Stay ConnectedA weekly Python podcast hosted by Christopher Bailey with interviews, coding tips, and conversation with guests from the Python community.
The show covers a wide range of topics including Python programming best practices, career tips, and related software development topics. Join us every Friday morning to hear what’s new in the world of Python programming and become a more effective Pythonista.
Copyright: © 2020 Real Python
What are techniques for writing maintainable Python code? How do you make your Python more readable and easier to refactor? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
We discuss a recent article about writing code that is easy to maintain. We cover writing comments, creating meaningful names, avoiding magic numbers, and preparing code for your future self.
We also share several other articles and projects from the Python community, including release news, modifying the REPL, differences between Polars and pandas, generating realistic test data in Python, investigating quasars with Polars and marimo, creating simple meta tags for Django objects, and a GUI toolkit for grids of buttons.
Course Spotlight: Modern Python Linting With Ruff
Ruff is a blazing-fast, modern Python linter with a simple interface that can replace Pylint, isort, and Black—and it’s rapidly becoming popular.
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Our TOPPODCAST Picks marimo – Learn to visualize quasar redshift data by building an interactive marimo dashboard using Polars, pandas, and Matplotlib. You’ll practice retrieving, cleaning, and displaying data in your notebook. You’ll also build interactive UI components that live-update visualizations in the notebook.Discussion:
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How do you deploy your Python application without getting locked into an expensive cloud-based service? This week on the show, Michael Kennedy from the Talk Python podcast returns to discuss his new book, “Talk Python in Production.”
Michael runs multiple Python applications online, including a training site, blog, and two podcasts. While searching for the best solution for hosting his business, he documented his findings in a book. We talk about containerizing Python applications, generating static sites, preparing for traffic spikes, and avoiding cloud service lock-in.
Course Spotlight: Speed Up Python With Concurrency
Learn what concurrency means in Python and why you might want to use it. You’ll see a simple, non-concurrent approach and then look into why you’d want threading, asyncio, or multiprocessing.
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How does Python 3.14 perform under a few hand-crafted benchmarks? Does the performance of asyncio scale on the free-threaded build? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
At the top of the show, we have a mountain of release news and Python Enhancement Proposals to cover. Then, we dig into a couple of articles covering the performance of Python 3.14. The first is a benchmarking comparison of the last several Python versions and their variations, including JIT and free-threaded mode. The second explores the changes in 3.14 that enable asyncio to scale on CPython’s free-threaded build.
We also share several other articles and projects from the Python community, including an introduction to NiceGUI, a free-threaded Python library compatibility checker, an exploration of what is “good taste” in software engineering, HTML templating with t‑strings, and a tool for testing Sphinx docs instantly in the browser.
Course Spotlight: Documenting Python Projects With Sphinx and Read the Docs
In this video series, you’ll create project documentation from scratch using Sphinx, the de facto standard for Python. You’ll also hook your code repository up to Read the Docs to automatically build and publish your code documentation.
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wrapt – PEP 810 proposes adding explicit lazy imports to Python, but you can already achieve this with third-party libraries. This post shows you how using wrapt.Show Links:
asyncio Changes – asyncio changes are often overlooked. In the latest 3.14 release, there are three new asyncio features and changes.asyncio to scale on the free-threaded build of CPython.NiceGUI to turn Python scripts into interactive web apps without touching HTML, CSS, or JavaScript.Discussion:
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tdom: HTML Templating With t‑strings – Python 3.14 introduces t-strings, and this article showcases tdom, a new HTML DOM toolkit that takes advantage of them to produce safer output.Additional Links:
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How is teaching young students Python changing with the advent of LLMs? This week on the show, Kelly Schuster-Paredes from the Teaching Python podcast joins us to discuss coding and AI in the classroom.
Kelly shares her current thoughts on teaching Python to young students. She stresses that the earliest classes still need to cover the fundamentals. We also discuss how coding instruction is evolving toward reading and reviewing code more than writing it.
Course Spotlight: Building a Python GUI Application With Tkinter
In this video course, you’ll learn the basics of GUI programming with Tkinter, the de facto Python GUI framework. Master GUI programming concepts such as widgets, geometry managers, and event handlers. Then, put it all together by building two applications: a temperature converter and a text editor.
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Python 3.14 is here! Christopher Trudeau returns to discuss the new version with Real Python team member Bartosz Zaczyński. This year, Bartosz coordinated the series of preview articles with members of the Real Python team and wrote the showcase tutorial, “Python 3.14: Cool New Features for You to Try.” Christopher’s video course, “What’s New in Python 3.14”, covers the topics from the article and shows the new features in action.
Christopher and Bartosz dug into the new release to create code examples showcasing the new features for the tutorial and course. We look at the enhanced and more colorful REPL experience, better error messages, safer hooks for live debugging, and deferred annotation evaluation. We also discuss template strings, Zstandard compression, and multiple performance improvements.
