1,085 items tagged “python”
The Python programming language.
2020
2020 Web Milestones (via) A lot of stuff is happening in 2020! Mike Sherov rounds it up—highlights include the release of Chromium Edge (Microsoft’s Chrome-powered browser for Windows 7+), Web Components supported in every major browser, Deno 1.x, SameSite Cookies turned on by default (which should dramatically reduce CSRF exposure) and Python 2 and Flash EOLs.
Portable Cloud Functions with the Python Functions Framework (via) The new functions-framework library on PyPI lets you run Google Cloud Functions written in Python in other environments—on your local developer machine or bundled in a Docker container for example. I have real trouble trusting serverless platforms that lock you into a single provider (AWS Lambda makes me very uncomfortable) so this is a breath of fresh air.
Async Support—HTTPX (via) HTTPX is the new async-friendly HTTP library for Python spearheaded by Tom Christie. It works in both async and non-async mode with an API very similar to requests. The async support is particularly interesting—it’s a really clean API, and now that Jupyter supports top-level await you can run ’(await httpx.AsyncClient().get(url)).text’ directly in a cell and get back the response. Most excitingly the library lets you pass an ASGI app directly to the client and then perform requests against it—ideal for unit tests.
Better Python Object Serialization. TIL about functions.singledispatch, a decorator which makes it easy to create Python functions with implementations that vary based on the type of their arguments and which can have additional implementations registered after the fact—great for things like custom JSON serialization.
2019
Datasette 0.31. Released today: this version adds compatibility with Python 3.8 and breaks compatibility with Python 3.5. Since Glitch support Python 3.7.3 now I decided I could finally give up on 3.5. This means Datasette can use f-strings now, but more importantly it opens up the opportunity to start taking advantage of Starlette, which makes all kinds of interesting new ASGI-based plugins much easier to build.
My Python Development Environment, 2020 Edition (via) Jacob Kaplan-Moss shares what works for him as a Python environment coming into 2020: pyenv, poetry, and pipx. I’m not a frequent user of any of those tools—it definitely looks like I should be.
Automate the Boring Stuff with Python: Working with PDF and Word Documents.
I stumbled across this while trying to extract some data from a PDF file (the kind of file with actual text in it as opposed to dodgy scanned images) and it worked perfectly: PyPDF2.PdfFileReader(open("file.pdf", "rb")).getPage(0).extractText()
Why you should use `python -m pip` (via) Brett Cannon explains why he prefers “python -m pip install...” to “pip install...”—it ensures you always know exactly which Python interpreter environment you are installing packages for. He also makes the case for always installing into a virtual environment, created using “python -m venv”.
Streamlit: Turn Python Scripts into Beautiful ML Tools (via) A really interesting new tool / application development framework. Streamlit is designed to help machine learning engineers build usable web frontends for their work. It does this by providing a simple, productive Python environment which lets you declaratively build up a sort-of Notebook style interface for your code. It includes the ability to insert a DataFrame, geospatial map rendering, chart or image into the application with a single Python function call. It’s hard to describe how it works, but the tutorial and demo worked really well for me: “pip install streamlit” and then “streamlit hello” to get a full-featured demo in a browser, then you can run through the tutorial to start building a real interactive application in a few dozen lines of code.
PyPI now supports uploading via API token (via) All of my open source Python libraries are set up to automatically deploy new tagged releases as PyPI packages using Circle CI or Travis, but I’ve always get a bit uncomfortable about sharing my PyPI password with those CI platforms to get this to work. PyPI just added scopes authentication tokens, which means I can issue a token that’s only allowed to upload a specific project and see an audit log of when that token was last used.
Using memory-profiler to debug excessive memory usage in healthkit-to-sqlite. This morning I figured out how to use the memory-profiler module (and mprof command line tool) to debug memory usage of Python processes. I added the details, including screenshots, to this GitHub issue. It helped me knock down RAM usage for my healthkit-to-sqlite from 2.5GB to just 80MB by making smarter usage of the ElementTree pull parser.
PugSQL. Interesting new twist on a definitely-not-an-ORM library for Python. With PugSQL you define SQL queries in files, give them names and then load them into a module which allows you to execute them as Python methods with keyword arguments. You can mark statements as only returning a single row (or a single scalar value) with a comment at the top of their file.
json-flatten. A little Python library I wrote that attempts to flatten a JSON object into a set of key/value pairs suitable for transmitting in a query string or using to construct an HTML form. I first wrote this back in 2015 as a Gist—I’ve reconstructed the Gist commit history in a new repository and shipped it to PyPI.
