Book Image

Getting Started with Python

By : Fabrizio Romano, Benjamin Baka, Dusty Phillips
Book Image

Getting Started with Python

By: Fabrizio Romano, Benjamin Baka, Dusty Phillips

Overview of this book

This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: • Learn Python Programming - Second Edition by Fabrizio Romano • Python Data Structures and Algorithms by Benjamin Baka • Python 3 Object-Oriented Programming by Dusty Phillips
Table of Contents (31 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
8
Stacks and Queues
10
Hashing and Symbol Tables
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 that 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 that you can iterate on, from those elements of iterables 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)))

Note how we use is_multiple_of_five to filter the first n natural numbers. This seems a bit excessive, the task is simple and we don't need to keep the is_multiple_of_five...