Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying The Python Workshop
  • Table Of Contents Toc
The Python Workshop

The Python Workshop

By : Bird, Dr. Lau Cher Han, Mario Corchero Jiménez , Graham Lee, Wade
4.3 (36)
close
close
The Python Workshop

The Python Workshop

4.3 (36)
By: Bird, Dr. Lau Cher Han, Mario Corchero Jiménez , Graham Lee, Wade

Overview of this book

Have you always wanted to learn Python, but never quite known how to start? More applications than we realize are being developed using Python because it is easy to learn, read, and write. You can now start learning the language quickly and effectively with the help of this interactive tutorial. The Python Workshop starts by showing you how to correctly apply Python syntax to write simple programs, and how to use appropriate Python structures to store and retrieve data. You'll see how to handle files, deal with errors, and use classes and methods to write concise, reusable, and efficient code. As you advance, you'll understand how to use the standard library, debug code to troubleshoot problems, and write unit tests to validate application behavior. You'll gain insights into using the pandas and NumPy libraries for analyzing data, and the graphical libraries of Matplotlib and Seaborn to create impactful data visualizations. By focusing on entry-level data science, you'll build your practical Python skills in a way that mirrors real-world development. Finally, you'll discover the key steps in building and using simple machine learning algorithms. By the end of this Python book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Python.
Table of Contents (13 chapters)
close
close

Functools

The final module of the standard library you are going to look at allows constructs with a minimal amount of code. In this topic, you are going to see how to use lru_cache and partial.

Caching with functools.lru_cache

Often, you have a function that is heavy to compute, in which you just want to cache results. Many developers will create their own caching implementation by using a dictionary, but that is error-prone and adds unnecessary code to our project. The functools module comes with a decorator — that is, functools.lru_cache, which is provided exactly for these situations. It is a recently used cache, with a max_size that is provided when the code is constructed. This means that you can specify a number of input values that you want to cache as a maximum, to limit the memory this function can take, or it can grow indefinitely. Once you reach the maximum number of different inputs that we want to cache, the input that was the least recently used will be...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
The Python Workshop
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon