DSS comes with a complete set of Python API.
In many parts of DSS, you can write Python code (recipes, notebooks, scenarios, webapps, …). This Python code interacts with DSS (for example, to read datasets) using the Python APIs of DSS.
In addition, you can use the Python APIs to automate many parts of the interaction with DSS.
Most of the Python APIs can be used both within DSS and outside of DSS.
The Dataiku Python APIs are contained within two Python packages:
dataikuapipackage contains a wrapper for the public REST API, allowing you to automate all kinds of tasks in DSS
dataikupackage contains lower-level interaction, notably what you would in most cases use in recipes, notebooks, …
- Using the APIs inside of DSS
- Using the APIs outside of DSS
- API for interacting with datasets
- API for interacting with Pyspark
- API for managed folders
- API for interacting with saved models
- API for scenarios
- API for performing SQL, Hive and Impala queries
- API for performing SQL, Hive and Impala queries like the recipes
- API for metrics and checks
- API For creating static insights
- Reference API documentation of
- API for plugin components
dataikuapi: The REST API client