{
    "info": {
        "author": "Stephen Tierney",
        "author_email": "sjtrny@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License"
        ],
        "description": "[![Build Status](https://travis-ci.org/sjtrny/jitcache.svg?branch=master)](https://travis-ci.org/sjtrny/jitcache)\n[![Documentation Status](https://readthedocs.org/projects/jitcache/badge/?version=latest)](https://jitcache.readthedocs.io/en/latest/?badge=latest)\n[![Downloads](https://pepy.tech/badge/jitcache)](https://pepy.tech/project/jitcache)\n\n# jitcache\n\njitcache is a just-in-time key-value cache that is thread/process safe. jitcache also prevents repeated computation\nwhen multiple workers request the same value.\n\njitcache was designed to improve the performance of Plot.ly Dash apps by caching results and reducing CPU load.\n\nInstallation\n-------------------\n\nInstall via pip:\n\n    $ pip install jitcache\n\nDocumentation\n-------------------\n\nFull documentation available here [https://jitcache.readthedocs.io/](https://jitcache.readthedocs.io/en/latest/)\n\nBasic Usage\n-------------------\n\n    from jitcache import Cache\n    import time\n\n\n    cache = Cache()\n\n\n    @cache.memoize\n    def slow_fn(input_1, input_2, input_3=10):\n        print(\"Slow Function Called\")\n        time.sleep(1)\n        return input_1 * input_2 * input_3\n\n\n    print(slow_fn(10, 2))\n\n\n Output:\n\n    Slow Function Called\n    40\n\n\nPlot.ly Dash Usage\n-------------------\n\n    import dash\n    import dash_html_components as html\n    from jitcache import Cache\n    import dash_core_components as dcc\n\n\n    cache = Cache()\n\n    app = dash.Dash(__name__)\n\n    server = app.server\n    app.layout = html.Div(\n        children=[\n            html.Div(id=\"output-container-dropdown1\", children=[]),\n            html.Div(id=\"output-container-dropdown2\", children=[]),\n            dcc.Dropdown(\n                options=[\n                    {\"label\": \"New York City\", \"value\": \"NYC\"},\n                    {\"label\": \"Montr\u00e9al\", \"value\": \"MTL\"},\n                    {\"label\": \"San Francisco\", \"value\": \"SF\"},\n                ],\n                value=\"MTL\",\n                id=\"dropdown\",\n            ),\n        ]\n    )\n\n\n    @app.callback(\n        dash.dependencies.Output(\"output-container-dropdown1\", \"children\"),\n        [dash.dependencies.Input(\"dropdown\", \"value\")],\n    )\n    @cache.memoize\n    def update_output1(input_dropdown):\n        print(\"run1\")\n\n        return input_dropdown\n\n\n    @app.callback(\n        dash.dependencies.Output(\"output-container-dropdown2\", \"children\"),\n        [dash.dependencies.Input(\"dropdown\", \"value\")],\n    )\n    @cache.memoize\n    def update_output2(input_dropdown):\n        print(\"run2\")\n\n        return input_dropdown\n\n\n    if __name__ == \"__main__\":\n        app.run_server(debug=True)\n\n\n",
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        "keywords": "cache jit key value dictionary thread process",
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        "name": "jitcache",
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