Toward a “Kernel Python” (via) Glyph makes a strong case for releasing a slimmed down “kernel” version of Python with the minimal possible standard library, and argues that the current standard library is proving impossible for a single core team to productively maintain. “If I wanted to update the colorsys module to be more modern—perhaps to have a Color object rather than a collection of free functions, perhaps to support integer color models—I’d likely have to wait 500 days, or more, for a review.”
quicktype code generator for Python. Really interesting tool: give it an example JSON document and it will code-generate the equivalent set of Python classes (with type annotations) instantly in your browser. It also accepts input in JSON Schema or TypeScript and can generate code in 18 different languages.
Smaller Python Docker Containers with Multi-Stage Builds and Python Wheels (via) Clear tutorial on how to use Docker’s multi-stage build feature to create smaller final images by taking advantage of Python’s wheel format—so an initial stage can install a full compiler toolchain and compile C dependencies into wheels, then a later stage can install those pre-compiled wheels into a slimmer container without including the C compiler.
An Intro to Threading in Python (via) Real Python consistently produces really comprehensive, high quality articles and tutorials. This is an excellent introduction to threading in Python, covering threads, locks, queues, ThreadPoolExecutor and more.
Pyodide: Bringing the scientific Python stack to the browser (via) More fun with WebAssembly: Pyodide attempts (and mostly succeeds) to bring the full Python data stack to the browser: CPython, NumPy, Pandas, Scipy, and Matplotlib. Also includes interesting bridge tools for e.g. driving a canvas element from Python. Really interesting project from the Firefox Data Platform team.
Wasmer: a Python library for executing WebAssembly binaries. This is a really interesting new tool: “pip install wasmer” and now you can load code that has been compiled to WebAssembly and call those functions directly from Python. It’s built on top of the wasmer universal WebAssembly runtime, written over just the past year in Rust by a team lead by Syrus Akbary, the author of the Graphene GraphQL library for Python.
Ministry of Silly Runtimes: Vintage Python on Cloud Run (via) Cloud Run is an exciting new hosting service from Google that lets you define a container using a Dockerfile and then run that container in a “scale to zero” environment, so you only pay for time spent serving traffic. It’s similar to the now-deprecated Zeit Now 1.0 which inspired me to create Datasette. Here Dustin Ingram demonstrates how powerful Docker can be as the underlying abstraction by deploying a web app using a 25 year old version of Python 1.x.
Generator Tricks for Systems Programmers (via) David Beazley’s definitive generators tutorial from 2008, updated for Python 3.7 in October 2018.
VisiData
(via)
Intriguing tool by Saul Pwanson: VisiData is a command-line "textpunk utility" for browsing and manipulating tabular data. pip3 install visidata and then vd myfile.csv (or .json or .xls or SQLite or others) and get an interactive terminal UI for quickly searching through the data, conducting frequency analysis of columns, manipulating it and much more besides. Two tips for if you start playing with it: hit gq to exit, and hit Ctrl+H to view the help screen.
huey. Charles Leifer’s “little task queue for Python”. Similar to Celery, but it’s designed to work with Redis, SQLite or in the parent process using background greenlets. Worth checking out for the really neat design. The project is new to me, but it’s been under active development since 2011 and has a very healthy looking rate of releases.
parameterized. I love the @parametrize decorator in pytest, which lets you run the same test multiple times against multiple parameters. The only catch is that the decorator in pytest doesn’t work for old-style unittest TestCase tests, which means you can’t easily add it to test suites that were built using the older model. I just found out about parameterized which works with unittest tests whether or not you are running them using the pytest test runner.
Launching LiteCLI (via) Really neat alternative command-line client for SQLite, written in Python and using the same underlying framework as the similar pgcli (PostgreSQL) and mycli (MySQL) tools. Provides really intuitive autocomplete against table names, columns and other bits and pieces of SQLite syntax. Installation is as easy as “pip install litecli”.
2018
benfred/py-spy (via) A Python port of Julia Evans’ rbspy profiler, which she describes as “probably better” than the original. I just tried it out and it’s really impressive: it’s written in Rust but has precompiled binaries so you can just run “pip install py-spy” to install it. Shows live output in the terminal while your program is running and also includes the option to generate neat SVG flame graphs.
PEP 8016 -- The Steering Council Model (via) The votes are in and Python has a new governance model, partly inspired by the model used by the Django Software Foundation. A core elected council of five people (with a maximum of two employees from any individual company) will oversee the project.
Pampy: Pattern Matching for Python (via) Ingenious implementation of Erlang/Rust style pattern matching in just 150 lines of extremely cleanly designed and well-tested Python.
The ASGI specification provides an opportunity for Python to hit a productivity/performance sweet-spot for a wide range of use-cases, from writing high-volume proxy servers through to bringing large-scale web applications to market at speed.
The subset of reStructuredText worth committing to memory
reStructuredText is the standard for documentation in the Python world.
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