|11 months ago||about 14 hours ago|
|MIT License||MIT License|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
We haven't tracked posts mentioning waffleweb yet.
Tracking mentions began in Dec 2020.
Concert - My submission for MongoDB Hackathon on DEV
4 projects | dev.to | 8 Dec 2022
My app fits into multiple categories 1) Since you can search for stages with Atlas Search 2) The entire app is real-time 3) The backend was built with Python and Sanic ASGI framework.
A Look on Python Web Performance at the end of 2022
10 projects | dev.to | 14 Nov 2022
Sanic is very very popular with 16.6k stars, 1.5k forks, opencollective sponsors and a very active github. Falcon is more popular than japronto with 8.9k stars, 898 forks, opencollective sponsors and a very active github too. Despite Japronto been keeped as first place by TechEmPower, Falcon is a way better solution in general with performance similar to fastify an very fast node.js framework that hits 575k requests per second in this benchmark.
Ask HN: Programming Without a Build System?
15 projects | news.ycombinator.com | 12 Nov 2022
> trying to build a lifeboat for Twitter, Python works, but then modules require builds that break.
> Alternatively, any good resources for the above?
There are many, _unbelievably many_ writeups and tools for Python building and packaging. Some of them are really neat! But paralysis of choice is real. So is the reality that many of the new/fully integrated/cutting edge tools, however superior they may be, just won't get long term support to catch on and stay relevant.
When getting started with Python, I very personally like to choose from a few simple options (others are likely to pipe up with their own, and that's great; mine aren't The One Right Way, just some fairly cold/mainstream takes).
1. First pick what stack you'll be using to develop and test software. In Python this is sadly often going to be different from the stack you'll use to deploy/run it in production, but here we are. There are two sub-choices to be made here:
1.a. How will you be running the _python interpreter_ in dev/test? "I just want to use the Python that came with my laptop" is fine to a point, but breaks down a lot sooner than folks expect (again, the reasons for this are variously reasonable and stupid, but here we are). Personally, I like pyenv (https://github.com/pyenv/pyenv) here. It's a simple tool that builds interpreters on your system and provides shell aliases to adjust pathing so they can optionally be used. At the opposite extreme from pyenv, some folks choose Python-in-Docker here (pros: reproducible, makes deployment environments very consistent with dev; cons: IDE/quick build-and-run automations get tricker). There are some other tools that wrap/automate the same stuff that pyenv does.
1.b. How will you be isolating your project's dependencies? "I want to install dependencies globally" breaks down (or worse, breaks your laptop!) pretty quickly, yes it's a bummer. There are three options here: if you really eschew automations/wrappers/thick tools in general, you can do this yourself (i.e. via "pip install --local", optionally in a dedicated development workstation user account); you can use venv (https://docs.python.org/3/library/venv.html stdlib version of virtualenv, yes the names suck and confusing, here we are etc. etc.), which is widely standardized upon and manually use "pip install" while inside your virtualenv, and you can optionally integrate your virtualenv with pyenv so "inside your virtualenv" is easy to achieve via pyenv-virtualenv (https://github.com/pyenv/pyenv-virtualenv); or you can say "hell with this, I want maximum convenience via a wrapper that manages my whole project" and use Poetry (https://python-poetry.org/). There's no right point on that spectrum, it's up to you to decide where you fall on the "I want an integrated experience and to start prototyping quickly" versus "I want to reduce customizations/wrappers/tooling layers" spectrum.
2. Then, pick how you'll be developing said software: what frameworks or tools you'll be using. A Twitter lifeboat sounds like a webapp, so you'll likely want a web framework. Python has a spectrum of those of varying "thickness"/batteries-included-ness. At the minimum of thickness are tools like Flask (https://flask.palletsprojects.com/en/2.2.x/) and Sanic (like Flask, but with a bias towards performance at the cost of using async and some newer Python programming techniques which tend, in Python, to be harder than the traditional Flask approach: https://sanic.dev). At the maximum of thickness are things like Django/Pyramid. With the minimally-thick frameworks you'll end up plugging together other libraries for things like e.g. database access or web content serving/templating, with the maximally-thick approach that is included but opinionated. Same as before: no right answers, but be clear on the axis (or axes) along with you're choosing.
