I'm trying to do a "hello world" with new boto3 client for AWS.
The use-case I have is fairly simple: get object from S3 and save it to the file.
In boto 2.X I would do it like this:
import boto
key = boto.connect_s3().get_bucket('foo').get_key('foo')
key.get_contents_to_filename('/tmp/foo')
In boto 3 . I can't find a clean way to do the same thing, so I'm manually iterating over the "Streaming" object:
import boto3
key = boto3.resource('s3').Object('fooo', 'docker/my-image.tar.gz').get()
with open('/tmp/my-image.tar.gz', 'w') as f:
chunk = key['Body'].read(1024*8)
while chunk:
f.write(chunk)
chunk = key['Body'].read(1024*8)
or
import boto3
key = boto3.resource('s3').Object('fooo', 'docker/my-image.tar.gz').get()
with open('/tmp/my-image.tar.gz', 'w') as f:
for chunk in iter(lambda: key['Body'].read(4096), b''):
f.write(chunk)
And it works fine. I was wondering is there any "native" boto3 function that will do the same task?
There is a customization that went into Boto3 recently which helps with this (among other things). It is currently exposed on the low-level S3 client, and can be used like this:
s3_client = boto3.client('s3')
open('hello.txt').write('Hello, world!')
# Upload the file to S3
s3_client.upload_file('hello.txt', 'MyBucket', 'hello-remote.txt')
# Download the file from S3
s3_client.download_file('MyBucket', 'hello-remote.txt', 'hello2.txt')
print(open('hello2.txt').read())
These functions will automatically handle reading/writing files as well as doing multipart uploads in parallel for large files.
Note that s3_client.download_file
won't create a directory. It can be created as pathlib.Path('/path/to/file.txt').parent.mkdir(parents=True, exist_ok=True)
.