Showing 5 open source projects for "performance"

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  • 1
    Fast CSV

    Fast CSV

    CSV parser and formatter for node

    A high-performance Node.js library for parsing and formatting CSV data efficiently.
    Downloads: 0 This Week
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  • 2
    QSV

    QSV

    Blazing-fast Data-Wrangling toolkit

    ...It’s designed to make working with CSV files at scale easy and efficient, offering over 40 powerful subcommands for tasks like querying, sampling, splitting, deduplicating, and more. qsv is ideal for data engineers, analysts, and developers who need high-performance CSV manipulation on the command line.
    Downloads: 0 This Week
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  • 3
    Papa Parse

    Papa Parse

    CSV parser that handles large files and malformed input

    The world's first multi-threaded CSV parser for the browser. Use Papa when performance, privacy, and correctness matter to you. Papa alleviates privacy concerns related to uploading files. Malformed CSV is handled gracefully with a detailed error report. Now the fastest JavaScript CSV parser for the browser. Papa can handle files gigabytes in size without crashing. CSV to JSON and JSON to CSV. Auto-detect delimiter, open local files, download remote files, stream local and remote files, multi-threaded, header row support, type conversion, skip commented lines, fast mode, graceful error handling, and optional sprinkle of jQuery. ...
    Downloads: 0 This Week
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  • 4
    CSV Comparator

    CSV Comparator

    CSV Comparator is a tool for comparing files which contain CSV-Data.

    CSV Comparator is a tool for comparing files which contain CSV-Data. It was created for performance engineers to be able to have a easy way to compare data from two testruns and be able to automate the comparing process of various files with scripts. There is a command line tool as well as a user interface. In case you need to compare .xml-Files you can convert them to .csv-Files with my other project CSV Transformer.
    Downloads: 0 This Week
    Last Update:
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  • 5
    ktdata is a C++ library for accessing tabular data, like from CSV files. Its goals are: 1. object design 2. portability (Linux and Windows support at least) 3. high performance 4. support for common data file formats, like CSV, ARFF (Weka), etc.
    Downloads: 0 This Week
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