Showing 6 open source projects for "gnu-darwin"

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  • 1
    harmonypy

    harmonypy

    Integrate multiple high-dimensional datasets with fuzzy k-means

    Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq.
    Downloads: 0 This Week
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  • 2
    Mara Pipelines

    Mara Pipelines

    A lightweight opinionated ETL framework, halfway between plain scripts

    ...Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code. PostgreSQL as a data processing engine. Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines. GNU make semantics. Nodes depend on the completion of upstream nodes. No data dependencies or data flows. No in-app data processing: command line tools as the main tool for interacting with databases and data. Single machine pipeline execution based on Python's multiprocessing. No need for distributed task queues. Easy debugging and output logging. ...
    Downloads: 0 This Week
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  • 3
    A tool for autonomous and virtual topical data integration using the focused web-harvesting method.
    Downloads: 0 This Week
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  • 4
    DataSync Suite
    DataSync Suite is an open source platform for integrating tools like Zimbra, SugarCRM, and Drupal. The tool is focused on a single sign-on, application data integration, and fast, flexible deployment.
    Downloads: 0 This Week
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  • 5
    SnapLogic is an Open Source Data Integration framework that combines the power of state-of-the-art dynamic programming languages with standard Web interfaces to solve today's most pressing problems in data integration.
    Downloads: 1 This Week
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  • 6
    A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining
    Downloads: 0 This Week
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