A JupyterLab extension that displays currently used variables and their values for Python, R, and Scala notebooks.
JupyterLab Variable Inspector is an extension for JupyterLab that shows currently used variables and their values in real-time. It helps data scientists and developers inspect their workspace, view data structures like matrices and data frames, and debug code more effectively within Jupyter notebooks and consoles.
Data scientists, researchers, and developers using JupyterLab for interactive computing in Python, R, or Scala who need to monitor variable states and inspect data during analysis or development.
It provides a built-in, language-aware variable inspection panel directly within JupyterLab, eliminating the need for external debugging tools and offering support for popular data science libraries like pandas, numpy, PyTorch, and TensorFlow.
Variable Inspector extension for Jupyterlab
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Inspects variables in Python, R, and Scala (via almond kernel), catering to diverse data science workflows, though with varying feature completeness as noted in the README.
Displays matrices and data frames in an interactive grid for easy exploration directly within JupyterLab, enhancing data inspection without external tools.
Allows inline and interactive inspection of ipywidgets, making it seamless to debug interactive components within the variable inspector, as shown in the README screenshot.
Works with both notebooks and consoles to fetch variable data in real-time from the kernel, providing a live overview of the workspace state.
Inspecting large datasets can dramatically increase memory usage and significantly slow down the browser, a trade-off explicitly warned in the README's 'How it Works' section.
Support for R and Scala is less comprehensive than for Python, with different levels of feature completeness, limiting utility for multi-language teams.
Full functionality requires installing additional libraries like pandas, numpy, and specific ML frameworks (e.g., PyTorch, TensorFlow), adding complexity and potential compatibility issues.