The Real Python Podcast

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 [https://realpython.com/courses/history-python-versions-features/] Explore Python’s evolution from the 1990s to today with a brief history and demos of key features added throughout its lifetime. Topics: * 00:00:00 – Introduction * 00:03:02 – PEP 728: TypedDict With Typed Extra Items * 00:04:09 – Django security releases issued: 5.2.6, 5.1.12, and 4.2.24 * 00:04:37 – Python Type System and Tooling Survey 2025 * 00:04:56 – Python: The Documentary - An Origin Story * 00:14:11 – A History of Python Versions and Features * 00:16:58 – Sponsor: Influxdata * 00:17:48 – Regex Affordances * 00:21:34 – Where to Host Your Python App * 00:26:48 – Best hosting platforms for Python applications and Python scripts * 00:30:18 – Video Course Spotlight * 00:31:59 – 330× Faster: Four Different Ways to Speed Up Your Code * 00:37:18 – beets: Music Library Manager * 00:39:12 – Memory Graph - GitHub * 00:40:49 – colour: Colour Science for Python * 00:42:35 – Thanks and goodbye News: * PEP 728: TypedDict With Typed Extra Items (Accepted) [https://peps.python.org/pep-0728/] * Django security releases issued: 5.2.6, 5.1.12, and 4.2.24 [https://www.djangoproject.com/weblog/2025/sep/03/security-releases/] * Python Type System and Tooling Survey 2025 [https://docs.google.com/forms/d/e/1FAIpQLSeOFkLutxMLqsU6GPe60OJFYVN699vqjXPtuvUoxbz108eDWQ/viewform?pli=1] Show Links: * Python: The Documentary - An Origin Story - YouTube [https://www.youtube.com/watch?v=GfH4QL4VqJ0] – “This is the story of the world’s most beloved programming language: Python. What began as a side project in Amsterdam during the 1990s became the software powering artificial intelligence, data science and some of the world’s biggest companies.” * A History of Python Versions and Features – Video Course [https://realpython.com/courses/history-python-versions-features/] * Regex Affordances [https://nedbatchelder.com/blog/202504/regex_affordances.html] – A tour of some real code showing little-used power features of the Python regular expression module, including verbose regex syntax, calling re.sub() with a function reference, and more. * Where to Host Your Python App [https://judoscale.com/blog/where-to-host-python-app] – Whether it’s Django, Flask, FastAPI, or some other Python web framework, your hosting options are plenty. This guide will show you how to choose. * Best hosting platforms for Python applications and Python scripts [https://www.python-engineer.com/posts/hosting-platforms-for-python/] * 330× Faster: Four Different Ways to Speed Up Your Code [https://pythonspeed.com/articles/different-ways-speed/] – There are many approaches to speeding up Python code; applying multiple approaches can make your code even faster. This post talks about four different ways you can achieve speed-up. Projects: * beets: Music Library Manager [https://github.com/beetbox/beets] * Memory Graph - GitHub [https://github.com/bterwijn/memory_graph] * colour: Colour Science for Python [https://github.com/colour-science/colour] Additional Links: * What’s in which Python - Ned Batchelder [https://nedbatchelder.com/text/which-py.html] * Anvil [https://anvil.works/] * Opalstack: Managed Hosting [https://www.opalstack.com/] Level up your Python skills with our expert-led courses: * Handling Missing Keys With the Python defaultdict Type [https://realpython.com/courses/python-defaultdict-type/] * Using Structural Pattern Matching in Python [https://realpython.com/courses/structural-pattern-matching/] * A History of Python Versions and Features [https://realpython.com/courses/history-python-versions-features/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]

