9 Top eBooks for Python Programming

• no 1 Best seller in Object Oriented software design

 

3. Learn Python 3.0 the Hard Way - Zed Shaw 

Shaw also stresses the importance of discipline and repetition in mastering programming. Readers learn to debug code, write clean and readable scripts, and develop problem-solving abilities. The book's methodical approach ensures that learners gain a deep and practical understanding of Python, preparing them for more advanced programming challenges.

4. Automate the boring stuff with Python 3: Practical Programming for Total Beginners - Al Stweigart

 

 

 

Automate the Boring Stuff with Python" is a popular programming book by Al Sweigart that teaches readers how to use Python to automate daily tasks. The third edition, scheduled for release on May 20, 2025, is expected to include:

• Updated Content: Reflecting the latest Python 3 features and best practices.
• New Chapters: Covering advanced topics such as data analysis, web scraping, and GUI automation.
• Practical Projects: Including examples like automating Excel spreadsheets, parsing PDFs, and sending reminder emails.
• Hands-on Exercises: Providing readers with opportunities to apply their knowledge.

This edition aims to empower both beginners and experienced programmers to streamline their workflows using Python.

 

5. Machine Learning using Python by Manaranjan Pradhan and U Dinesh Kumar

 

  

• Ratings: 4.3/5 over 687 ratings.

Machine Learning using Python," authored by Manaranjan Pradhan and U Dinesh Kumar, is a practical guide that bridges machine learning theory with Python implementation. Key features include:

• Practical Focus:
  • It emphasizes real-world case studies and examples.
  • It provides a step-by-step approach to building and optimizing models.
• Comprehensive Coverage:
  • It covers foundational and advanced machine learning concepts.
  • It includes topics like regression, decision trees, and text analytics.
  • It gives clear instruction on how to utilize python libraries for machine learning.
• Expert Authorship:
  • Both authors bring extensive academic and industry experience.
  • U Dinesh Kumar is a respected professor, and Manaranjan Pradhan brings real world industry experience.

The book is designed to equip readers with the skills to effectively apply machine learning using Python.

6. Elements of Programming Interviews in Python: The Insiders' Guide Adnan Aziz, Amit Prakash, Tsung Hsien Lee

• Ratings: 4.5/5 over 875 ratings

"Elements of Programming Interviews in Python: The Insiders' Guide" by Adnan Aziz, Amit Prakash, and Tsung Hsien Lee is essential for coding interview preparation. It covers problem-solving strategies, including algorithm design (divide-and-conquer, dynamic programming, greedy algorithms) and data structures (arrays, linked lists, stacks, queues, trees, graphs).

The book emphasizes complexity analysis, time and space optimization, and coding techniques like recursion, iteration, sorting, and searching. Key areas include arrays, strings, linked lists, stacks, queues, and advanced topics like tree/graph traversal (DFS, BFS) and shortest path algorithms. It delves into dynamic programming with memoization and tabulation, and system design considerations. The guide includes over 250 practice problems, detailed solutions, and mock interview scenarios, along with preparation for behavioral interviews. This comprehensive resource enhances problem-solving skills, algorithm application, and interview readiness.

7. Python Programming : Introduction to Computer Science – John Zelle

    

• Ratings: 4.6/5 over 385 ratings

"Python Programming: Introduction to Computer Science" by John Zelle offers a comprehensive introduction to Python and core computer science concepts. Key lessons include Python basics like syntax, variables, and control structures (conditionals, loops). The book covers functions, modular programming, and essential data structures (lists, strings, dictionaries, sets).

It delves into object-oriented programming (classes, objects, inheritance, polymorphism) and file I/O operations. Algorithm design principles, such as recursion, iteration, sorting, and searching, are also explored. The text introduces event-driven programming with GUIs using Tkinter and emphasizes computational thinking through abstraction and decomposition. Software development practices like debugging, testing, code documentation, and version control are highlighted. This book is ideal for beginners, providing a solid foundation in both Python and computer science.

 

8. Python Cookbook: Recipes for Mastering Python 3, Third Edition 

 

• Ratings:  4.5/5 over 590 ratings

9. Data Structure and Algorithim made easy- Narasimha Karumanchi

• Ratings : 2nd most gifted book. 4.3/5 over 600 ratings

"Data Structure and Algorithmic Thinking with Python" by Narasimha Karumanchi focuses on building problem-solving skills using data structures and algorithms. Key lessons include understanding basic data structures like arrays, lists, stacks, queues, and linked lists, as well as advanced structures such as hash tables, balanced trees (AVL, Red-Black), and tries. The book covers tree and graph algorithms, including binary trees, heaps, BFS, DFS, and graph representations. It delves into algorithm design with sorting (quick sort, merge sort), searching (binary search), dynamic programming, and greedy algorithms.

Techniques like recursion, backtracking, and divide and conquer are emphasized. Algorithmic thinking is developed through complexity analysis and practical applications. The book also provides extensive Python implementations and problem sets to enhance coding skills. This guide is essential for mastering data structures and algorithms in Python.

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