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            "License :: OSI Approved :: MIT License",
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            "Programming Language :: Python :: 3.7"
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        "description": "# graphtimer\n\nThis library is based around generating nice graphs for timings.\nIt's highly modular and provides an interface to quickly and cleanly use modules. \n\nThe high-level interface is the `Plotter` class which takes a timer class as its only argument. The builtin timer is `MultiTimer`, where `TimerNamespace` builds it without you having to. \n\nFrom here you have three steps:\n\n1. Time the code by using the timer provided. Usual usage is `repeat`, as `timeit` only times the functions once and skips step 2.\n2. Perform the statistical analysis on the timings. Most of the time you'll want to use `min`, which gets the lowest value that isn't an outlier. And shows the error bars from the lowest outlier to Q<sub>3</sub>.\n3. Plot the data on the graph. This by default uses `matplotlib` via the `MatPlotLib` class.\n\n```python\nimport matplotlib.pyplot as plt\nfrom graphtimer import Plotter, TimerNamespace\n\n\nclass ManualListCreation(TimerNamespace):\n    def test_comprehension(iterable):\n        return [i for i in iterable]\n\n    def test_append(iterable):\n        a = []\n        append = a.append\n        for i in iterable:\n            append(i)\n        return a\n\n\nfig, axs = plt.subplots()\n(\n    Plotter(ManualListCreation)\n        .repeat(100, 5, list(range(0, 10001, 1000)), args_conv=range)\n        .min()\n        .plot(axs)\n)\nfig.show()\n```\n\n## Installation\n\nTo install graphtimer, just use pip:\n\n```\n$ pip install graphtimer\n```\n\n",
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        "keywords": "timer graph performance",
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