Documentation for packages used to interact with Cognite Data Fusion (CDF)
$ pip install cognite-sdkThis package provides an interface to CDF in Python that is tightly integrated with Pandas. It lets you work with all the data in the platform in a simple and efficient manner.
Click here to learn more and see the documentation.
$ pip install cognite-model-hostingThis library provides certain utilities for working with the Model Hosting Environment made available through the Cognite API. It lets you create data specs describing data in the platform and methods for downloading the specified data.
Click here to learn more and see the documentation.
A walkthrough of the concepts in the model hosting environment can be found here.
$ pip install cognite-model-hosting-notebookThis library provides a way for users of the Model Hosting Environment to deploy code to production directly from a Jupyter Notebook.
Click here to learn more and see the documentation.
A walkthrough of the concepts in the model hosting environment can be found here.
$ pip install cognite-correlationThe library contains tools for computing cross correlation between time series data, meant for finding useful relations between data from sensors.
Click here to learn more and see the documentation.
$ pip install cognite-replicatorThe library contains tools for copying data between tenants, meant to facilitate the creation of development and testing tenants.
Click here to learn more and see the documentation.
Examples on using the Cognite Data Platform in Python can be found here. This github repository contains a collection of scripts and Jupyter Notebooks explaining how to use the platform to perform different tasks.