Python Bytes

Topics covered in this episode: Free-threaded Python: past, present, and future django-admin-site-search Qwen 3.6 27B is the sweet spot for local development A large batch of PEPs are finalized Extras Joke Watch on YouTube Show Intro Sponsored by us! Support our work through: Our courses at Talk Python Consulting from Six Feet Up Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Calvin #1: Free-threaded Python: past, present, and future The GIL has prevented true multi-threaded parallelism in CPython since the beginning — multiple past attempts to remove it failed on performance grounds Sam Gross at Meta finally solved it; his work became PEP 703 and ships as free-threaded CPython today Python 3.13 was experimental with 20–40% single-threaded slowdown; 3.14 brought that to 0–10% Python 3.15 (October 2026) delivers a unified ABI — one extension binary works on both GIL and free-threaded builds Already >50% of the top PyPI binary wheels support free threading Wouters predicts free-threaded becomes the default between 3.16–3.20 (2027–2031), with the GIL eventually disappearing next decade Michael #2: django-admin-site-search via Adam Parkin A global/site search modal for the Django admin, by Ahmed Aljawahiry. Hit cmd+k anywhere in the admin and you get a command-palette-style search window, kind of like the one in VS Code. It doesn't just search one model's list page. It searches your entire site in one box: App labels Model labels and field attributes Actual model instances (your data) Two ways to search the instances: model_char_fields (the default): runs an __icontains across every CharField (and subclasses) on the model. Zero config, works out of the box. admin_search_fields: defers to each ModelAdmin's existing get_search_results(), so it respects the search_fields you've already set up. The part I like: it's permission-aware out of the box. Users only see results for the apps and models they actually have view permission on, so you're not leaking anything through search. Results appear as you type, with throttling/debouncing so you're not hammering the server on every keystroke, and it's full keyboard nav: cmd+k to open, up/down to move, enter to go. It's responsive, does dark and light mode, and it pulls Django's built-in admin CSS variables so it just matches whatever admin theme you're running. Under the hood it's Alpine.js, but bundled into static so there's no external CDN dependency. Setup is about what you'd expect: pip install django-admin-site-search, add it to INSTALLED_APPS, mix the AdminSiteSearchView into your AdminSite, and drop a few template includes into base_site.html. Supports Python 3.8 through 3.14 and Django 3.2 through 6.0, MIT licensed, and everything is overridable if you want to skip certain models, add TextField matching, etc. Calvin #3: Qwen 3.6 27B is the sweet spot for local development Qwen 3.6 27B is being called the first local model that genuinely competes as a general-purpose intelligence — benchmarks put it at roughly mid-2025 frontier level (comparable to GPT-5 / Claude Sonnet 4.5) Runs locally via llama.cpp; on an M5 MacBook Max with 8-bit quantization + multi-token prediction, it hits ~32 tokens/sec using ~42GB RAM 4-bit quantization gets it under 18GB, runnable on 32GB devices; Nvidia RTX cards run it even faster The dense 27B is recommended over the faster MoE 35B A3B — author prefers higher quality output over raw speed Privacy and reliability are the pitch: fine-tunable, can't be taken down, suitable for sensitive/proprietary data Author sees this as a stepping stone — frontier open-weight models like GLM 5.2 are now locally runnable with company-grade hardware, and smarter-still local models are coming Michael #4: A large batch of PEPs are finalized A bunch of PEPs went from accepted to final. 668, 687, 691, 699, 701, 703, 728, 770, 773, 829 But this wasn’t them making their way into CPython. It’s an admin sorta thing. (Thanks PyCoders) See the commit. Extras Calvin: More fun bling for your terminal this time - https://charm.land/ Michael: Follow up from pls, What the pls? Thanks Pito. Joke: BEMoji A production-grade utility and component framework built entirely on emoji class names via Jeff Triplett

