JupyterLab Desktop App Now Available: A Data Science Tool That Bundles A Python Environment With Python Libraries

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The JupyterLab application is an independent cross-platform program that developers can use in data science workflows, like those found within scientific computing. The latest addition to the scientific computing and data science revolution, this desktop application bundles a Python environment with several popular libraries ready for use in your work. You can now download the JupyterLab installer for Linux, macOS and Windows from the GitHub page.

JupyterLab is a browser-based application that uses the open source framework Electron. It runs on top of it, providing access to Jupyter Lab’s front end code and libraries for executing Python programs in an embedded environment through conda – including numpy , scipy, pandas ipygidets, matplotlib among others.

Open Source OmniParseBench · by Datalab · Apache 2.0 Benchmark any document parser on tables, math, forms and handwriting. Yes/no tests per page across text, table and layout families. Score vendor parsers on the Hugging Face dataset or your own PDFs with score and predict primitives. ★ Star on GitHub Multi-column, rotated text, degraded scans · tagged by script and language github.com/datalab-to/omni_parse_bench Fork it · Add your parser
https://blog.jupyter.org/jupyterlab-desktop-app-now-available-b8b661b17e9a

The JupyterLab app has been updated with many new features. The most notable updates are a modernized user interface and quicker performance.

Github: https://github.com/jupyterlab/jupyterlab_app#download

Source: https://blog.jupyter.org/jupyterlab-desktop-app-now-available-b8b661b17e9a

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Shobha is a data analyst with a proven track record of developing innovative machine-learning solutions that drive business value.