Showing 4 open source projects for "mod-apache-snmp"

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  • 1
    marimo

    marimo

    A reactive notebook for Python

    marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,...
    Downloads: 4 This Week
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  • 2
    Modin

    Modin

    Scale your Pandas workflows by changing a single line of code

    Scale your pandas workflow by changing a single line of code. Modin uses Ray, Dask or Unidist to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical. It is not necessary to know in advance the available hardware resources in order to use Modin. Additionally, it is not necessary to...
    Downloads: 0 This Week
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  • 3
    gravitino

    gravitino

    Unified metadata lake for data & AI assets.

    Apache Gravitino is a high-performance, geo-distributed, and federated metadata lake. It manages metadata directly in different sources, types, and regions, providing users with unified metadata access for data and AI assets.
    Downloads: 8 This Week
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  • 4
    Vaex

    Vaex

    Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python

    Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive...
    Downloads: 0 This Week
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