Book Image

Learn Python Programming - Second Edition

By : Fabrizio Romano
4.5 (2)
Book Image

Learn Python Programming - Second Edition

4.5 (2)
By: Fabrizio Romano

Overview of this book

Learn Python Programming is a quick, thorough, and practical introduction to Python - an extremely flexible and powerful programming language that can be applied to many disciplines. Unlike other books, it doesn't bore you with elaborate explanations of the basics but gets you up-and-running, using the language. You will begin by learning the fundamentals of Python so that you have a rock-solid foundation to build upon. You will explore the foundations of Python programming and learn how Python can be manipulated to achieve results. Explore different programming paradigms and find the best approach to a situation; understand how to carry out performance optimization and effective debugging; control the flow of a program; and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens. Learn Python Programming will give you a thorough understanding of the Python language. You'll learn how to write programs, build websites, and work with data by harnessing Python's renowned data science libraries. Filled with real-world examples and projects, the book covers various types of applications, and concludes by building real-world projects based on the concepts you have learned.
Table of Contents (16 chapters)

A quick peek at the itertools module

A chapter about iterables, iterators, conditional logic, and looping wouldn't be complete without a few words about the itertools module. If you are into iterating, this is a kind of heaven.

According to the Python official documentation (https://docs.python.org/2/library/itertools.html), the itertools module is:

This module which implements a number of iterator building blocks inspired by constructs from APL, Haskell, and SML. Each has been recast in a form suitable for Python. The module standardizes a core set of fast, memory efficient tools that are useful by themselves or in combination. Together, they form an “iterator algebra” making it possible to construct specialized tools succinctly and efficiently in pure Python.

By no means do I have the room here to show you all the goodies you can find in this module, so I...