Python Bytes

Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Michael: #0: Python Bytes is 6 years old this week. Thank you!

Watch on YouTube About the show Sponsored by Complier Podcast from RedHat Michael #0: New livestream time - 11am PT on Tuesdays. Also, subscribe to the youtube channel and “hit the bell” to get notified of all the live streams. Brian #1: It’s PyCon US 2023 CFP time Will be held in Salt Lake City, Salt Palace Convention Center Talks are Friday - Sunday, April 19-23 PyCon US 2023 launch announcement PyCon 2023 site features images taken from past PyCon artwork Call for proposals open until Dec 9, but please don’t wait that long. Michael #2: Any.io AnyIO is an asynchronous networking and concurrency library that works on top of either asyncio or trio. It implements trio-like structured concurrency (SC) on top of asyncio. Cool interpretability between native threads and asyncio Using subprocesses: AnyIO allows you to run arbitrary executables in subprocesses, either as a one-shot call or by opening a process handle for you that gives you more control over the subprocess. Async file I/O: AnyIO provides

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Michael #1: Python 3.11 is released Live stream of the actual release procedure Talk Python episode coming next week (live stream on Friday) Major new features of the 3.11 series, compared to 3.10 General changes PEP 657 -- Include Fine-Grained Error Locations in Tracebacks PEP 654 -- Exception Groups and except* PEP 680 -- tomllib: Support for Parsing TOML in the Standard Library gh-90908 -- Introduce task groups to asyncio gh-34627 -- Atomic grouping ((?>...)) and possessive quantifiers (*+, ++, ?+, {m,n}+) are now supported in regular expressions. The Faster CPython Project is already yielding some exciting results. Python 3.11 is up to 10-60% faster than Python 3.10. On average, we measured a 1.22x speedup on the standard benchmark suite. See Faster CPython for details. Typing and typing language changes PEP 673 -- Self Type PEP 646 -- Variadic Generics PEP 675 -- Arbitrary Literal String

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Brian #1: Awesome pytest speedup Neyts Zupan A checklist of best practices to speed up your pytest suite. as a talk at Plone NAMUR 2022 Measure first Then make sure (all items have explanations) Hardware is fast use a faster computer also try a self-hosted runner seriously, a dedicated computer (or a few) for making test runs faster might be worth it. CI resources are usually slower in cloud than local, and even expensive VM farms are often slower. Try local Collection is fast utilize norecursedirs and specifying the location of the tests, either on the command line or with testpaths PYTHONDONTWRITEBYTECODE=1 is set might help Built-in pytest plugins are disabled try -p no:pastebin -p no:nose -p no:doctest Only a subset of tests are executed Especially when developing or debugging, run a subset and skip the slow tests. Network access is disabled pytest-socket can make sure of that Di

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Michael #0: Scorpions concert Check out this short video if you're interested. Michael #1: Pyscript 2022.09.1 is out Beware of the breaking changes Brian #2: Decorator shortcuts by Ned Batchelder Michael #3: Panel (of Holoviz) on Pyscript via Marc Skov Madsen Panel can now run on pyodide and pyscript with no backend server. Brian #4: auto-walrus Marco Gorelli Also, a reminder about pyupgrade, mentioned on the show back in 2018 Especially, look at the --py38-plus through --py39-plus flags. There are flags for 3.10 and 3.11, but limited testing for them. Joke: I need a new shirt

Watch the live stream: Watch on YouTube About the show Sponsored by Compiler Podcast from RedHat Brian #1: Ten tasty ingredients for a delicious pull request on wagtail blog, from LB Great tips for helping out with open source projects. But even for closed source, there’s good stuff there to know for people transitioning to single person projects to working on a team. The tips Read the [development] instructions. The contributing guide, etc. Read the issue and comments Create a fresh branch for your contribution Keep the changes focused Write unit tests also, extending tests for untested or under-tested features are a great way to contributes Give your pull request a name with context Reference the issue being fixed or resolved in the pull request Review & fix the CI failures Push to the same branch with fixes and do not open a new pull request Be patient. (Article lists this as “Eagerness balanced with patience”). Michael #2: textX via Rhet Turnbull textX is a meta-language for building

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Michael #1: Human regular expressions revisited via Mikael Honkala We mentioned of Al Sweigart's humre in Python Bytes… Mikael went on a little search and compiled my findings into this repo. A lot of people feel that re needs some help. At least 3 of the "serious" packages I found came out in the last few months. Since a package like this is not overly complex to make, all the ways to approach the problem are clearly being explored. Unfortunately these seem to be mostly single-person efforts, and many have fallen to the wayside before long. Hopefully there's some consolidation on the horizon, to share some of the maintenance effort and establish some of the packages as here for the long haul. The list could be useful to you if you are: Looking for a tool: Check the list to get a quick idea of the "look and feel" of each package. Thinking about building a tool: Check the list for alternative appro

