fastapi-azure-auth
spleeter
fastapi-azure-auth | spleeter | |
---|---|---|
17 | 230 | |
390 | 24,925 | |
2.1% | 0.6% | |
7.6 | 1.5 | |
about 1 month ago | about 2 months ago | |
Python | Python | |
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.
fastapi-azure-auth
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FastUI: Build Better UIs Faster
I'm under the impression that you work for a company that sells services related to FastAPI? https://github.com/Intility/fastapi-azure-auth
I maintain an open source library in my spare time for free, that you are welcome to ignore if you find better alternatives.
- Implement AzureAD in 10 minutes with FastAPI-Azure-Auth - full tutorial in the documentation
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FastAPI Azure Auth đź”’ Now supports B2C (as well as single- and multi-tenant applications)
The documentation has a full tutorial in “Tiangolo-style”, which means it guided through setting up a project from scratch, and how to configure Azure appregs from scratch.
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Ask HN: Good Python projects to read for modern Python?
I think, in general, most FastAPI and Pydantic related libraries are heavily typed, use poetry, GitHub pipelines, black, isort, flake8 etc. so if you want to look at the ecosystem around a package I’ll recommend a few here, that has a smaller scope than the huge libraries Pydantic/FastAPI are. All packages listed below has all these things.
FastAPI-Azure-Auth [0] is a library to do authentication and authorization through Azure AD using tokens.
ASGI—Correlation-ID[1] is a package that utilizes contextvars to store information through the asyncio stack, in order to attach correlation/request ID to every log message from a request. Available for Django in [2].
Pydantic-factories [3] is an awesome library to mock data for your pydantic models.
[0] https://github.com/Intility/fastapi-azure-auth
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OAuth2 authorization with other flows beyond password.
If you want to use an external auth provider, I have written a library called FastAPI-Azure-Auth for authentication and authorization using Azure AD (which is free for something like 10.000 users). The tutorial should get you up and running quickly. Please note that this library is only intended to use for APIs (such as I sing a SPA frontend), so if you use jinja templates or render HTML from FastAPI this might not be the solution for you.
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FastAPI Azure AD Authentication đź”’ Now supports both single- and multi-tenants applications
Hi! I’m the author of FastAPI-Azure-Auth, a package to handle Azure AD authentication and authorization for your FastAPI APIs. It’s a heavily tested package, supports trio, and the documentation has a full tutorial on how to set up both Azure and FastAPI from scratch.
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Tips for Making a Popular Open-Source Project in 2021 [Ultimate Guide]
I agree with you. Most my packages are around ~100 stars, and I'm met with a lot of respect and appreciatio.n[1][2]
My library for Correlation-IDs in Django[3] got implemented by AWX, which also was a nice experience![4] I maintain a lot of small packages, and maybe it is the Django/FastAPI community, but "you'll get a load of entitled users" is straight up not true in my experience.
[1] https://github.com/Intility/fastapi-azure-auth/issues/24
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Show HN: Implement Azure AD auth for your FastAPI
The documentation[1] contains a full tutorial on how to configure Azure AD and FastAPI for both single- and multi-tenant applications. It includes examples on how to lock down your APIs to certain scopes, tenants, roles etc.
[1] https://intility.github.io/fastapi-azure-auth/)
- Azure AD authentication for FastAPI đź”’ Now supports both single- and multi-tenants. Documentation includes a full tutorial on how to set it up from scratch
- Azure AD authentication đź”’ Now supports both single- and multi-tenants, and has a full setup tutorial for both FastAPI and Azure.
spleeter
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Are stems a good way of making mashups
virtual dj and others stem separator is shrinked model of this https://github.com/deezer/spleeter you will get better results downloading original + their large model.
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Big News!
I have used multiple tools at this point. It depends on the scene. I use https://ultimatevocalremover.com/, https://github.com/deezer/spleeter/, iZotope RX. There are also multiple options online, I would personally recommend https://vocalremover.org/.
- Anybody here know what AI model does Steinberg's Spectralayers use to do stem separation?
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Show HN: Free AI-based music demixing in the browser
I tried to use it but I had some issues as others in the thread.
I have tried many sources and method over the years and settled on spleeter [0]. Works well even for 10+ minute songs, varying styles from flamenco to heavy metal.
[0] https://github.com/deezer/spleeter
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AI tools list sorted by category in one place
Spleeter is pretty good https://github.com/deezer/spleeter. Apparently it is used in some dj applications
- Software to lower tracks?
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Where does one legally get stems for remixes?
Haha GitHub and command lines and all can be confusing, but it’s certainly worth the effort because it lets you do everything for free.. here’s the online tutorial: https://github.com/deezer/spleeter/wiki/1.-Installation
- Audio and python help
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Are there any websites or programs that can separate vocals and drums from samples?
Chopped from their website Simple Stems is a quick and easy way to decompose any audio into it’s constituent parts. The plugin uses the well established Spleeter algorithm by Deezer to deconstruct songs into 2, 4 or 5 stems. The results are stunning, though more complicated mixes and live recordings are not always perfectly decomposed.
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Ask HN: Is there an ML model that can go from an audio song to sheet music?
I was going to post basic pitch from Spotify but it looks like billconan beat me to it. That said I can give you a bit more advice. The Spotify basic pitch model isn't too good at multi-track input. It's capable of it, but you may actually get better results if you separate out the tracks first and then run them individually through the basic pitch model.
In order to do this you can use a source/stem separation model like spleeter (https://github.com/deezer/spleeter) and then run the basic pitch model (or any other midi transcription model). There's other you can try which may yield better results, for example: (https://github.com/Music-and-Culture-Technology-Lab/omnizart)
Either way the key words you want to be looking for are "midi transcription" and "stem separation", should help you find more models to try for both steps. Good luck! :)
What are some alternatives?
full-stack-fastapi-template - Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.
ultimatevocalremovergui - GUI for a Vocal Remover that uses Deep Neural Networks.
azure-functions-python-samples - Azure Functions Python Sample Codes. NOTE: The project, hosted in a repository, is no longer actively maintained by its creators or contributors. There won't be any further updates, bug fixes, or support from the original developers in the project.
open-unmix-pytorch - Open-Unmix - Music Source Separation for PyTorch
best-of-web-python - 🏆 A ranked list of awesome python libraries for web development. Updated weekly.
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
uvicorn-gunicorn-fastapi-docker - Docker image with Uvicorn managed by Gunicorn for high-performance FastAPI web applications in Python with performance auto-tuning.
SpleeterGui - Windows desktop front end for Spleeter - AI source separation
asgi-correlation-id - Request ID propagation for ASGI apps
SpleetGUI - Spleeter GUI version
Installation - The premier source of truth powering network automation. Open source under Apache 2. Public demo: https://demo.netbox.dev
spleeter-web - Self-hostable web app for isolating the vocal, accompaniment, bass, and drums of any song. Supports Spleeter, D3Net, Demucs, Tasnet, X-UMX. Built with React and Django.