Top book for learn data structures and algorithms in python năm 2024

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Top book for learn data structures and algorithms in python năm 2024

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Top book for learn data structures and algorithms in python năm 2024

Data Structures and Algorithms in Python Hardcover – 8 March 2013


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Top book for learn data structures and algorithms in python năm 2024

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Based on the authors' market leading data structures books in Java and C++, this textbook offers a comprehensive, definitive introduction to data structures in Python by respected authors. Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++.

  1. Publication date 8 March 2013
  2. Dimensions 20.32 x 2.54 x 25.4 cm

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Product description

From the Publisher

Michael Goodrich, PhD in Computer Science from Purdue University, 1987; Chancellor's Professor of Computer Science at University of California, Irvine; co-author (with Tamassia) of three other Wiley textbooks and a new computer security text, Addison Wesley, 2011.

Roberto Tamassia, PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, 1988; Plastech Professor of Computer Science and Chair of the CS Dept at Brown University; co-author with Goodrich, see texts above.

Michael Goldwasser, PhD in Computer Science from Stanford University, 1997; Associate Professor and Director of CS at St. Louis University; author of Object-Oriented Programming in Python, Pearson, 2008.

From the Inside Flap

This all-new Data Structures and Algorithms in Python is designed to provide an introduction to data structures and algorithms, including their design, analysis, and implementation. The authors take advantage of the beauty and simplicity of Python to present executable source code that is clear and concise. Furthermore, a consistent object-oriented viewpoint is retained throughout the book, including the use of inheritance, both to maximize code reuse and to draw attention to the clear similarities and differences of various abstract data types and algorithmic approaches.

This is a “sister” book to Goodrich & Tamassia’s Data Structures and Algorithms in Java and Goodrich, Tamassia and Mount’s Data Structures and Algorithms in C++. This Python version retains much of the same pedagogical approach and general structure as the Java and C++ versions, so that curriculums that teach data structures in Python, Java, and C++ can share the same core syllabus.

Key Features of this Book

  • A primer that reviews the basics of programming in Python (Chapter 1), followed by a separate introduction to object-oriented programming in Python (Chapter 2).
  • Extensive coverage of recursion (Chapter 4).
  • A chapter describing the array-based underpinnings of Python’s standard list, string, and tuple classes (Chapter 5), including both theoretical and empirical analyses of their efficiencies.
  • Source code with complete implementations of the majority of data structures and algorithms described in the book; the code follows modern standards for Python 3, and makes use of the standard collections module.
  • 500 illustrations that present data structures and algorithms in a clear, visual manner.
  • More than 750 exercises, divided into categories of reinforcement, creativity, and projects.

About the cover:

The cover art is based on an indigenous Australian painting style portraying what is known as Dreamtime. This style is traditionally iconic and representative of connections between points of interest or concepts; hence, it is a fitting way to capture at a high level the connections and points of interest used to visualize data structures and algorithms.

Product details

  • Publisher ‏ : ‎ Wiley; 1st edition (8 March 2013)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 768 pages
  • ISBN-10 ‏ : ‎ 1118290275
  • ISBN-13 ‏ : ‎ 978-1118290279
  • Dimensions ‏ : ‎ 20.32 x 2.54 x 25.4 cm
  • Best Sellers Rank: 208,006 in Books (See Top 100 in Books)
    • 12 in Computer Algorithm Date Structures
    • 43 in Computer Programming Structured Design
    • 266 in Computer Programming Languages Textbooks
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5.0 out of 5 stars Usefull

Reviewed in India on 8 May 2023

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Usefull but youtube is much better

5.0 out of 5 stars Educational-grade textbook

Reviewed in the United States on 26 November 2019

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I'm currently enrolled with a online university, and currently studying Data Structures and Algorithms. I was unsatisfied with the course textbook, so I purchased this textbook to supplement my learning. The gamble was worth it, and I'm impressed with how well this textbook is written, with the number of chapter exercises it provides (granted, no answers to the exercises), and with the quality of content. I do have programming experience with Java at my previous brick-and-mortar school, so I can't say if this would be a good introductory textbook to someone who has little coding experiencing and is trying to learn Python, but in any case, this would definitely be one of my reference-books in the future.

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3.0 out of 5 stars Libro stampato artigianalmente

Reviewed in Italy on 21 March 2019

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Ho comprato la versione con copertina morbida e quindi indiana, sembra un libro stampato e rilegato a casa, il contenuto è identico all'originale ma le pagine a volte sono stampate storte e sono finissime. il prezzo vale la candela poichè probabilmente si spenderebbe di piu a farlo stampare in tipografia.

5.0 out of 5 stars Great Algorithms Book for Python devs

Reviewed in Canada on 4 October 2017

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I am a developer (primarily Python these days) with close to 8 years of experience. It is never too late to get back to tightening fundamentals, especially something as important as algorithms and data structures. After a fair bit of research, I chose this book for some reasons relevant to me:

1. The book has great coverage on the subject - sufficiently in-depth for my needs and more

2. The book illustrates all concepts using Python, the language I love and that I am extremely comfortable with. This helps my brain focus on the concepts at hand rather than trying to decipher psuedocode and notations.

3. The book is very readable! The language is friendly and isn't at all too academic.

4. (Bonus) the authors have done a very good job covering not just Python fundamentals, but also higher level programming concepts like OOPS and design patterns, which I think is a neat bonus for this package.

All in all great book, and it is totally worth buying the hardcover.

3 people found this helpful

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3.0 out of 5 stars It's a decent textbook

Reviewed in the United Kingdom on 16 February 2014

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Delivery was satisfactory, and the book itself has all the material you need for python, but honestly I find the internet to be much easier to work from

What is the best book for algorithms and data structures in Python?

Python Algorithms by Magnus Lie Hetland With a focus on problem-solving, this book covers various data structures and algorithms, along with a hands-on approach to implement them in Python. It's a valuable resource for those looking to deepen their Python programming skills and algorithmic thinking.

What is the best source to learn data structures and algorithms in Python?

Data Structures and Algorithms Python – The Complete Bootcamp (Udemy) This course provided by Udemy is the best-known DSA course for beginners. This course covers every topic from concept, and visualization, to the implementation part.

Which book is best for learning data structures and algorithms?

“Introduction to Algorithms” by Thomas H. ... .

“Data Structures and Algorithms Made Easy” by Narasimha Karumanchi: ... .

“Algorithms” by Robert Sedgewick and Kevin Wayne: ... .

“Data Structures and Algorithm Analysis in Java” by Mark Allen Weiss: ... .

“Cracking the Coding Interview” by Gayle Laakmann McDowell:.

Is Python good to learn data structures and algorithms?

Python for DSA: Pros: Simplicity: Python's simple and readable syntax is ideal for beginners. It allows you to focus on algorithm design rather than intricate language details. Vast Community: Python has a massive community and a wealth of libraries like NumPy and pandas, making DSA implementation more accessible.