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Brian #1: Can Amazon’s CodeWhisperer write better Python than you? Brian Tarbox “Despite the clickbait-y title, whether CW’s code is better or worse than mine is at the margins and not really important. What is significant is that it has the potential to save me a ton of time and mental space to focus on improving, refactoring and testing. It’s making me a better programmer by taking on some of the undifferentiated heavy lifting.” Some decent code generation, starting with Amazon API examples. The generated dataclass method was neat, but really, the comment “prompt” probably took as much time to write as the code would have. The generated test case is workable, but I would not consider that a good test. Perhaps don’t lump together construction, attribute access, and tests for all methods in one test function. That said, I’ve seen way worse test methods in my career. So, decent starting point. Rel

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Michael #1: PythonAnywhere: Our Commitment to Providing Free Accounts via Matthew Kramer In light of Heroku’s cancelling their free tiers… They believe free tiers are important for beginners Two part solution: Limit outbound internet access for free accounts “Proof of life” to keep running - 3 months for apps, 1 yr for accounts BTW, they were acquired by Anaconda Inc. Brian #2: ruff: An extremely fast Python linter, written in Rust. Announcement article: Python tooling could be much, much faster Charlie Marsh Quite the star history, as it’s a new repo as of Aug 30. Now at 1.8k. It is extremely fast. I installed it and tried it on a small project. It ran so fast I thought it didn’t do anything. I went and added some errors to convince myself it was running. $ time flake8 src tests ... flake8 src tests 0.29s user 0.02s system 98% cpu 0.311 total $ time ruff src/ tests/

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Special guest: Seth Larson Brian #1: Test your packages and wheels I’ve been building some wheels the last couple of weeks with various tools: flit, flit-core, and flit build hatch, hatchling, and hatch build setuptools, build_meta, and python -m build There are a few projects I’ve used to make sure my projects are in good shape wheel-inspect - you can inspect within Python code through inspect_wheel() function that converts to json. Or use on the command line with wheel2json check-wheel-contents - a linter for wheels tox - easily test the building, installation, and running of a package locally I actually start here, then utilize the other two tools Should have been obvious, but it wasn’t to me Projects saved on git (such as gitHub) don’t keep wheels in git. (this was obvious) When installing from git using pip install git+https://path/to/git/repo.git Your local pip will run the packaging

Watch the live stream: Watch on YouTube About the show Sponsored by the IRL Podcast from Mozilla Michael #1: Careful with that PyPI email via John Hagen There is a widespread Phishing attack going on against PyPI users. The PyPA is currently tweeting about it: https://twitter.com/pypi/status/1562442188285308929 Brian #2: IEEE Top Programming Languages 2022 : Python’s still No. 1, but employers love to see SQL skills by Stephen Cass Related: The Rise of SQL It’s become the second programming language everyone needs to know by Rina Diane Caballar Good to see Python on top for Spectrum and Trending But interesting to see growth and strength in SQL SQL is actually top for Jobs SQL is a skill you can’t ignore. Not only are relational databases just as important for large systems, they’re increasingly more important for small and even local systems, and are ever growing the responsibility of developers, not left to database specialists. Will #3: Using Mypy in production at Spring by Charlie Marsh

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Brian #1: Uncommon Uses of Python in Commonly Used Libraries by Eugene Yan Specifically, Using relative imports Example from sklearn’s base.py from .utils.validation import check_X_y from .utils.validation import check_array “Relative imports ensure we search the current package (and import from it) before searching the rest of the PYTHONPATH. “ For relative imports, we have to use the from .something import thing form. We cannot use import .something since later on in the code .something isn’t valid. There’s a good discussion of relative imports in pep 328 Michael #2: Skyplane Cloud Transfers Skyplane is a tool for blazingly fast bulk data transfers in the cloud. Skyplane manages parallelism, data partitioning, and network paths to optimize data transfers, and can also spin up VM instances to increase transfer throughput. You can use Skyplane to transfer data: Between buckets within a clou

Watch the live stream: Watch on YouTube About the show Sponsored by the IRL Podcast from Mozilla Michael #1: SQLCodeGen via Josh Thurston This is a tool that reads the structure of an existing database and generates the appropriate SQLAlchemy model code, using the declarative style if possible. This tool was written as a replacement for sqlautocode, which was suffering from several issues (including, but not limited to, incompatibility with Python 3 and the latest SQLAlchemy version). Features: Supports SQLAlchemy 1.4.x Produces declarative code that almost looks like it was hand written Produces PEP 8 compliant code Accurately determines relationships, including many-to-many, one-to-one Automatically detects joined table inheritance Excellent test coverage Brian #2: The death of setup.py*, long live pyproject.toml for Python-only projects Juan Luis Cano Rodriguez tweet pip install --``editable . now works with setuptools, as of version 64.0.0 To be clear, setup.cfg also not required. So everyth

