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Python Program: Maximum connection Pool size analysis


Write a Python program that sets the maximum connection pool size and observe how it affects the number of simultaneous connections made. Use urllib3.

Sample Solution:

Python Code :

import urllib3

# Set the maximum connection pool size
max_pool_size = 5

# Create a PoolManager with the specified maximum connection pool size
http = urllib3.PoolManager(maxsize=max_pool_size)

# URLs to make requests to (example URLs)
urls = [
    'https://example.com/api/endpoint1',
    'https://example.com/api/endpoint2',
    'https://example.com/api/endpoint3',
    'https://example.com/api/endpoint4',
    'https://example.com/api/endpoint5',
    'https://example.com/api/endpoint6',
    'https://example.com/api/endpoint7',
]

# Make requests to the URLs and observe the number of simultaneous connections
for url in urls:
    response = http.request('GET', url)
    print(f"Request to {url} completed with status code: {response.status}")

# Close the connection pool
http.clear()

Sample Output:

Request to https://example.com/api/endpoint1 completed with status code: 404
Request to https://example.com/api/endpoint2 completed with status code: 404
Request to https://example.com/api/endpoint3 completed with status code: 404
Request to https://example.com/api/endpoint4 completed with status code: 404
Request to https://example.com/api/endpoint5 completed with status code: 404
Request to https://example.com/api/endpoint6 completed with status code: 404
Request to https://example.com/api/endpoint7 completed with status code: 404

Explanation:

Here's a brief explanation of the above Python urllib3 library code:

  • Setting Maximum Connection Pool Size: The max_pool_size variable specifies the maximum size of the connection pool.
  • Creating PoolManager: A PoolManager object is created using urllib3.PoolManager(maxsize=max_pool_size) with the specified maximum connection pool size.
  • Defining URLs: A list of example URLs ('urls') is defined to simulate requests to different endpoints.
  • Making Requests: A loop iterates through the URLs, and for each URL, a GET request is made using http.request('GET', url).
  • Observing Connections: The status code of each request is printed to observe how many connections are made simultaneously based on the maximum pool size.
  • Closing Connection Pool: Finally, the connection pool is cleared using "http.clear()" to release any resources associated with it.

Flowchart:

Flowchart: Python Program: Maximum connection Pool size analysis.

Python Code Editor :

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