Async client for amazon services using botocore and aiohttp/asyncio.
This library is a mostly full featured asynchronous version of botocore.
$ pip install aiobotocore
import asyncio
from aiobotocore.session import get_session
AWS_ACCESS_KEY_ID = "xxx"
AWS_SECRET_ACCESS_KEY = "xxx"
async def go():
bucket = 'dataintake'
filename = 'dummy.bin'
folder = 'aiobotocore'
key = '{}/{}'.format(folder, filename)
session = get_session()
async with session.create_client('s3', region_name='us-west-2',
aws_secret_access_key=AWS_SECRET_ACCESS_KEY,
aws_access_key_id=AWS_ACCESS_KEY_ID) as client:
# upload object to amazon s3
data = b'\x01'*1024
resp = await client.put_object(Bucket=bucket,
Key=key,
Body=data)
print(resp)
# getting s3 object properties of file we just uploaded
resp = await client.get_object_acl(Bucket=bucket, Key=key)
print(resp)
# get object from s3
response = await client.get_object(Bucket=bucket, Key=key)
# this will ensure the connection is correctly re-used/closed
async with response['Body'] as stream:
assert await stream.read() == data
# list s3 objects using paginator
paginator = client.get_paginator('list_objects')
async for result in paginator.paginate(Bucket=bucket, Prefix=folder):
for c in result.get('Contents', []):
print(c)
# delete object from s3
resp = await client.delete_object(Bucket=bucket, Key=key)
print(resp)
loop = asyncio.get_event_loop()
loop.run_until_complete(go())from contextlib import AsyncExitStack
from aiobotocore.session import AioSession
# How to use in existing context manager
class Manager:
def __init__(self):
self._exit_stack = AsyncExitStack()
self._s3_client = None
async def __aenter__(self):
session = AioSession()
self._s3_client = await self._exit_stack.enter_async_context(session.create_client('s3'))
async def __aexit__(self, exc_type, exc_val, exc_tb):
await self._exit_stack.__aexit__(exc_type, exc_val, exc_tb)
# How to use with an external exit_stack
async def create_s3_client(session: AioSession, exit_stack: AsyncExitStack):
# Create client and add cleanup
client = await exit_stack.enter_async_context(session.create_client('s3'))
return client
async def non_manager_example():
session = AioSession()
async with AsyncExitStack() as exit_stack:
s3_client = await create_s3_client(session, exit_stack)
# do work with s3_clientThis is a non-exuastive list of what tests aiobotocore runs against AWS services. Not all methods are tested but we aim to test the majority of commonly used methods.
| Service | Status |
|---|---|
| S3 | Working |
| DynamoDB | Basic methods tested |
| SNS | Basic methods tested |
| SQS | Basic methods tested |
| CloudFormation | Stack creation tested |
| Kinesis | Basic methods tested |
Due to the way boto3 is implemented, its highly likely that even if services are not listed above that you can take any boto3.client('service') and stick await infront of methods to make them async, e.g. await client.list_named_queries() would asynchronous list all of the named Athena queries.
If a service is not listed here and you could do with some tests or examples feel free to raise an issue.
Make sure you have development requirements installed and your amazon key and secret accessible via environment variables:
$ cd aiobotocore $ export AWS_ACCESS_KEY_ID=xxx $ export AWS_SECRET_ACCESS_KEY=xxx $ pipenv sync --dev
Execute tests suite:
$ py.test -v tests
https://groups.google.com/forum/#!forum/aio-libs
awscli depends on a single version of botocore, however aiobotocore only supports a specific range of botocore versions. To ensure you install the latest version of awscli that your specific combination or aiobotocore and botocore can support use:
pip install -U aiobotocore[awscli]