node-fetchvspycurl

MIT 241 10 8,860

553.6 million (month) Dec 28 2012 3.3.2(2023-11-30 14:10:12 ago)

1,147 10 6 LGPL-2.1

Feb 25 2003 5.2 million (month) 7.45.7(2025-09-24 13:35:56 ago)

node-fetch is a lightweight library that provides a fetch()-like API for making HTTP requests in Node.js. It is a light-weight implementation of the Fetch API, which is mostly compatible with the browser's version.

node-fetch is primarily known as almost identical package fetch() is included in web browsers so it shares the same use common API. It's great starting point for people coming from front-end environment.

PycURL is a Python interface to libcurl, a multi-protocol file transfer library written in C. PycURL allows developers to use a variety of network protocols in their Python programs, including HTTP, FTP, SMTP, POP3, and many more.

PycURL is often used in web scraping, data analysis, and automation tasks, as it allows developers to send and receive data over the internet. It can be used to perform various types of requests, such as GET, POST, PUT, and DELETE, and can also handle file uploads and downloads, cookies, and redirects.

One of the key features of PycURL is its support for SSL and proxy servers, which allows developers to securely transfer data over the internet and work around any network restrictions. PycURL also supports a wide range of authentication methods, such as Basic, Digest, and NTLM, and allows developers to easily set custom headers and query parameters.

Just like cURL itself, PycURL is also highly configurable and allows for fine-grained control over various aspects of the transfer, such as timeouts, retries, buffer sizes, and verbosity levels. Additionally, PycURL also provides easy access to the underlying libcurl library, which allows developers to access advanced functionality that is not exposed by the PycURL API.

It's important to note that PycURL is a wrapper around the libcurl library and therefore provides the same functionality and performance as libcurl.

Main strengths of PycURL is that it uses cURL which is one of the most feature rich low-level http clients. The downside is that it's a very low-level client (see the examples below) with complex API making use in web scraping very difficult and niche.

Highlights

popular

uses-curlhttp2multi-partresponse-streaminghttp-proxy

Example Use

```javascript const fetch = require('node-fetch'); // fetch supports both Promises and async/await fetch('http://httpbin.org/get') .then(res => res.text()) .then(body => console.log(body)) .catch(err => console.error(err)); const response = await fetch('http://httpbin.org/get'); // for concurrent scraping Promise.all can be used const results = await Promise.all([ fetch('http://httpbin.org/html'), fetch('http://httpbin.org/html'), fetch('http://httpbin.org/html'), ]) // POST requests await fetch('http://httpbin.org/post', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ name: 'John Doe' }), }) // Proxy use: const agent = new https.Agent({ rejectUnauthorized: false, proxy: { host: 'proxy.example.com', port: 8080 } }); await fetch('https://httpbin.org/ip', { agent }) // setting headers and cookies const headers = new fetch.Headers(); headers.append('Cookie', 'myCookie=123'); headers.append('X-My-Header', 'myValue'); await fetch('https://httpbin.org/headers', { headers }) ```

```python import pycurl from io import BytesIO buf = BytesIO() headers = BytesIO() c = pycurl.Curl() c.setopt(c.HTTP_VERSION, c.CURL_HTTP_VERSION_2_0) # set to use http2 # set proxy c.setopt(c.PROXY, 'http://proxy.example.com:8080') c.setopt(c.PROXYUSERNAME, 'username') c.setopt(c.PROXYPASSWORD, 'password') # make a request c.setopt(c.URL, 'https://httpbin.org/get') c.setopt(c.WRITEFUNCTION, buf.write) # where to save response body c.setopt(c.HEADERFUNCTION, headers.write) # where to save response headers # to make post request enable POST option: # c.setopt(c.POST, 1) # c.setopt(c.POSTFIELDS, 'key1=value1&key2=value2') c.perform() # send request # read response data = buf.getvalue().decode() headers = headers.getvalue().decode() # headers as a string headers = dict([h.split(': ') for h in headers.splitlines() if ': ' in h]) # headers as a dict c.close() # multiple concurrent requests can be made using CurlMulti object: # Create a CurlMulti object multi = pycurl.CurlMulti() # Set the number of maximum connections multi.setopt(pycurl.MAXCONNECTS, 5) # Create a list to store the Curl objects curls = [] # Add the first request c1 = pycurl.Curl() c1.setopt(c1.URL, 'https://httpbin.org/get') c1.setopt(c1.WRITEFUNCTION, BytesIO().write) multi.add_handle(c1) curls.append(c1) # Add the second request c2 = pycurl.Curl() c2.setopt(c2.URL, 'https://httpbin.org/') c2.setopt(c2.WRITEFUNCTION, BytesIO().write) multi.add_handle(c2) curls.append(c2) # Start the requests while True: ret, _ = multi.perform() if ret != pycurl.E_CALL_MULTI_PERFORM: break # Close the connections for c in curls: multi.remove_handle(c) c.close() ```

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