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Python Bytes

Python Bytes

Written by: Michael Kennedy and Calvin Hendryx-Parker
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Python Bytes is a weekly podcast hosted by Michael Kennedy and Calvin Hendryx-Parker. The show is a short discussion on the headlines and noteworthy news in the Python, developer, and data science space.Copyright 2016-2026 Politics & Government
Episodes
  • #487 Minimum requirements

    #487 Minimum requirements
    Jul 7 2026
    Topics covered in this episode: dust - a better duHermes Agent: The AI agent that grows with youllm-coding-agent 0.1a0ExtrasJokeWatch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk PythonConsulting from Six Feet Up Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedInCalvin: Mastodon / BlueSky / X / LinkedInShow: 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. Michael #1: dust - a better du du + Rust = dust - a fast, visual, intuitive disk-usage CLIRun dust and immediately see the biggest directories and files without piping through sort, head, or awkSmart recursive output focuses on what matters instead of dumping every folderColored bars show relative size and parent/child hierarchy, making “where did the space go?” obviousPerfect for Python projects bloated by .venv, caches, Docker volumes, downloaded datasets, and local AI modelsInstall via brew, cargo install du-dust, conda-forge, Scoop, Snap, deb-get, or GitHub releases Calvin #2: A Way better ARchive format for Python packaging war - new archive format spec from Astral (same team as uv/ruff), v0.0.2, still no binary encoding defined yetHeader-Index-Store layout: header IDs the file, index maps names to store offsets, store holds compressed dataIndex uses a finite-state transducer (FST) to dedupe common path prefixes across entry namesSupports three entry types (file, directory, link) and three compression modes (store/DEFLATE/zstd), plus an "executable" metadata flagUnpacking is atomic - writes to a temp dir, then renames into place, so a failed extract never leaves a half-unpacked directoryStrict name-segment rules (no NUL/control chars, no leading/trailing whitespace, blocks Windows-reserved names like CON/PRN) to avoid path traversal and cross-platform footguns Michael #3: Hermes Agent: The AI agent that grows with you Hermes Agent is an open-source, Python-built AI agent framework from Nous Research - think ChatGPT-style assistant, but connected to your tools, files, shell, browser, calendar, memory, and messaging appsI’m using it in Discord as a long-running agent conversation, not just a one-off chatbot sessionHermes can connect through a gateway to platforms like Discord, Telegram, Slack, WhatsApp, email, webhooks, and more - so the same assistant can follow you across surfacesIn my setup, I can send Hermes voice/text from Discord, keep project context across turns as threads, and ask it to actually do things: read GitHub repos, run commands, edit files, schedule calendar events, generate drafts, and verify resultsA fun workflow: I can trigger one-shot actions from an Apple Watch shortcut - dictate a request, send it to Hermes, and have the agent execute it asynchronouslyHermes has persistent memory, so it can remember durable preferences and facts - for example, how I like my research formattedIt also has “skills,” which are reusable procedures the agent can load later, so Hermes can self-improve over time instead of rediscovering the same workflow repeatedlyIt supports scheduled jobs / cron-style automations, so it can proactively watch for releases, send summaries, run checks, or remind you about thingsIt’s provider-agnostic: OpenRouter, Anthropic, Google, xAI, local models, Nous Portal, and othersThe big idea: Hermes turns an LLM from “a chat box I visit” into “an agent I can reach from anywhere that knows my workflows and can take real actions and learns over time.” Calvin #4: llm-coding-agent 0.1a0 Simon Willison built a Claude/Codex-style coding agent on top of his llm library, using an alpha of the llm package plus his python-lib-template-repoBuilt almost entirely via prompted TDD - asked an agent to write a spec.md, then commit + implement with red/green tests, occasionally hitting a real OpenAI key to sanity-checkShipped to PyPI as an alpha: uvx --prerelease=allow --with llm-coding-agent llm codeTool set mirrors familiar coding-agent primitives: read_file, edit_file (exact string replace + diff), write_file, list_files, search_files, execute_commandAlso exposes a Python API - CodingAgent(model="gpt-5.5", root=..., approve=True).run(...) - which Simon didn't ask for but got anywayDemo: llm code --yolo told GPT-5.5 to build a SwiftUI CLI clock; model correctly noted SwiftUI isn't really CLI-friendly and still produced an ASCII-art time display Extras Calvin: Slides, but for developers https://sli.dev/Wanna reduce your token usage…. only issue is that its lossy https://github.com/teamchong/pxpipePEP 772 - Python Packaging Council inaugural election dates set, nominations open July 28, voting September 1-15 Michael: What the pls? revisited! Joke: Min requirements for ...
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    28 mins
  • #486 underscore-underscore-ghost-emoji

    #486 underscore-underscore-ghost-emoji
    Jun 30 2026
    Topics covered in this episode: Free-threaded Python: past, present, and futuredjango-admin-site-searchQwen 3.6 27B is the sweet spot for local developmentA large batch of PEPs are finalizedExtrasJokeWatch on YouTube Show Intro Sponsored by us! Support our work through: Our courses at Talk PythonConsulting from Six Feet Up Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedInCalvin: Mastodon / BlueSky / X / LinkedInShow: 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 groundsSam Gross at Meta finally solved it; his work became PEP 703 and ships as free-threaded CPython todayPython 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 buildsAlready >50% of the top PyPI binary wheels support free threadingWouters 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 ParkinA 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 labelsModel labels and field attributesActual 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 RAM4-bit quantization gets it under 18GB, runnable on 32GB devices; Nvidia RTX cards run it even fasterThe dense 27B is recommended over the faster MoE 35B A3B — author prefers higher quality output over raw speedPrivacy and reliability are the pitch: fine-tunable, can't be taken down, suitable for sensitive/proprietary dataAuthor 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, 829But 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 namesvia Jeff Triplett
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    30 mins
  • #485 Creating memories

    #485 Creating memories
    Jun 23 2026
    Topics covered in this episode: Backup Docker volumes locally or to any S3Pyodide 314.0 Releasenb-cli: A Command-Line Interface for AI Agents and Notebook AutomationHindsight Agent Memory That LearnsExtrasJokeWatch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk PythonAWS 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 / LinkedInCalvin: Mastodon / BlueSky / X / LinkedInShow: 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...
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    38 mins
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