Topics covered in this episode: Backup Docker volumes locally or to any S3 Pyodide 314.0 Release nb-cli: A Command-Line Interface for AI Agents and Notebook Automation Hindsight Agent Memory That Learns Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python AWS Community Day Midwest tomorrow Wednesday the 24th in downtown Indianapolis, Six Feet Up is sponsoring and there are 2 Sixies presenting Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an bonus digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Backup Docker volumes locally or to any S3 Via Bryan Weber (thanks Bryan!), who spotted it over on Virtualization HowTo. Find Bryan at bryanwweber.com. offen/docker-volume-backup is a lightweight companion container that backs up the volumes your apps actually depend on, then ships them somewhere safe. It's tiny: written in Go and about 25MB compressed, roughly 1/20th the size of the shell-based image (jareware/docker-volume-backup) that inspired it. Drop it into your docker compose file as a backup service, mount the volumes you care about as read-only, and you're off. Push backups to a pile of destinations: a local directory, plus any S3, WebDAV, Azure Blob Storage, Dropbox, Google Drive, or SSH-compatible target. Mix and match as many as you want in one run. Recurring cron-style backups in a Compose setup, or one-off backups straight from the Docker CLI. Production-friendly touches worth calling out: Rotates away old backups so you don't quietly fill the disk. GPG encryption for your archives. Notifications on finished and failed runs (so you find out about failures before you need the backup). Stop a container during backup for a consistent snapshot using a simple docker-volume-backup.stop-during-backup=true label, then auto-restart it. Run custom commands during the backup lifecycle (great for a database dump before the file copy). Docker Swarm support, plus arm64 and arm/v7 builds. Hello, Raspberry Pi homelab. Fun aside from Bryan: he searched our back catalog for this tool and the search came back so fast he thought it hadn't run. Love to hear it. Calvin #2: Pyodide 314.0 Release PEP 783 is the real news — Pyodide maintainers used to hand-build 300+ packages. Now anyone can publish Pyodide wheels to PyPI with cibuildwheel. The version jump from 0.29 to 314.0 is intentional — it now tracks the Python version, so 314.x = Python 3.14. Binary compatibility is locked per Python cycle, meaning packages you build today won't break on the next Pyodide release. sqlite3, ssl, and lzma are back in the default stdlib — no more await pyodide.loadPackage("sqlite3"). Bigger download, but a much smoother experience for newcomers. bigint precision bug is fixed — values above 2^53 were silently losing precision when crossing the Python/JS boundary. The new JsBigInt type makes the roundtrip correct. Worth flagging if anyone is doing numeric work in a browser app. Experimental TCP sockets in Node.js — you can now connect Pyodide to a real database (MySQL, PostgreSQL, Redis tested) when running server-side. Blurs the line between "Python in the browser" and "Python runtime anywhere Wasm runs." Michael #3: nb-cli: A Command-Line Interface for AI Agents and Notebook Automation From Piyush Jain (Jupyter and LangChain maintainer) on the Jupyter blog: nb-cli: A Command-Line Interface for AI Agents and Notebook Automation. nb-cli is an experimental, Rust-based CLI to read, write, execute, and search Jupyter notebooks. The premise: agents are great at CLIs but terrible at hand-editing the nested JSON in an .ipynb, so let them operate on the notebook from the outside instead of running inside it. Works with or without a Jupyter server. No server? It reads/writes .ipynb files directly and talks to kernels over ZeroMQ. Connected to a live JupyterLab, your edits show up instantly via Y.js (the same CRDT Jupyter uses). Smart output format: instead of token-heavy JSON or ambiguous plain markdown, it uses @@cell / @@output sentinels with inline metadata. Less wasted context, unambiguous structure, and it degrades gracefully on truncation. The payoff is composability. "Add a summary section and run it" becomes one shell pipeline instead of six agent tool calls. And nb search notebook.ipynb --with-errors returns only the failing cells, so the agent skips the cells that worked. Claude Code tie-in: it ships as an agent skill. npx skills install jupyter-ai-contrib/nb-cli and your agent can drive notebooks via nb. Out of jupyter-ai-contrib, which aims to become an official Jupyter AI subproject. Still early (crates.io is at v0.0.5), so kick the tires before anything load-bearing. See also marimo-pair. Calvin #4: Hindsight Agent Memory That Learns AI agents forget everything between sessions — Hindsight gives them persistent memory that learns over time Simple three-method API: retain(), recall(), reflect() — store, retrieve, and reason over memories TEMPR retrieval runs semantic, keyword, graph, and temporal search in parallel for accurate results Automatically consolidates related facts into durable observations instead of piling up duplicates pip install hindsight-all runs the entire server in-process; integrates with LangChain, LlamaIndex, Pydantic AI, CrewAI, and more Extras Calvin: Clanker: A Word For The Machine **Ponytail — You know him. Long ponytail. Oval glasses. Has been at the company longer than the version control** **Klangk: Multi-User AI Sandboxing, Collaboration and Coding Platform** Cursor announces Origin performative-ui to quick start your new idea Michael: Astral Joins OpenAI: The Interview SpaceX to acquire Cursor And OpenAI renews Open Source support Portuguese subtitles are now available for Talk Python courses DSF is hiring including Six Feet Up support Joke: Oh Babe…

