Python Logger API reference

Overview of using Neptune with Python's Logger.

You can useNeptuneHandlerto track logs from the PythonLogger.

NeptuneHandler

A handler that sends the records created by the logger to Neptune.

Logs will be stored as aStringSeriesfield.

Parameters

Name	Type	Default	Description
run	Run, optional	None	An existing run reference, as returned byneptune.init_run().
level	int, optional	logging.NOTSET	Log levelof the logs to be captured by the handler. Defaults tologging.NOTSET, which captures all logs that match the logger level.
path	str, optional	None	Path to theStringSeriesfield used for captured logs. If None, tracked metadata will be stored under themonitoringnamespace.

Examples

Create a logger:

import logging

logger = logging.getLogger("root_experiment")
logger.setLevel(logging.DEBUG)

Create a Neptune run:

import neptune

run = neptune.init_run()

As a best practice, you should save your Neptune API token and project name as environment variables:

export NEPTUNE_API_TOKEN="h0dHBzOi8aHR0cHM6Lkc78ghs74kl0jv...Yh3Kb8"

export NEPTUNE_PROJECT="ml-team/classification"

Alternatively, you can pass the information when using a function that takesapi_tokenandprojectas arguments:

run = neptune.init_run(
 api_token="h0dHBzOi8aHR0cHM6Lkc78ghs74kl0jv...Yh3Kb8", # (1)!
 project="ml-team/classification", # (2)!
)

In the bottom-left corner, expand the user menu and select Get my API token .
You can copy the path from the project details ( → Details & privacy ).

If you haven't registered, you can log anonymously to a public project:

api_token=neptune.ANONYMOUS_API_TOKEN
project="common/quickstarts"

Make sure not to publish sensitive data through your code!

Create a NeptuneHandler object to capture the logs:

from neptune.integrations.python_logger import NeptuneHandler

npt_handler = NeptuneHandler(run=run)
logger.addHandler(npt_handler)

# Log something to the logger
logger.debug("Starting data preparation")
logger.debug("Data preparation done")