Make your libraries available in Dotscience.
When you set up a Dotscience runner, you work inside a Docker container on that runner. This means that to use libraries in your model, it isn’t sufficient just to have them installed on the runner. They also need to be accessible inside the container.
Note that some common data science libraries (Panda, Numpy, Tensorflow) are installed in the container by default.
If you need to install a library that isn’t installed, the easiest way to do so is via the terminal on the JupyterLab web interface.
1. Launch Jupyter, and select File > New > Terminal.
2. Install your library.
pip is available for installing Python packages.
Note that at present you will need to repeat this process every time you launch Jupyter. An improved method to specify libraries and automatically load them into your workspace is on the product roadmap.