This is the code repository for Hands-On Data Structures and Algorithms with Python - Second Edition, published by Packt.
Learn to implement complex data structures and algorithms using Python
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.
This book covers the following exciting features:
If you feel this book is for you, get your copy today!
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All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
class Node:
def __init__(self, data=None):
self.data = data
self.next = NoneFollowing is what you need for this book: This book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
With the following software and hardware list you can run all code files present in the book (Chapter 1-15).
| Chapter | Software required | OS required |
|---|---|---|
| 1 | Python 3.7 | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Dr. Basant Agarwal works as an associate professor at Swami Keshvanand Institute of Technology, Management, and Gramothan, India. He has been awarded an M.Tech and Ph.D. from MNIT, Jaipur, India, and has more than 8 years' experience in academia and research. He has been awarded the prestigious PostDoc Fellowship by ERCIM (the European Research Consortium for Informatics and Mathematics) through the Alain Bensoussan Fellowship Programme. He has also worked at Temasek Laboratories, the National University of Singapore. He has authored a book on sentiment analysis in the Springer Book Series: Socio-Affective Computing series, and is published in more than 50 reputed conferences and journals. His research interests are focused on NLP, machine learning, and deep learning.
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