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    "info": {
        "author": "Daniel Bok",
        "author_email": "daniel.bok@outlook.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Programming Language :: Python :: 3"
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        "description": "Kantopark Python\n================\n\nThis package contains Kantopark's python utility functions. The functions and types inside make it easier to develop Python instances. \n\n## Installation\n\n```bash\npip install kantopy\n```\n\n## Usage\n\nA typical function is listed below.\n\n```python\nimport json\n\ndef my_func(event):\n    payload = event.json\n    # some operations with the payload later\n    # ...\n    return json.dumps(payload)\n```\n\nSince Kantopark's python function must always return a string or byte object (data transferred over the web are essentially byte data after all), it might be tedious to use `json.dumps(...)`.\n\nWith `kantopy`, here's how the above can be re-written\n\n```python\nfrom kantopy import Event, as_json\n\ndef my_func(event: Event):  # notice the typings here\n    payload = event.json  # minimize misspelling with typings\n    # some operations later\n    # ...\n    return as_json(payload)\n```\n\nIf you're returning a graph (matplotlib or plotly), here's how you can use it.\n\n```python\nfrom kantopy import Event, as_png\nfrom matplotlib.figure import Figure\nfrom matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas\n\ndef create_figure():\n    fig = Figure()\n    axis = fig.add_subplot(1, 1, 1)\n    xs = range(100)\n    ys = [x * 2 + 3 for x in xs]\n    axis.plot(xs, ys)  # just a straight line\n    return fig\n\ndef my_func(event: Event):\n    fig = create_figure()\n    return as_png(fig)  # this would return the output as a png image\n```\n\n",
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        "license": "MIT",
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        "name": "kantopy",
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        "project_url": "https://pypi.org/project/kantopy/",
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        "summary": "Utility library for Kantopark's python instances",
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