Classic Computer Science Problems in Python

It has been a while since I have made a post. Recently I have been working on a challenging book called Classic Computer Science Problems in Python by David Kopec. The book is available for purchase here: https://www.manning.com/books/classic-computer-science-problems-in-python  and here is the author's website for the series https://classicproblems.com/.

The book teaches various programming techniques as well as algorithms taught in computer science courses. And on top of these, the author tries to introduce many different helpful Python libraries. One game changing module introduced in the book is the dataclasses module which makes creating classes and using them a breeze. dataclasses allows you to do away the awkward __init__() method and define your data in a few short lines. Here is a great talk introducing this module https://www.youtube.com/watch?v=Udz4jjd46ho.

As a self-taught data analyst, the content of the book has been very challenging for me. I often have to find supplementary material to help me understand the various concepts. The author's insistence on using type hints certainly made it harder - it is also something new I have to deal with in the book. Overall, it's been difficult yet rewarding so far.

I have created a Github repo to track my progress of going through the book. I have converted much of the content and code to Jupyter Notebooks - mainly for my own benefit. Here is a link to the Github repo:  https://github.com/wlsamchen01/Classic-Computer-Science-Problems-in-Python

A word of warning. The content covered in the book is not for beginners. You need to be intermediate or above to fully understand the content.