query, and manage databases using Python, enabling you to build data-driven applications.
Unit Testing and Test-Driven Development: Discover the importance of writing unit tests using Python’s unittest framework and adopt test-driven development practices to ensure code reliability and maintainability.
File Handling and Exceptions: Develop skills in managing file I/O operations and implementing effective error handling to ensure your programs are both functional and resilient.
Best Practices and Code Optimization: Adopt Pythonic coding standards, optimize your code for performance, and maintain high-quality software through best practices.
Advanced Python Topics: Explore decorators, generators, context managers, and other advanced features that enhance your programming capabilities.

Table of Contents

Introduction

• Introduction
• Acknowledgments
• Table of Contents

Part I: Introduction to Python

• Getting Started with Python
• Introduction to Python
• Python’s Philosophy
• Installing Python (Windows, macOS, Linux)
• Running Python Scripts
• Basic Syntax and Data Types
  • Python Syntax and Indentation
  • Variables and Constants
  • Data Types: Numbers, Strings, Booleans
  • Type Conversion
  • Operators in Python
• Basic Input and Output Operations
• Control Structures
  • Conditional Statements
  • Looping Constructs
  • Control Flow Tools
  • Comprehensions (List, Dictionary, Set)
• Functions and Modules
  • Defining and Calling Functions
  • Function Arguments and Return Values
  • Variable Scope and Lifetime in Python
  • Lambda Functions and Anonymous Functions in Python
  • Modules and Packages
  • The Python Standard Library Overview
• Error Handling and Exceptions
  • Understanding Exceptions in Python
• Working with Files
  • File Operations (Open, Read, Write, Close)
  • Working with File Paths
  • Handling Different File Formats: Text, CSV, and JSON

Part II: Core Python Concepts

• Data Structures
  • Lists and List Operations
  • Tuples and Their Uses in Python
  • Dictionaries
  • Sets and Set Operations
  • Choosing the Right Data Structure
• Object-Oriented Programming (OOP)
  • Classes and Objects
  • Attributes and Methods
  • Inheritance and Polymorphism
  • Encapsulation and Abstraction
  • Special Methods and Operator Overloading
• Advanced Functions
  • Decorators
  • Generators and Iterators
  • Closures
  • Recursion
  • Higher-Order Functions
• Modules and Packages
  • Creating and Importing Modules
  • Exploring Python’s Built-in Modules
  • Managing Packages with pip
  • Virtual Environments
  • Packaging Your Python Projects
• File and Directory Management
  • OS Module Basics
  • Working with Paths Using pathlib
  • Reading and Writing Binary Files
• Generators
  • Generator Expressions
  • Creating Custom Generators

Part III: Advanced Python

• Understanding Iterables
• Creating Custom Iterators
• The itertools Module
• Decorators and Metaclasses
  • Advanced Decorator Usage
  • Introduction to Metaclasses
• Concurrency and Parallelism
  • Understanding Threads and Processes
  • The threading Module
  • The multiprocessing Module
  • Async Programming with asyncio
  • Concurrent Futures
• Memory Management and Garbage Collection
  • Python’s Memory Model
  • Reference Counting
  • Garbage Collection Mechanisms
  • Managing Memory in Large Applications
• Descriptors and Context Managers
  • Creating and Using Descriptors
  • Implementing Context Managers
  • Advanced Usage of the with Statement
• Python Internals
  • Python Bytecode and the Interpreter
  • Understanding the Global Interpreter Lock (GIL)
  • Performance Optimization Techniques
  • Profiling and Debugging Python Code
• Database Interaction
  • Working with SQL Databases using sqlite3 and SQLAlchemy
  • NoSQL Databases (MongoDB) with PyMongo
  • Object-Relational Mapping (ORM) Concepts
  • Database Transactions
• Networking and APIs
  • Basics of Networking
  • Building Network Applications with socket
  • Understanding REST and GraphQL
• Testing and Debugging
  • Writing Unit Tests with unittest
  • Writing Unit Tests with pytest
  • Test-Driven Development (TDD)
  • Measuring Code Coverage with pytest
  • Debugging Techniques and Tools

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