Python Bytes

Topics covered in this episode:

chardet ,AI, and licensing

refined-github

pgdog: PostgreSQL connection pooler, load balancer and database sharder

Agentic Engineering Patterns

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 10am 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: chardet ,AI, and licensing

Thanks Ian Lessing

Wow, where to start?

A bit of legal precedence research.

Chardet dispute shows how AI will kill software licensing, argues Bruce Perens on the Register

Also see this GitHub issue.

Dan Blanchard, maintainer of a Python character encoding detection library called chardet, released a new version of the library under a new software license. (LGPL → MIT)

Dan is allowed to make this change because v7 is a complete “clean room” rewrite using AI

BTW, v7 is WAY better:

The result is a 48x increase in detection speed for a project that lives in the hot loops of many projects. That will lead to noticeable performance increases for literally millions of users (the package gets ~130M downloads per month).

It paves a path towards inclusion in the standard library (assuming they don’t institute policies against using AI tools).

Thread-safe detect() and detect_all() with no measurable overhead; scales on free-threaded Python 3.13t+

An individual claiming to be Mark Pilgrim, the original creator of the library, opened an issue in the project's GitHub repo arguing that Blanchard had no right to change the software license, citing the LPGL requirement that the license remain unchanged.

A 'complete rewrite' is irrelevant, since they had ample exposure to the originally licensed code (i.e. this is not a 'clean room' implementation).

Blanchard disagreed, citing how version 7.0.0 and 6.0.0 compare when subjected to JPlag, a library for detecting plagiarism.

Blanchard told The Register he had wanted to get chardet added to the Python standard library for more than a decade since it’s a core dependency to most Python projects.

Brian #2: refined-github

Suggested by Matthias Schöttle

A browser plugin that improves the GitHub experience

A sampling

Adds a build/CI status icon next to the repo’s name.

Adds a link back to the PR that ran the workflow.

Enables tab and shift tab for indentation in comment fields.

Auto-resizes comment fields to fit their content and no longer show scroll bars.

Highlights the most useful comment in issues.

Changes the default sort order of issues/PRs to Recently updated.

But really, it’s a huge list of improvements

Michael #3: pgdog: PostgreSQL connection pooler, load balancer and database sharder

PgDog is a proxy for scaling PostgreSQL.

It supports connection pooling, load balancing queries and sharding entire databases.

Written in Rust, PgDog is fast, secure and can manage thousands of connections on commodity hardware.

Features

PgDog is an application layer load balancer for PostgreSQL

Health Checks: PgDog maintains a real-time list of healthy hosts. When a database fails a health check, it's removed from the active rotation and queries are re-routed to other replicas

Single Endpoint: PgDog can detect writes (e.g. INSERT, UPDATE, CREATE TABLE, etc.) and send them to the primary, leaving the replicas to serve reads

Failover: PgDog monitors Postgres replication state and can automatically redirect writes to a different database if a replica is promoted

Sharding: PgDog is able to manage databases with multiple shards

Brian #4: Agentic Engineering Patterns

Simon Willison

So much great stuff here, especially

Anti-patterns: things to avoid

And 3 sections on testing

Red/green TDD

First run the test

Agentic manual testing

Extras

Brian:

<code>uv python upgrade</code> will upgrade all versions of Python installed with uv to latest patch release

suggested by John Hagen

Coding After Coders: The End of Computer Programming as We Know It

NY Times Article

Suggested by Christopher

Best quote: “Pushing code that fails pytest is unacceptable and embarrassing.”

Michael:

Talk Python Training users get a better account dashboard

Package Managers Need to Cool Down

Will AI Kill Open Source, article + video

My Always activate the venv is now a zsh-plugin, sorta.

Joke: Ergonomic keyboard

Also pretty good and related:

<code>Claude Code Mandated</code>

Links

legal precedence research

Chardet dispute shows how AI will kill software licensing, argues Bruce Perens

this GitHub issue

citing

JPlag

refined-github

Agentic Engineering Patterns

Anti-patterns: things to avoid

Red/green TDD

First run the test

Agentic manual testing

<code>uv python upgrade</code>

Coding After Coders: The End of Computer Programming as We Know It

Suggested by Christopher

a better account dashboard

Package Managers Need to Cool Down

Will AI Kill Open Source

Always activate the venv

now a zsh-plugin

Ergonomic keyboard

<code>Claude Code Mandated</code>

claude-mandated.png

blobs.pythonbytes.fm/keyboard-joke.jpeg?cache_id=a6026b

Topics covered in this episode:

Setting up a Python monorepo with uv workspaces

cattrs: Flexible Object Serialization and Validation

Learning to program in the AI age

VS Code extension for FastAPI and friends

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: Setting up a Python monorepo with uv workspaces

Dennis Traub

The 3 things

Give the Root a Distinct Name

Use workspace = true for Inter-Package Deps

Use importlib Mode for pytest

Michael #2: cattrs: Flexible Object Serialization and Validation

cattrs is a Swiss Army knife for (un)structuring and validating data in Python.

