Showing 4 open source projects for "node link"

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  • 1
    subconverter

    subconverter

    Utility to convert between various subscription format

    Utility to convert between various subscription format. Shadowrocket users should use ss, ssr or v2ray as target. You can add &remark= to Telegram-liked HTTP/Socks 5 links to set a remark for this node. Add a Personal Access Token into gistconf.ini in the root directory, then add &upload=true to the local subscription link, then when you access this link, the program will automatically update the content to Gist repository.
    Downloads: 13 This Week
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  • 2
    Barfi

    Barfi

    A Python visual Flow Based Programming library

    ...Then the schema is executed with barfi.ComputeEngine. Each barfi.Block has some properties that enable the FBP and schema building. Firstly, each Block has Input and Output interfaces that link to other Blocks. Each Block can carry an executable function, that is specified by the user. This function can access/get data from the Input interface, perform computations or calculations, and set the Output interface. In general, Barfi is an abstraction of Graphical Programming, Flow-Based Programming, or Node programming. Where the Block is synonymous to a Node, and a Link (connection) is synonymous with an Edge. ...
    Downloads: 0 This Week
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  • 3
    Pyrlang

    Pyrlang

    Erlang node implemented in Python 3.5+ (Asyncio-based)

    This is a drop-in Erlang node implementation in Python 3, implementing a network Erlang node protocol. It was designed to allow interoperation between existing Python projects and BEAM languages: Erlang, Elixir, Gleam, Luaerl, LFE, Clojerl, and such. With just a few lines of startup code your Python program becomes an Erlang network node, participating in the Erlang cluster.
    Downloads: 0 This Week
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  • 4
    node2vec

    node2vec

    Learn continuous vector embeddings for nodes in a graph using biased R

    The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction....
    Downloads: 1 This Week
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