Book Image

Learning Python

By : Fabrizio Romano
Book Image

Learning Python

By: Fabrizio 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

Some performance considerations


So, we've seen that we have many different ways to achieve the same result. We can use any combination of map, zip, filter, or choose to go with a comprehension, or maybe choose to use a generator, either function or expression. We may even decide to go with for loops: when the logic to apply to each running parameter isn't simple, they may be the best option.

Other than readability concerns though, let's talk about performances. When it comes to performances, usually there are two factors which play a major role: space and time.

Space means the size of the memory that a data structure is going to take up. The best way to choose is to ask yourself if you really need a list (or tuple) or if a simple generator function would work as well. If the answer is yes, go with the generator, it'll save a lot of space. Same goes with functions: if you don't actually need them to return a list or tuple, then you can transform them in generator functions as well.

Sometimes...