Getting started#

Neptune Service Shutdown - March 5, 2026

Following its acquisition by OpenAI, Neptune services will be permanently discontinued.
All remaining data will be deleted at shutdown and cannot be recovered.

See timelines, export instructions, and migration guides in the Transition Hub.

The following is a quick procedure for getting set up in a typical environment. Fore more installation details, see Install Neptune.

Create a project.
Install the Neptune client library:
```
pip install -U neptune
```
Set your Neptune API token to the NEPTUNE_API_TOKEN environment variable.
```
export NEPTUNE_API_TOKEN="uyVrZXkiOiIzNTd0Zj..ifQ=="
```
To have API tokens for sharing or non-human accounts, you can create a service account.
Set the name of your Neptune project to the NEPTUNE_PROJECT environment variable.

You can copy the full name in your project's Details & privacy menu.
```
export NEPTUNE_PROJECT="workspace-name/project-name"
```

For more detailed instructions, see the pages in the left menu.

All set

You can now import Neptune in your code and start logging.

import neptune

run = neptune.init_run() # (1)!

run["my/namespace/structure"] = some_metadata

We don't recommend it, but you can also pass your info when initializing Neptune:

import neptune

run = neptune.init_run(
    project="your-workspace-name/your-project-name",
    api_token="YourNeptuneApiToken",
)

Neptune also integrates directly with the most popular ML frameworks. Instead of manual logging, you can use the integrations to log typical metadata. For more, see Integrations

Next steps:

Do the Quickstart to run a basic logging example.
See Add Neptune to your code for beginner tips.
View how-to guides and examples of Using Neptune