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python requests cache

Narkw Brahma

Narkw Brahma

• 2 min read

Python Requests Cache

If you are building a web scraping tool or any other web-based application using Python, you may often find yourself making repeated requests to the same webpages. This can lead to slow performance and a waste of bandwidth. One way to improve performance is to use caching in Python Requests.

What is Caching?

Caching is the process of storing frequently accessed data in memory or on disk so that it can be quickly retrieved when needed again. In the context of web applications, caching can be used to store the responses of HTTP requests in memory, so that if the same request is made again, the response can be retrieved from the cache instead of making a new request to the server.

How to Implement Caching in Python Requests?

The Python Requests library provides built-in support for caching using the cachecontrol module. To use caching in your requests, you need to install cachecontrol by running:

pip install cachecontrol

Once you have installed cachecontrol, you can use it to set up a cache for your requests. Here's an example:

import requests
from cachecontrol import CacheControl

session = requests.session()
cached_session = CacheControl(session)

url = 'https://www.example.com/'

# First request (not cached)
response = cached_session.get(url)

# Second request (cached)
response = cached_session.get(url)

When you run the above code, the first request to the URL will be made as usual. However, on the second request, the response will be retrieved from the cache instead of making a new request to the server.

Types of Cache Backend

The cache backend is responsible for storing and retrieving cached responses. There are different types of cache backends available, including:

  • MemoryCache: Stores cache in memory. This is the default backend used by CacheControl.
  • FileCache: Stores cache on disk.
  • RedisCache: Stores cache in Redis, a popular in-memory data store.

You can choose the backend you want to use by passing it as an argument when creating the CacheControl object. Here's an example:

import requests
from cachecontrol import CacheControl
from cachecontrol.caches import FileCache

session = requests.session()
cached_session = CacheControl(session, cache=FileCache('.web_cache'))

url = 'https://www.example.com/'

# First request (not cached)
response = cached_session.get(url)

# Second request (cached)
response = cached_session.get(url)

In the above example, we are using the FileCache backend to store the cache on disk in the '.web_cache' folder.

Cache Expiration

By default, CacheControl will cache responses indefinitely. However, you can set an expiration time for the cache entries to avoid storing stale data. Here's an example:

import requests
from cachecontrol import CacheControl
from datetime import timedelta

session = requests.session()
cached_session = CacheControl(session, cache=FileCache('.web_cache'), 
                              heuristic=timedelta(days=7))

url = 'https://www.example.com/'

# First request (not cached)
response = cached_session.get(url)

# Second request (cached)
response = cached_session.get(url)

In this example, we are setting the cache expiration time to 7 days using the 'heuristic' argument.

Conclusion

Caching responses can significantly improve the performance of your web-based applications. By using the CacheControl module in Python Requests, you can easily implement caching in your requests and improve performance. Just keep in mind that caching can lead to stale data, so make sure to set an appropriate expiration time for your cache entries.

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