The Real Python Podcast

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 [https://realpython.com/courses/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. Topics: * 00:00:00 – Introduction * 00:02:06 – Ben’s background and starting with Python * 00:04:34 – Chris’ background and starting with Python * 00:07:16 – What has sped up Python for your use? * 00:08:22 – How did idea for the book start? * 00:11:30 – Shifting publisher and new release time frame * 00:12:24 – Three potential audiences * 00:13:20 – The ubiquitous need for programming skills in science * 00:15:05 – Difficult workflows with chemistry equipment * 00:16:06 – What is a chart recorder? * 00:16:34 – Working with proprietary equipment and exporting data * 00:23:37 – Explaining how programming will help chemists * 00:27:31 – Finding the problems to solve * 00:29:09 – The classic common chemistry workflow * 00:30:48 – Teaching Python in a classroom and starting with functions * 00:35:05 – Helping students cultivate inspiration * 00:37:06 – LLM and AI use by students * 00:41:19 – Video Course Spotlight * 00:42:36 – Using Spyder IDE and Positron * 00:45:29 – How does the book cover notebooks and managing packages? * 00:48:08 – Using marimo for archiving and sharing projects * 00:50:25 – What was difficult to put into the book? * 00:54:04 – What were you eager to share in the book? * 00:55:54 – Teaching students about file management * 00:58:13 – Sharing tools to plot data * 01:01:45 – Choosing not to teach pandas and using NumPy arrays instead * 01:04:03 – How can people learn more about the book? * 01:05:20 – What are you excited about in the world of Python? * 01:07:58 – What do you want to learn next? * 01:10:50 – How can people follow your work? * 01:12:15 – Thanks and goodbye Show Links: * Coding For Chemists - Getting Started [https://codingforchemistsbook.com/getting-started/index.html] * Ben Lear - Eberly College of Science [https://science.psu.edu/chem/people/bul14] * Christopher Johnson - Department of Chemistry [https://www.stonybrook.edu/commcms/chemistry/people/faculty_profiles/johnson-christopher.php#ResearchDescription] * Chart recorder - Wikipedia [https://en.wikipedia.org/wiki/Chart_recorder] * pandas - Python Data Analysis Library [https://pandas.pydata.org/] * NumPy [https://numpy.org/] * Spyder - The Python IDE that scientists and data analysts deserve [https://www.spyder-ide.org/] * Positron [https://positron.posit.co/] * marimo - A next-generation Python notebook [https://marimo.io/] * Streamlit - A faster way to build and share data apps [https://streamlit.io/] * Plotly - Data Apps for Production [https://plotly.com/] * Bokeh [https://bokeh.org/] * Vega-Altair: Declarative Visualization in Python [https://altair-viz.github.io/] * codechembook - PyPI [https://pypi.org/project/codechembook/] * CodeChemBook: Companion library for Coding for Chemists Book - GitHub [https://github.com/chrisjohnsonSBU/CodeChemBook] * Data Meets Design [https://data-meets-design.com/] * The Lear Laboratory [https://thelearlab.com/] * Statistical Inference - 2nd Edition - George Casella - Roger Berger [https://www.routledge.com/Statistical-Inference/Casella-Berger/p/book/9781032593036?srsltid=AfmBOorJsJdPQiCROH5OEIx9jGqkBW8XgAJfE407BF1dkeVNUDBsl0rx] * Johnson Lab @SBU [https://sites.google.com/a/stonybrook.edu/johnsonlab/] * Christopher J. Johnson - Google Scholar [https://scholar.google.com/citations?user=IetGM5cAAAAJ&hl=en] * Benjamin Lear - Google Scholar [https://scholar.google.com/citations?hl=en&user=nL7taSoAAAAJ] Level up your Python skills with our expert-led courses: * Defining Python Functions With Optional Arguments [https://realpython.com/courses/defining-python-functions-with-optional-arguments/] * Data Visualization Interfaces in Python With Dash [https://realpython.com/courses/data-viz-with-dash/] * NumPy Techniques and Practical Examples [https://realpython.com/courses/numpy-techniques-practical-examples/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]