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 [https://realpython.com/courses/closures-examples-use-cases/] Learn about Python closures: function-like objects with extended scope used for decorators, factories, and stateful functions. Topics: * 00:00:00 – Introduction * 00:03:00 – Recent conferences and talks * 00:04:18 – What’s going on with LLMs? * 00:06:06 – What happened with the GPT-5 release? * 00:08:14 – Simon Willison - 2025 in LLMs so far * 00:09:00 – How did we get here? * 00:10:37 – OpenAI’s and scaling laws * 00:12:25 – Pivoting to post-training * 00:16:01 – Some history of AI eras * 00:17:54 – Issues with measuring performance and benchmarks * 00:22:19 – Chatbot Arena * 00:24:06 – Languages are finite * 00:26:22 – LLMs and the illusion of humanity * 00:30:41 – Sponsor: Influxdata * 00:31:34 – Types of solutions to move past these limits * 00:36:57 – Does AI actually boost developer productivity? * 00:44:19 – Agentic Al Programming with Python * 00:48:02 – Results of non-programmers vibe coding * 00:50:18 – Back to the concept of overfitting * 00:52:52 – The money involved in training * 00:56:50 – Video Course Spotlight * 00:58:21 – Deepseek and new methods of training * 01:01:02 – Quantizing and fitting on a local machine * 01:04:48 – The layoffs and the economic changes * 01:10:32 – AI implementation failures * 01:21:01 – Don’t doubt yourself as a developer * 01:24:06 – What are you excited about in the world of Python? * 01:25:39 – What do you want to learn next? * 01:26:42 – What’s the best way to follow your work online? * 01:27:04 – Thanks and goodbye Survey: * Listener Survey - Help Shape the Future of the Real Python Podcast [https://tally.so/r/nWbKgJ] Show Links: * EuroPython 2025 - July 14th-20th 2025 - Prague, Czech Republic & Remote [https://ep2025.europython.eu/] * Episode #232: Exploring Modern Sentiment Analysis Approaches in Python [https://realpython.com/podcasts/rpp/232/] * GPT-5: Overdue, overhyped and underwhelming. And that’s not the worst of it. [https://garymarcus.substack.com/p/gpt-5-overdue-overhyped-and-underwhelming] * GPT 5’s Rocky Launch Highlights AI Disillusionment - IEEE Spectrum [https://spectrum.ieee.org/gpt-5-trough-of-disillusionment] * 2025 in LLMs so far, illustrated by Pelicans on Bicycles — Simon Willison [https://www.youtube.com/watch?v=YpY83-kA7Bo] * Attention is All You Need - Google [https://research.google/pubs/attention-is-all-you-need/] * Scaling laws for neural language models - OpenAI [https://openai.com/index/scaling-laws-for-neural-language-models/] * What if AI Doesn’t Get Much Better Than This? - Cal Newport [https://calnewport.com/what-if-ai-doesnt-get-much-better-than-this/] * Hiltzik: AI hype is fading fast - Los Angeles Times [https://www.latimes.com/business/story/2025-08-20/say-farewell-to-the-ai-bubble-and-get-ready-for-the-crash] * Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford - YouTube [https://www.youtube.com/watch?v=tbDDYKRFjhk] * Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity - METR [https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/] * Amazon Cloud Chief: Replacing Junior Staff With AI Is ‘Dumbest’ Idea - Business Insider [https://www.businessinsider.com/amazon-cloud-chief-replacing-junior-staff-ai-matt-garman-2025-8] * 20 LLM evaluation benchmarks and how they work [https://www.evidentlyai.com/llm-guide/llm-benchmarks#reasoning-and-language-understanding-benchmarks] * MMLU - Measuring Massive Multitask Language Understanding [https://arxiv.org/abs/2009.03300] * HellaSwag: Can a Machine Really Finish Your Sentence? [https://arxiv.org/abs/1905.07830] * Mechanical Turk - Wikipedia [https://en.m.wikipedia.org/wiki/Mechanical_Turk] * Amazon Mechanical Turk [https://www.mturk.com/] * Chatbot Arena - LMArena [https://lmarena.ai/?leaderboard] * LLMs Can’t Reason - The Reversal Curse, The Alice In Wonderland Test, And The ARC - AGI Challenge - CustomGPT [https://customgpt.ai/llm-reasoning-vs-memorization/] * Mirror, mirror: LLMs and the illusion of humanity - Jodie Burchell - NDC Oslo 2024 - YouTube [https://www.youtube.com/watch?v=kqJ7rZHFx84] * Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens [https://arxiv.org/pdf/2508.01191] * Context Rot: How Increasing Input Tokens Impacts LLM Performance - YouTube [https://www.youtube.com/watch?v=TUjQuC4ugak&list=WL&index=1] * Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford - YouTube [https://www.youtube.com/watch?v=tbDDYKRFjhk] * AWS CEO says no more programmers in 2 years - Tech Industry - Blind [https://www.teamblind.com/post/aws-ceo-says-no-more-programmers-in-2-years-wqarugct] * MIT report: 95% of generative AI pilots at companies are failing - Fortune [https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/] * Agentic Al Programming with Python - Talk Python To Me Podcast [https://talkpython.fm/episodes/show/517/agentic-al-programming-with-python] * Vibe coding through the GPT-5 mess - The Verge [https://www.theverge.com/the-vergecast/759768/gpt5-backlash-vibe-coding-attempts-corporate-stunts] * Overfitting - Wikipedia [https://en.wikipedia.org/wiki/Overfitting] * Andrej Karpathy - Busy Person’s Intro to LLMs - YouTube [https://www.youtube.com/watch?v=zjkBMFhNj_g&t=107s] * AI Isn’t Taking Your Job – The Economy Is - Andrew Stiefel [https://andrewstiefel.com/ai-layoff-myth/] * Commonwealth Bank backtracks on AI job cuts, apologizes for ‘error’ as call volumes rise - ABC News [https://www.abc.net.au/news/2025-08-21/cba-backtracks-on-ai-job-cuts-as-chatbot-lifts-call-volumes/105679492] * Klarna CEO Reverses Course By Hiring More Humans, Not AI | Entrepreneur [https://www.entrepreneur.com/business-news/klarna-ceo-reverses-course-by-hiring-more-humans-not-ai/491396] * Has Duolingo Lost Its Streak? - Matt Jones - Medium [https://medium.com/follow-the-rabbit/has-duolingo-lost-its-streak-9cb362232eeb] * McDonald’s removes AI drive-throughs after order errors [https://www.bbc.com/news/articles/c722gne7qngo] * OpenAI Usage Plummets in the Summer, When Students Aren’t Cheating on Homework [https://futurism.com/openai-use-cheating-homework] * What Happened When I Tried to Replace Myself with ChatGPT in My English Classroom - Literary Hub [https://lithub.com/what-happened-when-i-tried-to-replace-myself-with-chatgpt-in-my-english-classroom/] * Learning to code in the age of AI — Sheena O’Connell - YouTube [https://www.youtube.com/watch?app=desktop&v=CcTC3I5SF7k] * Jodie Burchell - The JetBrains Blog [https://blog.jetbrains.com/author/jodie-burchell-jetbrains-com/] * Jodie Burchell’s Blog - Standard error [https://t-redactyl.io/] * Jodie Burchell (@t-redactyl.bsky.social) — Bluesky [https://bsky.app/profile/t-redactyl.bsky.social] * Jodie Burchell 🇦🇺🇩🇪 (@t_redactyl@fosstodon.org) - Fosstodon [https://fosstodon.org/@t_redactyl] * JetBrains: Essential tools for software developers and teams [https://www.jetbrains.com/] Level up your Python skills with our expert-led courses: * Python Decorators 101 [https://realpython.com/courses/python-decorators-101/] * A History of Python Versions and Features [https://realpython.com/courses/history-python-versions-features/] * Exploring Python Closures: Examples and Use Cases [https://realpython.com/courses/closures-examples-use-cases/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]

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 [https://realpython.com/courses/solid-principles-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. Topics: * 00:00:00 – Introduction * 00:03:14 – Python 3.13.7 Released * 00:03:38 – Python 3.14.0rc2 Released * 00:04:10 – PEP 802: Display Syntax for the Empty Set * 00:04:59 – Announcing the PSF Board Candidates for 2025 * 00:05:26 – Rodrigo - PSF - Community Service Award for Q2 2025 * 00:06:06 – Python Developers Survey 2024 Results * 00:13:27 – pyx: A Python-Native Package Registry * 00:15:12 – Test & Code Final Episode * 00:15:48 – You Might Not Need a Python Class * 00:20:52 – Sponsor: Influxdata * 00:21:44 – asyncio: A Library With Too Many Sharp Corners * 00:25:43 – How JIT Builds of