Neptune API

The Neptune API consists of two Python packages:

• neptune-scale, for logging metadata to Neptune.
• neptune-fetcher, for fetching logged metadata from Neptune.

Setup

For installation instructions, see Get started.

Usage

To import Neptune in your model-training code:

from neptune_scale import Run

You can then work with Run objects to create or resume experiments:

run = Run(...)

caution

Neptune's worker process creation method requires the standard Python "main guard":

if __name__ == "__main__":
    # your Neptune code
    run = Run(...)

For details, see the Python documentation.

Related

• Log metadata
• Query metadata

FAQ

How does the Neptune client handle errors?

In case of metadata inconsistencies or other failures, you can control what happens by configuring the NEPTUNE_LOG_FAILURE_ACTION environment variable.

For more information, see Neptune API error handling.

Can we filter out Neptune warnings from our logs?

Yes, you can define a filter callback for Neptune-related warnings. For instructions, see Filter out Neptune warnings from logs.

How can we migrate our code from legacy Neptune?

See the Neptune Python client 1.x migration guide.