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 is a good way to add isolated, reusable functionality to Python classes? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher covers a recent Real Python tutorial about developing mixin classes to reuse code across multiple Python classes. He describes how mixins rely on multiple inheritance to combine features from different classes, enhancing flexibility and code reuse.
We also share several other articles and projects from the Python community, including a news roundup, highlights from the 2024 Python Developers Survey, reasons you might not need a Python class, an exploration of asyncio’s sharp corners, an explanation of how JIT builds of CPython work, a web-based GUI library, and a project for quickly querying Python lists.
This episode is sponsored by InfluxData.
Course Spotlight: Design and Guidance: Object-Oriented Programming in Python
In this video course, you’ll learn about the SOLID principles, which are five well-established standards for improving your object-oriented design in Python. By applying these principles, you can create object-oriented code that’s more maintainable, extensible, scalable, and testable.
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Our TOPPODCAST Picks asyncio: A Library With Too Many Sharp Corners – asyncio has a few gotchas and this post describes five different problems, including: cancellation, disappearing tasks, and more.Projects:
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What went into developing the open-source Python tools data scientists use every day? This week on the show, we talk with Travis Oliphant about his work on SciPy, NumPy, Numba, and many other contributions to the Python scientific community.
Travis discusses his initial involvement in the open-source community and how he discovered Python while working in biomedical imaging. He was trying to find ways to manage large sets of numerical data, which led to his initial contributions and collaborations in building scientific libraries.
His appearance on the show coincides with the release of the Python documentary, in which he’s featured. We discuss the myriad organizations Travis founded, including Quansight, OpenTeams, and Anaconda. We dig into his underlying mission to continue fostering the growth of the open-source scientific computing community.
This episode is sponsored by InfluxData.
Course Spotlight: NumPy Techniques and Practical Examples
In this video course, you’ll learn how to use NumPy by exploring several interesting examples. You’ll read data from a file into an array and analyze structured arrays to perform a reconciliation. You’ll also learn how to quickly chart an analysis and turn a custom function into a vectorized function.
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When considering an object-oriented programming problem, should you prefer inheritance or composition? Why wouldn’t it just be simpler to use functions? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher shares an article about structuring code using inheritance, composition, or only functions. We discuss how the piece is a good exploration of the trade-offs of each solution. Unlike the tutorials beginners typically encounter while learning the fundamentals, the article goes much deeper into the “why” of object-oriented programming.
We also share several other articles and projects from the Python community, including a news roundup, processing audio in Python, reasons why you shouldn’t call dunder methods, smuggling arbitrary data through an emoji, an HTML to markdown converter, and a library to convert Python requests into curl commands.
Course Spotlight: Single and Double Underscore Naming Conventions in Python
In this video course, you’ll learn a few Python naming conventions involving single and double underscores (_). You’ll learn how to use this character to differentiate between public and non-public names in APIs, write safe classes for subclassing purposes, avoid name clashes, and more.
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pedalboard – The pedalboard library for Python is aimed at audio processing of various sorts, from converting between formats to adding audio effects. This post summarizes a PyCon US talk on pedalboard and its uses.Projects:
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What are the advantages of using Polars for your Python data projects? When should you use the lazy or eager APIs, and what are the benefits of each? This week on the show, we speak with Jeroen Janssens and Thijs Nieuwdorp about their new book, Python Polars: The Definitive Guide.
Jeroen and Thijs describe how they were introduced to Polars while working at Xomnia. They were converting a large data project to Python and saw surprising speed increases using the new library.
We discuss converting projects from pandas to Polars, getting away from indexes, consistent syntax, and using lazy vs eager APIs. Along the way, Jeroen and Thijs offer tips for getting the most out of Polars in your code.
We dig into the process of writing a definitive guide and the advantages of working collaboratively on a book project. They also share resources for practicing data wrangling and building visualizations with Pydy Tuesday.
Course Spotlight: Working With Python Polars
Welcome to the world of Polars, a powerful DataFrame library for Python. In this video course, you’ll get a hands-on introduction to Polars’ core features and see why this library is catching so much buzz.
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Do the design patterns learned in other programming languages translate to coding in Python? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher dives into an article that tackles popular object-oriented design patterns from the famous Gang of Four book. These patterns offer solutions to common coding problems, but as Christopher explores, Python often doesn’t even have the problems these solutions try to fix. He discusses several common design patterns and the simpler, more Pythonic ways to achieve the same goals.
We also share several other articles and projects from the Python community, including an exceptionally robust news roundup, running coverage on tests, an exploration of expert generalists, a preview of template strings from Python 3.14, a quiz on f-strings, and a project that calculates the complexity of your Python code.
Course Spotlight: Working With Python’s Built-in Exceptions
Learn the most common built-in Python exceptions, when they occur, how to handle them, and how to raise them properly in your code.
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What goes into supporting more than 650,000 projects and nearly a million users of the Python Package Index? This week on the show, we speak with Maria Ashna about her first year as the inaugural PyPI Support Specialist.