CPython Actually Work * 00:35:21 – Video Course Spotlight * 00:37:12 – What Are Mixin Classes in Python? * 00:44:05 – nicegui: Create Web-Based UI With Python * 00:46:51 – leopards: Quickly query your Python lists * 00:49:00 – Thanks and goodbye Survey: * Listener Survey - Help Shape the Future of the Real Python Podcast [https://tally.so/r/nWbKgJ] News: * Python 3.13.7 Released [https://docs.python.org/release/3.13.7/whatsnew/changelog.html] * Python 3.14.0rc2 Released [https://pythoninsider.blogspot.com/2025/08/python-3140rc2-and-3137-are-go.html] * PEP 802: Display Syntax for the Empty Set (Added) [https://peps.python.org/pep-0802/] * Announcing the PSF Board Candidates for 2025 [https://pyfound.blogspot.com/2025/08/announcing-psf-board-candidates-for-2025.html] – The Python Software Foundation elections are upon us, and this post announces this year’s candidates. Voting is September 2nd to 16th. To vote, you must be registered by August 26th. * Rodrigo - PSF - Community Service Award for Q2 2025 [https://bsky.app/profile/mathspp.com/post/3lwhb3a3gzk2d] * Python Developers Survey 2024 Results [https://lp.jetbrains.com/python-developers-survey-2024/] * The State of Python 2025 - The PyCharm Blog [https://blog.jetbrains.com/pycharm/2025/08/the-state-of-python-2025/] * pyx: A Python-Native Package Registry, Now in Beta [https://astral.sh/blog/introducing-pyx] – The folks at Astral, who brought you uv and more, have created a new commercial Python-native package registry called “pyx”. * Test & Code Final Episode [https://testandcode.com/episodes/so-long-and-thanks-for-all-the-fish] – After 10 years and 237 episodes, Brian Okken has decided to stop recording Test & Code. He’ll still be contributing to Python Bytes. Here’s to all his work on a great podcast over the last decade. Show Links: * You Might Not Need a Python Class [https://adamgrant.micro.blog/2025/07/24/123050.html] – If you’re coming from other languages, you might think a class is the easiest way to do something, but Python has other options. This post shows you some alternatives and why you might choose them. * asyncio: A Library With Too Many Sharp Corners [https://sailor.li/asyncio] – asyncio has a few gotchas and this post describes five different problems, including: cancellation, disappearing tasks, and more. * How JIT Builds of CPython Actually Work [https://savannah.dev/posts/how-your-code-runs-in-a-jit-build/] – You don’t have to be a compiler engineer to understand how your code runs in a JIT build of CPython. This article runs you through just what happens under the covers. * What Are Mixin Classes in Python? [https://realpython.com/python-mixin/] – Learn how to use Python mixin classes to write modular, reusable, and flexible code with practical examples and design tips. Projects: * nicegui: Create Web-Based UI With Python [https://github.com/zauberzeug/nicegui] * leopards: Quickly query your Python lists [https://github.com/mkalioby/leopards] Additional Links: * Episode #259: Design Patterns That Don’t Translate to Python [https://realpython.com/podcasts/rpp/259/] * Episode #123: Creating a Python Code Completer & More Abstract Syntax Tree Projects [https://realpython.com/podcasts/rpp/123/] * Specializing Adaptive Interpreter [https://peps.python.org/pep-0659/] * The LLVM Compiler Infrastructure Project [https://llvm.org/] * PEP 774 – Removing the LLVM requirement for JIT builds [https://peps.python.org/pep-0774/] * Building a JIT compiler for CPython [https://www.youtube.com/watch?v=kMO3Ju0QCDo] * What they don’t tell you about building a JIT compiler for CPython [https://www.youtube.com/watch?v=NE-Oq8I3X_w] * Quiz: What Are Mixin Classes in Python? [https://realpython.com/quizzes/python-mixin/] * NiceGUI [https://nicegui.io/] Level up your Python skills with our expert-led courses: * Class Concepts: Object-Oriented Programming in Python [https://realpython.com/courses/python-class-object/] * Inheritance and Internals: Object-Oriented Programming in Python [https://realpython.com/courses/python-class-inheritance/] * Design and Guidance: Object-Oriented Programming in Python [https://realpython.com/courses/solid-principles-python/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]

