Book Image

Learning Python

By : Romano
Book Image

Learning Python

By: Romano

Overview of this book

Learning Python has a dynamic and varied nature. It reads easily and lays a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring very different topics, like GUIs, web apps and data science. The book takes you all the way to creating a fully fledged application. The book begins by exploring the essentials of programming, data structures and teaches you how to manipulate them. It then moves on to controlling the flow of a program and writing reusable and error proof code. You will then explore different programming paradigms that will allow you to find the best approach to any situation, and also learn how to perform performance optimization as well as effective debugging. Throughout, the book steers you through the various types of applications, and it concludes with a complete mini website built upon all the concepts that you learned.
Table of Contents (20 chapters)
Learning Python
Credits
About the Author
Acknowledgements
About the Reviewers
www.PacktPub.com
Preface
Index

Anonymous functions


One last type of functions that I want to talk about are anonymous functions. These functions, which are called lambdas in Python, are usually used when a fully-fledged function with its own name would be overkill, and all we want is a quick, simple one-liner that does the job.

Imagine that you want a list of all the numbers up to N which are multiples of five. Imagine that you want to filter those out using the filter function, which takes a function and an iterable and constructs a filter object which you can iterate on, from those elements of iterable for which the function returns True. Without using an anonymous function, you would do something like this:

filter.regular.py

def is_multiple_of_five(n):
    return not n % 5
def get_multiples_of_five(n):
    return list(filter(is_multiple_of_five, range(n)))
print(get_multiples_of_five(50))

I have highlighted the main logic of get_multiples_of_five. Note how the filter uses is_multiple_of_five to filter the first n natural...