Making the Most of Proxies in aiohttp for Python

When making requests with the popular Python aiohttp library, proxies can be useful for a variety of reasons - masking your identity, load balancing, or circumventing geographic restrictions.

In this guide, we'll cover the ins and outs of working with proxies in aiohttp, including some handy tricks to make proxy integration smooth and efficient.

Why Use Proxies with aiohttp?

Here are some of the main reasons for using proxies with the aiohttp library:

Enabling Proxies in aiohttp

The first step is installing aiohttp along with the aiohttp-proxy package which helps manage and configure proxies:

pip install aiohttp aiohttp-proxy

Then we can enable a proxy using the ProxyConnector class:

import aiohttp
from aiohttp_proxy import ProxyConnector

async with aiohttp.ClientSession() as session:
    proxy = "http://user:pass@192.168.1.42:8080"
    connector = ProxyConnector(
        proxy="http://user:pass@192.168.1.42:8080"
    ) 
    session = aiohttp.ClientSession(connector=connector)

Any requests we make from this session will now be routed through the proxy server we specified.

The ProxyConnector handles proxy auth for us automatically if the proxy URL contains a username/password component.

Using a Pool of Proxies

To avoid overloading a single proxy, we can create a pool of proxies to choose from randomly on each request:

proxy_pool = [
  "http://user:pass@192.168.1.42:8080",
  "http://user:pass@198.51.100.205:8080",
  "http://user:pass@176.121.2.169:4145"
]

# Choose a random proxy from pool for each request
proxy = random.choice(proxy_pool)  
connector = ProxyConnector(proxy=proxy)
async with aiohttp.ClientSession(connector=connector) as session:
  # Make request
  await session.get("http://www.example.com")

This spreads our requests across multiple proxy IPs.

Handling Proxy Errors

It's common for proxies to sometimes fail or respond with errors. We can implement some error handling to retry with a fresh proxy:

max_errors = 10
num_errors = 0

while True:
  proxy = get_random_proxy() # Get random proxy  
  try:
    async with aiohttp.ClientSession(connector=ProxyConnector(proxy=proxy)) as session:
      await make_request(session)
    break # If no errors break loop to stop retrying

  except aiohttp.ClientConnectorError:
    if num_errors > max_errors:
       raise Exception("Too many proxy errors")

    num_errors += 1
    continue # Try again with a new proxy

This automatically attempts a new proxy if we run into connectivity issues.

Caching Proxy IPs

To avoid needing to specify the same proxies repeatedly, we can create a simple proxy cache that stores a collection of working proxies we find:

from aiohttp_proxy import ProxyConnector
import aiofiles

proxy_cache = []

async def load_proxy_cache():
  async with aiofiles.open('proxies.txt') as f:
    proxy_cache.extend([line.strip() for line in await f.readlines()])

async def save_proxy(proxy):
  async with aiofiles.open('proxies.txt', 'a') as f:   
    await f.write(f"{proxy}\n")

# Save newly found working proxies  
async with aiohttp.ClientSession(connector=ProxyConnector(proxy=proxy)) as session:
  await save_proxy(proxy) 

Now we have a growing list of proxies we can rely on without needing to research and find new ones!

Final Thoughts

That covers some of the key concepts for unlocking the capabilities of proxies within the aiohttp library.

Properly using proxies allows you to build robust applications that carefully control and distribute web requests while maintaining performance and reliability.

As you integrate proxies, keep in mind factors like error handling, caching working proxies safely, and rotating amongst a pool of proxies instead of overusing a single source.

By mastering proxies in aiohttp, you can scrape and interact with more websites in a resilient and efficient way!