#439 That Astral Episode Podcast By cover art

#439 That Astral Episode

#439 That Astral Episode

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 Topics covered in this episode: * ty documentation site and uv migration guide** uv build backend is now stable + other Astral news** Refactoring long boolean expressions** fastapi-ml-skeleton*ExtrasJokeWatch on YouTube About the show Sponsored by Sentry: pythonbytes.fm/sentry Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky)Brian: @brianokken@fosstodon.org / @brianokken.bsky.socialShow: @pythonbytes@fosstodon.org / @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: ty documentation site and uv migration guide via Skyler KaskoAstral created a documentation site for ty (PR #744 in release 0.0.1-alpha.13).Astral added a page on migrating from pip to a uv project in the uv documentation. (PR #12382 in release 0.7.19).Talk Python episode on ty. Brian #2: uv build backend is now stable + other Astral news The uv build backend is now stable Tim Hopper via Python Developer Tooling HandbookFrom Charlie Marsh “The uv build backend is now stable, and considered ready for production use. An alternative to setuptools, hatchling, etc. for pure Python projects, with a focus on good defaults, user-friendly error messages, and performance. When used with uv, it's 10-35x faster.”“(In a future release, we'll make this the default.)” [build-system] requires = ["uv_build>=0.7.19,<0.8.0"] build-backend = "uv_build" I believe it’s faster, but I agree with Brett Cannon in asking “What's being benchmarked? I'm not sure what a "backend sync" is referring to other than maybe installing the build back-end?”See also: uv: Making Python Local Workflows FAST and BORING in 2025 - Hynek Brian #3: Refactoring long boolean expressions Trey HunnerThis is applied boolean logic, and even folks who learned this in a CS program probably did so early on, and may have forgotten it.How can you improve the readability of long Boolean expressions in Python? Put parens around the whole expression and separate clauses onto different linesWhere to put boolean operators between clauses? at the end of the line or the beginning? PEP8 recommends the beginning if (expression1 and expression2 and expression3): ... Naming sub-expressions with variables Odd downside that wouldn’t occur to me. All expressions are evaluated, thus not taking advantage of expression short-circuiting.Naming operations with functions Less readable, but takes advantage of short-circuitingUsing De Morgan’s Law : replacing a compound expression with a similar (and hopefully easier to read) expression # neither: we want both to be false not (a or b) == (not a) and (not b) # never_both: at least one false not (a and b) == (not a) or (not b) Michael #4: fastapi-ml-skeleton FastAPI Skeleton App to serve machine learning models production-ready.This repository contains a skeleton app which can be used to speed-up your next machine learning project.The code is fully tested and provides a preconfigured tox to quickly expand this sample code.A sample regression model for house price prediction is included in this project.Short write up on "What does set -a do?" Extras Brian: OCF Michael: via Wei LeeExtra Airflow ruff rules: Starting from Ruff version 0.11.13, most changes from Airflow 2 to Airflow 3 can be automated using AIR3. (It’s still in preview so a “—-preview” flag is needed) e.g., if you have the following Airflow 2 code import datetime from airflow.models import DAG from airflow.operators.empty import EmptyOperator with DAG( dag_id="my_dag_name", start_date=datetime.datetime(2021, 1, 1), schedule_interval="@daily", ): EmptyOperator(task_id="task") it can be fixed with uvx ruff check --select AIR3 --fix --unsafe-fixes --preview import datetime from airflow.sdk import DAG from airflow.providers.standard.operators.empty import EmptyOperator with DAG( dag_id="my_dag_name", start_date=datetime.datetime(2021, 1, 1), schedule="@daily", ): EmptyOperator(task_id="task") which works with Airflow 3. Joke: Front Toward Enemy
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