KNIME Analytics Platform has no limits on the technology you use in your data science stack
Run Python scripts in KNIME workflows with the KNIME Python Integration
Use components to package and share Python scripts with colleagues who don’t know scripting languages - environment propagation solves dependency issues
Deploy and productionize Python scripts in workflows on KNIME Server as REST Services or as data science applications
Integrate and Run Python in KNIME
Data scientists who also want to use Python can run their scripts seamlessly in KNIME workflows with the KNIME Python Integration. Nodes support scripting, model building and prediction, and visualizations. These workflows can then, for instance, be deployed as REST services with KNIME Server. Or you can use KNIME nodes to build a UI for your workflow and make it available for business users as a data app.Access Python Integration
Make Your Python Scripts Available to Non-Experts
Bundle Python scripts as reusable components to make them available to colleagues to use without needing to know Python. Your components can then be implemented like any other node by all team members.See Python Components in Action
Keep Python Dependencies Up to Date with Environment Propagation
Conda Environment Propagation ensures that your code’s Python package dependencies are always documented and available with your workflows and components. Replicate Conda environments and propagate to any new execution location, e.g. KNIME Server in a production setting. No need for manual intervention or configuring.Read More
Use the Python Tools you Like
KNIME supports calling Python code bundled in Jupyter Notebooks via the KNIME Python scripting nodes.
The KNIME Extension for Apache Spark makes the PySpark API available to users but in the familiar look and feel of the Python Scripting nodes. Mix PySpark jobs into your existing KNIME workflow.