Improve Matplotlib With Style Sheets & Python Async for the Web
The Real Python Podcast
The H U M R E, Which Is Human Readable Regular Expressions
Last week's guest, Al Swiger, has worked on a library called hum ray. The concept behind it is human readable regular expressions. And then the other one I wanted to mention that is in there is another previous guest. Mox, N-O-X would be a good project to look at just for that.
Have you thought the standard output from Matplotlib is a bit generic looking? Would you like a quick way to add style and consistency to your data visualizations? This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
We cover an article about the magic of creating style sheets for Matplotlib. You can quickly customize plots and graphs with a single line of code. We share additional resources for you to try out new styles and learn what parameters are customizable.
Christopher covers an article about using async for web development in Python. The creation of Python generators inspired the development of async functionality. He discusses recent changes and async additions within Python web frameworks.
We cover several other articles and projects from the Python community, including how to install a pre-release version of Python, cache in Python with lru_cache, and get better at debugging, along with suggestions of libraries that deserve attention, a Python library for creating mathematical animations, and an extremely fast Python linter that’s written in Rust.
Course Spotlight: Python Debugging With pdb
In this hands-on course, you’ll learn the basics of using pdb, Python’s interactive source code debugger. pdb is a great tool for tracking down hard-to-find bugs, and it allows you to fix faulty code more quickly.
Topics:
- 00:00:00 – Introduction
- 00:02:21 – Python releases 3.10.7, 3.9.14, 3.8.14, and 3.7.14 are now available
- 00:03:51 – How Can You Install a Pre-Release Version of Python?
- 00:08:13 – Understanding async Python for the Web
- 00:17:11 – The Magic of Matplotlib Style Sheets
- 00:24:20 – Sponsor: Platform.sh
- 00:24:56 – Caching in Python With lru_cache
- 00:29:41 – Some Ways to Get Better at Debugging
- 00:38:14 – Video Course Spotlight
- 00:39:26 – Suggest a Lesser Known Library Deserving Attention
- 00:44:52 – ruff: An Extremely Fast Python Linter, Written in Rust
- 00:48:19 – Manim: Python Library for Creating Mathematical Animations
- 00:51:50 – Thanks and goodbye
Show Links:
- Python releases 3.10.7, 3.9.14, 3.8.14, and 3.7.14 are now available
- How Can You Install a Pre-Release Version of Python? – If you want to have a peek at what’s coming in the next stable version of Python, then you can install a pre-release version. In this tutorial, you’ll learn how to access the latest Python versions and help test them.
- Understanding async Python for the Web – “Recently Django 4.1 was released, and the thing most people seem interested in is the expanded
asyncsupport. The Python web ecosystem has been seeing new frameworks pop up which are fullyasync, or support going fully async, from the start.” Learn more aboutasyncand its use in web frameworks. - The Magic of Matplotlib Stylesheets – With a single line of code, you can integrate a style sheet with your Matplotlib visualization. In this tutorial, you’ll learn how to make your very own custom reusable style sheet.
- Caching in Python With lru_cache – Caching is an essential optimization technique. In this video course, you’ll learn how to use Python’s
@lru_cachedecorator to cache the results of your functions using the LRU cache strategy. This is a powerful technique you can use to leverage the power of caching in your implementations. - Some Ways to Get Better at Debugging – This is a short summary of a couple of academic papers on how to improve your debugging skills. The suggestions are to learn the codebase, learn the system, learn your tools, learn strategies, and gain experience.
Discussions:
Projects:
- ruff: An Extremely Fast Python Linter, Written in Rust
- Manim: Python Library for Creating Mathematical Animations
Additional Links:
- Managing Multiple Python Versions With pyenv – Real Python
- Your Python Coding Environment on Windows: Setup Guide – Real Python
- Customizing Matplotlib with style sheets and rcParams — Matplotlib 3.5.3 documentation
- dhaitz/matplotlib-stylesheets: Stylesheets for Matplotlib
- Kaggle: Your Home for Data Science
- wizard zines
- Rubber Duck Debugging – Debugging software with a rubber ducky
- pudb · PyPI
- Humre · PyPI
- Welcome to Nox — Nox 2022.8.7 documentation
- Episode #21: Exploring K-means Clustering and Building a Gradebook With Pandas – The Real Python Podcast
- 3Blue1Brown - YouTube
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