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        "author": "chillar anand",
        "author_email": "chillar@avilpage.com",
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        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
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        "description": "stocktrends\n===========\n\nA python package to calcuate trends in stock markets.\n\n.. image:: https://img.shields.io/pypi/v/stocktrends.svg\n    :target: https://pypi.python.org/pypi/stocktrends\n    :alt: Latest PyPI version\n\n\nInstallation\n------------\n\nTo install stable version from pypi, run\n\n.. code-block:: shell\n\n    pip install stocktrends\n\n\nTo install latest code from github, run\n\n.. code-block:: shell\n\n    pip install git+https://github.com/chillaranand/stocktrends\n\n\n\n\n\nUsage\n-----\n\n| The following code from demo.py file shows how to construct dataframe from a csv file and then plot Renko, Line Break and PnF charts.\n\n\n.. code-block:: python\n\n    \"\"\"\n    Sample data from tests/HDFCLIFE file.\n\n    Date,Symbol,Series,Prev Close,Open,High,Low,Last,Close,VWAP,Volume,Turnover,Trades,Deliverable Volume,%Deliverble\n    2017-11-17,HDFCLIFE,EQ,290.0,310.0,369.0,307.0,343.9,344.6,327.26,168836552,5525288229115000.0,1177530,82044782,0.48590000000000005\n    2017-11-20,HDFCLIFE,EQ,344.6,344.7,358.9,344.0,355.0,355.35,353.18,14650240,517410581605000.0,166263,6761287,0.4615\n    2017-11-21,HDFCLIFE,EQ,355.35,356.4,418.9,352.5,386.9,385.3,389.24,43078194,1676786001315000.0,450090,11584111,0.26890000000000003\n    2017-11-22,HDFCLIFE,EQ,385.3,388.0,408.0,386.9,394.0,395.2,397.38,15227642,605123098895000.0,166870,3475999,0.22829999999999998\n    \"\"\"\n\n    import pandas as pd\n\n    from stocktrends import indicators\n\n\n    df = pd.read_csv('tests/HDFCLIFE')\n    df.columns = [i.lower() for i in df.columns]\n    rows = 5\n\n    pnf = indicators.PnF(df)\n    pnf.box_size = 10\n    pnf.reversal_size = 3\n\n\n    print('\\n\\nPnF bar data - based on close column')\n    data = pnf.get_bar_ohlc_data(source='close')\n    print(data.head(rows))\n\n\n    print('\\n\\nPnF box data - based on close column')\n    pnf_data = pnf.get_ohlc_data(source='close')\n    print(pnf_data.head(rows))\n\n\n    print('\\n\\nPnF box data - based on high/low columns')\n    data = pnf.get_bar_ohlc_data(source='hl')\n    print(data.head(rows))\n\n\n    renko = indicators.Renko(df)\n\n\n    print('\\n\\nRenko box calcuation based on periodic close')\n    renko.brick_size = 2\n    renko.chart_type = indicators.Renko.PERIOD_CLOSE\n    data = renko.get_ohlc_data()\n    print(data.tail(rows))\n\n\n    # print('\\n\\nRenko box calcuation based on price movement')\n    # renko.chart_type = indicators.Renko.PRICE_MOVEMENT\n    # data = renko.get_ohlc_data()\n    # print(data.tail(rows))\n\n\n    lb = indicators.LineBreak(df)\n\n    print('\\n\\nLine break chart')\n    lb.line_number = 3\n    data = lb.get_ohlc_data()\n    print(data.tail(rows))\n",
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