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 [https://realpython.com/courses/sqlite-sqlalchemy-python-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. Topics: * 00:00:00 – Introduction * 00:02:26 – Followup - marimo and LaTeX * 00:03:26 – PEP 734: Multiple Interpreters in the Stdlib (Accepted) * 00:03:52 – Python 3.13.4, 3.12.11, 3.11.13, 3.10.18 and 3.9.23 Security Releases * 00:04:21 – Python Insider: Python 3.14.0 beta 3 is here! * 00:04:30 – Django Bugfix Releases: 5.2.3, 5.1.11, and 4.2.23 * 00:04:52 – NumPy v2.3.0 Released * 00:05:02 – scikit-learn 1.7 Released * 00:05:12 – PyData Virginia 2025 Talks * 00:05:52 – How Can You Structure Your Python Script? * 00:12:08 – State of Free-Threaded Python * 00:18:23 – 5 Non-LLM Software Trends to Be Excited About * 00:29:50 – Video Course Spotlight * 00:31:23 – Better Django Management Commands * 00:33:56 – Advice for time management as a manager * 00:46:49 – positron: Data Science IDE * 00:50:05 – ahocorasick_rs: Check for Multiple Patterns in a Single String * 00:52:41 – 10 Polars Tools and Techniques To Level Up Your Data Science - Podcast Episode * 00:53:22 – Thanks and goodbye News: * PEP 734: Multiple Interpreters in the Stdlib (Accepted) [https://peps.python.org/pep-0734/] * Python 3.13.4, 3.12.11, 3.11.13, 3.10.18 and 3.9.23 Security Releases [https://pythoninsider.blogspot.com/2025/06/python-3134-31211-31113-31018-and-3923.html] * Python 3.13.5 Released [https://docs.python.org/release/3.13.5/whatsnew/changelog.html] * Python Insider: Python 3.14.0 beta 3 is here! [https://pythoninsider.blogspot.com/2025/06/python-3140-beta-3-is-here.html] * Django Bugfix Releases: 5.2.3, 5.1.11, and 4.2.23 [https://www.djangoproject.com/weblog/2025/jun/10/bugfix-releases/] * NumPy v2.3.0 Released [https://github.com/numpy/numpy/releases/tag/v2.3.0] * scikit-learn 1.7 Released [https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_7_0.html] * PyData Virginia 2025 Talks [https://www.youtube.com/playlist?list=PLGVZCDnMOq0qLS7Mk-jI9jhb4t5UY6yDW] – A list of the recorded talks from PyData Virginia 2025. Show Links: * How Can You Structure Your Python Script? [https://realpython.com/python-script-structure/] – Structure your Python script like a pro. This guide shows you how to organize your code, manage dependencies with PEP 723, and handle command-line arguments. * State of Free-Threaded Python [https://pyfound.blogspot.com/2025/06/python-language-summit-2025-state-of-free-threaded-python.html] – This is a blog post from the Python Language Summit 2025 giving an update on the progress of free-threaded Python. You may also be interested in the complete list of Language Summit Blogs [https://discuss.python.org/t/announcing-the-python-language-summit-2025-blog-posts/95282]. * PEP 779 – Criteria for supported status for free-threaded Python [https://peps.python.org/pep-0779/] * 5 Non-LLM Software Trends to Be Excited About [https://read.engineerscodex.com/p/5-non-llm-software-trends-to-be-excited] – Tired of reading about AI and LLMs? This post talks about other tech that is rapidly changing in the software world, including local-first applications, web assembly, the improvement of cross-platform tools, and more. * Better Django Management Commands [https://www.revsys.com/tidbits/better-django-management-commands-with-django-click-and-django-typer/] – Writing Django management commands can involve a ton of boilerplate code. This article shows you how to use two libraries that could cut your management command code in half: django-click and django-typer. Discussion: * Advice for time management as a manager - benkuhn.net [https://www.benkuhn.net/tmgr/] Projects: * positron: Data Science IDE [https://github.com/posit-dev/positron] * ahocorasick_rs: Check for Multiple Patterns in a Single String [https://github.com/G-Research/ahocorasick_rs] Additional Links: * Visualize outputs - Mardown editor and LaTeX - marimo [https://docs.marimo.io/guides/outputs/?h=latex#markdown-editor] * PyCon US 2025 - YouTube [https://www.youtube.com/playlist?list=PL2Uw4_HvXqvb98mQjN0-rYQjdDxJ_hcrs] * DjangoCon Europe 2025 Dublin - YouTube [https://www.youtube.com/playlist?list=PLY_che_OEsX19RNHHqERLODTtYs1YAtMA] * Executing Python Scripts With a Shebang [https://realpython.com/python-shebang/] * Local-first software: You own your data, in spite of the cloud [https://www.inkandswitch.com/essay/local-first/] * Code OSS [https://github.com/microsoft/vscode] * Episode #510 - 10 Polars Tools and Techniques To Level Up Your Data Science - Talk Python To Me Podcast [https://talkpython.fm/episodes/show/510/10-polars-tools-and-techniques-to-level-up-your-data-science] * PyCoder’s Weekly - Submit a Link [https://pycoders.com/submissions] Level up your Python skills with our expert-led courses: * Execute Your Python Scripts With a Shebang [https://realpython.com/courses/execute-python-scripts-with-shebang/] * Django Admin Customization [https://realpython.com/courses/django-admin-customization/] * SQLite and SQLAlchemy in Python: Move Your Data Beyond Flat Files [https://realpython.com/courses/sqlite-sqlalchemy-python-beyond-flat-files/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]

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 [https://realpython.com/courses/first-steps-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. Topics: * 00:00:00 – Introduction * 00:02:23 – Scaling a Django project using Kubernetes * 00:05:35 – Elastic Kubernets Service (EKS) * 00:09:10 – Kubernetes terminology and improvements in tooling * 00:11:29 – The Control Plane and the API * 00:14:06 – Video Course Spotlight * 00:15:11 – scaf: providing DevOps engineers a blueprint for new projects * 00:17:21 – What have been the benefits of scaf for internal teams? * 00:20:18 – How do you identify and reproduce scaling issues? * 00:22:44 – Dealing with IP address scaling * 00:26:03 – Why use other observability tools beyond AWS internal ones? * 00:29:22 – Other lessons learned and moving toward refactoring code * 00:33:53 – Scaling a voice-based LLM application * 00:35:35 – Sponsor: AMD * 00:36:11 – Looking at limitations and bottlenecks * 00:38:08 – Configuring a Kubernetes operator to act on itself * 00:39:47 – What project components are within a pod of containers? * 00:42:31 – Budgeting for scale using Karpenter * 00:43:58 – Tools for running containers locally * 00:46:01 – Are containers still a primary development tool for you? * 00:50:58 – Resources for learning DevOps and Kubernetes * 00:52:54 – Conferences and talks * 00:53:56 – Battle of the Bots: comparing coding agents * 00:55:15 – What are you excited about in the world of Python? * 00:56:20 – What do you want to learn next? * 01:02:42 – What’s the best way for people to follow your work online? * 01:03:33 – Thanks and goodbye Show Links: * Six Feet Up - Python and AI for Good, Custom Software Development [https://sixfeetup.com/] * Kubernetes - Tutorials [https://kubernetes.io/docs/tutorials/] * Managed Kubernetes Service - Amazon EKS - AWS [https://aws.amazon.com/eks/] * Karpenter [https://karpenter.sh/] * Kustomize - Kubernetes native configuration management [https://kustomize.io/] * Kubernetes Components - Control Plane Components [https://kubernetes.io/docs/concepts/overview/components/#control-plane-components] * Continuous Integration and Deployment for Python With GitHub Actions [https://realpython.com/github-actions-python/] * Argo CD [https://argoproj.github.io/cd/] * scaf: Provides developers and DevOps engineers with a complete blueprint for a new project [https://github.com/sixfeetup/scaf] * Streamline the Dev Experience with Kubernetes and Scaf™ [https://sixfeetup.com/company/news/streamline-developer-experience-with-kubernetes-and-scaf-tm] * Scaf™ — Six Feet Up [https://sixfeetup.com/company/scaf-a-blueprint-for-developers] * Scaf: Complete blueprint for new Python