API reference#
-
 Init functions
Initialize new or existing Neptune objects.
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 Management functions
Manage your workspace and users.
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 Field types
A field is a location where metadata is logged. Depending on their types, fields have different methods and properties.
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 Environment variables
Use environment variables to make your setup more smooth and secure.
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 Connection modes
Set the logging and synchronization mode.
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 CLI
You can use the Neptune Command Line Interface to manage and sync locally stored metadata.
Neptune client library#
Python#
The Neptune Python API has the following structure:
- Packages:
neptune
andmanagement
- Modules:
utils
- Classes:
Run
,Model
,MovelVersion
, andProject
View client library on GitHub 
R#
The Neptune R package includes most of the functionality that is available in the Python library.
You can find most up to date API reference on the CRAN package page .
Integrations#
We provide API references for the classes and functions exposed by Neptune integrations with other ML frameworks.
- Apache Airflow
- Catalyst
- Detectron2
- fastai
Transformers
- Kedro
- Keras
- LightGBM
- Lightning
- Optuna
- Prophet
- PyTorch
- PyTorch Ignite
- Sacred
- scikit-learn
- skorch
- TensorBoard
- XGBoost
Errors, warnings, and other messages#
See also#
- System namespace (
sys
) – explore the basic metadata that is logged for each Neptune object. - Change the location of the
.neptune
folder – and how to access the folder from elsewhere in your system. - Set up a Neptune error handling function
- Help ≫ Debugging options