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 [https://realpython.com/courses/numpy-techniques-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. Topics: * 00:00:00 – Introduction * 00:02:41 – Python documentary * 00:07:44 – Getting involved in open source * 00:12:04 – Numeric Python * 00:15:36 – SciPy and the SciPy community * 00:17:35 – Starting to think about entrepreneurship * 00:18:16 – NumPy evolving from the work of Numeric * 00:22:01 – Sponsor: Influxdata * 00:22:53 – Python as controlling code for lower-level libraries * 00:23:37 – Numba open-source JIT compiler * 00:30:09 – Starting to build in Python before learning it all * 00:34:45 – Python as the language AI generates * 00:36:31 – Guilds and sharing knowledge * 00:40:15 – More NumPy backstory * 00:46:36 – Contributing to Python * 00:48:24 – Video Course Spotlight * 00:49:41 – The investment of companies in Python * 00:51:22 – Quansight and businesses in open source * 00:53:09 – Open Teams and Quansight details * 00:57:14 – NumFOCUS and Anaconda * 00:58:51 – FairOSS * 01:02:36 – Documenting these efforts * 01:05:37 – What are you excited about in the world of Python? * 01:07:12 – What do you want to learn next? * 01:08:10 – How can people follow your work online? * 01:10:03 – Thanks and goodbye Show Links: * Python: The Documentary - OFFICIAL TRAILER - Coming August 28 - YouTube [https://www.youtube.com/watch?v=pqBqdNIPrbo] * The Python Matrix Object: Extending Python for Numerical Computation [http://hugunin.net/papers/hugunin95numpy.html] * Jim Fulton [https://j1m.dev/] * Jim Hugunin - Home [http://hugunin.net/] * History of SciPy - SciPy wiki dump [https://scipy.github.io/old-wiki/pages/History_of_SciPy] * SciPy [https://scipy.org/] * NumPy [https://numpy.org/] * Numba: A High Performance Python Compiler [https://numba.pydata.org/] * LPython - High performance typed Python compiler [https://lpython.org/] * OpenTeams: Open SaaS AI Solutions [https://openteams.com/] * Quansight Consulting [https://quansight.com/] * OpenTeams Incubator [https://otincubator.com/] * NumFOCUS: A Nonprofit Supporting Open Code for Better Science [https://numfocus.org/] * Anaconda [https://anaconda.com/] * FairOSS [https://faiross.org/] * faster-cpython [https://github.com/faster-cpython/] * Travis Oliphant (@teoliphant) / X [https://x.com/teoliphant] * Travis Oliphant - LinkedIn [https://www.linkedin.com/in/teoliphant/] Level up your Python skills with our expert-led courses: * Data Cleaning With pandas and NumPy [https://realpython.com/courses/data-cleaning-with-pandas-and-numpy/] * Stacks and Queues: Selecting the Ideal Data Structure [https://realpython.com/courses/stacks-queues-ideal-data-structure/] * 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]

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 [https://realpython.com/courses/single-double-underscore-naming-conventions/] 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. Topics: * 00:00:00 – Introduction * 00:02:23 – Python 3.13.6 Released * 00:02:47 – Django 5.2.5 Released * 00:02:55 – Django REST Framework Release v3.16.1 * 00:03:09 – Narwhals v2.0.0 Released * 00:03:22 – mypy 1.17 Released * 00:03:42 – PEP 798: Unpacking in Comprehensions * 00:04:11 – PEP 799: A Dedicated Profilers Package for Organizing Python Profiling Tools * 00:06:12 – PyPI Users Email Phishing Attack * 00:07:33 – Django in Action * 00:08:00 – Call for proposals deadline - PyCon NL * 00:08:59 – Python Audio Processing With pedalboard * 00:18:49 – Smuggling Arbitrary Data Through an Emoji * 00:21:53 – Don’t Call Dunder Methods * 00:28:51 – Video Course Spotlight * 00:30:27 – Inheritance Over Composition, Sometimes * 00:40:03 – html-to-markdown: HTML to Markdown Converter * 00:42:20 – curlify: A library to convert Python requests request object into curl commands * 00:44:18 – transfunctions: Support Both Sync and Async * 00:45:18 – Thanks and goodbye Survey: * Listener Survey - Help Shape the Future of the Real Python Podcast [https://tally.so/r/nWbKgJ] News: * Python 3.13.6 Released [https://docs.python.org/release/3.13.6/whatsnew/changelog.html] * Django 5.2.5 Released [https://docs.djangoproject.com/en/5.2/releases/5.2.5/] * Django REST Framework Release v3.16.1 [https://github.com/encode/django-rest-framework/releases/tag/3.16.1?utm_campaign=Django%2BNewsletter&utm_medium=email&utm_source=Django_Newsletter_297] * Narwhals v2.0.0 Released [https://github.com/narwhals-dev/narwhals/releases/tag/v2.0.0] * Mypy 1.17 Released [https://mypy-lang.blogspot.com/2025/07/mypy-117-released.html] * PEP 798: Unpacking in Comprehensions (Added) [https://peps.python.org/pep-0798/] * PEP 799: A Dedicated Profilers Package for Organizing Python Profiling Tools (Added) [https://peps.python.org/pep-0799/] * PyPI Users Email Phishing Attack [https://blog.pypi.org/posts/2025-07-28-pypi-phishing-attack/] – PyPI users are being targeted by an email phishing attack attempting to trick them into logging into a fake PyPI site. This post from the Security Engineer at PyPI discusses what’s happening and what you should do about it. There’s also a follow-up post [https://blog.pypi.org/posts/2025-07-31-incident-report-phishing-attack/]. * PyCon NL 2025 - Call for Papers [https://pycon-nl.org/call-for-papers] * Django in Action - Christopher Trudeau - Code ladjango40 [https://www.manning.com/books/django-in-action] Topics: * Python Audio Processing With pedalboard [https://lwn.net/Articles/1027814/] – 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. * Smuggling Arbitrary Data Through an Emoji [https://paulbutler.org/2025/smuggling-arbitrary-data-through-an-emoji/] – Unicode includes flexibility through the use of variation selectors. These include the ability to change characters through a consecutive series of coding points. But, when used with code points that don’t need them, they’re ignored, so you can hide data in them. * Don’t Call Dunder Methods [https://www.pythonmorsels.com/avoid-dunder-methods/] – It’s best to avoid calling dunder methods. It’s common to define dunder methods, but uncommon to call them directly. * Inheritance Over Composition, Sometimes [https://death.andgravity.com/over-composition] – In an older post, Adrian wrote some code using inheritance. He got questions from his readers asking why it wouldn’t just be simpler to use functions. This post re-implements the code with inheritance, composition, and plain old functions, then compares the approaches. Projects: * html-to-markdown: HTML to Markdown Converter [https://github.com/Goldziher/html-to-markdown] * curlify: A library to convert Python requests request object to curl command [https://github.com/ofw/curlify] * transfunctions: Support Both Sync and Async [https://github.com/pomponchik/transfunctions] Additional Links: * Working with Audio in Python (feat. Pedalboard) - Peter Sobot - YouTube [https://www.youtube.com/watch?v=kpKrsFqJgXc] * Python’s Magic Methods: Leverage Their Power in Your Classes – Tutorial [https://realpython.com/python-magic-methods/] Level up your Python skills with our expert-led courses: * Class Concepts: Object-Oriented Programming in Python [https://realpython.com/courses/python-class-object/] * Single and Double Underscore Naming Conventions in Python [https://realpython.com/courses/single-double-underscore-naming-conventions/] * Inheritance and Internals: Object-Oriented Programming in Python [https://realpython.com/courses/python-class-inheritance/] Support the podcast & join our community of Pythonistas [https://realpython.com/join]