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Improve Matplotlib With Style Sheets & Python Async for the Web

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Manage episode 341361363 series 2637014
Konten disediakan oleh Real Python. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Real Python atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

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 async support. The Python web ecosystem has been seeing new frameworks pop up which are fully async, or support going fully async, from the start.” Learn more about async and 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_cache decorator 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:

Additional Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

203 episode

Artwork
iconBagikan
 
Manage episode 341361363 series 2637014
Konten disediakan oleh Real Python. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Real Python atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

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 async support. The Python web ecosystem has been seeing new frameworks pop up which are fully async, or support going fully async, from the start.” Learn more about async and 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_cache decorator 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:

Additional Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

203 episode

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