S3FS is a PyFilesystem interface to Amazon S3 cloud storage.
As a PyFilesystem concrete class, S3FS allows you to work with S3 in the same way as any other supported filesystem.
You can install S3FS from pip as follows:
pip install fs-s3fs
Open an S3FS by explicitly using the constructor:
from fs_s3fs import S3FS s3fs = S3FS('mybucket')
Or with a FS URL:
from fs import open_fs s3fs = open_fs('s3://mybucket')
To download files from an S3 bucket, open a file on the S3
filesystem for reading, then write the data to a file on the local
filesystem. Here's an example that copies a file example.mov from
S3 to your HD:
from fs.tools import copy_file_data with s3fs.open('example.mov', 'rb') as remote_file: with open('example.mov', 'wb') as local_file: copy_file_data(remote_file, local_file)
Although it is preferable to use the higher-level functionality in the
fs.copy module. Here's an example:
from fs.copy import copy_file copy_file(s3fs, 'example.mov', './', 'example.mov')
You can upload files in the same way. Simply copy a file from a source filesystem to the S3 filesystem. See Moving and Copying for more information.
S3 objects have additional properties, beyond a traditional
filesystem. These options can be set using the upload_args
and download_args properties. which are handed to upload
and download methods, as appropriate, for the lifetime of the
filesystem instance.
For example, to set the cache-control header of all objects
uploaded to a bucket:
import fs, fs.mirror s3fs = S3FS('example', upload_args={"CacheControl": "max-age=2592000", "ACL": "public-read"}) fs.mirror.mirror('/path/to/mirror', s3fs)
see the Boto3 docs for more information.
acl and cache_control are exposed explicitly for convenience, and can be used in URLs.
It is important to URL-Escape the cache_control value in a URL, as it may contain special characters.
import fs, fs.mirror with open fs.open_fs('s3://example?acl=public-read&cache_control=max-age%3D2592000%2Cpublic') as s3fs fs.mirror.mirror('/path/to/mirror', s3fs)
You can get a public URL to a file on a S3 bucket as follows:
movie_url = s3fs.geturl('example.mov')