3. Choose how you'll be deploying/running the software, maybe after prototyping for awhile. This isn't "lock yourself into a cloud provider/hosting platform", but rather a choice about what tools you use with the hosting environment. Docker is pretty uncontentious here, if you want a generic way to run your Python app on many environments. So is "configure Linux instances to run equivalent Python/package versions to your dev/test environment". If you choose the latter, be aware that (and this is very important/often not discussed) many tools that the Python community suggests for local development or testing are very unsuitable for managing production environments (e.g. a tool based around shell state mutation is going to be extremely inconvenient to productionize).
Yeah, that's a lot of choices, but in general there are some pretty obvious/uncontentious paths there. Pyenv-for-interpreters/Poetry-for-packaging-and-project-management/Flask-for-web-serving/Docker-for-production is not going to surprise anyone or break any assumptions. Docker/raw-venv/Django is going to be just as easy to Google your way through.
Again, no one obvious right way (ha!) but plenty of valid options!
Not sure if that's what you were after. If you want a "just show me how to get started"-type writeup rather than an overview on the choices involved, I'm sure folks here or some quick googling will turn up many!
An alternative to Elasticsearch that runs on a few MBs of RAM
65 projects | news.ycombinator.com | 24 Oct 2022
sanic - an express.js-like web framework built in C
2 projects | /r/opensource | 23 Oct 2022
You might want to consider a different name though, as there's already a very popular python web framework called sanic: https://sanic.dev/
I've made a webapp to play Two Rooms and a Boom, and I'd love for you all to try it out!
3 projects | /r/boardgames | 13 Oct 2022
For those interested in the nitty-gritty of the application itself, the frontend is developed using vue.js with bulma.io css framework for styling. The backend is running on a laptop in my basement and is served by sanic.dev both for static content and api/websockets.
Top Python Coding Repos
6 projects | dev.to | 5 Sep 2022
requests - A simple, yet elegant, HTTP library. sanic - Next generation Python web server/framework | Build fast. Run fast. click - Python composable command line interface toolkit elasticsearch-dsl-py - High level Python client for Elasticsearch panel - A high-level app and dashboarding solution for Python internetarchive - A Python and Command-Line Interface to Archive.org coconut - Simple, elegant, Pythonic functional programming
Social media app made with FastAPI
5 projects | /r/Python | 21 Jul 2022
Personally I haven’t used it outside of trying a few very basic things. I’d recommend blacksheep if you want small, performant and low overhead, or sanic which, in my opinion, is the best choice if you do not need all the Django fluff.
Building a fullstack Bitcoin related webapp (hobby project), looking for a partner!
2 projects | /r/Bitcoin | 9 Jun 2022
check out https://sanic.dev or https://www.djangoproject.com for your backend
Honeycomb, Python, and I: an OpenTelemetry Horror Story (With a Happy Ending)
3 projects | dev.to | 18 Apr 2022
It's no surprise that my apps are mostly written using Sanic as I'm pretty involved with the project. I've been wanting to start testing honeycomb out as well, so it seemed the perfect opportunity to try out.
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
uvicorn-gunicorn-docker - Docker image with Uvicorn managed by Gunicorn for high-performance web applications in Python with performance auto-tuning. Optionally with Alpine Linux.
ipywidgets - Interactive Widgets for the Jupyter Notebook
Svelte - Cybernetically enhanced web apps
justpy - An object oriented high-level Python Web Framework that requires no frontend programming
python-socketio - Python Socket.IO server and client
opentelemetry-python - OpenTelemetry Python API and SDK
snmp-poller - Polling data via SNMPv3
BlackSheep - Fast ASGI web framework for Python
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python