We share our thoughts on the updates and offer advice about incorporating them into your projects. We also discuss when you should start running Python 3.14.
Course Spotlight: What’s New in Python 3.14
Covers Python 3.14’s key changes: free-threading, subinterpreters, t-strings, lazy annotations, new REPL features, and improved error messages.
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What’s changed about learning Python over the last few years? What new techniques and updated advice should beginners have as they start their journey? This week on the show, Stephen Gruppetta and Martin Breuss return to discuss beginning to learn Python.
We share techniques for finding motivation, building projects, and learning the fundamentals. We provide advice on installing Python and not obsessing over finding the perfect editor. We also examine incorporating LLMs into learning to code and practicing asking good questions.
Stephen shares details about our upcoming eight-week live course, Python for Beginners: Code With Confidence. Check out realpython.com/live to learn more and reserve your spot.
Course Spotlight: 11 Beginner Tips for Learning Python
In this course, you’ll see several learning strategies and tips that will help you jumpstart your journey towards becoming a successful Python programmer.
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What’s a good way to enable or disable code paths without redeploying the software? How can you use feature flags to toggle functionality for specific users of your application? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher shares an article exploring the use of feature flags. The piece advises targeting specific users, storing schemas, and relying on well-worn code paths. He also discusses the danger of the exponential growth of functionality tests as feature flags are added.
We dig into a comparison of six popular Python visualization libraries. The article provides code examples along with their respective visual output to highlight features and make selecting the optimal library for your work easier.
We also share several other articles and projects from the Python community, including a news roundup, benchmarking MicroPython, simplifying IPs and networks in Python, a “scream” cipher, and a browser-based graphical viewer for the output of Python’s cProfile module.
This episode is sponsored by InfluxData.
Course Spotlight: Exploring Astrophysics in Python With pandas and Matplotlib
This course uses three problems often covered in introductory astrophysics courses to explore in Python. Along the way, you’ll learn some astronomy and how to use a variety of data science libraries like NumPy, Matplotlib, pandas, and pint.
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ipaddress – Python’s built-in ipaddress module makes handling IP addresses and networks clean and reliable. This article shows how to validate, iterate, and manage addresses and subnets while avoiding common pitfalls of string-based handling.Projects:
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When converting an existing REST API to the Model Context Protocol, what should you consider? What anti-patterns should you avoid to keep an AI agent’s context clean? This week on the show, Kyle Stratis returns to discuss his upcoming book, “AI Agents with MCP”.
Kyle has been busy since he last appeared on the show in 2020. He’s taken his experience working in machine learning startups and started his own consultancy, Stratis Data Labs. He’s been documenting his explorations working with LLMs and MCP on his blog, The Signal Path.
Kyle is also writing a book about building MCP clients, services, and end-to-end agents. We discuss a recent article he wrote about the hazards of using an automated tool to convert a REST API into an MCP server. He shares his personal experiences with building MCP tools and provides additional resources for you to learn more about the topic.
This episode is sponsored by InfluxData.
Spotlight: Python for Beginners: Code With Confidence – Real Python
Learn Programming Fundamentals and Pythonic Coding in Eight Weeks—With a Structured Course
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What are your options for hosting your Python application or scripts? What are the advantages of a platform as a service, container-based hosts, or setting up a virtual machine? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
We discuss a recent article about hosting Python applications. The piece digs into the differences between using containers or platform-provided tools to automatically configure your project. We also cover an older article listing several free hosting options for smaller projects or Python scripts.
The Python documentary premiered this past week, and we provide a synopsis and our thoughts. Following a similar theme, we cover our recent code conversation video course, which explores the history of Python versions and the features added across the releases.
We also share several other articles and projects from the Python community, including a news roundup, regex affordances, four different ways to speed up your code, a Python-based music library manager, a tool to visualize the structure of your data in Python, and a project for exploring color science in Python.
This episode is sponsored by InfluxData.
Course Spotlight: A History of Python Versions and Features
Explore Python’s evolution from the 1990s to today with a brief history and demos of key features added throughout its lifetime.
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re.sub() with a function reference, and more.Projects:
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What’s happening with the latest releases of large language models? Is the industry hitting the edge of the scaling laws, and do the current benchmarks provide reliable performance assessments? This week on the show, Jodie Burchell returns to discuss the current state of LLM releases.
The most recent release of GPT-5 has been a wake-up call for the LLM industry. We discuss how the current scaling of these systems is reaching a diminishing edge. Jodie also shares how many AI model assessments and benchmarks are flawed. We also take a sober look at the productivity gains from using these tools for software development within companies.
We discuss how newer developers should consider additional factors when looking at the current job market. Jodie digs into how economic changes and rising interest rates are influencing layoffs and hiring freezes. Then we share a wide collection of resources for you to continue exploring these topics.
This episode is sponsored by InfluxData.
Course Spotlight: Exploring Python Closures: Examples and Use Cases
Learn about Python closures: function-like objects with extended scope used for decorators, factories, and stateful functions.
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