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crulvsaiohttp

MIT 16 1 101
61.7 thousand (month) Nov 09 2016 1.4.0(1 year, 7 months ago)
14,508 30 499 Apache 2
3.9.3(2 months ago) Jul 26 2019 105.3 million (month)

crul is a R library for sending HTTP requests and web scraping. It is designed to be simple and easy to use, while still providing powerful functionality for working with HTTP requests and scraping web pages.

One of the main features of crul is its intuitive and easy-to-use syntax for sending HTTP requests. It allows you to easily specify the HTTP method, headers, and body of a request, and also provides a simple way to handle the response.

crul also has the ability to handle different types of requests and responses, including GET, POST, PUT, DELETE, and PATCH. It also support for handling redirects, cookies, and authentication.

Another feature of crul is its support for web scraping. The library provides a simple and efficient way to extract data from web pages, using a syntax similar to that of the XML and httr libraries. It also allows to easily filter the extracted data based on a specific criteria.

crul also supports parallel scraping, which allows to make multiple requests at the same time, thus speeding up the scraping process.

In addition to these features, crul has a good compatibility with other R packages such as tidyverse and purrr which facilitates the manipulation of the data obtained after scraping.

aiohttp is an asynchronous HTTP client/server framework for asyncio and Python. It provides a simple API for making HTTP requests and handling both client and server functionality. Like the requests package, aiohttp is designed to be easy to use and handle many of the low-level details of working with HTTP.

The main benefit of aiohttp over requests is that it is built on top of the asyncio library, which means that it can handle many requests at the same time without blocking the execution of your program. This can lead to significant performance improvements when making many small requests, or when dealing with slow or unreliable network connections.

aiohttp provides both client and server side functionality, so you can use it to create web servers and handle client requests in a non-blocking manner. It also supports WebSocket protocol, so it can be used for building real-time application like chat, game, etc.

aiohttp also provide several features for handling connection errors, managing timeouts, and client sessions. It also provide similar features like requests package like redirect handling, cookies, and support for several authentication modules.

You can install aiohttp via pip package manager:

pip install aiohttp

In terms of API design, aiohttp is similar to requests and thus should be familiar to anyone who has used the requests library, but it provides an async with block to manage the context of the connection and used await statement to wait for the result.

It''s worth noting that aiohttp is built on top of asyncio and is designed to be used in Python 3.5 and above. It provides the same functionality as httpx but it is specifically built for the asyncio framework.

Highlights


http2uses-curlasync
asynciowebsocketshttp2http-servermulti-partresponse-streaminghttp-proxy

Example Use


library(crul)

# Sending a GET request to a website
response <- HttpClient$new("https://www.example.com")$get()
# Sending a POST request to a website
request_body <- list(param1 = "value1", param2 = "value2")
response <- HttpClient$new("https://www.example.com")$post(body = request_body)

# Extracting the status code and body of the response
status_code <- response$status_code()
body <- response$body()

# crul also allows easy asynchronous requests:
urls <- c("https://www.example1.com", "https://www.example2.com", "https://www.example3.com")
# Creating a list of request objects from urls
requests <- lapply(urls, function(url) {
  HttpClient$new(url)$get()
})

# Sending the requests asynchronously
responses <- async(requests)

# Extracting the status code and body of the responses
status_codes <- lapply(responses, function(response) response$status_code())
bodies <- lapply(responses, function(response) response$body())
import asyncio
from aiohttp import ClientSession, WSMsgType

# aiohttp only provides async client so we must use a coroutine:
async def run():
    async with ClientSession(headers={"User-Agent": "webscraping.fyi"}) as session:
        # we can use the session to make requests:
        response = await session.get("http://httpbin.org/headers")
        print(response.status)
        # note: to read the response body we must use await:
        print(await response.text())

        # aiohttp also comes with convenience methods for common requests:
        # POST json
        resp = await session.post("http://httpbin.org/post", json={"key": "value"})
        # POST form data
        resp = await session.post("http://httpbin.org/post", data={"key": "value"})
        # decode response as json
        resp = await session.get("http://httpbin.org/json")
        data = await resp.json()
        print(data)

        # aiohttp also supports websocket connections
        # which can be used to scrape websites that use websockets:
        async with session.ws_connect("http://example.org/ws") as ws:
            async for msg in ws:
                if msg.type == WSMsgType.TEXT:
                    if msg.data == "close cmd":
                        await ws.close()
                        break
                    else:
                        await ws.send_str(msg.data + "/answer")
                elif msg.type == WSMsgType.ERROR:
                    break


asyncio.run(run())

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