Algorithmic Problem Solving with Python
by John B. Schneider, Shira Lynn Broschat, Jess Dahmen
Publisher: Washington State University 2015
Number of pages: 360
Python's syntax and idioms are much easier to learn than those of most other full-featured languages. This book uses programming language Python to introduce folks to programming and algorithmic thinking. The book is completely hyper-linked.
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by Hans Petter Langtangen - Springer
With a primary focus on examples and applications of relevance to computational scientists, this useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts.
by Kristian Rother - GitBook
This is a tutorial for novice programmers, it works best if you follow the exercises step by step. If you are fluent in any programming language, this might be very easy for you. It contains little material on the higher abstraction levels in Python.
by Richard Gruet
This reference covers invocation options, environment variables, lexical entities, basic types and their operations, advanced types, statements, iterators, generators, descriptors, decorators, built-in functions, built-in exceptions, and more.
by Caleb Hattingh - O'Reilly Media
This report helps you explore some of the lesser known Python libraries and tools that deserve more attention. Hattingh diligently spent time finding and testing hidden gems that are easy to install and use, cross-platform, and not yet popular.