KNIME and Python

Combine the best of visual programming with scripting.

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

  • Create Python scripts automatically with an AI coding assistant to do the heavy lifting for you

  • 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 Business Hub as REST Services or as data apps.

Read documentation and download the KNIME Python Integration from KNIME Community Hub.

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. You can also have Python scripts auto-created at your finger tips with an AI-powered coding assistant. These workflows can then, for instance, be deployed as REST services with KNIME Business Hub. Or you can use KNIME nodes to build a UI for your workflow and make it available for business users as a data app.

Get Started with the KNIME 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 Business Hub in a production setting. No need for manual intervention or configuring.

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Use the Python Tools you Like

Execute Workflows from Python

Execute KNIME workflows on KNIME Business Hub from your Python script using knimepy. Local data can be used as input, while your output is received back as Pandas DataFrames or conventional Python dicts.

(Re-)Use Code from Jupyter in KNIME

KNIME supports calling Python code bundled in Jupyter Notebooks via the KNIME Python scripting nodes.

Do You Use PySpark?

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.


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