Topics covered in this episode: pi + superpowers Terminal: Warp.dev + OhMyZSH {Blink,kitty} + mosh + tmux Claude code MacWhisper or Handy Tailscale Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training Six Feet Up is hosting a LinkedIn Live Connect with the hosts Michael: @[email protected] / @mkennedy.codes (bsky) Calvin: @[email protected] / @calvinhp.com (bsky) Show: @[email protected] / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Calvin #1: pi + superpowers terminal-first, open-source coding agent Session management is a first-class citizen Extension model is what makes pi special — it's aggressively composable Superpowers brings a structured software development methodology as loadable skills Steps back and asks you what you're really trying to do “hand you the keys to the car” mode vs guardrails might not be for everyone Michael #2: Terminal: Warp.dev + OhMyZSH If you’re using the base terminal with default settings, you have so much head-room for improvement. I’ve been using Warp.dev since Elvis talked me into it. ;) Remarkable terminal but the AI side of things is a bit junky, can be turned off OhMyZSH gives better autocomplete e.g. git branch [HTML_REMOVED] lists all branches in the local repo! Commandbookapp.com is excellent to keep the terminal focused on terminal things and more server commands and other automation in Command Book. Calvin #3: {Blink,kitty} + mosh + tmux Kitty Terminal — GPU-accelerated terminal emulator for macOS, Linux, and Windows with support for graphics, ligatures, and a powerful tiling layout system built right in. Blink Shell — The go-to terminal for iPad/iPhone power users; full SSH and Mosh client with a gorgeous interface built specifically for mobile professional workflows. Mosh — Mobile Shell replaces SSH for remote connections, surviving network switches, sleep cycles, and flaky Wi-Fi with zero dropped sessions — essential for staying connected to long-running agentic jobs. tmux — Terminal multiplexer that keeps sessions alive on your Linux server indefinitely; detach from a Mosh session on your Mac, reconnect from your iPad, and your agent is right where you left it. The combo — Kitty or Blink + Mosh + tmux creates a "persistent remote brain" pattern: your beefy Linux homelab runs the compute-heavy agent sessions 24/7, and any device becomes a thin client to drop in and out at will. Michael #4: Claude code I prefer the IDE experience, the new PyCharm + Claude integration is really good. VS Code too. Why IDE? Because we should still be present with our code and managing context is much easier. Use the best/latest models on high thinking. “Speed” is not your friend, it’s just shortcuts. Create skills and agents and use them. Curate your own rules (e.g. Talk Python’s Claude.md) Works well on non-coding things. Just create a folder, put a ton of files in there and it’s like NotebookLM + Chat + more. Calvin #5: MacWhisper or Handy Transcribes your speech using your choice of Whisper or Parakeet models. All transcription is done on your device, no data leaves your machine. Automatic Speaker Recognition with local models. Handy is more basic, but open source and runs on all platforms. Michael #6: Tailscale No need to open ports at all, Tailscale makes machines inside the same network accessible to each other Works great for laptops, desktops, etc. But also available for servers. Though I still use cloud firewalls for servers. How I use it: My dev database server, preloaded with QA data, is always running on my home mac mini m4 pro. All my apps look for that server before looking locally and tailscale makes them always accessible to each other My local LLMs expose OpenAI API compatible APIs. Tailscale makes these accessible even while traveling or at a coffee shop. Use my mini as an exit node. All traffic is routed outbound from my local fiber network. Great to restricted IPs like accessing my servers without caring about the local IP. Screen share back to my home machines even while traveling. Listen to the Talk Python episode with Alex for a deeper conversation. Extras Calvin: Telescopo great Mac Markdown viewer/editor. Michael: One more: Typora markdown editor. Created formal documentation for many of my open source packages using Great Docs. Via Mark Little: Statement on the US government directive to suspend access to Fable 5 and Mythos 5 Joke: No second date

