jupyter-telemetry 0.1.0

Jupyter telemetry library

Telemetry

Telemetry for Jupyter Applications and extensions.

Telemetry (təˈlemətrē): the process of recording and transmitting the readings of an instrument. [Oxford Dictionaries]

Jupyter Telemetry enables Jupyter Applications (e.g. Jupyter Server, Jupyter Notebook, JupyterLab, JupyterHub, etc.) to record events—i.e. actions by application users—and transmit them to remote (or local) destinations as structured data. It works with Python's standard logging library to handle the transmission of events allowing users to send events to local files, over the web, etc.

Install

Jupyter's Telemetry library can be installed from PyPI.

pip install jupyter_telemetry

Basic Usage

Telemetry provides a configurable traitlets object, EventLog, for structured event-logging in Python. It leverages Python's standard logging library for filtering, handling, and recording events. All events are validated (using jsonschema) against registered JSON schemas.

Let's look at a basic example of an EventLog.

import logging
from jupyter_telemetry import EventLog


eventlog = EventLog(
    # Use logging handlers to route where events
    # should be record.
    handlers=[
        logging.FileHandler('events.log')
    ],
    # List schemas of events that should be recorded.
    allowed_schemas=[
        'uri.to.event.schema'
    ]
)

EventLog has two configurable traits:

• handlers: a list of Python's logging handlers.
• allowed_schemas: a list of event schemas to record.

Event schemas must be registered with the EventLog for events to be recorded. An event schema looks something like:

{
  "$id": "url.to.event.schema",
  "title": "My Event",
  "description": "All events must have a name property.",
  "type": "object",
  "properties": {
    "name": {
      "title": "Name",
      "description": "Name of event",
      "type": "string"
    }
  },
  "required": ["name"],
  "version": 1
}

2 fields are required:

• $id: a valid URI to identify the schema (and possibly fetch it from a remote address).
• version: the version of the schema.

The other fields follow standard JSON schema structure.

Schemas can be registered from a Python dict object, a file, or a URL. This example loads the above example schema from file.

# Register the schema.
eventlog.register_schema_file('schema.json')

Events are recorded using the record_event method. This method validates the event data and routes the JSON string to the Python logging handlers listed in the EventLog.

# Record an example event.
event = {'name': 'example event'}
eventlog.record_event(
    schema_id='url.to.event.schema',
    version=1,
    event=event
)