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    "info": {
        "author": "Dev Aggarwal",
        "author_email": "devxpy@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy"
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        "description": "\n# Oscilloscope\n**An oscilloscope for python that just works\u2122**\n\n## Features\n\n### Simple to use\n\n[*This*](examples/simple_signal.py)\n```python3\nimport random\nfrom time import sleep\n\nfrom oscilloscope import Osc\n\nosc = Osc()\n\n\n@osc.signal\ndef simple_random_signal(state):\n    while True:\n        state.draw(random.random())\n        sleep(0.1)\n\n\nosc.start()\n```\n*Gives you this*\n\n<img src=\"https://i.imgur.com/BMeYoXG.png\" height=\"300\" />\n\n### Parallel compute\n\nEach `osc.signal` gets it's own process.\n\n[*This*](examples/parallel_signals.py)\n```python3\nimport random\nfrom time import sleep\n\nfrom oscilloscope import Osc\n\n\nosc = Osc(nrows=2, ncols=3)\n\n\n@osc.signal\ndef signal1(state):\n    while True:\n        state.draw((random.random())\n        sleep(0.1)\n\n\n@osc.signal\ndef signal2(state):\n    while True:\n        state.draw(random.random(), row=1, col=2)\n        sleep(0.1)\n\n\nosc.start()\n```\n*Gives you this*\n\n<img src=\"https://i.imgur.com/PPC7z4m.png\" height=\"300\" />\n\nP.S. Don't worry about race conditions, `state.draw()` is atomic. (See [zproc](https://github.com/pycampers/zproc))\n\n### Dynamic axis scale\n\nThe Y-axis's scale is dynamic, meaning that the graph's y axis scales with your signal.\n\n[*This*](examples/increasing.py)\n```python3\nimport random\nfrom time import sleep\n\nfrom oscilloscope import Osc\n\n\n# adjust window_sec and intensity to improve visibility\nosc = Osc(window_sec=10, intensity=1)\n\n\n@osc.signal\ndef increasing_signal(state):\n    delta = 1\n\n    while True:\n        state.draw(random.randint(-delta, delta))\n        delta += 5\n        sleep(0.01)\n\n\nosc.start()\n```\n*Gives you this*\n\n<img src=\"https://i.imgur.com/r1vHcKH.png\" height=\"300\" />\n\n### Automatic normalization\n\n[*This*](examples/normalized.py)\n```python3\nimport random\nfrom time import sleep\n\nfrom oscilloscope import Osc\n\n\n# turn on normalization\nosc = Osc(normalize=True)\n\n\n@osc.signal\ndef increasing_signal(state):\n    delta = 1\n\n    while True:\n        state.draw(random.randint(-delta, delta))\n        delta += 5\n        sleep(0.01)\n\n\nosc.start()\n```\n*Gives you this*\n\n<img src=\"https://i.imgur.com/Dlve8rJ.png\" height=\"300\" />\n\nThis was the same signal as the [earlier](#Automatic normalization) one, \nbut it looks a lot like the simple example, because we turned on normalization! \n\nThe Y-axis will now show, % max-amplitude encountered at the time, not the raw value.\n\n\n## Install\n\n\n[![PyPI](https://img.shields.io/pypi/v/oscilloscope.svg?style=for-the-badge)](https://pypi.org/project/oscilloscope/)\n\n\n`pip install oscilloscope`\n\nMIT Licence<br>\nPython 3.6+ only.\n\n---\n\n[\ud83d\udc0d\ud83c\udfd5\ufe0f](http://www.pycampers.com/)\n\n",
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