Topics covered in this episode: Vulnerability and malware checks in uv HTTP GET requests with the Python standard library Millions of AI agents imperiled by critical vulnerability in open source package alembic-git-revisions Extras Joke Watch on YouTube About the show Goodbye and Thanks Brian Thanks Calvin for being part of this and future episodes! Also new time for the live show. Thanks Brian for all the hard work over the years. Calvin #1: Vulnerability and malware checks in uv release just yesterday by Astral https://astral.sh/blog/uv-audit uv audit scans dependencies for known vulnerabilities and abandoned packages via the OSV database — runs 4–10x faster than pip-audit Malware check runs on every install/sync, catching actively malicious packages (credential stealers, etc.) before they execute — including ones PyPI quarantined but lockfiles can still reference Enable malware scanning with UV_MALWARE_CHECK=1 — it's opt-in and in preview Future roadmap includes a resolver that steers toward vulnerability-free versions and install-time warnings scoped to newly added deps only Michael #2: HTTP GET requests with the Python standard library If you’re doing HTTP in Python, you’re probably using one of three popular libraries: requests, httpx, or urllib3. There have been issues with httpx lately. Niquest is another option: Drop-in replacement for Requests. Automatic HTTP/1.1, HTTP/2, and HTTP/3. WebSocket, and SSE included. But maybe less is more, especially in the age of agentic AI A good candidate needs two things to be true at once, not one: the used surface is small, and the behavior behind that surface is shallow. Calvin #3: Millions of AI agents imperiled by critical vulnerability in open source package "BadHost" (CVE-2026-48710) is a critical vulnerability in Starlette — the ASGI framework underlying FastAPI — with 325 million weekly downloads; also affects vLLM, LiteLLM, and most MCP server tooling The exploit is trivial: injecting a single character into an HTTP Host header bypasses path-based authentication, and can lead to credential theft, SSRF, and in some cases remote code execution MCP servers are a prime target since they store credentials for external services (email, databases, cloud accounts) — exposed data in the wild includes biopharma clinical trial DBs, full mailboxes, HR/PII pipelines, and AWS topology Fix is available — patch to Starlette 1.0.1 immediately; use the free scanner at mcp-scan.nemesis.services to check if your servers are still running a vulnerable version Open source sustainability footnote: the maintainer triages near-daily security reports solo, in his free time — most are AI-generated noise, and real ones like this still compete for the same evenings and weekends Michael #4: alembic-git-revisions By Julien Danjou from Mergify Automatic Alembic migration chaining based on git commit history. No more Multiple head revisions are present for given argument 'head'. See the introductory article Caused by two migrations landed with the same down_revision, and Alembic doesn’t know which one comes first. The fix is always the same: someone manually edits the migration file to re-chain the revisions. The insight: git already knows the order Extras Calvin: GNU make can do pattern matching in the target. Not new at all, mentioned in the 1994-era docs. just and task don’t have this super power on the target name yet. train-%: uv run ./train.py $* --save-hyper-params --overwrite $(TRAIN_ARGS) Michael: Updated my HTTP client using packages from httpx to httpx2: listmonk, umami, and memberful. For motivation, see this reddit thread. Joke: Accurate

Topics covered in this episode: CVE-2026-48710: A Maintainer's Perspective daily-stars-explorer Markdown to pdf with pandoc and typst postman2pytest Extras Joke Watch on YouTube About the show Brian #1: CVE-2026-48710: A Maintainer's Perspective Marcelo Trylesinski suggested by Lee Luocks Short version: users of Starlette: upgrade to Starlette 1.0.1 security professionals: we can’t treat open source projects like corporations This top link is a Starlette security advisory with the title Missing Host header validation poisons request.url.path, bypassing path-based security checks The CVE apparently caused some negative press targeting starlette. However, “the vulnerability came from the application pattern and the deployment, never from something Starlette intended.” A quote from an OSTIF article: “This bug is a classic “responsibility gap” where if this maintainer didn’t patch, thousands of exposed projects would have to individually secure their projects. In doing this work, they’ve voluntarily taken on the responsibility to protect the ecosystem from long-term systemic harm. As with all open source projects, they owed us nothing and could have left this to be everyone else’s problem and took the extraordinary steps of helping the ecosystem.” Both X40 D-Sec and Ars Technica expected immediate fixes and responses from Starlette. That’s not good. We can do better. Michael #2: daily-stars-explorer Explore the full history of any GitHub repository. 