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Python Programming: Basics to Advanced Concepts

This book is 100% completeLast updated on 2026-06-12
Anshuman Mishra
Want to learn Python from the ground up and master its real-world applications? Python Programming: Basics to Advanced Concepts is your complete guide to one of the world's most powerful and versatile programming languages. Whether you are a BCA or MCA student, an aspiring software developer, a competitive examination candidate, or a technology enthusiast, this book provides a structured learning…

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Python Programming: Basics to Advanced Concepts

Python has become one of the most influential and versatile programming languages in the modern computing era. Its simplicity, readability, extensive ecosystem, and powerful capabilities have made it the preferred language for software development, data science, artificial intelligence, machine learning, cybersecurity, web development, automation, and scientific computing.

Python Programming: Basics to Advanced Concepts is a comprehensive academic and practical guide designed specifically for undergraduate and postgraduate students, aspiring programmers, software developers, and technology enthusiasts who wish to build a strong foundation in Python and progress toward advanced applications.

Written by Anshuman Kumar Mishra, an experienced educator with more than eighteen years of teaching experience in Computer Science, this book provides a structured learning pathway that takes readers from fundamental programming concepts to advanced Python technologies used in modern industry.

The book begins with the essentials of Python programming, including syntax, variables, data types, operators, control structures, and functions. It then gradually introduces advanced concepts such as object-oriented programming, exception handling, file management, modules, packages, decorators, generators, and performance optimization.

A major strength of this book is its practical orientation. Each topic is supported by examples, exercises, and real-world scenarios that help readers understand not only how Python works but also how it can be applied to solve real problems.

The book further explores modern Python applications including database programming, GUI development using Tkinter, web development with Flask and Django, data analysis using NumPy and Pandas, machine learning fundamentals, network programming, and cybersecurity applications.

Special emphasis has been placed on helping students develop industry-ready skills. By combining academic concepts with practical projects, readers gain hands-on experience that prepares them for higher education, competitive examinations, internships, and professional software development roles.

Whether you are a beginner learning your first programming language, a university student preparing for examinations, or a professional seeking to enhance your Python expertise, this book serves as a complete roadmap for mastering Python programming from fundamentals to advanced concepts.

With clear explanations, practical examples, project-oriented learning, and industry relevance, this book provides readers with the knowledge and confidence needed to become proficient Python developers in today's technology-driven world.

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Computer Programming/Artificial Intelligence/PythonPython

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About the Author

Anshuman Mishra

Anshuman Kumar Mishra, M.Tech (Computer Science) Assistant Professor, Doranda College, Ranchi University

Prolific Author of 50+ Books on AI, Machine Learning & Computer Science | 20+ Years Experience

Anshuman Kumar Mishra is a dedicated educator, researcher, and highly prolific author with over 20 years of experience in Computer Science and Information Technology. Holding an M.Tech in Computer Science from BIT Mesra, he brings a rare combination of academic depth and practical teaching expertise.

Currently serving as Assistant Professor at Doranda College under Ranchi University, he has mentored thousands of students, helping them build strong foundations in programming, data science, and artificial intelligence. His student-centric teaching style emphasizes conceptual clarity, hands-on practice, and real-world application.

Anshuman is a prolific author with more than 50 books published across a wide spectrum of computer science and emerging technology domains. From foundational programming languages to advanced topics in Artificial Intelligence, Machine Learning, Reinforcement Learning, Decision Theory, and Computer Vision — his books are widely appreciated by students, educators, and professionals for their clear explanations, strong theoretical foundation, and practical approach.

His extensive body of work reflects his deep commitment to making complex subjects accessible and meaningful for learners at all levels. He is particularly recognized for creating well-structured learning paths that help readers progress from beginner to advanced levels with confidence.

Driven by the mission to democratize quality technical education, Anshuman continues to write and update books that bridge the gap between academic theory and industry practice.

When not teaching or writing, he actively follows and explores new developments in AI, Quantum Machine Learning, and Ethical Intelligence systems.

