uvicorn VS autoscraper

This tells Heroku to run uvicorn, which is a web server implementation in Python.

FastAPI uses Uvicorn, an ASGI (Asynchronous Server Gateway Interface) web server implementation for Python.

Now, let’s run our FastAPI application using Uvicorn: uvicorn main:app --reload

Uvicorn + Starlette 8k requests/s

I switched to Hypercorn because Uvicorn currently supports HTTP/1.1 and WebSockets as mentioned at https://www.uvicorn.org

This will set up Chroma and run it as a server with uvicorn, making port 8000 accessible outside the net docker network. The command also mounts a persistent docker volume for Chroma's database, found at chroma/chroma from your project's root.

There's an open discussion under the Uvicorn repository and we prepared a repository for Reproduction GitHub Repo

FastAPI is a popular Python Web framework that developers use to create RESTful APIs. It is based on Pydantic and Python-type hints that assist in the serialization, deserialization, and validation of data. In this tutorial, we will use FastAPI to create a simple "Hello World" application. We test and run the application locally. FastAPI requires a ASGI server to run the application production such as Uvicorn.

- [3] https://github.com/encode/uvicorn/issues/527

Uvicorn and Daphne are both ASGI server implementations that can be used with Django to serve your application using the ASGI protocol. Uvicorn is built on top of the uvloop library, which is a fast implementation of the event loop based on libuv, while Daphne is maintained as part of the Django Channels project and was designed to handle the unique requirements of Django applications that utilize asynchronous features, such as real-time updates, bidirectional communication, and long-lived connections.

See if something like autoscraper or mlscraper suits your needs.

GitHub - alirezamika/autoscraper: A Smart, Automatic, Fast and Lightweight Web Scraper for Python

In this article, we will learn how to create a simple e-commerce search API with multiple platform support: eBay and Amazon. AutoScraper and FastAPi provide the ability to create a powerful JSON API for the date. With Playwright's help, we'll extend our scraper and avoid blocking by using ScrapingAnt's web scraping API.

Maybe you could try out this tool never used it myself https://github.com/alirezamika/autoscraper Or you would need to train a neural network which does the parsing for you but the accuracy won't be 100% with this method https://github.com/scrapy/scrapely To answer your question there is no way to write one program which scrapes different pages correctly because their structure is not the same and some of them probably will have protection which will block your scraper so that would need extra attention or additional code