📈 Full Star History - Complete daily star counts for any repo ⏰ Hourly Stars - Hour-by-hour activity with timezone support 🔀 Compare Repos - Side-by-side comparison of any two repositories 📊 Activity Timelines - Commits, PRs, Issues, Forks, Contributors over time 📌 Pin Favorites - Bookmark repos for quick access without retyping 📰 Feed Mentions - See when repos were mentioned on HN, Reddit, YouTube, GitHub 💾 Export Data - Download as CSV or JSON 🌙 Dark Mode - Easy on the eyes Try/use it online at emanuelef.github.io/daily-stars-explorer or install it for yourself. Brian #3: Markdown to pdf with pandoc and typst typst suggestion from Matt Harrison Markdown is awesome Pandoc is great for converting markdown to tons of stuff but for pdf, it goes through LaTeX, which is … yuk (my opinion) Pandoc also can convert to typst And typst creates beautiful pdfs and is way easier (my opinion) to deal with than LaTeX. New tools brew upgrade pandoc brew install typst Now convert pandoc something.md --to typst -o something.typ typst compile something.typ something.pdf Michael #4: postman2pytest via Mikhail Based on postman app Convert Postman Collection v2.1 JSON into executable pytest test suites Postman collections document your API. postman2pytest turns that documentation into executable regression tests that run in CI. No manual rewriting, no drift. Extras: New blog, who dis? - testandcode.org is now on .org and a blog and soon to be a “publisher”. Joke: Centering a div

Topics covered in this episode: Dumb Ways for an Open Source Project to Die How to create a pylock.toml lockfile https://github.com/facebook/Lifeguard Choosing a Python Logging Library in 2026 Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @[email protected] / @mkennedy.codes (bsky) Brian: @[email protected] / @brianokken.bsky.social Show: @[email protected] / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Dumb Ways for an Open Source Project to Die Core categories The maintainer left The maintainer is still there Sabotage and capture The release pipeline broke Force majeure The world moved on The project split - Examples Bulma PRs still from 2023, issues and PRs with no maintainer response for years, last release 1.5 years ago diskcache Similar, got hired by OpenAI, crickets after that Brian #2: How to create a pylock.toml lockfile Tim Hopper Tim walks through using uv, pip and pdm to create pylock.toml files. Recommendation: use uv export --format pylock.toml -o pylock.toml He also has How to install from a pylock.toml lockfile with pip but the short version is: use -r because tools treat it like a requirements file Michael #3: https://github.com/facebook/Lifeguard Lifeguard is a static analyzer to detect Lazy Imports incompatibilities and ease the adoption overhead for Lazy Imports in Python. I’m more excited about lazy imports after my Cutting Python Web App Memory Over 31% experience Some Python patterns depend on imports executing immediately. For example: Module-level side effects — a module that registers a handler or modifies global state at import time will behave differently if that import is deferred. The registry pattern — a module that registers itself (e.g., adding to a global dict) when imported will silently fail to register under Lazy Imports. sys.modules manipulation — code that reads or writes sys.modules assumes prior imports have already executed. Metaclasses and __init_subclass__ — class creation side effects may depend on imports being resolved. Project Stage: Beta Lifeguard is in active development. We are aiming to be ready for general use by the Python 3.15 final release. Brian #4: Choosing a Python Logging Library in 2026 Ayooluwa Isaiah " which libraries matter, how they compare, where they overlap with the standard module, and when each one makes sense.” The slant with this article is the need to log json output, which seems reasonable as things like API entry and exit point logging will include json. Covered libraries standard library logging with a hat tip to python-json-logger Same site has a guide to setting up python-json-logger structlog Loguru Logbook picologging Some benchmarks with structlog, stdlib+json, and Loguru, with structlog coming out faster I liked the Loguru example I’m going to have to try @logger.catch and logger.exception() for easily logging exceptions and serialize=True to enable JSON output. Extras Brian: When Women Stopped Coding - Planet Money segment , spotted on BlueSky from Savannah Ostrowski Lean TDD is now leaner Still working on audio version, but some great changes in 0.7.1 version Ch 6, TDD Interpretations, move ATDD and some of BDD to chapter Ch 7, Change name to TDD with Teams: BDD and ATDD Ch 9, Lean TDD, streamline steps and chapter Ch 10, Change name to Lean TDD with Teams: Lean ATDD Ch 11, Lean TDD with AI, Add short discussion about guardrails and security Michael: New course: Python Web Security: OWASP Top 10 with Agentic AI All courses now with Spanish subtitles, see announcement Joke: Stop texting me

