The Real Python Podcast

This week, Mike Fiedler, PyPI's Safety & Security Engineer, talks about how he started as a contributor and became a maintainer. They discuss securing accounts using 2FA and a new publishing method called trusted publishing. Mike also shares advice on giving back to open source.

The podcast discusses fundamental developer skills for new Python users, software design philosophy, and knowledge sharing within an organization. It also covers the results of the Python Developer Survey and shares various articles and projects from the Python community. Topics include building a blog in Django, optimizing code without multiple cores, and using Python dataframes. The episode concludes with discussions on managing developers from non-CS backgrounds, measuring code quality, and a TUI app for daily writing.

Geir Arne Hjelle and Christopher Trudeau discuss the new features of Python 3.12, including better error messaging, more intuitive f-strings, subinterpreters, the Linux perf profiler, improved typing syntax, and more. They provide advice on incorporating the updates into your projects and discuss when to start running Python 3.12.

Al Sweigart, a programmer and author, discusses his experiments using ChatGPT to review his book on recursion programming. They explore the positive and negative results of the review and consider its value as a learning tool. They also discuss the potentials and pitfalls of using ChatGPT as a learning resource for Python developers.

This podcast discusses getting involved in open source projects, providing resources for beginners and sharing experiences with contributing to projects. It also covers creating QR codes with Python, caching in Python with LRU cache, and explores various articles and projects from the Python community.

Emery Berger, professor of computer science, talks about Scalene, a high-performance CPU, GPU, and memory profiler. It can analyze code at the function or line level, compare Python vs C code, and provide AI-powered optimization proposals. He also shares additional Python code-assistant tools from his lab.

Topics include Pythonic examples, language mistakes, Microsoft's Python in Excel beta program, PSF announcements, Polars DataFrame library showcase, immortal objects in Python, code image generator project, MS Paint clone in terminal, Django ORM cheatsheet.

Philipp Acsany, a Real Python author and core team member, talks about choosing the right coding font for programming in Python. They discuss the importance of differentiating characters, the impact of syntax on font choice, and provide resources to find the perfect monospace font. The podcast also mentions a course on building a Python wordle clone and a discussion about the Haiti programming language.

Author and Python trainer Matt Harrison discusses his new book on improving classification models with XGBoost. He emphasizes the importance of exploratory data analysis and provides tools to explain models to stakeholders. The podcast also covers the popularity of XGBoost, the concept of prediction in data science, and the application of XGBoost in classification models.

Have you ever encountered strange behavior when trying something new in Python? What are common quirks hiding within the language? This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects. We discuss a recent blog post that lists a collection of quirky Python behaviors. We share a few examples with explanations but leave several as puzzles to dig into. Christopher transitions our discussion into Python features that can be difficult to explain to a new programmer. We also share some of our own stumbling blocks while learning the language. We cover several other articles and projects from the Python community, including a news update, previewing Python 3.12’s more intuitive and consistent f-strings, finding performance bottlenecks with profiling, emulating the 6502 processor in Python, using Rich to inspect Python objects, and plotting statistical data with Lets-Plot. This week’s episode is brought to you by Porkbun. Course Spotlight: Graph Your Data With Python and ggplot In this course, you’ll learn how to use ggplot in Python to build data visualizations with plotnine. You’ll discover what a grammar of graphics is and how it can help you create plots in a very concise and consistent way. Topics: 00:00:00 – Introduction 00:02:12 – Steering Council Announces Optional GIL 00:04:05 – Polars is Starting a Company 00:05:13 – Python 3.12 Preview: More Intuitive and Consistent F-Strings 00:09:29 – Sponsor: Porkbun 00:10:22 – Profiling in Python: How to Find Performance Bottlenecks 00:21:01 – Writing a 6502 Emulator in Python 00:24:36 – Python Quirks 00:32:30 – Video Course Spotlight 00:34:02 – What Python feature would you have trouble explaining to a new programmer? 00:42:25 – Using Rich Inspect to Interrogate Python Objects 00:44:36 – Lets-Plot: Plotting Library for Statistical Data 00:48:01 – Thanks and goodbye News: Steering Council Announces Optional GIL Polars is Starting a Company Show Links: Python 3.12 Preview: More Intuitive and Consistent F-Strings – In this tutorial, you’ll preview one of the upcoming features of Python 3.12, which introduces a new f-string syntax formalization and implementation. The new implementation lifts some restrictions and limitations that affect f-string literals in Python versions lower than 3.12. Profiling in Python: How to Find Performance Bottlenecks – In this tutorial, you’ll learn how to profile your Python programs using numerous tools available in the standard library, third-party libraries, as well as a powerful tool foreign to Python. Along the way, you’ll learn what profiling is and cover a few related concepts. Writing a 6502 Emulator in Python – The 6502 processor from Motorola was quite popular and could be found in the Nintendo and Sega consoles as well as the Commodore 64. This very detailed article shows you how to build an emulator for the processor in Python. Python Quirks – A straight-out list of code snippets showing off some of the weird and unexpected behavior of your favorite language. Discussion What Python feature would you have trouble explaining to a new programmer? - Trey Hunner on Twitter Projects: Using Rich Inspect to Interrogate Python Objects – You might know the Rich library as the terminal color tool, but it has a few utilities that are generally helpful in your code. This article shows you the inspect feature, which gives you loads of information on an object. Lets-Plot: Plotting Library for Statistical Data Additional Links: Polars Python 3.12 Preview: Support For the Linux perf Profiler – Real Python Python Timer Functions: Three Ways to Monitor Your Code – Real Python Episode #128: Using a Memory Profiler in Python & What It Can Teach You – The Real Python Podcast Defining Your Own Python Function – Mutable Default Parameters Level up your Python skills with our expert-led courses: Using Jupyter Notebooks Creating Web Maps From Your Data With Python Folium Graph Your Data With Python and ggplot Support the podcast & join our community of Pythonistas