Contents

Table of Contents

1. Introduction to Python Programming 1-13 1.1 History and Features of Python 1.2 Understanding Python Interpreter and IDEs (IDLE, PyCharm, Jupyter Notebook) 1.3 Installing Python and Setting up the Environment 1.4 Writing Your First Python Program 1.5 Python vs Other Programming Languages 2. Basics of Python Programming 14-26 2.1 Syntax and Indentation 2.2 Variables and Constants 2.3 Data Types (int, float, string, boolean, complex) 2.4 Type Conversion and Casting 2.5 Input and Output Statements 3. Operators and Expressions 27-38 3.1 Arithmetic Operators 3.2 Relational and Logical Operators 3.3 Assignment Operators 3.4 Bitwise Operators 3.5 Membership and Identity Operators 3.6 Operator Precedence and Associativity 4. Control Flow Statements 39-54 4.1 Conditional Statements (if, if-else, if-elif-else) 4.2 Loops (for, while, nested loops) 4.3 Loop Control Statements (break, continue, pass) 5. Python Data Structures 55-69 5.1 Lists: Creation, Accessing, Slicing, and Manipulating 5.2 Tuples: Characteristics, Accessing, and Manipulating 5.3 Sets: Creating, Operations, and Applications 5.4 Dictionaries: Keys, Values, and Operations 5.5 Strings: Methods, Slicing, and Immutability 6. Functions in Python 70-81 6.1 Function Definition and Invocation 6.2 Function Arguments (Default, Keyword, Variable-length) 6.3 Scope of Variables (Global and Local) 6.4 Recursive Functions 6.5 Lambda Functions and Anonymous Functions 7. Modules and Packages 82-95 7.1 Creating and Using Modules 7.2 Python Built-in Modules (os, sys, math, random) 7.3 Importing Modules (import, from-import) 7.4 Creating and Using Packages 8. Object-Oriented Programming (OOP) in Python 96-112 8.1 Concepts of OOP (Class, Object, Inheritance, Polymorphism) 8.2 Creating Classes and Objects 8.3 Constructors and Destructors 8.4 Inheritance (Single, Multiple, Multilevel, Hierarchical) 8.5 Method Overloading and Overriding 8.6 Encapsulation and Data Hiding 9. Exception Handling 113-125 9.1 Understanding Errors and Exceptions 9.2 Handling Exceptions (try, except, finally) 9.3 Raising Exceptions 9.4 Built-in Exceptions 10. File Handling 126-146 10.1 File Modes (Read, Write, Append) 10.2 Reading and Writing Text Files 10.3 Working with Binary Files 10.4 File Methods and Attributes 10.5 Exception Handling in File Operations 11. Advanced Python Topics 147-160 11.1 Regular Expressions 11.2 List Comprehensions 11.3 Generators and Iterators 11.4 Decorators 11.5 Context Managers (with Statement) 12. Python for Data Handling 161-175 12.1 Working with CSV Files 12.2 Working with JSON Files 12.3 Understanding Pandas for Data Analysis 12.4 Numpy for Numerical Computations 13. Python for Database Programming 176-185 13.1 Overview of Databases and SQL 13.2 Connecting Python to Databases (SQLite, MySQL) 13.3 Performing CRUD Operations 13.4 Using ORM with SQLAlchemy 14. GUI Programming in Python 186-201 14.1 Introduction to Tkinter 14.2 Creating Basic GUI Applications 14.3 Event Handling in Tkinter 14.4 Widgets (Label, Button, Entry, Frame, etc.) 15. Python for Web Development 202-219 15.1 Introduction to Flask and Django Frameworks 15.2 Creating a Simple Web Application using Flask 15.3 Routing and Templates 15.4 Database Connectivity in Flask 16. Python for Data Science and Machine Learning 220-231 16.1 Basics of Data Science with Python 16.2 Introduction to Machine Learning Libraries (Scikit-learn, TensorFlow) 16.3 Writing Simple ML Algorithms 16.4 Data Visualization with Matplotlib and Seaborn 17. Python for Network Programming 232-243 17.1 Understanding Sockets 17.2 Client-Server Communication 17.3 Building Simple Chat Applications 17.4 Using Python for Network Automation 18. Python for Cybersecurity 284-256 18.1 Basics of Cryptography in Python 18.2 Creating Hashes (MD5, SHA) 18.3 Working with SSL and TLS 19. Testing and Debugging in Python 257-273 19.1 Debugging Techniques 19.2 Unit Testing with unit test 19.3 Integration Testing 20. Python Performance Optimization 274-282 20.1 Understanding Memory Management in Python 20.2 Profiling and Optimization Tools 20.3 Using Cython for Speed Improvement 21. Python Project Development 283-291 21.1 Steps to Build a Python Project 21.2 Case Study: Developing a Python-based Application 21.3 Deploying Python Applications

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