Portal

Dataiku APIs

Dataiku provides a number of APIs for programmatically operating Dataiku DSS.

Working within Dataiku (Basics)

Python API

Using the internal Python API, a Data Scientist can read a Dataiku DSS dataset into a dataframe, process the dataframe with Python code, and then write back to a Dataiku DSS dataset. Examples include:


R API

Using the internal R API, a Data Scientist can read a Dataiku DSS dataset into a dataframe, process the dataframe with R code, and then write back to a Dataiku DSS dataset. Examples include:


Javascript API

Using the internal Javascript API, a Data Scientist can read a Dataiku DSS dataset into a dataframe. Examples include:

Automating your work in Dataiku

Custom scenarios

A Data Scientist can create custom scenarios using the internal Python API.


Scoring Services

An Application Developer can query scoring services on the Dataiku API node.


Bundle and Service Package Deployment

Using the Public API, a Production Environment Manager can:

Extending Dataiku

Creating Plugins

A Data Scientist can create plugins that contain custom recipes, datasets, and processors, using mostly the Python API, though the R API can be used for custom recipes. Examples include:

Administering Dataiku Remotely

Using the Public API, an Administrator can:

  • Manage security settings, such as creating users, groups, and projects, on a Dataiku DSS instance
  • Manage connections from Dataiku to various data stores
  • Populate a project with datasets, recipes, and models according to preset configurations

In this way, you can spin up and take down Dataiku instances as they are needed on cloud infrastructures.