Showing 5 open source projects for "cli-parser"

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    IronCalc

    IronCalc

    Main engine of the IronCalc ecosystem

    IronCalc is a new, modern, work-in-progress spreadsheet engine and set of tools to work with spreadsheets in diverse settings. IronCalc is a lightweight, open-source computational engine designed for performing mathematical operations, formula calculations, and data-driven tasks.
    Downloads: 0 This Week
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  • 2
    Arkflow

    Arkflow

    High performance Rust stream processing engine

    Arkflow is a Rust-based framework for building reactive, event-driven data pipelines. Inspired by tools like Airflow and Dagster, it focuses on strong typing, modularity, and performance. Arkflow is ideal for developers who want a fast, extensible way to orchestrate workflows and data transformations in Rust.
    Downloads: 0 This Week
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  • 3
    CocoIndex

    CocoIndex

    ETL framework to index data for AI, such as RAG

    CocoIndex is an open-source framework designed for building powerful, local-first semantic search systems. It lets users index and retrieve content based on meaning rather than keywords, making it ideal for modern AI-based search applications. CocoIndex leverages vector embeddings and integrates with various models and frameworks, including OpenAI and Hugging Face, to provide high-quality semantic understanding. It’s built for transparency, ease of use, and local control over your search...
    Downloads: 2 This Week
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  • 4
    wasm-pack

    wasm-pack

    Your favorite rust -> wasm workflow tool!

    ...Long-term, this will be replaced by a Rust-only version. If you would rather use another package manager that interfaces with the npm registry you may, however, the pack, publish, and login commands wrap the npm CLI interface and as a result require that npm be installed.
    Downloads: 2 This Week
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  • 5
    xsv

    xsv

    A fast CSV command line toolkit written in Rust

    xsv is a command line program for indexing, slicing, analyzing, splitting and joining CSV files. Commands should be simple, fast and composable. Simple tasks should be easy. Performance trade offs should be exposed in the CLI interface. Composition should not come at the expense of performance. Let's say you're playing with some of the data from the Data Science Toolkit, which contains several CSV files. Maybe you're interested in the population counts of each city in the world. So grab the data and start examining it. The next thing you might want to do is get an overview of the kind of data that appears in each column. ...
    Downloads: 0 This Week
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