cannerflow-jupyter-contents 1.2.0

Azure Contents Manager for Jupyter

CannerFlow Jupyter Contents

An S3, GCS, Blob backed ContentsManager implementation for Jupyter. Based on s3Contens

Installation

$ pip install cannerflow-jupyter-contents

Jupyter config

Edit ~/.jupyter/jupyter_notebook_config.py based on the backend you want to based on the examples below. Replace credentials as needed.

AWS S3

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 refresh

Example 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"

AWS EC2 role auth setup

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.

AWS key refresh

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_boto3

GCP Cloud Storage

from 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

Azure blob storage with SAS

import os

from s3contents import BlobContentsManager from s3contents.blobmanager import auth_shared_access_signature token = auth_shared_access_signature( account_key=os.environ["AZURE_ACCOUNT_KEY"], account_name=os.environ["AZURE_ACCOUNT_NAME"] ) c.NotebookApp.contents_manager_class = BlobContentsManager c.BlobContentsManager.credential=token c.BlobContensManager.account_key=os.environ["AZURE_ACCOUNT_KEY"] c.BlobContentsManager.container_name=os.environ["AZURE_CONTAINER_NAME"] c.BlobContentsManager.account_name=os.environ["AZURE_ACCOUNT_NAME"]

Access local files

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",
    },
}