CachingProxy magically records usage of arbitrary objects and allows you to replay the same behavior later (with serializable representation that can be stored on disk)
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Proxy for interacting with something (which is slow and otherwise unwieldy to change) recording all the interactions and then replaying that without interacting with the original object.

Let's say you have some code that talks to launchpad and generates a report. Each launchpad call / attribute reference is slow as it has to go across the wire. The report you are writing needs some changes and has no infrastructure for working against canned data.

Let's say you have some code that uses launchpad in the use_lp() function:

def use_lp(lp):
    print("Launchpad object is", repr(lp))
    print("Link to first bug is", lp.bugs[1].web_link)

Normally each time you call that it will take forever (longer than 30ms) to run so iterating on it is unwieldy and annoying. Instead of doing it that way you can record the interaction once, save it to a file and then keep editing use_lp() to do what you want. As long as you are still using all the proxied objects the same way you can iterate quickly.

# Use fake repr() so that none of the proxy is visible
# Record everything in memory but don't use it

# Create a real launchpad object and wrap it in a proxy 
from launchpadlib.launchpad import Launchpad
lp = CachingProxy(Launchpad.login_anonymously("testapp"))

# Use launchpad object somehow

The cache can be saved on disk and restored later, it does not depend on the classes in your code in any way:

# Save the cache
cache = CachingProxy.to_cache(lp)

# Create a dummy from the cache
lp2 = CachingProxy.from_cache(cache)

Now you can use a fake object created from the cache and call your functions again:

# Switch to pure mode -- we're working on fake objects anyway

# Use the fake launchpad object in the same way as before