Topics covered in this episode: Using Django Tasks in production Co-authored with Claude? PyPI packages are increasing rapidly httpx2 Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @[email protected] / @mkennedy.codes (bsky) Brian: @[email protected] / @brianokken.bsky.social Show: @[email protected] / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Using Django Tasks in production Tim Schilling shares how the Djangonaut Space website has been using Django’s new tasks framework and some of the info missing from the official Django docs. Tasks require a third party package, django-tasks-db to actually run the tasks. Article walks through all changes necessary to get an email process running to notify admins of new testimonials. Cool simple example. With the db backend, you can monitor progress of tasks in the admin, to see which tasks are scheduled, completed, or have errors. Some wishes for the community to implement new tutorial in the Django docs Django Debug toolbar panel for tasks test/mock backend Great title for wish list: Thinks I’d like to see, but I’m too lazy to implement myself. Michael #2: Co-authored with Claude? Via Nik T. We don’t put “executed on macOS”, “edited with PyCharm”, etc. in our commits. Why Claude? Seems like a growth hack to me, that I don’t really care to participate in. Some projects that have formalized their thoughts on this: The Generative AI Policy Landscape in Open Source Adjust to turn off in ~/.claude/settings.json see the docs. { "attribution": { "commit": "", "pr": "" } } Brian #3: PyPI packages are increasing rapidly Artem Golubin There’s been an increase of published packages per week on PyPI A pretty big increase in the last handful of months. 30% increase since 2025, clearly due to AI Artem is building hexora, a malicious Python code detector. Cool package too, it can: Audit project dependencies to catch potential supply-chain attacks Detect malicious scripts found on platforms like Pastebin, GitHub, or open directories Analyze IoC files from past security incidents Audit new packages uploaded to PyPi. Artem is using hexora to analyze recently published pypi packages and many are obviously vibecoded and trigger false positives for abuses of eval, exec, and subprocess Side note: I don’t think that’s necessarily a false positive. Not malicious, but maybe a stupid-code-detector? Lots are LLM related, Lots have bots contributing code Publishing rate is crazy, dozens to hundreds of published versions in a day is a bug, not a feature Brian’s proposal, PyPI should limit releases per day for any package to something a sane human would do, even if they make a mistake on a release, to maybe like 2-3, definitely under 10, in a day. And if the repo has obvious agent contributors listed, maybe lower to the limit to 1-2 a day? Honestly, “move fast and break things” doesn’t apply to breaking the commons. Michael #4: httpx2 More on the httpx, httpxyz, etc changes: Pydantic people started their own fork, httpx2. Michiel says “while we think httpxyz was definitely needed, we welcome httpx2 and think it should be the ‘blessed’ fork.” Kludex, who is among other things maintainer of Starlette, was considering a fork As it stands, httpx2 is lacking the performance improvements they added to httpxyz. But it will not be long before they will add those, too. Also they already made some smart decisions: they are switching from certifi to truststore they are switching to compression.zstd on Python 3.14+, enabling zstd compression by default they merged httpcore and vendored it in their repository Discussion on Hacker News Extras Brian: The Four Horsemen of the LLM Apocalypse - Anarcat Django/JetBrains 2026 developer survey is open Pyrefly 1.0 : “meaning we are confident that Pyrefly is ready for production use.” Michael: Just about ready to release Python Web Security: OWASP Top 10 with Agentic AI course. Be sure to be on the courses newsletter to get notified. Joke: Proud Parents

