Convinient access to threadlocal boto3 clients and resources.
Suppose you have non-trivial serverless project with several lambdas and some shared common code. Normally you would want to create used resources outside of the lambda handler so that they don't need to be recreated during a warm start of the lambda. Also you might want to share the created resources in different parts of the code. This might lead to you creating lots of resources that end up not being needed on the actual code path that gets taken by the lambda function.
With threadlocal-aws the resources are created as a side effect of the first call on the code path and subsequent calls use the same resources from a threadlocal cache. The arguments to the functions are used as cache keys so you can trivially use clients that interact with different regions for example just by passing the region to the threadlocal function you use and a matching session will be found.
Different accounts can be used by creating sessions towards the accounts and passing them to the threadlocal function.
All of the created resources are stored for the lifetime of the program so it is only a good idea to use in places where the lifetime of the program is limited. Also an environment with lots of threads combined with a long lifetime like some web development frameworks is not a good idea.
Lots of boto3 aws modules have resources. For example easy to iterate all instances:
from threadlocal_aws.resources import ec2
for instance in ec2().instances.all():
print(instance.id)You can get an item from dynamo with just two lines of code:
from threadlocal_aws.resources import dynamodb_Table as table
dynamo_resp = table("my-table", region="eu-central-1").get_item(Key="foo#bar#123")Or iterate all objects in a bucket:
from threadlocal_aws.resources import s3_Bucket as bucket
for s3_obj in bucket("my-unique-bucket").objects.all():
print(s3_obj.key)from threadlocal_aws.clients import ec2
instance = ec2().describe_instances(InstanceIds=["i-0fd31cg97d77ddfff"])