Items tagged python, async
Filters: python × async × Sorted by date
aiolimiter. I found myself wanting an asyncio rate limiter for Python today—so I could send POSTs to an API endpoint no more than once every 10 seconds. This library worked out really well—it has a very neat design and lets you set up rate limits for things like “no more than 50 items every 10 seconds”, implemented using the leaky bucket algorithm. # 20th February 2024, 1:15 am
Weeknotes: Parallel SQL queries for Datasette, plus some middleware tricks
A promising new performance optimization for Datasette, plus new datasette-gzip and datasette-total-page-time plugins.
Finding and reporting an asyncio bug in Python 3.10
I found a bug in Python 3.10 today! Some notes on how I found it and my process for handling it once I figured out what was going on.
[... 1789 words]Async functions require an event loop to run. Flask, as a WSGI application, uses one worker to handle one request/response cycle. When a request comes in to an async view, Flask will start an event loop in a thread, run the view function there, then return the result.
Each request still ties up one worker, even for async views. The upside is that you can run async code within a view, for example to make multiple concurrent database queries, HTTP requests to an external API, etc. However, the number of requests your application can handle at one time will remain the same.
— Using async and await in Flask 2.0 # 12th May 2021, 5:59 pm
New Major Versions Released! Flask 2.0, Werkzeug 2.0, Jinja 3.0, Click 8.0, ItsDangerous 2.0, and MarkupSafe 2.0. Huge set of releases from the Pallets team. Python 3.6+ required and comprehensive type annotations. Flask now supports async views, Jinja async templates (used extensively by Datasette) “no longer requires patching”, Click has a bunch of new code around shell tab completion, ItsDangerous supports key rotation and so much more. # 12th May 2021, 5:37 pm
unasync (via) Today I started wondering out loud if one could write code that takes an asyncio Python library and transforms it into the synchronous equivalent by using some regular expressions to strip out the “await ...” keywords and suchlike. Turns out that can indeed work, and Ratan Kulshreshtha built it! unasync uses the standard library tokenize module to run some transformations against an async library and spit out the sync version automatically. I’m now considering using this for sqlite-utils. # 27th February 2021, 10:20 pm
datasette-ripgrep: deploy a regular expression search engine for your source code
This week I built datasette-ripgrep—a web application for running regular expression searches against source code, built on top of the amazing ripgrep command-line tool.
[... 1362 words]Inevitably we got round to talking about async.
As much of an unneeded complication as it is for so many day-to-day use-cases, it’s important for Python because, if and when you do need the high throughput handling of these io-bound use-cases, you don’t want to have to switch language.
The same for Django: most of what you’re doing has no need of async but you don’t want to have to change web framework just because you need a sprinkling of non-blocking IO.
— Carlton Gibson # 27th September 2020, 3:09 pm
The “await me maybe” pattern for Python asyncio
I’ve identified a pattern for handling potentially-asynchronous callback functions in Python which I’m calling the “await me maybe” pattern. It works by letting you return a value, a callable function that returns a value OR an awaitable function that returns that value.
[... 787 words]Waiting in asyncio. Handy cheatsheet explaining the differences between asyncio.gather(), asyncio.wait_for(), asyncio.as_completed() and asyncio.wait() by Hynek Schlawack. # 26th May 2020, 3:28 pm
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. # 10th January 2020, 4:49 am
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.
— Tom Christie # 8th October 2018, 2:43 pm
Trio Tutorial. Trio is a really nice async library for Python—a simpler alternative to asyncio, with some very clean API design. Best of all, the tutorial is fantastic—it provides a very clear explanation of async/await without diving into the intricacies of coroutines. # 17th March 2018, 3:55 pm
Python & Async Simplified. Andrew Godwin: “Python’s async framework is actually relatively simple when you treat it at face value, but a lot of tutorials and documentation discuss it in minute implementation detail, so I wanted to make a higher-level overview that deliberately ignores some of the small facts and focuses on the practicalities of writing projects that mix both kinds of code.” This is really useful: clearly explains the two separate worlds of Python (sync and async functions) and describes Andrew’s clever sync_to_async and async_to_sync decorators as well. # 20th February 2018, 12:30 am
Channels 2.0. Andrew just shipped Channels 2.0—a major rewrite and redesign of the Channels project he started back in 2014. Channels brings async to Django, providing a logical, standardized way of supporting things like WebSockets and asynchronous execution on top of a Django application. Previously it required you to run a separate Twisted server and redis/RabbitMQ queue, but thanks to Python 3 async everything can now be deployed as a single process. And the new ASGI spec means its turtles all the way down! Everything from URL routing to view functions to middleware can be composed together using the same ASGI interface. # 2nd February 2018, 6:19 pm
Deploying an asynchronous Python microservice with Sanic and Zeit Now
Back in 2008 Natalie Downe and I deployed what today we would call a microservice: json-head, a tiny Google App Engine app that allowed you to make an HTTP head request against a URL and get back the HTTP headers as JSON. One of our initial use-scase for this was Natalie’s addSizes.js, an unobtrusive jQuery script that could annotate links to PDFs and other large files with their corresponding file size pulled from the Content-Length header. Another potential use-case is detecting broken links, since the API can be used to spot 404 status codes (as in this example).
Sanic. “Sanic is a Flask-like Python 3.5+ web server that’s written to go fast [...] On top of being Flask-like, Sanic supports async request handlers. This means you can use the new shiny async/await syntax from Python 3.5, making your code non-blocking and speedy”. # 7th October 2017, 6:39 pm
uvloop: Blazing fast Python networking. “uvloop makes asyncio fast. In fact, it is at least 2x faster than nodejs, gevent, as well as any other Python asynchronous framework. The performance of uvloop-based asyncio is close to that of Go programs.” # 7th October 2017, 5:53 pm
Socket Benchmark of Asynchronous Servers in Python. A comparison of eight different asynchronous networking frameworks in Python. Tornado comes out on top in most of the benchmarks, but the post is most interesting for the direct comparison of simple code examples for each of the frameworks. # 22nd December 2009, 10:34 pm
Twisted inlineCallbacks and deferredGenerator. inlineCallbacks are a brilliant (but seemingly under-promoted) feature of Twisted which use the ability to return a value from a yield statement to make asynchronous callbacks look much more like regular sequential programming. # 25th October 2009, 11:30 pm
Diesel. Yet Another Asynchronous Python Comet Library, of interest because this is the first one I’ve seen that uses Python’s generator coroutines, taking advantage of the return value of the yield statement to feed messages in to a generator function. Currently only works on Python 2.6 on Linux due to a dependency on 2.6’s epoll support. # 23rd September 2009, 5:15 pm