Topics covered in this episode: httpxyz one month in Learn concurrency - a deep dive into multithreading with Python pip 26.1 - lockfiles and dependency cooldowns Python 3.15 sentinal values from PEP 661 Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @[email protected] / @mkennedy.codes (bsky) Brian: @[email protected] / @brianokken.bsky.social Show: @[email protected] / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: httpxyz one month in First version of httpxyz contained just the fixes to get zstd working, and the fixes to get the test suite running on python 3.14, some ‘housekeeping’ changes related to the renaming End of March: a compatibility shim that allows you to use httpxyz even with third-party packages that import httpx themselves, as long as you import httpxyz first. Importing httpxyz automatically registers it under the httpx name in sys.modules , see https://httpxyz.org/httpx-compatibility/ Fixed a WHOLE bunch of performance related issues by forking httpcore Brian #2: Learn concurrency - a deep dive into multithreading with Python Nikos Vaggalis “Whenever you are trying to speed up code using multiple cores, always ask yourself: “Do these threads need to talk to each other right now?” If the answer is yes, it will be slow. The best parallel code splits a big job into completely isolated chunks, processes them separately, and merges the results at the finish line.” Good overview of thread concurrency with Python and how that’s been improved dramatically with free-threaded Python Defines lots of terms you come across, including “embarrassingly parallel multithreading” There’s a counter example that’s nice Start with a shared resource, a counter, and multiple threads updating it Attempt to fix with threading.Lock(), which fixes it, but slows things down Good explanation of why Proper fix with concurrent.futures and separating the work of different threads so that they can be independent and their results can be combined when they’re all finished. Michael #3: pip 26.1 - lockfiles and dependency cooldowns Python 3.9 is no longer supported Experimental: installing from pylock files Dependency cooldowns (see my post about this) Lifting several 2020 resolver limitations Brian #4: Python 3.15 sentinal values from PEP 661 MISSING = sentinel("MISSING") def next_value(default: int | MISSING = MISSING): ... if default is MISSING: ... Take a name str as a constructor parameter Intended to be compared with is operator, similar to None Sentinal objects can be used as a type, also similar to None and can be combined with other types with |. Unlike None, sentinal values are truthy. (Elipses ... are also truthy) This seems like a strange choice. but I guess it must have made sense to someone. It does force you to use is instead of depending on False-ness, so I guess it’ll make code using sentinels more readable. Interesting that the PEP was started in 2021, and we’re finally getting it this year. Extras Brian: Before GitHub - Armin Ronacher tenacity - cross-platform multi-track audio editor/recorder learned about it from Armin’s article Joke: Joke option Make it myself Seems similar to what people think about software now Links httpxyz one month in httpxyz.org/httpx-compatibility Learn concurrency - a deep dive into multithreading with Python pip 26.1 - lockfiles and dependency cooldowns my post about this Python 3.15 sentinal values from PEP 661 Before GitHub tenacity Make it myself

Topics covered in this episode: profiling-explorer Reverting the incremental GC in Python 3.14 and 3.15 VSCode AI Co-author defaults to on, then off django freeze Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @[email protected] / @mkennedy.codes (bsky) Brian: @[email protected] / @brianokken.bsky.social Show: @[email protected] / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: profiling-explorer Adam Johnson And intro post Python: introducing profiling-explorer “profiling-explorer is a tool for exploring profiling data from Python’s built-in profilers, which are stored in pstats files. ” Features Dark mode Click the calls, internal ms, or cumulative ms column headers to sort by that column. Use the search box to filter by filename or function name. Hover by a filename + line number pair to reveal the copy button, which copies the location to your clipboard for faster opening. Click the callers or callees links on the right of a row (not pictured above) to see the callers or callees of that function. Michael #2: Reverting the incremental GC in Python 3.14 and 3.15 Python 3.14 shipped with a new incremental garbage collector, but production reports of severe memory pressure (Neil Schemenauer measured up to 5× peak RSS on pathological cyclic workloads) have pushed the core team and Steering Council to revert it in both 3.14 and 3.15 - returning to the 3.13-era generational GC. This is the second time the inc GC has been pulled back: it was also reverted right before 3.13.0 final, and it shipped in 3.14 without going through the PEP process. The tradeoff is real: Neil's benchmarks showed max GC pause times of 1.3ms with inc GC versus 26ms with the generational one - great for latency-sensitive apps, terrible for memory-constrained ones. Release manager Hugo van Kemenade will ship 3.14.5 early with the revert, and Gregory Smith floated the idea of a 3.14.5rc1 - the first patch-release RC since 3.9.2 back in 2021. Tim Peters spent the thread doing