Watch the live stream: Watch on YouTube About the show Sponsored by the IRL Podcast from Mozilla Brian #1: Pip constraints files by luminousmen You can put some constraints on your dependencies with a constraints file. “Constraints files are requirements files that only control which version of a requirement is installed, not whether it is installed or not. “ Syntax is a subset of requirements.txt syntax but all the restrictions seem reasonable, considering must have a name can’t be editable can’t specify extras (that one is maybe slightly weird) You can put --constraint constraints.txt right at the top of your requirements.txt file or specify it on command line, pip install --constraint constraints.txt -r requirements.txt Or, my favorite, stick it at the top of requirements.in file. yes. pip-compile correctly handles constraints when generating requirements.txt. Example requirements.in --constraint constraints.txt typer constraints.txt click<8.1.3 Output from pip-compile requirements.in #

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Michael #1: Faster routing for Flask & Quart Flask and Quart both utilise Werkzeug's HTTP route With the upcoming 2.2 release of Werkzeug this router will be significantly faster, with up to a factor of 5. Better for large sets of routes Micro-benchmarks are unaffected and are unlikely to show a speedup. Started with tree-based radix algorithm Moved to state machine algorithm because of wild cards Brian #2: Quarto: an open-source scientific and technical publishing system built on Pandoc suggested by Paul Mackenzie Power of Pandoc and Jupyter Build documents - html, pdf, word presentations - Revealjs, PowerPoint, Beemer websites books - html, pdf, word, epub journal articles - acm, plos, elsevier, acs, jss Publish GitHub pages, Netlify, … kinda related - Kindle to support ePub Michael #3: Flet UI via Mikael Honkala New and upcoming UI framework by Feodor Fitzner: flet. It has a very

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Michael #1: Specialist: Python 3.11 perf highlighter via Alex Waygood Visualize CPython 3.11's specializing, adaptive interpreter.

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Special guest: Ashley Anderson Ashley #1: PSF security key giveaway for critical package maintainers Giving away 4000 2FA hardware keys Surely a team effort but I found it via @di_codes twitter (Dustin Ingram) links to previous talks on PyPI/supply chain security Interesting idea for helping with supply-chain vulnerabilities At least one dev pulled a critical package in response Previously: <add some links to prior discussions> I don’t have any critical projects Armin Ronacher has an interesting take Michael #2: PyLeft-Pad via Dan Bader Markus Unterwaditzer was maintaining atomicwrites More on how this relates to a project (Home Assistant) I wonder if PyPI will become immutable once an item is published Brian #3: FastAPI Filter Suggested and created by Arthur Rio “I loved using django-filter with DRF and wanted an equivalent for FastAPI.” - Arthur Add query string filters to your api

Watch the live stream: Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Brian #1: rich-codex by Phil Ewels suggested by Will McGugan “A GitHub Action / command-line tool which generates screen grab images of a terminal window, containing command outputs or code snippets.” Generate images from commands embedded in markdown files, like README.md, for example. Searches through markdown files for stuff like:  then runs the command, and generates the image. Can be done within a GitHub action Can also send code snippets or json to rich-cli, then generate an image. You can also have commands in a config file, Very easy to use, makes very professional looking images for documentation, that’s always up to date. Michael #2: Pydastic via Roman Right, by Rami Awar Pydastic is an elasticsearch python ORM based on Pydantic. Core Features Simple CRUD operations supported Sessions for simplifying bulk operations (a la SQLAlchemy) Dynamic

Watch the live stream: Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training Test & Code Podcast Patreon Supporters Michael #1: Python License tracker by Tom Nijhof/Nyhof Every package depends on other package with sometimes different licenses. Tom made a tool to find out what licenses you all need for a project: PyTest alone needs 4 different licenses for itself and its dependencies. Tensorflow is even worst Brian #2: undataclass Trey Hunner As a teaching aid, and to show how much dataclasses do for you, this is a module and an application that converts dataclasses to normal classes, and fills in all of the dunder methods you need. Example in app: from dataclasses import dataclass @dataclass() class Point: x: float y: float z: float Converts to class Point: __match_args__ = ('x', 'y', 'z') def __init__(self, x: float, y: float, z: float) -> None: self.x = x

Watch the live stream: Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training Test & Code Podcast Patreon Supporters Special guest: Nick Muoh Brian #1: picologging From a tweet by Anthony Shaw From README.md “early-alpha” stage project with some incomplete features. (cool to be so up front about that) “Picologging is a high-performance logging library for Python. picologging is 4-10x faster than the logging module in the standard library.” “Picologging is designed to be used as a drop-in replacement for applications which already use logging, and supports the same API as the logging module.” Now you’ve definitely got my attention. For many common use cases, it’s just way faster. Sounds great, why not use it? A few limitations listed: process and thread name not captured. Some logging globals not observed: logging.logThreads, logging.logMultiprocessing, logging.logProcesses Logger will always default to the Sys.stderr and not observe