DSS and Python¶
DSS includes deep integration with Python. In many parts of DSS, you can write Python code:
- In recipes
- In Jupyter notebooks
- In standard webapp backends
- In scenarios, metrics and checks
- In plugins
- For custom models in visual ML
- In API node, for custom prediction models or custom functions endpoints
Any Python package may be used in DSS.
In addition, DSS features a complete Python API, which has its own complete documentation.
The following highlights how a few specific Python packages can be used in DSS. DSS features advanced integration with most of the packages described below.
- Installing Python packages
- Installing in a specific code environment (recommended)
- Installing in the built-in DSS environment (not recommended)
- Installing custom Python packages
- Reusing Python code
- Using Matplotlib
- Using Bokeh
- Using Plot.ly
- Using Ggplot
- Using Jupyter Widgets