Kubernetes projects - Talk Python To Me Podcast E496 [https://talkpython.fm/episodes/show/496/scaf-complete-blueprint-for-new-python-kubernetes-projects] * kind [https://kind.sigs.k8s.io/] * Locust - A modern load testing framework [https://locust.io/] * Grafana: The open and composable observability platform [https://grafana.com/] * Grafana Loki OSS - Log aggregation system [https://grafana.com/oss/loki/] * Prometheus - client_python [https://prometheus.github.io/client_python/] * Elastic network interfaces - Amazon Elastic Compute Cloud [https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-eni.html] * eks-node-viewer: EKS Node Viewer [https://github.com/awslabs/eks-node-viewer] * k9s: 🐶 Kubernetes CLI To Manage Your Clusters In Style! [https://github.com/derailed/k9s] * OrbStack · Fast, light, simple Docker & Linux [https://orbstack.dev/] * NixOS Wiki - Python [https://wiki.nixos.org/wiki/Python] * TechWorld with Nana - YouTube [https://www.youtube.com/c/techworldwithnana] * Python: The Documentary [OFFICIAL TRAILER] - YouTube [https://www.youtube.com/watch?v=pqBqdNIPrbo] * Calvin Hendryx-Parker - LinkedIn [https://www.linkedin.com/in/calvinhp/] Conferences and Meetups: * All Things Open 2025 - All Things Open [https://allthingsopen.org/events/all-things-open-2025] * All Things Open AI Conference [https://allthingsopen.ai/] * All Things Open AI 2025 - AI Builders Track - YouTube [https://www.youtube.com/playlist?list=PL6kQg8bP1Ji4JC8KR_q9yYs8rUN77zBG7] * Rolling out Enterprise AI: Tools, Insights, & Team Empowerment - Calvin Hendryx-Parker, Six Feet Up - YouTube [https://www.youtube.com/watch?v=HEawRMNGlMU&list=PL6kQg8bP1Ji4JC8KR_q9yYs8rUN77zBG7&index=5] * PyCon US 2025 - PyCon US 2025 [https://us.pycon.org/2025/] * PyOhio 2025 [https://www.pyohio.org/2025/] * IndyPy Events [https://www.meetup.com/indypy/events/] AI Coding Tools: * Battle of the Bots - Developer Tools Showdown - YouTube [https://www.youtube.com/watch?v=Ix68u1MM3FY&t=1298s] * Aider - AI Pair Programming in Your Terminal [https://aider.chat/] * codename goose [https://block.github.io/goose/] * An entirely open-source AI code assistant inside your editor - Ollama Blog [https://ollama.com/blog/continue-code-assistant] * Devstral - Mistral AI [https://mistral.ai/news/devstral] * 10 LLM Observability Tools to Know in 2025 - Coralogix [https://coralogix.com/guides/llm-observability-tools/] * How often do LLMs snitch? Recreating Theo’s SnitchBench with LLM [https://simonwillison.net/2025/May/31/snitchbench-with-llm/] * The lethal trifecta for AI agents: private data, untrusted content, and external communication [https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/] * vllm-proxy: Proxy for vLLM enabling multi-model operation, cache-aware routing, and load balancing. [https://github.com/RobertFischer/vllm-proxy] Level up your Python skills with our expert-led courses: * Python Continuous Integration and Deployment Using GitHub Actions [https://realpython.com/courses/cicd-github-actions/] * First Steps With LangChain [https://realpython.com/courses/first-steps-langchain/] * Managing Dependencies With Python Poetry [https://realpython.com/courses/managing-dependencies-with-poetry/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]

Looking for a guide on getting started with marimo notebooks? How do you build a reproducible notebook for sharing or create a dashboard with interactive UI elements? