- Dec 2023
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www.bitecode.dev www.bitecode.dev
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Fast API
Fast API is a high-level web framework like flask, but that happens to be async, unlike flask. With the added benefit of using type hints and pydantic to generate schemas.
It's not a building block like twisted, gevent, trio or asyncio. In fact, it's built on top of asyncio. It's in the same group as flask, bottle, django, pyramid, etc. Although it's a micro-framework, so it's focused on routing, data validation and API delivery.
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So what's the deal with asyncio, twisted, gevent, trio and all that stuff?
asyncio
asyncio is the modern module for asynchronous network programming provided with the python stdlib since 3.4. In other words, it's the default stuff at your disposal if you want to code something without waiting on the network.
asyncio replaces the old deprecated asyncore module. It is quite low level, so while you can manually code most network-related things with it, you are still at the level of TCP or UDP. If you want higher-level protocols, like FTP, HTTP or SSH, you have to either code it yourself, or install a third party library or module.
Because asyncio is the default solution, it has a the biggest ecosystem of 3rd party libs, and pretty much everything async strives to be compatible with it directly, or through compatibility layers like anyio.
Twisted
20 years ago, there was no asyncio, there was no async/await, nodejs didn't exist and Python 3 was half a decade away. Yet, it was the .com bubble, everything needed to be connected now. And so was born twisted, the grandfather of all the asynchronous frameworks we have today. Twisted ecosystem grew to include everything, from mail to ssh.
To this day, twisted is still a robust and versatile tool. But you do pay the price of its age. It doesn't follow PEP8 very well, and the design lean on the heavy size.
Tornado
Tornado was developed after Twisted, by FriendFeed, at this weird 2005-2015 web dev period where everything needed to be social web scale. It was like Twisted, but tooted to be faster, and was higher level. Out of the box, the HTTP story is way nicer.
Today, you are unlikely to use Tornado unless you work at Facebook or contribute to jupyter. After all, if you want to make async web things, the default tool is FastAPI in 2023.
gevent
Gevent came about in 2009, the same year as Tornado, but with a fundamentally different design. Instead of attempting to provide an asychronous API, it decided to do black magic. When you use gevent, you call
from gevent import monkey; monkey.patch_all()and it changes the underlying mechanism of Python networking, making everything non-blocking.
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- Mar 2023
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blog.devops.dev blog.devops.dev
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In this example, we’ve defined an API endpoint called /predict_image that accepts a file upload using FastAPI's UploadFile type. When a client sends an image file to this endpoint, the file is read and its contents are passed to a preprocessing function that prepares the image for input into the model. Once the image has been preprocessed, the model can make a prediction on it, and the result can be returned to the client as a JSON response.
Example above shows how to upload an image to an API endpoint with FastAPI.
Example below is a bit more complex.
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For example, if you are using TensorFlow, you might save your model as a .h5 file using the Keras API. If you are using PyTorch, you might save your model as a .pt file using the torch.save() function. By saving your model as a file, you can easily load it into a deployment environment (such as FastAPI) and use it to make predictions on new images
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- Jun 2022
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fastapi.tiangolo.com fastapi.tiangolo.comFastAPI1
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@app.get("/items/{item_id}") def read_item(item_id: int, q: Union[str, None] = None): return {"item_id": item_id, "q": q}
Con la siguiente url, por ejemplo http://127.0.0.1:8000/items/1?q=hola
devuelve:
{ "item_id": 1, "q": "hola" }
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- Jan 2022
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levelup.gitconnected.com levelup.gitconnected.com
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you can also mount different FastAPI applications within the FastAPI application. This would mean that every sub-FastAPI application would have its docs, would run independent of other applications, and will handle its path-specific requests. To mount this, simply create a master application and sub-application file. Now, import the app object from the sub-application file to the master application file and pass this object directly to the mount function of the master application object.
It's possible to mount FastAPI applications within a FastAPI application
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- Oct 2021
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github.com github.com
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You probably shouldn't use Alpine for Python projects, instead use the slim Docker image versions.
(have a look below this highlight for a full reasoning)
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- Jul 2021
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The fact that FastAPI does not come with a development server is both a positive and a negative in my opinion. On the one hand, it does take a bit more to serve up the app in development mode. On the other, this helps to conceptually separate the web framework from the web server, which is often a source of confusion for beginners when one moves from development to production with a web framework that does have a built-in development server (like Django or Flask).
FastAPI does not include a web server like Flask. Therefore, it requires Uvicorn.
Not having a web server has pros and cons listed here
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FastAPI makes it easy to deliver routes asynchronously. As long as you don't have any blocking I/O calls in the handler, you can simply declare the handler as asynchronous by adding the async keyword like so:
FastAPI makes it effortless to convert synchronous handlers to asynchronous ones
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- Jun 2021
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betterprogramming.pub betterprogramming.pub
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Uses Pydantic which enforces type hints at runtime.
pydanticused by FastAPI
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- Aug 2020
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fastapi.tiangolo.com fastapi.tiangolo.com
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from fastapi import FastAPI app = FastAPI() @app.get("/") async def root(): return {"message": "Hello World"}
Basic get api with fastapi
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