dispatch
fastapi
dispatch | fastapi | |
---|---|---|
20 | 467 | |
4,602 | 71,023 | |
1.0% | - | |
9.9 | 9.8 | |
4 days ago | 5 days ago | |
Python | Python | |
Apache License 2.0 | 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.
dispatch
- Netflix Dispatch
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Is there any open source project that uses FasAPI?
They use only sync routes in the project and can’t explain why https://github.com/Netflix/dispatch/issues/1073
- Is it really advisable to try to run fastapi with predominantly sync routes in a real world application?
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How to build a scalable project file structure for a beginner.
By far my favorite production FastAPI app to use as a references of how to use these technologies well is NetFlix Dispatch: https://github.com/Netflix/dispatch
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FastAPI Boilerplate using MongoDB, Motor, Docker
Hey, I have a lot of opinions about this template, but these are just my opinions based on my own experiences being burned by these things so take from them what you will: 1. Your version of poetry is outdated, dependency groups don't work that way anymore and this will fail to install on modern poetry 2. You list pyyaml as a dependency but don't use it anywhere 3. The healthcheck endpoint is interesting, but expensive and a security risk. I like the value this provides, but I don't know if exposing it this way or using it as a healthcheck is a good idea 1. You typically don't want to touch external systems (mongo) as part of a healthcheck as this can cause cascading failure chains that get out of hand quickly 2. You typically don't want to touch the underlying system itself 1. which means you can / should get rid of psutil as a dependency 4. You don't need and shouldn't use pytest-asyncio for a FastAPI project. It comes built-in with its own async test handlers that you should be using 5. Having python-dotenv installed in production has burned me many times. I recommend removing this complete, otherwise just moving it to a dev dep 6. Using the src layout prevents a lot of weird import time problems from cropping up in production, I recommend checking it out 7. The entrypoint for the Docker container should be using 1 worker, as containers really prefer if you have only a single root PID chain and nothing else. Deploying this into k8s would cause a lot of issues 8. Native python logging really isn't great for modern production applications. Structlog or Loguru are great alternatives and much easier to use (which should remove your only dependency on pyyaml) 9. The configuration management may not work the way you want since it is weakly typed. Since FastAPI uses Pydantic, you have access to BaseSettings which is a far superior product for configuration management, especially with environment variables 10. The app and API folder structure is an anti-pattern that doesn't scale past projects the size of a tutorial on how to laern FastAPI. I strongly recommend changing this to move of a vertical slice or folder per feature layout such as is used in https://github.com/Netflix/dispatch/tree/master/src/dispatch 11. FastAPI routes don't need `response_model=` anymore in favor of adding the return type to your function signature such as `async def create_thing() -> Thing:` 12. The uuid_masker function is interesting, but exposing UUIDs in logs usually doesn't pose a security risk and only makes debugging more difficult 13. You have some type lies in your code that could burn you such as https://github.com/alexk1919/fastapi-motor-mongo-template/blob/main/app/db/db.py#L10 . This pattern for the global DB handle has also burned me in the past and I had to go back and refactor out all of them to instead to purely use the FastAPI dependency injection chaining 14. datetime.datetime isn't safe to use as it is in sample_resource_common.py, you need a timezone aware implementation 15. Your test suite is stateful, require a running database, leak a lot of implementation details of the underlying models. This is every anti-pattern in the book for unit testing. And if you are going to do integration tests, then you would be better off with tooling designed for it such as playwright. Again, these are all just my opinions and may alone not be enough to warrant changing anything you have here.
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Python projects with best practices on Github?
Two random examples I found from 30 seconds of googling: Here’s Netflix using it in their crisis management tool, and here’s Uber using it in their deep learning framework.
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Open Source Projects based on FastAPI
netflix dispatch
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As a long time programmer what are some important coding styles ?
As someone who uses FastAPI, I find the https://github.com/Netflix/dispatch code to be a great reference.
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CEO faces backlash after quoting Martin Luther King Jr. in announcing layoffs
Besides that paying $21 to $41 per user for this nuts. Set up a VPS with Dispatch (opensourced by Netflix) and save your company some money.
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Total beginner, use FastAPI?
For production ready code examples I use: https://github.com/Netflix/dispatch
fastapi
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FastAPI Best Practices: A Condensed Guide with Examples
FastAPI is a modern, high-performance web framework for building APIs with Python, based on standard Python type hints.
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Building an Email Assistant Application with Burr
In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it.
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FastAPI Got Me an OpenAPI Spec Really... Fast
That’s when I found FastAPI.
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How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
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Analysing FastAPI Middleware Performance
Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696
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LangChain, Python, and Heroku
An API application framework (such as FastAPI)
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Litestar – powerful, flexible, and highly performant Python ASGI framework
It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.
This ends up made worse if you’re using sync routes.
If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.
This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759
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AI-Powered Image Search with CLIP, pgvector, and Fast API
Fast API.
- Ask HN: What is your go-to stack for the web?
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Fun with Avatars: Crafting the core engine | Part. 1
We will create our API using FastAPI, a modern high-performance web framework for building fast APIs with Python. It is designed to be easy to use, efficient, and highly scalable. Some key features of FastAPI include:
What are some alternatives?
fastapi-best-practices - FastAPI Best Practices and Conventions we used at our startup
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
full-stack-fastapi-template - Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
fastapi-router-controller - A FastAPI utility to allow Controller Class usage
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
opal - Fork of https://github.com/permitio/opal
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
databases - Async database support for Python. 🗄
Flask - The Python micro framework for building web applications.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.