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects. We cover a recent Real Python article by Ian Eyre about using narimo notebooks. The tutorial covers installing Marimo, taking advantage of reactivity, building interactive dashboards, and managing a notebook’s environment through sandboxing. The piece ends by examining the limitations of traditional linear notebooks and how Marimo addresses them. Christopher discusses an article about how to store the configurations for your Python scripts and projects. Whether you’re managing resource handles to a database, deployment variables, or credentials to external services, you’ll need a way to save and load the details into your Python project. The piece compares saving configurations in several common file formats or through environment variables. We also share several other articles and projects from the Python community, including a news roundup, the discourse between generative AI coding proponents and detractors, catching memory leaks with your test suite, epigrams on programming, a command line tool to check packages on PyPI, and a collection of string, file, and object utilities. This episode is sponsored by Six Feet Up. Course Spotlight: Python Continuous Integration and Deployment Using GitHub Actions [https://realpython.com/courses/cicd-github-actions/] With most software following agile methodologies, it’s essential to have robust DevOps systems in place to manage, maintain, and automate common tasks with a continually changing codebase. By using GitHub Actions, you can automate your workflows efficiently, especially for Python projects. Topics: * 00:00:00 – Introduction * 00:02:44 – Python Release 3.14.0b2 * 00:03:09 – Django security releases issued: 5.2.2, 5.1.10, and 4.2.22 * 00:03:27 – PyBay 2025 * 00:03:43 – PyCon NL 2025 - Call for Proposals * 00:04:05 – Django Forum: Supporting t-strings * 00:04:44 – Ruff Users: What Rules Are You Using and What Are You Ignoring? * 00:05:19 – My Shot at Real Python * 00:06:03 – My AI Skeptic Friends Are All Nuts * 00:10:06 – I Think I’m Done Thinking About genAI For Now * 00:11:12 – AI Changes Everything * 00:23:01 – Video Course Spotlight * 00:24:14 – Configuration of Python Applications * 00:29:15 – marimo: A Reactive, Reproducible Notebook * 00:35:15 – Sponsor: Six Feet Up * 00:36:02 – Catching memory leaks with your test suite * 00:41:45 – Epigrams on Programming * 00:46:54 – whatsonpypi: Check PyPI From the Command Line * 00:48:18 – strif: String, File, and Object Utilities * 00:49:44 – PyCoder’s Weekly - Submit a Link * 00:50:13 – Thanks and goodbye News: * Python Release 3.14.0b2 [https://www.python.org/downloads/release/python-3140b2/] * Django security releases issued: 5.2.2, 5.1.10, and 4.2.22 [https://www.djangoproject.com/weblog/2025/jun/04/security-releases/] * PyBay 2025 [https://pybay.org/speaking/call-for-proposals/] * PyCon NL 2025 - Call for Proposals [https://docs.google.com/forms/d/e/1FAIpQLSdv-shKzLId7WMwxmVNfSsWZjCd4eNuB7ExKvu_B3s4yONR-Q/viewform] * Django Forum: Supporting t-strings [https://forum.djangoproject.com/t/supporting-t-strings-from-python-3-14/40925] * Ruff Users: What Rules Are You Using and What Are You Ignoring? [https://old.reddit.com/r/Python/comments/1kttfst/ruff_users_what_rules_are_using_and_what_are_you/] * My Shot at Real Python [https://lonercode.hashnode.dev/my-shot-at-real-python] – Amanda has recently written her first article for Real Python and this post talks about her experience doing so. If you want to check out the article, it’s on Nested Loops [https://realpython.com/nested-loops-python/]. Show Links: * My AI Skeptic Friends Are All Nuts [https://fly.io/blog/youre-all-nuts/] * I Think I’m Done Thinking About genAI For Now [https://blog.glyph.im/2025/06/i-think-im-done-thinking-about-genai-for-now.html] * AI Changes Everything [https://lucumr.pocoo.org/2025/6/4/changes/] * AI Blog Comparison - Armin Ronacher [https://chatgpt.com/share/68419e9e-ed78-8009-b4d5-97a6b68bfdb3] * Configuration of Python Applications [https://robertrode.com/2023/10/02/configuration-in-python-applications-no-magic-just-necessary-practice.html] – This post talks about how to store configuration for your script and how and when to load the information into your program. * marimo: A Reactive, Reproducible Notebook [https://realpython.com/marimo-notebook/] – Discover how marimo notebook simplifies coding with reactive updates, UI elements, and sandboxing for safe, sharable notebooks. * Catching