depository

This repository provides tooling and workflow recommendations for storing, scheduling, and publishing notebooks.

Automatic Notebook Versioning

Every save of a notebook creates an immutable copy of the notebook on object storage.

To ease implementation, we'll rely on S3 as the object store, using versioned buckets.

Storage Paths

All notebooks are archived to a single versioned S3 bucket with specific prefixes denoting the lifecycle of the notebook:

• /workspace - where users edit
• /scheduled - notebooks currently scheduled
• /published - public notebooks (to an organization)

Each notebook path is a namespace that an external service ties into the schedule. We archive off versions, keeping the path intact (until a user changes them).

Transitioning to this Storage Plan

Since most people are on a regular filesystem, we'll start with writing to the /workspace prefix as Archival Storage (writing on save using a post_save_hook for a Jupyter contents manager).

Configuration

from depository import depositoryContentsArchiver

# jupyter config
# At ~/.jupyter/jupyter_notebook_config.py for user installs
# At __ for system installs
c = get_config()

c.NotebookApp.contents_manager_class = depositoryContentsArchiver

c.depository.workspace_prefix = "/workspace/kylek/notebooks"
c.depository.published_prefix = "/published/kylek/notebooks"  
c.depository.scheduled_prefix = "/scheduled/kylek/notebooks"  

# Optional, in case you're using a different contents manager
# This defaults to notebook.services.contents.manager.ContentsManager
# c.depository.Archiver.underlying_contents_manager_class = ADifferentContentsManager

c.depository.Backend = "s3"
c.depository.S3.bucket = "<bucket-name>"

# Note: if depository is used from an EC2 instance with the right IAM role, you don't
# have to specify these
c.depository.S3.access_key_id = <AWS Access Key ID / IAM Access Key ID>
c.depository.S3.secret_access_key = <AWS Secret Access Key / IAM Secret Access Key>