A natural alternative/follow on from DataClass Wizard

Converts to ←→ from dictionaries

cattrs also focuses on functional composition and not coupling your data model to its serialization and validation rules.

When you’re handed unstructured data (by your network, file system, database, …), cattrs helps to convert this data into trustworthy structured data.

Batteries Included: cattrs comes with pre-configured converters for a number of serialization libraries, including JSON (standard library, orjson, UltraJSON), msgpack, cbor2, bson, PyYAML, tomlkit and msgspec (supports only JSON at this time).

Brian #3: Learning to program in the AI age

Jose Blanca

“I teach a couple of introductory Python courses and I've been thinking about which advice to give to my students, that are studying how to program for the first time. I have collected my ideas in these blog posts”

Why learning to program is as useful as ever, even with powerful AI tools available.

How to use AI as a tutor rather than a shortcut, and why practice remains the key to real understanding.

What the real learning objectives are: mental models, managing complexity, and thinking like a software developer.

Michael #4: VS Code extension for FastAPI and friends

Enhances the FastAPI development experience in Visual Studio Code

Path Operation Explorer: Provides a hierarchical tree view of all FastAPI routes in your application.

Search for routes: Use the Command Palette and quickly search for routes by path, method, or name.

CodeLens links appear above HTTP client calls like client.get('/items'), letting you jump directly to the matching route definition.

Deploy your application directly to FastAPI Cloud from the status bar with zero config.

View real-time logs from your FastAPI Cloud deployed applications directly within VS Code.

Install from Marketplace.

Extras

Brian:

Guido van Rossum interviews key Python developers from the first 25 years

Interview with Brett Cannon

Interview with Thomas Wouters
Michael:

IntelliJ IDEA: The Documentary | An origin story video

Cursor Joined the ACP Registry and Is Now Live in Your JetBrains IDE

What hyper-personal software looks like

I’m doing in-person training again (limited scope):

On-site, hands-on AI engineering enablement for software teams with Michael

Joke: Saas is dead

Topics covered in this episode:

Raw+DC: The ORM pattern of 2026?

pytest-check releases

Dataclass Wizard

SQLiteo - “native macOS SQLite browser built for normal people”

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: Raw+DC: The ORM pattern of 2026?

ORMs/ODMs provide great support and abstractions for developers

They are not the native language of agentic AI

Raw queries are trained 100x+ more than standard ORMs

Using raw queries at the data access optimizes for AI coding

Returning some sort of object mapped to the data optimizes for type safety and devs

Brian #2: pytest-check releases

3 merged pull requests

8 closed issues

at one point got to 0 PR’s and 1 enhancement request

Now back to 2 issues and 1 PR, but activity means it’s still alive and being used. so cool

Check out changelog for all mods

A lot of changes around supporting mypy

I’ve decided to NOT have the examples be fully --strict as I find it reduces readability

See tox.ini for explanation

But src is --strict clean now, so user tests can be --strict clean.

Michael #3: Dataclass Wizard

Simple, elegant wizarding tools for Python’s dataclasses.

Features

🚀 Fast — code-generated loaders and dumpers

🪶 Lightweight — pure Python, minimal dependencies

🧠 Typed — powered by Python type hints

🧙 Flexible — JSON, YAML, TOML, and environment variables

🧪 Reliable — battle-tested with extensive test coverage

No Inheritance Needed

Brian #4: SQLiteo - “native macOS SQLite browser built for normal people”

Adam Hill

This is a fun tool, built by someone I trust.

That trust part is something I’m thinking about a lot in these days of dev+agent built tools

Some notes on my thoughts when evaluating

I know mac rules around installing .dmg files not from the apple store are picky.

And I like that

But I’m ok with the override when something comes from a dev I trust

The contributors are all Adam

I’m still not sure how I feel about letting agents do commits in repos

There’s “AGENTS” folder and markdown files in the project for agents, so Ad

Extras

Michael:

PyTV Python Unplugged This Week

IBM Crashes 11% in 4 Hours - $24 Billion Wiped Out After Anthropic's Claude Code Threatens the Entire COBOL Consulting Industry

Loving my 40” ultrawide monitor more every day

Updatest for updating all the mac things

Ice has Thawed out (mac menubar app)

Joke: House is read-only!

Topics covered in this episode:

Better Python tests with inline-snapshot

jolt Battery intelligence for your laptop

Markdown code formatting with ruff

act - run your GitHub actions locally

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: Better Python tests with inline-snapshot

Alex Hall, on Pydantic blog

Great for testing complex data structures

Allows you to write a test like this:

from inline_snapshot import snapshot
def test_user_creation():
user = create_user(id=123, name="test_user")
assert user.dict() == snapshot({})

Then run pytest --inline-snapshot=fix

And the library updates the test source code to look like this:

def test_user_creation():
user = create_user(id=123, name="test_user")
assert user.dict() == snapshot({
"id": 123,
"name": "test_user",
"status": "active"
})

Now, when you run the code without “fix” the collected data is used for comparison

Awesome to be able to visually inspect the test data right there in the test code.

