JetBrains DataSpell vs. MicroPython vs. QML vs. marimo Comparison Chart

Switch between command and editor modes with a single keystroke. Navigate over cells with arrow keys. Use all of the standard Jupyter shortcuts. Enjoy fully interactive outputs – right under the cell. When editing code cells, enjoy smart code completion, on-the-fly error checking and quick-fixes, easy navigation, and much more. Work with local Jupyter notebooks or connect easily to remote Jupyter, JupyterHub, or JupyterLab servers right from the IDE. Run Python scripts or arbitrary expressions interactively in a Python Console. See the outputs and the state of variables in real-time. Split Python scripts into code cells with the #%% separator and run them individually as you would in a Jupyter notebook. Browse DataFrames and visualizations right in place via interactive controls. All popular Python scientific libraries are supported, including Plotly, Bokeh, Altair, ipywidgets, and others.

QML is a declarative language that allows user interfaces to be described in terms of their visual components and how they interact and relate with one another. It is a highly readable language that was designed to enable components to be interconnected in a dynamic manner, and it allows components to be easily reused and customized within a user interface. Using the QtQuick module, designers and developers can easily build fluid animated user interfaces in QML, and have the option of connecting these user interfaces to any back-end C++ libraries. QML is a user interface specification and programming language. It allows developers and designers alike to create highly performant, fluidly animated and visually appealing applications. QML offers a highly readable, declarative, JSON-like syntax with support for imperative JavaScript expressions combined with dynamic property bindings.