jupyters3 0.0.8

Jupyter Notebook Contents Manager for AWS S3

Jupyter S3

Jupyter Notebook Contents Manager for AWS S3.

Installation

pip install jupyters3

Configuration

To configure Jupyter Notebook to use JupterS3, you can add the following to your notebook config file.

from jupters3 import JupyterS3
c = get_config()
c.NotebookApp.contents_manager_class = JupyterS3

You must also set the following settings on c.JupyterS3 in your config file. None of them are optional.

Setting	Description	Example
aws_region	The AWS region in which the bucket is located	'eu-west-1'
aws_host	The hostname of the AWS S3 API. Typically, this is of the form <bucket-name>.s3.<aws-region>.amazonaws.com.	'my-example-bucket.s3.eu-west-1.amazonaws.com'
aws_access_key_id	The ID of the AWS access key used to sign the requests to the AWS S3 API.	ommitted
aws_secret_access_key	The secret part of the AWS access key used to sign the requests to the AWS S3 API.	ommitted
prefix	The prefix to all keys used to store notebooks and checkpoints. This can be the empty string ''. If non-empty, typically this would end in a forward slash /.	'some-prefix/'

Differences from S3Contents

• There are no extra dependencies over those already required for Jupyter Notebook. Specifically, there is not a virtual filesystem abstraction used internally.

• Checkpoints are also saved to S3, under the key <file_name>/.checkpoints/.

• Multiple checkpoints are saved.

• The event loop is mostly not blocked during requests to S3. There are some exceptions due to Jupyter Notebook expecting certain requests to block.

• Requests to S3 are host-style, using a custom domain for the bucket, rather that path-style.

• AWS roles are not supported, although this may change.