Configure PyCharm as a local IDE

Cloudera Machine Learning supports using editors on your machine that allow remote execution and/or file sync over SSH, such as PyCharm.

This topic describes the tasks you need to perform to configure Cloudera Machine Learning to act as a remote SSH interpreter for PyCharm. Once finished, you can use PyCharm to edit and sync the changes to Cloudera Machine Learning. To perform actions such as deploying a model, use the Cloudera Machine Learningg web UI.

Before you begin, ensure that the following prerequisites are met:

You have an edition of PyCharm that supports SSH, such as the Professional Edition.
You have an SSH public/private key pair for your local machine.
You have Contributor permissions for an existing Cloudera Machine Learning project. Alternatively, create a new project you have access to.