memory leaks with your test suite [https://pythonspeed.com/articles/identifying-resource-leaks-with-pytest/] – “If you have a good test suite, you may be able to use pytest fixtures to identify memory and other resource leaks.” Discussion: * Epigrams on Programming [https://web.archive.org/web/19990117034445/http://www-pu.informatik.uni-tuebingen.de/users/klaeren/epigrams.html] * Alan Perlis - Wikipedia [https://en.wikipedia.org/wiki/Alan_Perlis] Projects: * whatsonpypi: Check PyPI From the Command Line [https://github.com/viseshrp/whatsonpypi] * strif: String, File, and Object Utilities [https://github.com/jlevy/strif] Additional Links: * Episode #238: Charlie Marsh: Accelerating Python Tooling With Ruff and uv [https://realpython.com/podcasts/rpp/238/] * Episode #250: DjangoCon Europe 2025: Live Recording From Dublin [https://realpython.com/podcasts/rpp/250/] * Episode #236: Simon Willison: Using LLMs for Python Development [https://realpython.com/podcasts/rpp/236/] * GenAI Criticism and Moral Quandaries - Armin Ronacher [https://lucumr.pocoo.org/2025/6/10/genai-criticism/] * Math support in Markdown - The GitHub Blog [https://github.blog/news-insights/product-news/math-support-in-markdown/] * Quiz: marimo: A Reactive, Reproducible Notebook [https://realpython.com/quizzes/marimo-notebook/] * Episode #42: What Is Data Engineering and Researching 10 Million Jupyter Notebooks [https://realpython.com/podcasts/rpp/42/] * We Downloaded 10,000,000 Jupyter Notebooks From Github – This Is What We Learned [https://blog.jetbrains.com/datalore/2020/12/17/we-downloaded-10-000-000-jupyter-notebooks-from-github-this-is-what-we-learned/] * Episode #230: marimo: Reactive Notebooks and Deployable Web Apps in Python [https://realpython.com/podcasts/rpp/230/] * Episode #501 - marimo - Reactive Notebooks for Python - Talk Python To Me Podcast [https://talkpython.fm/episodes/show/501/marimo-reactive-notebooks-for-python] * Episode #24: Options for Packaging Your Python Application: Wheels, Docker, and More - Itamar Turner-Trauring [https://realpython.com/podcasts/rpp/24/] * Episode #128: Using a Memory Profiler in Python & What It Can Teach You [https://realpython.com/podcasts/rpp/128/] * Episode #172: Measuring Multiple Facets of Python Performance With Scalene [https://realpython.com/podcasts/rpp/172/] * PyCoder’s Weekly - Submit a Link [https://pycoders.com/submissions] Level up your Python skills with our expert-led courses: * Python Continuous Integration and Deployment Using GitHub Actions [https://realpython.com/courses/cicd-github-actions/] * Python mmap: Doing File I/O With Memory Mapping [https://realpython.com/courses/python-mmap-io/] * Testing Your Code With pytest [https://realpython.com/courses/testing-your-code-with-pytest/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]

Once you’ve learned the vocabulary and syntax of the Python language, how do you progress into learning the right combinations to put into your code? How can Python’s built-in itertools library enhance your skills? This week on the show, we speak with Rodrigo Girão Serrão about teaching Python through his blog and his passion for the itertools library. We discuss Rodrigo’s different approaches to writing on his blog. He likes to document smaller concepts about Python and building code in his “Today I Learned” series. He’s also been collecting advice about the best way to use core Python features in another series called “Pydon’ts.” We cover his recent PyCon US tutorial about the built-in itertools module. The functions contained in the module create iterators for efficient looping. We discuss the categories of tools inside the collection and ways to simplify your code. We also explore the concept of vocabulary versus idioms in writing. Idioms are a group of words that hold a symbolic meaning that goes beyond the literal meaning of the individual words. We dig into how that applies to learning Python and building a personal collection