requests-html
uvicorn
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requests-html | uvicorn | |
---|---|---|
14 | 56 | |
13,553 | 7,682 | |
0.5% | 2.7% | |
0.0 | 8.8 | |
about 1 month ago | 9 days ago | |
Python | Python | |
MIT License | BSD 3-clause "New" or "Revised" 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.
requests-html
- will requests-html library work as selenium
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8 Most Popular Python HTML Web Scraping Packages with Benchmarks
requests-html
- Note, the first time you ever run the render() method, it will download Chromium into your home directory (e.g. ~/.pyppeteer/). This only happens once.
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Which string to lower case method to you use?
Example: requests-html which has a rather exhaustive README.md, but their dedicated page is not that helpful, if I remember correctly, and currently the domain is suspended.
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Top python libraries/ frameworks that you suggest every one
When it comes to web scraping, the usual people recommend is beautifulsoup, lxml, or selenium. But I highly recommend people check out requests-html also. Its a library that is a happy medium between ease of use as in beautifulsoup and also good enough to be used for dynamic, javascript data where it would be overkill to use a browser emulator like selenium.
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Web Scraping in a professional setting: Selenium vs. BeautifulSoup
What I do is try to see if I can use requests_html first before trying selenium. requests_html is usually enough if I dont need to interact with browser widgets or if the authentication isnt too difficult to reverse engineer.
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The best Python libraries
I'm not sure what is left to do, it is essentially a lightweight wrapper that consolidates a bunch of other libraries (like parse, requests, chromium, etc). The whole package is basically one file requests_html.py.
uvicorn
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LangChain, Python, and Heroku
This tells Heroku to run uvicorn, which is a web server implementation in Python.
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Fun with Avatars: Crafting the core engine | Part. 1
FastAPI uses Uvicorn, an ASGI (Asynchronous Server Gateway Interface) web server implementation for Python.
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Effortless API Documentation: Accelerating Development with FastAPI, Swagger, and ReDoc
Now, let’s run our FastAPI application using Uvicorn: uvicorn main:app --reload
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FastHttp for Python (64k requests/s)
Uvicorn + Starlette 8k requests/s
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Ask HN: Where to Host a FastAPI App
I switched to Hypercorn because Uvicorn currently supports HTTP/1.1 and WebSockets as mentioned at https://www.uvicorn.org
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How to use Chroma to store and query vector embeddings
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.
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Unresolved Memory Management Issues in FastAPI/Starlette/Uvicorn/Python During High-Load Scenarios
There's an open discussion under the Uvicorn repository and we prepared a repository for Reproduction GitHub Repo
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How to Dockerize and Deploy a Fast API Application to Kubernetes Cluster
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.
- FastAPI 0.100.0:Release Notes
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Unlocking Performance: A Guide to Async Support in Django
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.
What are some alternatives?
daphne - Django Channels HTTP/WebSocket server
hypercorn
Scrapy - Scrapy, a fast high-level web crawling & scraping framework for Python.
hypercorn - Hypercorn is an ASGI and WSGI Server based on Hyper libraries and inspired by Gunicorn.
Flask - The Python micro framework for building web applications.
dash - Data Apps & Dashboards for Python. No JavaScript Required.
starlette - The little ASGI framework that shines. 🌟
uvloop - Ultra fast asyncio event loop.
MechanicalSoup - A Python library for automating interaction with websites.
requests - A simple, yet elegant HTTP library. [Moved to: https://github.com/psf/requests]
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
mkcert - A simple zero-config tool to make locally trusted development certificates with any names you'd like.