live forensics on Windows, running a toy deque program that should cap at 1GB and watching it balloon to 15.6GB on a 16GB machine - and discovered the gen0 collector effectively never fires under the new scheme. Tim's bigger meta-point: CPython has a chronic shortage of real-world GC benchmarks, pyperformance has "basically no interesting" cyclic workloads, and users almost never share real data - so core devs keep flying blind on changes like this. Django maintainer Adam Johnson published a blog post mid-thread documenting a real memory "leak" in Django's migration system caused by inc GC, with a manual gc.collect() workaround - the listener-facing receipt that this wasn't just theoretical. If the inc GC comes back for 3.16, it'll go through a proper PEP, and the discussion is already shifting toward keeping both collectors available via a startup flag - which Neil and Sergey Miryanov have both prototyped. Brian #3: VSCode AI Co-author defaults to on, then off VSCode merges Enabling ai co author by default - 3 week ago Ton’s of “why would you do this” and related comments VSCode merges Change default for git.addAICoAuthor to off - yesterday Take-away, don’t rely on default, set addAICoAuthor to off yourself Michael #4: django freeze Convert your dynamic django site to a static one with one line of code. Just run python manage.py generate_static_site :) Features Generate the static version of your Django site, optionally compressed .zip file Generate/download the static site using urls (only superuser and staff) Follow sitemap.xml urls Follow internal links founded in each page Follow redirects Report invalid/broken urls Selectively include/exclude media and static files Custom base url (very useful if the static site will run in a specific folder different by the document-root) Convert urls to relative urls (very useful if the static site will run offline or in an unknown folder different by the document-root) Prevent local directory index Extras Brian: Thinking Less, Trusting More: GenAI’s Impacts on Students’ Cognitive Habits Michael: Vercel breached, employee to blame Introducing the new Talk Python web player GitHub uptime (a couple of views 1, 2) Joke: Friends in tech

Topics covered in this episode: Django Modern Rest Already playing with Python 3.15 Cutting Python Web App Memory Over 31% tryke - A Rust-based Ptyhon test runner with a Jest-style API Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @[email protected] / @mkennedy.codes (bsky) Brian: @[email protected] / @brianokken.bsky.social Show: @[email protected] / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Django Modern Rest Modern REST framework for Django with types and async support Supports Pydantic, Attrs, and msgspec Has ai coding support with llms.txt See an example at the “showcase” section Brian #2: Already playing with Python 3.15 3.15.0a8, 2.14.4 and 3.13.13 are out Hugo von Kemenade beta comes in May, CRs in Sept, and Final planned for October But still, there’s awesome stuff here already, here’s what I’m looking forward to: PEP 810: Explicit lazy imports PEP 814: frozendict built-in type PEP 798: Unpacking in comprehensions with * and ** PEP 686: Python now uses UTF-8 as the default encoding Michael #3: Cutting Python Web App Memory Over 31% I cut 3.2 GB of memory usage from our Python web apps using five techniques: async workers import isolation the Raw+DC database pattern local imports for heavy libraries disk-based caching See the full article for details. Brian #4: tryke - A Rust-based Ptyhon test runner with a Jest-style API Justin Chapman Watch mode, Native async support, Fast test discovery, In-source testing, Support for doctests, Client/server mode for fast editor integrations, Pretty, per-assertion diagnostics, Filtering and marks, Changed mode (like pytest-picked), Concurrent tests, Soft assertions, JSON, JUnit, Dot, and LLM reporters Honestly haven’t tried it yet, but you know, I’m kinda a fan of thinking outside the box with testing strategies so I welcome new ideas. Extras Brian: Why are’t we uv yet? Interesting take on the “agents prefer pip” Problem with analysis. Many projects are libraries and don’t publish uv.lock file Even with uv, it still often seen as a developer preference for non-libarries. You can sitll use uv with requirements.txt PyCon US 2026 talks schedule is up Interesting that there’s an AI track now. I won’t be attending, but I might have a bot watch the videos and summarize for me. :) What has technology done to us? Justin Jackson Lean TDD new cover Also, 0.6.1 is so ready for me to start f-ing reading the audio book and get on with this shipping the actual f-ing book and yes I realize I seem like I’m old because I use “f-ing” while typing. Michael: Python 3.14.4 is out Beanie 2.1 release Joke: HumanDB - Blazingly slow. Emotionally consistent.