Maria has a varied background in creative arts and neuroscience. She decided to apply for the PyPI support position, defying common misconceptions about who can take on roles inside the Python Software Foundation, and challenging imposter syndrome along the way.
Her recent talks at PyCon US 2025 and EuroPython 2025 were about her experiences in the role. She describes tackling the backlogs of account recovery and PEP 541 requests, and we also discuss PyPI community and company organizations.
Course Spotlight: Publishing Python Packages to PyPI
In this video course, you’ll learn how to create a Python package for your project and how to publish it to PyPI, the Python Package Index. Quickly get up to speed on everything from naming your package to configuring it using setup.cfg.
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How does the performance of an algorithm hold up when you put it into a realistic context? Where might Python code defy Big O notation expectations when using a profiler? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher shares an article about why real-world performance often defies Big O expectations. The piece starts with a task coded in Go and then optimized from O(n²) to O(n). Can an interpreted language like Python compete with a compiled language? Profiling the performance of both versions provides some interesting results.
We also share several other articles and projects from the Python community, including a news roundup, the fastest way to detect a vowel in a string, whether Python dictionaries are ordered data structures, an overview of Python’s enum module, a Python client library for Google Data Commons, and a project to convert plain ASCII to “smart” punctuation.
Course Spotlight: Building Enumerations With Python’s enum
In this video course, you’ll discover the art of creating and using enumerations of logically connected constants in Python. To accomplish this, you’ll explore the Enum class and other associated tools and types from the enum module in the Python standard library.
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enum Overview – This article gives an overview of the tools available in the module enum and how to use them, including Enum, auto, StrEnum, Flag, and more.Projects:
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What motivates someone to learn how to code as a scientist? How do you harness the excitement of solving problems quickly and make the connection to the benefits of coding in your scientific work? This week on the show, we speak with Ben Lear and Christopher Johnson about their book “Coding For Chemists.”
Christopher is an associate professor of chemistry at Stony Brook University. Ben is a professor of chemistry at Penn State’s Eberly College of Science. They’re long-time friends who decided to collaborate on a book after discussing the challenges of teaching coding to chemistry students.
The book targets chemists and other researchers who want to streamline common workflows with Python. It covers core Python concepts, data visualization, and data analysis topics by sharing common problems encountered in chemical research and presenting a complete Python-based solution for each problem.
We discuss how they collaborated on the book and decided what libraries and tools to include. We cover how LLM tools have affected classroom teaching and require new techniques to reinforce learning. We also dig into what motivates students to learn how to code.
Course Spotlight: Defining Python Functions With Optional Arguments
In this video course, you’ll learn about Python optional arguments and how to define functions with default values. You’ll also learn how to create functions that accept any number of arguments using args and kwargs.
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What goes into crafting an effective Python script? How do you organize your code, manage dependencies with PEP 723, and handle command-line arguments for the best results? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.
We dig into a recent Real Python article about how to structure your Python scripts. It includes advice for adding inline script metadata as defined in PEP 723, which helps tools automatically create an environment and install dependencies when the script is run. The piece also covers choosing appropriate data structures, improving runtime feedback, and making your code more maintainable with constants and entry points.
We discuss a collection of software trends happening behind the scenes of the constant LLM news. The piece starts with local-first software, prioritizing processing and storing private data on personal devices rather than relying on the cloud. The other trends include common themes and tools we’ve shared over the past few years, including WebAssembly, SQLite’s renaissance, and improvements to cross-platform mobile development.
We also share several other articles and projects from the Python community, including a news roundup, the state of free-threaded Python, tips for improving Django management commands, advice for time management as a manager, a data science-focused IDE, and a project to check for multiple patterns in a single string.
Course Spotlight: SQLite and SQLAlchemy in Python: Move Your Data Beyond Flat Files
In this video course, you’ll learn how to store and retrieve data using Python, SQLite, SQLAlchemy, and flat files. Using SQLite with Python brings with it the additional benefit of accessing data with SQL. By adding SQLAlchemy, you can work with data in terms of objects and methods.
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What goes into scaling a web application today? What are resources for learning and practicing DevOps skills? This week on the show, Calvin Hendryx-Parker is back to discuss the tools and infrastructure for autoscaling web applications with Kubernetes and Karpenter.
Calvin is the co-founder and CTO of Six Feet Up, a Python and AI consultancy. He shares how they recently helped a client scale a web application that employs video, audio, and chat sessions. We dig deep into the tooling behind modern Kubernetes systems management and performance monitoring.
Calvin shares a project bootstrap tool for streamlining the development and deployment of a web application. The tool includes a complete blueprint for the infrastructure needed to get started.
We also dig into a collection of coding tools Calvin has been experimenting with. We discuss his recent IndyPy presentation, “Battle of the Bots,” which put several AI code assistants through their paces.
This episode is sponsored by AMD.
Course Spotlight: First Steps With LangChain
Large language models (LLMs) have taken the world by storm. In this step-by-step video course, you’ll learn to use the LangChain library to build LLM-assisted applications.
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