fastapi-azure-auth VS flet

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.

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.

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

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.

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.

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

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/)

> When you run flet build command it ... Packages Python app using package command of serious_python package. -- https://flet.dev/docs/guides/python/packaging-app-for-distri...

It looks like Flet is for client-side code. It lets you write Flutter apps with Python instead of Dart.

> Simple Architecture - No more complex architecture with JavaScript frontend, REST API backend, database, cache, etc. With Flet you just write a monolith stateful app in Python only and get multi-user, realtime Single-Page Application (SPA). -- https://flet.dev

If I'm writing Python that runs on the mobile device, it must talk to a server to read & write data. Doesn't this still require an API backend, database, cache, etc?

I just learned of Flet (https://flet.dev) which seems interesting for Python. I may try this as well.

maybe check out https://flet.dev

When developing or selecting an MRZ (Machine Readable Zone) recognition SDK, the primary challenge lies in finding an appropriate dataset for testing. Acquiring genuine MRZ images is challenging, and due to privacy concerns, they aren't publicly accessible. Therefore, crafting MRZ images becomes a practical solution. Fortunately, there's an open-source Python MRZ generator project, available for download from pypi, eliminating the need to start from scratch. This article aims to illustrate how to integrate and run Python scripts within web applications. First, We will showcase how to employ the Python MRZ SDK and Flet to construct a cross-platform MRZ generator. Subsequently, we will reuse the Python script with Pyodide, HTML5, and the Dynamsoft JavaScript MRZ SDK, creating an advanced online MRZ tool that can handle both MRZ creation and MRZ detection.

"The fastest way to build Flutter apps in Python" is the title of Flet's web page. As someone coming from the Flutter world reading the line I draw an ideal picture of "swapping Dart language for Python and magically having the whole power of Flutter framework and the tips of your fingers".

Well I haven't seen anyone mention Flet, which is pleasant (if maybe not all that complete) if you have Dart/Flutter experience, so increment your counter at least one. :-)

https://flet.dev/