of programming idioms. This episode is sponsored by AMD. Course Spotlight: Working With Missing Data in Polars [https://realpython.com/courses/missing-data-polars/] In this video course, you’ll learn how to deal with missing data in Polars to ensure it doesn’t interfere with your data analysis. You’ll discover how to check for missing values, update them, and remove them. Topics: * 00:00:00 – Introduction * 00:02:34 – Creating Polars video course * 00:03:27 – How did you start programming and teaching Python? * 00:04:59 – Where did mathspp come from? * 00:05:38 – Exploring math and programming in university * 00:07:48 – Learning APL * 00:09:24 – What goes into building the blog? * 00:15:05 – The Pydon’ts and writing books * 00:18:37 – PyCon US 2025 * 00:20:46 – Sponsor: AMD * 00:21:23 – Teaching a tutorial about itertools * 00:28:58 – Categorizing itertools * 00:40:39 – Video Course Spotlight * 00:41:55 – The difference between me and Shakespeare * 00:46:51 – Learning and practicing with idioms * 00:51:01 – TIL and asking questions * 00:53:54 – What are you excited about in the world of Python? * 00:55:40 – What do you want to learn next? * 00:57:35 – How can people follow your work online? * 01:01:19 – Thanks and goodbye Show Links: * mathspp blog [https://mathspp.com/blog] * TIL (Today I Learned) - mathspp [https://mathspp.com/blog/til] * Working With Missing Data in Polars [https://realpython.com/courses/missing-data-polars/] * Paul Valéry - “A poem is never finished” - Oxford Reference [https://www.oxfordreference.com/display/10.1093/acref/9780191843730.001.0001/q-oro-ed5-00011125] * Personal highlights of PyCon US 2025 - mathspp [https://mathspp.com/blog/personal-highlights-of-pycon-us-2025] * PyCon US 2025 Lightning Talks - Friday, May 16th, 2025 PM - YouTube [https://www.youtube.com/watch?v=Uuhu-F05A7k] * PyCon US 2025 Tutorial Sneak Peek: “Reimplement itertools for fun & profit” Rodrigo Girão Serrão - YouTube [https://www.youtube.com/watch?v=xumSsPlhB2o] * Alan Perlis - Wikipedia [https://en.wikipedia.org/wiki/Alan_Perlis] * Epigrams on Programming [https://web.archive.org/web/19990117034445/http://www-pu.informatik.uni-tuebingen.de/users/klaeren/epigrams.html] * What learning APL taught me about Python - mathspp [https://mathspp.com/blog/what-learning-apl-taught-me-about-python] * What APL taught me about Python ⚡️ – lightning talk by Rodrigo Girão Serrão at EuroPython 2023 - YouTube [https://www.youtube.com/watch?v=vCMoWPTPdXo] * itertools — Functions creating iterators for efficient looping — Python 3.13.4 documentation [https://docs.python.org/3/library/itertools.html] * Module itertools overview - mathspp [https://mathspp.com/blog/module-itertools-overview] * The little book of itertools - mathspp [https://mathspp.com/books/the-little-book-of-itertools] * Python itertools By Example – Real Python [https://realpython.com/python-itertools/] * What’s new in Python 3.14 — Python 3.15.0a0 documentation [https://docs.python.org/3.15/whatsnew/3.14.html] * beehiiv — The newsletter platform built for growth [https://www.beehiiv.com/] * Python drops 🐍💧 newsletter - mathspp [https://mathspp.com/drops] * Books - mathspp [https://mathspp.com/books] * Rodrigo Girão Serrão 🐍🚀 (@mathspp.com) — Bluesky [https://bsky.app/profile/mathspp.com] * Rodrigo Girão Serrão - LinkedIn [https://www.linkedin.com/in/rodrigo-gir%C3%A3o-serr%C3%A3o/] * Rodrigo 🐍🚀 (@mathsppblog@fosstodon.org) - Fosstodon [https://fosstodon.org/@mathsppblog] * Rodrigo 🐍🚀 (@mathsppblog) / X [https://x.com/mathsppblog] Level up your Python skills with our expert-led courses: * Efficient Iterations With Python Iterators and Iterables [https://realpython.com/courses/efficient-iterations-iterators-iterables/] * Working With Python Polars [https://realpython.com/courses/working-with-python-polars/] * Working With Missing Data in Polars [https://realpython.com/courses/missing-data-polars/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]