Pyhon script (Bundled) can come with default KAP installer package.

It’s becoming increasingly important to enhance the integration and usability of Python scripts within KNIME, making the process as seamless as Jupiter’s fluidity. However, the current process of installing extensions can be tedious and cumbersome. Sharing KNIME workflows with others who are not accustomed to installing KNIME extensions adds another layer of complexity. Often, I find myself spending extra time guiding them through a series of steps for setup.

Considering KNIME’s potential, it’s worth envisioning it as a default data science IDE akin to R Studio, but with its unique node-based workflow intact. This approach could significantly elevate its appeal and user-friendliness, attracting more users to its platform. The question then arises: why aren’t developers pushing KNIME’s boundaries further through innovative enhancements?

The primary reasons I gravitate towards KNIME are its cost-effectiveness and collaborative nature. Its free-to-use model, coupled with the ability to collaborate seamlessly, makes it an attractive tool for data science. Furthermore, its capabilities are not only diverse but also highly innovative, adding to its appeal in the data science community.

Thank you @knime200087 for your feedback.
I will share this internally and get back to you.

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