Configure PyCharm as a Local IDE
Cloudera Data Science Workbench supports using local IDEs 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 Data Science Workbench to act as a remote SSH interpreter for PyCharm. Once
finished, you can use PyCharm to edit and sync the changes to Cloudera Data Science Workbench. To perform actions such as deploying a model, use the Cloudera Data Science Workbench 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 that is compatible with PyCharm. If you use OpenSSH to generate the key, include the -m PEM option because PyCharm does not support modern (RFC 4716) OpenSSH keys.
- You have Contributor permissions for an existing Cloudera Data Science project. Alternatively, create a new project you have access to.
Download cdswctl and Add an SSH Key
Initialize an SSH Connection to Cloudera Data Science Workbench
Add Cloudera Data Science Workbench as an Interpreter for PyCharm
Before you begin, ensure that the SSH endpoint for Cloudera Data Science Workbench is running on your
local machine. In PyCharm, you can configure an SSH interpreter. Cloudera Data Science Workbench uses this method to connect to PyCharm and act as its interpreter. These instructions were written for
the Professional Edition of PyCharm Version 2019.1 and are meant as a starting point. If additional information is required, see the documentation for your version of PyCharm for specific
instructions.
(Optional) Configure the Sync Between Cloudera Data Science Workbench and PyCharm
Before you configure syncing behavior between the remote editor and Cloudera Data Science Workbench,
ensure that you understand the policies set forth by IT and the Site Administrator. For example, a policy might require that data remains within the Cloudera Data Science Workbench deployment but
allow you to download and edit code. Configuring what files PyCharm ignores can help you adhere to IT policies.