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.
