Showing 2 open source projects for "python tools"

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  • The full-stack observability platform that protects your dataLayer, tags and conversion data Icon
    The full-stack observability platform that protects your dataLayer, tags and conversion data

    Stop losing revenue to bad data today. and protect your marketing data with Code-Cube.io.

    Code-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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  • MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design. Icon
    MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design.

    Microstation enables architects, engineers, and designers to create precise 2D and 3D drawings that bring complex projects to life.

    MicroStation is the only computer-aided design software for infrastructure design, helping architects and engineers like you bring their vision to life, present their designs to their clients, and deliver their projects to the community.
    Learn More
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    Grafana

    Grafana

    Leading open-source visualization and observability platform

    Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich...
    Downloads: 23 This Week
    Last Update:
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  • 2

    slycat

    Web-based data science analysis and visualization platform.

    This is Slycat - a web-based data science analysis and visualization platform, created at Sandia National Laboratories. The goal of the Slycat project is to develop processes, tools and techniques to support data science, particularly analysis of large, high-dimensional data.
    Downloads: 0 This Week
    Last Update:
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