![]() ![]() Stick await infront of methods to make them async, e.g. Not all methods are tested but we aim to test the majority ofĭue 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 This is a non-exuastive list of what tests aiobotocore runs against AWS services. 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_client Supported AWS Services _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. create_client ( 's3' )) async def _aexit_ ( self, exc_type, exc_val, exc_tb ): await self. _s3_client = None async def _aenter_ ( self ): session = AioSession () self. run_until_complete ( go ()) Context Manager Examples from contextlib import AsyncExitStack from ssion import AioSession # How to use in existing context manager class Manager : def _init_ ( self ): self. delete_object ( Bucket = bucket, Key = key ) print ( resp ) loop = asyncio. get ( 'Contents', ): print ( c ) # delete object from s3 resp = await client. ![]() paginate ( Bucket = bucket, Prefix = folder ): for c in result. get_paginator ( 'list_objects' ) async for result in paginator. read () = data # list s3 objects using paginator paginator = client. get_object ( Bucket = bucket, Key = key ) # this will ensure the connection is correctly re-used/closed async with response as stream : assert await stream. get_object_acl ( Bucket = bucket, Key = key ) print ( resp ) # get object from s3 response = await client. put_object ( Bucket = bucket, Key = key, Body = data ) print ( resp ) # getting s3 object properties of file we just uploaded resp = await client. 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. format ( folder, filename ) session = get_session () async with session. Install $ pip install aiobotocore Basic Example import asyncio from ssion import get_session AWS_ACCESS_KEY_ID = "xxx" AWS_SECRET_ACCESS_KEY = "xxx" async def go (): bucket = 'dataintake' filename = 'dummy.bin' folder = 'aiobotocore' key = ' '. ![]() This library is a mostly full featured asynchronous version of botocore. ![]() O.Async client for amazon services using botocore and aiohttp/ asyncio. While(o.outWidth / scale / 2 >= REQUIRED_SIZE & Decodes image and scales it to reduce memory consumptionīitmapFactory.Options o = new BitmapFactory.Options() īcodeStream(new FileInputStream(f), null, o) Then it finds the best inSampleSize value, it should be a power of 2, and finally the image is decoded. First it reads image size without decoding the content itself. This inSampleSize option reduces memory consumption. To fix the OutOfMemory error, you should do something like this: BitmapFactory.Options options = new BitmapFactory.Options() īitmap preview_bitmap = codeStream(is, null, options) ![]()
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