What are ways to improve how you’re using GitHub? How can you collaborate more effectively and improve your technical writing? This week on the show, Adam Johnson is back to talk about his new book, “Boost Your GitHub DX: Tame the Octocat and Elevate Your Productivity”.

Adam has written a series of books about improving developer experience (DX). In this episode, we dig into his newest book, which focuses on GitHub and how to get the most out of its features—from settings and keyboard shortcuts to hidden tools, CLI commands, and the command palette.

Adam also shares insights on the best ways to communicate on the platform. We discuss the nuances of GitHub-Flavored Markdown (GFM), best practices for effective communication in open source, the importance of maintaining civility in issue reports, and why he included a glossary of acronyms to help developers decode common shorthand like LGTM and FTFY.

This episode is sponsored by Honeybadger.

Course Spotlight: Introduction to Git and GitHub for Python Developers

What is Git, what is GitHub, and what’s the difference? Learn the basics of Git and GitHub from the perspective of a Pythonista in this step-by-step video course.

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How do you create automated tests to check your code for degraded performance as data sizes increase? What are the new features in pandas 3.0? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

Christopher digs into an article about building tests to make sure your software is fast, or at least doesn’t get slower as it scales. The piece focuses on testing Big-O scaling and its implications for algorithms.

We also discuss another article covering the top features in pandas 3.0, including the new dedicated string dtype, a cleaner way to perform column-based operations, and more predictable default copying behavior with Copy-on-Write.

We share several other articles and projects from the Python community, including a collection of recent releases and PEPs, a profiler for targeting individual functions, a quiz to test your Django knowledge, when to use each of the eight versions of UUID, the hard-to-swallow truths about being a software engineer, an offline reverse geocoding library, and a library for auto-generating CLIs from any Python object.

Our live Python cohorts start February 2, and we’re down to the last few seats. There are two tracks: Python for Beginners or Intermediate Deep Dive. Eight weeks of live instruction, small groups, and real accountability. Grab your seat at realpython.com/live.

This episode is sponsored by Honeybadger.

Course Spotlight: Intro to Object-Oriented Programming (OOP) in Python

Learn Python OOP fundamentals fast: master classes, objects, and constructors with hands-on lessons in this beginner-friendly video course.

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If you haven’t visited the Real Python website lately, then it’s time to check out a great batch of updates on realpython.com! Dan Bader returns to the show this week to discuss improvements to the site and more ways to learn Python.

Dan details changes to the website, including our Python reference area. This tool provides a quick reference for both beginners and experienced developers looking for concise definitions and refreshers on Python’s features.

We discuss the expansion of our live courses to include a beginner course and an intermediate deep dive. Dan also shares how we’re growing the team and highlights the ongoing commitment to our editorial standards.

Spotlight: Python for Beginners: Code With Confidence

Learn the fundamentals of Python step-by-step in a friendly, interactive cohort. Build confidence writing code and understand the “why” behind Python’s core concepts.

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How often have you heard about the speed of Python? What’s actually being measured, where are the bottlenecks—development time or run time—and which matters more for productivity? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

Christopher shares an article titled “The Uselessness of ‘Fast’ and ‘Slow’ in Programming.” It digs into how the different aspects of software performance span a wide range of orders of magnitude, and how developers can obsess over irrelevant performance details, often losing more time working in suboptimal environments than building what they need with tools they already know.

We also discuss an article about why uv is fast, which explains how most of its speed comes from engineering decisions rather than just being written in Rust.

We then share several other articles and projects from the Python community, including a roundup of 2025 year-end lists, an explanation of why Python’s deepcopy can be so slow, serving a website with FastAPI using Jinja2, Python numbers every programmer should know, a discussion of spec-driven development and whether waterfall is back, a tool to detect whether a PDF has a bad redaction, and a CLI for measuring HTTP request phases.

Course Spotlight: Jinja Templating

With Jinja, you can build rich templates that power the front end of your web applications. But you can also use Jinja without a web framework running in the background. Whenever you need to generate text files with dynamic content, Jinja provides a flexible and powerful solution.

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2025 Top List Roundup

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Are you looking for that solid foundation to begin your Python journey? Would the accountability of scheduled group classes help you get through the basics and start building something? This week, two members of the Python for Beginners live course discuss their experiences.

