Data Science Workbench¶
The Data Science Workbench image is a browser-based development container. The image extends the base code-server image and adds a Python-focused workspace for notebooks, scripts, and data tasks.
At a high level, this container provides the following features:
- A browser-accessible VS Code environment that operates through code-server
- A prebuilt Python virtual environment located at the
/home/coder/.venvpath - Support for Jupyter notebooks
- Common data science libraries
- The Actian client libraries that the image inherits from the base image
- Default installations of the Python and Jupyter VS Code extensions
Using Data Science Workbench¶
Use the Data Science Workbench image when you want an interactive data science environment that runs in Docker and functions like a desktop integrated development environment (IDE) in a web browser. The image is designed for the following use cases:
- Developing Python notebooks and scripts
- Connecting Python workloads to Actian databases through the integrated client libraries
- Providing users with a ready-to-use development container that includes consistent tools and package versions
- Running a persistent personal workbench where settings, extensions, and installed packages remain available after a container restart
This image is more appropriate than the base code-server image when you require immediate access to Python, Jupyter, and common analytics packages.
Data Science Workbench Components¶
The final container includes the base image and the workbench-specific modifications.
Base image features include the following components:
- The code-server application
- The Actian Client installation
- Default editor settings that are stored under the initial code-server user profile
Workbench modifications include the following packages:
jupyterlabnotebookipykernelnumpypandasscipypolarspyodbc