The Big Book of Small Python Projects (No Starch Press)
Wednesday, 21 July 2021

This collection of 81 Python projects will have you making digital art, games, animations, counting programs, and more right away. Al Sweigart shows how the code works, and explains how to experiment by adding your own custom touches. These simple, text-based programs are 256 lines of code or less. And whether it’s a vintage screensaver, a snail-racing game, a clickbait headline generator, or animated strands of DNA, each project is designed to be self-contained so you can easily share it online.

<ASIN:1718501242>

 

Author: Al Sweigart
Publisher: No Starch Press
Date: June 2021
Pages: 432
ISBN: 978-1718501249
Print: 1718501242
Kindle: B08FH9FV7M
Audience: Novice Python developers
Level: Introductory
Category: Python

bigpython

Examples include:

 

  • Hangman, Blackjack, and other games to play against your friends or the computer
  • Simulations of a forest fire, a million dice rolls, and a Japanese abacus
  • Animations like a virtual fish tank, a rotating cube, and a bouncing DVD logo screensaver
  • A first-person 3D maze game
  • Encryption programs that use ciphers like ROT13 and Vigenère to conceal text

 

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

For more Book Watch just click.

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

To have new titles included in Book Watch contact  BookWatch@i-programmer.info

Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.

 

 

Banner
 


Graph Databases in Action (Manning)

Author:  Dave Bechberger and Josh Perryman
Publisher: Manning
Pages: 366
ISBN: 978-1617296376
Print: 1617296376
Audience: Developers interested in graph databases
Rating: 4.5
Reviewer: Kay Ewbank

This book sets out to give developers building applications using graph databases an understanding o [ ... ]



Foundations of Deep Reinforcement Learning

Authors: Laura Graesser and Wah Loon Keng
Publisher: Addison-Wesley
Pages: 416
ISBN: 978-0135172384
Print: 0135172381
Kindle: B07ZVYZC6F
Audience: Developers in machine learning
Rating: 5
Reviewer: Mike James
Reinforcement learning seems to be able to do anything if you approach it in the right way, but [ ... ]


More Reviews