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python requests multithreading

Narkw Brahma

Narkw Brahma

• 1 min read

Python Requests Multithreading

As a programmer, I often encounter scenarios where I need to make multiple HTTP requests to the same or different servers. In such cases, multithreading can be a useful technique to speed up the process. Python Requests library is a popular choice for making HTTP requests in Python, and it provides built-in support for multithreading.

Using Python Requests with Threads

Python's threading module provides a way to create and manage threads in Python. To use Python Requests library with threads, we can simply create multiple threads and make HTTP requests in each thread. Here's an example:


import requests
import threading

def make_request(url):
    response = requests.get(url)
    print(response.status_code)

urls = [
    "https://www.google.com",
    "https://www.github.com",
    "https://www.python.org",
]

threads = []

for url in urls:
    thread = threading.Thread(target=make_request, args=(url,))
    thread.start()
    threads.append(thread)

for thread in threads:
    thread.join()

In this example, we define a function make_request that takes a URL as an argument and makes an HTTP GET request to that URL using the Requests library. Then we create multiple threads, each calling the make_request function with a different URL. Finally, we wait for all the threads to finish using the join() method.

Using ThreadPoolExecutor

Python's concurrent.futures module provides a high-level interface for asynchronously executing functions using threads or processes. The ThreadPoolExecutor class can be used to create a pool of threads and submit functions to be executed in the pool. Here's an example:


import requests
from concurrent.futures import ThreadPoolExecutor

def make_request(url):
    response = requests.get(url)
    print(response.status_code)

urls = [
    "https://www.google.com",
    "https://www.github.com",
    "https://www.python.org",
]

with ThreadPoolExecutor(max_workers=3) as executor:
    for url in urls:
        executor.submit(make_request, url)

In this example, we define the same make_request function as before, and create a ThreadPoolExecutor with a maximum of 3 threads. We then submit each URL to the executor using the submit() method, which returns a future object that can be used to retrieve the result of the function call.

Conclusion

Using multithreading with Python Requests can be a powerful technique to speed up HTTP requests. We can use Python's built-in threading module, or the concurrent.futures module, to create and manage threads in Python. Both approaches are effective, and the choice depends on the specific use case and personal preference.

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