We speak with course instructor Stephen Gruppetta about building a course where the participants start using their knowledge as soon as possible. He describes how he’s evolved his teaching techniques over years of working with beginners. We explore the advantages of having a curated collection of written tutorials, video courses, and a forum for asking those nagging questions.

We also speak with students Louis and Andrew about their experiences learning Python through the course. They discuss learning how to apply their new skills, employing them in their careers, and building confidence to continue their Python learning journey.

Spotlight: Python for Beginners: Code With Confidence

Learn the fundamentals of Python step-by-step in a friendly, interactive cohort. Build confidence writing code and understand the “why” behind Python’s core concepts.

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PyCoder’s Weekly included over 1,500 links to articles, blog posts, tutorials, and projects in 2025. Christopher Trudeau is back on the show this week to help wrap up everything by sharing some highlights and uncovering a few hidden gems from the pile.

We share the top links explored by PyCoder’s readers. We also dig into trends across all the articles and stories this year. We highlight a few gems that we didn’t cover on the show and a couple that explore the overall themes of the year.

We hope you enjoy this review! We look forward to bringing you an upcoming year full of great Python news, articles, topics, and projects.

Course Spotlight: Using Functional Programming in Python

Boost your Python skills with a quick dive into functional programming: what it is, how Python supports it, and why it matters.

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What are the advantages of spec-driven development compared to vibe coding with an LLM? Are these recent trends a move toward declarative programming? This week on the show, Marc Brooker, VP and Distinguished Engineer at AWS, joins us to discuss specification-driven development and Kiro.

Marc describes the process of developing an application by writing specifications, which outline what a program should do and what needs it should meet. We dig into a bit of computer science history to explore the differences between declarative and imperative programming.

We also discuss Kiro, a new integrated development environment from Amazon, built around turning prompts into structured requirements. We examine the various types of documents used to specify tasks, requirements, design, and steering.

Real Python Resource Spotlight: Python Coding With AI - Learning Path

Explore tools and workflows for AI in Python: coding partners, prompt engineering, RAG, ChromaDB, FastAPI chatbots, and MCP integrations. Stay current and start today.

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What are the recent advances in the field of quantum computing and high-performance computing? And what Python tools can you use to develop programs that run on quantum computers? This week on the show, Real Python author Negar Vahid discusses her tutorial, “Quantum Computing Basics With Qiskit.”

Negar digs into the fundamentals of quantum computers, describing qubits, superposition, entanglement, and interference. We discuss the concept of quantum advantage and the fields of exploration where quantum computing promises speed-ups over classical computers. She also shares tools for designing quantum circuits with Python.

Course Spotlight: Profiling Performance in Python

Learn to profile Python programs with built-in and popular third-party tools, and turn performance insights into faster code.

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What are the steps to get started building a FastAPI application? What are the different types of concurrency available in Python? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

We discuss a recent Real Python step-by-step tutorial about programming a FastAPI example application. You practice installing FastAPI, building your first endpoints, adding path and query parameters, and validating endpoints using Pydantic.

Christopher covers updates to his Real Python video course about concurrency in Python. The course digs into what concurrency means in Python and why you might want to incorporate it in your code. He describes the different methods and demonstrates how to approach coding using threading, asyncio, and multiprocessing.

We also share several other articles and projects from the Python community, including a news roundup, the PSF fundraiser campaign for 2025, where Python stores attributes, performance hacks for faster Python code, a project to transform functions into a web interface, and a Python disk-backed cache.

Course Spotlight: Python Descriptors

Learn what Python descriptors are, how the descriptor protocol works, and when descriptors are useful, with practical, hands-on examples.

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How do you prepare your Python data science projects for production? What are the essential tools and techniques to make your code reproducible, organized, and testable? This week on the show, Khuyen Tran from CodeCut discusses her new book, “Production Ready Data Science.”

Khuyen shares how she got into blogging and what motivated her to write a book. She shares tips on how to create repeatable workflows. We delve into modern Python tools that will help you bring your projects to production.

Course Spotlight: Python Project Management With uv

Create and manage Python projects with uv, a blazing-fast package and project manager built in Rust. Learn setup, workflow, and best practices.

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