Menu
Article Security Check

python requests post in parallel

Narkw Brahma

Narkw Brahma

• 1 min read

Python requests post in parallel

Python requests is a popular library for making HTTP requests in Python. It provides a simple API for making HTTP requests such as GET, POST, PUT, DELETE, etc. One of the requirements for most web applications is to make multiple HTTP requests simultaneously. This is where parallelization comes in handy.

Using ThreadPoolExecutor

One of the ways to make multiple HTTP requests in parallel is by using ThreadPoolExecutor from the concurrent.futures module. Here is an example:


import requests
from concurrent.futures import ThreadPoolExecutor

def post(url):
    data = {'key': 'value'}
    response = requests.post(url, data=data)
    return response

urls = ['https://url1.com', 'https://url2.com', 'https://url3.com']

with ThreadPoolExecutor(max_workers=3) as executor:
    results = executor.map(post, urls)

for result in results:
    print(result.json())

In the above example, we define a function post that makes a POST request to the given URL with some data. Then we define a list of URLs that we want to make POST requests to. We use ThreadPoolExecutor to create a pool of 3 threads to execute the post function for each URL in the urls list. Finally, we iterate over the results and print the JSON response for each request.

Using multiprocessing

Another way to make multiple HTTP requests in parallel is by using the multiprocessing module. Here is an example:


import requests
from multiprocessing import Pool

def post(url):
    data = {'key': 'value'}
    response = requests.post(url, data=data)
    return response

urls = ['https://url1.com', 'https://url2.com', 'https://url3.com']

with Pool(processes=3) as pool:
    results = pool.map(post, urls)

for result in results:
    print(result.json())

In the above example, we define a function post that makes a POST request to the given URL with some data. Then we define a list of URLs that we want to make POST requests to. We use the Pool function from the multiprocessing module to create a pool of 3 processes to execute the post function for each URL in the urls list. Finally, we iterate over the results and print the JSON response for each request.

Both of these methods allow you to make multiple HTTP requests in parallel, but they have their own pros and cons. For example, ThreadPoolExecutor is more efficient for I/O-bound tasks, while multiprocessing is more efficient for CPU-bound tasks.

Share