An S3 and GCS backed ContentsManager implementation for Jupyter.
It aims to a be a transparent, drop-in replacement for Jupyter standard filesystem-backed storage system. With this implementation of a Jupyter Contents Manager you can save all your notebooks, regular files, directories structure directly to a S3/GCS bucket, this could be on AWS/GCP or a self hosted S3 API compatible like minio.
Write access (valid credentials) to an S3/GCS bucket, this could be on AWS/GCP or a self hosted S3 like minio.
$ pip install s3contents
Edit ~/.jupyter/jupyter_notebook_config.py based on the backend you want to
based on the examples below. Replace credentials as needed.
from s3contents import S3ContentsManager
c = get_config()
# Tell Jupyter to use S3ContentsManager for all storage.
c.NotebookApp.contents_manager_class = S3ContentsManager
c.S3ContentsManager.access_key_id = "{{ AWS Access Key ID / IAM Access Key ID }}"
c.S3ContentsManager.secret_access_key = "{{ AWS Secret Access Key / IAM Secret Access Key }}"
c.S3ContentsManager.session_token = "{{ AWS Session Token / IAM Session Token }}"
c.S3ContentsManager.bucket = "{{ S3 bucket name }}"
# Optional settings:
c.S3ContentsManager.prefix = "this/is/a/prefix/on/the/s3/bucket"
c.S3ContentsManager.sse = "AES256"
c.S3ContentsManager.signature_version = "s3v4"
c.S3ContentsManager.init_s3_hook = init_function # See AWS key refreshExample for play.minio.io:9000:
from s3contents import S3ContentsManager
c = get_config()
# Tell Jupyter to use S3ContentsManager for all storage.
c.NotebookApp.contents_manager_class = S3ContentsManager
c.S3ContentsManager.access_key_id = "Q3AM3UQ867SPQQA43P2F"
c.S3ContentsManager.secret_access_key = "zuf+tfteSlswRu7BJ86wekitnifILbZam1KYY3TG"
c.S3ContentsManager.endpoint_url = "http://play.minio.io:9000"
c.S3ContentsManager.bucket = "s3contents-demo"
c.S3ContentsManager.prefix = "notebooks/test"It also possible to use IAM Role-based access to the S3 bucket from an Amazon EC2 instance.
To do that just leave access_key_id and secret_access_key set to their default values (None),
and ensure that the EC2 instance has an IAM role which provides sufficient permissions for the bucket and the operations necessary.
The optional init_s3_hook configuration can be used to enable AWS key rotation (described here and here) as follows:
from s3contents import S3ContentsManager
from botocore.credentials import RefreshableCredentials
from botocore.session import get_session
import botocore
import boto3
from configparser import ConfigParser
def refresh_external_credentials():
config = ConfigParser()
config.read('/home/jovyan/.aws/credentials')
return {
"access_key": config['default']['aws_access_key_id'],
"secret_key": config['default']['aws_secret_access_key'],
"token": config['default']['aws_session_token'],
"expiry_time": config['default']['aws_expiration']
}
session_credentials = RefreshableCredentials.create_from_metadata(
metadata = refresh_external_credentials(),
refresh_using = refresh_external_credentials,
method = 'custom-refreshing-key-file-reader'
)
def make_key_refresh_boto3(this_s3contents_instance):
refresh_session = get_session() # from botocore.session
refresh_session._credentials = session_credentials
my_s3_session = boto3.Session(botocore_session=refresh_session)
this_s3contents_instance.boto3_session = my_s3_session
# Tell Jupyter to use S3ContentsManager for all storage.
c.NotebookApp.contents_manager_class = S3ContentsManager
c.S3ContentsManager.init_s3_hook = make_key_refresh_boto3from s3contents import GCSContentsManager
c = get_config(
c.NotebookApp.contents_manager_class = GCSContentsManager
c.GCSContentsManager.project = "{{ your-project }}"
c.GCSContentsManager.token = "~/.config/gcloud/application_default_credentials.json"
c.GCSContentsManager.bucket = "{{ GCP bucket name }}"Note that the file ~/.config/gcloud/application_default_credentials.json assumes a posix system
when you did gcloud init
To access local file as well as remote files in S3 you can use hybridcontents.
First install it:
pip install hybridcontents
Use a configuration similar to this:
from s3contents import S3ContentsManager
from hybridcontents import HybridContentsManager
from IPython.html.services.contents.filemanager import FileContentsManager
c = get_config()
c.NotebookApp.contents_manager_class = HybridContentsManager
c.HybridContentsManager.manager_classes = {
# Associate the root directory with an S3ContentsManager.
# This manager will receive all requests that don"t fall under any of the
# other managers.
"": S3ContentsManager,
# Associate /directory with a FileContentsManager.
"local_directory": FileContentsManager,
}
c.HybridContentsManager.manager_kwargs = {
# Args for root S3ContentsManager.
"": {
"access_key_id": "{{ AWS Access Key ID / IAM Access Key ID }}",
"secret_access_key": "{{ AWS Secret Access Key / IAM Secret Access Key }}",
"bucket": "{{ S3 bucket name }}",
},
# Args for the FileContentsManager mapped to /directory
"local_directory": {
"root_dir": "/Users/danielfrg/Downloads",
},
}While there are some implementations of this already: (s3nb or s3drive), I wasn't able to make them work in newer versions of Jupyter Notebook. This aims to be a more tested version and it's based on PGContents.
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