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Total Size:
2.8 MB
Info Hash:
1AA466D4F94416AB9C256457F43A4A089E0DF1A9
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Added:
March 3, 2026, 12:54 a.m.
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(Last updated: March 3, 2026, 12:55 a.m.)
| File | Size |
|---|---|
| Gahler M. Python Made Easy. A Beginner's Guide...Practical Applications 2026.pdf | 2.8 MB |
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754.6 MB
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2023-07-01
| Uploaded by mainlyclassical | Size 754.6 MB | Health [ 22 /7 ] | Added 2023-07-01 |
NOTE
SOURCE: Gahler M. Python Made Easy. A Beginner's Guide...Practical Applications 2026
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MEDIAINFO
Textbook in PDF format
Python has become one of the most versatile and widely used programming languages, known for its simplicity and efficiency. Python Made Easy is designed to help beginner developers easily learn the fundamentals and intermediate concepts of Python. This book provides a structured approach to learning Python, covering essential topics from basic syntax to complex data structures and numerical computing.
The book starts with an introduction to Python, explaining its advantages, drawbacks, and the importance of style guides. It then delves into key programming concepts, including variables, lists, strings, dictionaries, tuples, and rare data structures, helping readers build a strong foundation. Readers will also explore loops, conditional statements, Boolean logic, essential mathematical operations, and NumPy's use for numerical computations. Complex topics such as object-oriented programming, inheritance, file handling, unit testing, and data visualization using Matplotlib are covered in depth. Additionally, the book introduces practical applications in numerical mathematics, including Monte Carlo integration and differential equations.
By the end, readers will have an understanding of Python’s core principles and practical applications, empowering them to write efficient, scalable, and well-structured code. This book is particularly helpful if you already know some other programming language and you want to kick start your Python knowledge.
What you will learn
Understand Python fundamentals, including variables, loops, and data structures.
What is object-oriented programming, inheritance, and file handling.
Explore numerical computing with NumPy and data visualization using Matplotlib.
Gain hands-on experience with unit testing, Monte Carlo integration, and real-world applications.
Who this book is for
Beginners and aspiring programmers, software professionals transitioning to Python and students
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