Clients and resources should be cached

When creating a vanilla client like session = boto3.Session(); s3 = session.client("s3"), the client returned is not cached. I can’t see any reason why this client would be different between different calls, and the time to create a client can be quite long. Especially given that it’s generally better to pass a session around than the clients directly, it’d be nice if the client was cached on first load.

It wouldn’t use caching if credentials or a Config object were passed, and it could maybe even have a single cache entry per service. Maybe it could be better solved with more caching in botocore.

It’s accomplishable today with the standard library’s functools, though with a “developer beware” label.

import functools
import boto3

boto3.Session.client = functools.cache(boto3.Session.client)
boto3.Session.resource = functools.cache(boto3.Session.resource)

[mbelang]

Yeah read your article couple weeks ago and I didn’t realize I was talking to you. What you explain is pretty clean and I do understand what I need to do now 😃

[benkehoe]

@mbelang The session itself represents configuration and credentials. It doesn’t need caching internal to boto3, but it’s intended to be passed around in your code wherever clients/resources are needed (and are intended to use the same config/credentials), i.e., “cached” in your code. The refreshable credentials for web identity, for example, are refreshed by the session for any client created on the session. I wrote an explainer on why to use sessions. For example, when you create a library that makes AWS API calls, it should take an optional session as input (creating one itself using boto3.Session() if none is provided), and then get the appropriate client from the session. This pattern can lead to clients being created on the session multiple times in different places, which is why client caching would be beneficial.