Projects mentioned

inline-snapshot

pytest-examples

syrupy

dirty-equals

executing

Michael #2: jolt Battery intelligence for your laptop

Support for both macOS and Linux

Battery Status — Charge percentage, time remaining, health, and cycle count

Power Monitoring — System power draw with CPU/GPU breakdown

Process Tracking — Processes sorted by energy impact with color-coded severity

Historical Graphs — Track battery and power trends over time

Themes — 10+ built-in themes with dark/light auto-detection

Background Daemon — Collect historical data even when the TUI isn't running

Process Management — Kill energy-hungry processes directly

Brian #3: Markdown code formatting with ruff

Suggested by Matthias Schoettle

ruff can now format code within markdown files

Will format valid Python code in code blocks marked with python, py, python3 or py3.

Also recognizes pyi as Python type stub files.

Includes the ability to turn off formatting with comment [HTML_REMOVED] , [HTML_REMOVED] blocks.

Requires preview mode

[tool.ruff.lint]
preview = true

Michael #4: act - run your GitHub actions locally

Run your GitHub Actions locally! Why would you want to do this? Two reasons:

Fast Feedback - Rather than having to commit/push every time you want to test out the changes you are making to your .github/workflows/ files (or for any changes to embedded GitHub actions), you can use act to run the actions locally. The environment variables and filesystem are all configured to match what GitHub provides.

Local Task Runner - I love make. However, I also hate repeating myself. With act, you can use the GitHub Actions defined in your .github/workflows/ to replace your Makefile!

When you run act it reads in your GitHub Actions from .github/workflows/ and determines the set of actions that need to be run.

Uses the Docker API to either pull or build the necessary images, as defined in your workflow files and finally determines the execution path based on the dependencies that were defined.

Once it has the execution path, it then uses the Docker API to run containers for each action based on the images prepared earlier.

The environment variables and filesystem are all configured to match what GitHub provides.

Extras

Michael:

Winter is coming: Frozendict accepted

Django ORM stand-alone

Command Book app announcement post

Joke: Plug ‘n Paste

Topics covered in this episode:

Command Book App

uvx.sh: Install Python tools without uv or Python

Ending 15 years of subprocess polling

monty: A minimal, secure Python interpreter written in Rust for use by AI

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 10am 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: Command Book App

New app from Michael

Command Book App is a native macOS app for developers, data scientists, AI enthusiasts and more.

This is a tool I've been using lately to help build Talk Python, Python Bytes, Talk Python Training, and many more applications.

It's a bit like advanced terminal commands or complex shell aliases, but hosted outside of your terminal. This leaves the terminal there for interactive commands, exploration, short actions.

Command Book manages commands like "tail this log while I'm developing the app", "Run the dev web server with true auto-reload", and even "Run MongoDB in Docker with exactly the settings I need"

I'd love it if you gave it a look, shared it with your team, and send me feedback.

Has a free version and paid version.

Build with Swift and Swift UI

Check it out at https://commandbookapp.com

Brian #2: uvx.sh: Install Python tools without uv or Python

Tim Hopper

Michael #3: Ending 15 years of subprocess polling

by Giampaolo Rodola

The standard library's subprocess module has relied on a busy-loop polling approach since the timeout parameter was added to Popen.wait() in Python 3.3, around 15 years ago

The problem with busy-polling

CPU wake-ups: even with exponential backoff (starting at 0.1ms, capping at 40ms), the system constantly wakes up to check process status, wasting CPU cycles and draining batteries.

Latency: there's always a gap between when a process actually terminates and when you detect it.

Scalability: monitoring many processes simultaneously magnifies all of the above.

+ L1/L2 CPU cache invalidations

It’s interesting to note that waiting via poll() (or kqueue()) puts the process into the exact same sleeping state as a plain time.sleep() call. From the kernel's perspective, both are interruptible sleeps.

Here is the merged PR for this change.

Brian #4: monty: A minimal, secure Python interpreter written in Rust for use by AI

Samuel Colvin and others at Pydantic

Still experimental

“Monty avoids the cost, latency, complexity and general faff of using a full container based sandbox for running LLM generated code. “

“Instead, it lets you safely run Python code written by an LLM embedded in your agent, with startup times measured in single digit microseconds not hundreds of milliseconds.”

Extras

Brian:

Expertise is the art of ignoring - Kevin Renskers

You don’t need to master the language. You need to master your slice.

Learning everything up front is wasted effort.

Experience changes what you pay attention to.

I hate fish - Rands (Michael Lopp)

Really about productivity systems

And a nice process for dealing with email

Michael:

Talk Python now has a CLI

New essay: It's not vibe coding - Agentic engineering

GitHub is having a day

Python 3.14.3 and 3.13.12 are available

Wall Street just lost $285 billion because of 13 markdown files

Joke: Silence, current side project!