#!/usr/bin/env python
"""
Script for rebuilding the samples for the Yahoo tests.
"""
from textwrap import dedent

import numpy as np
import pandas as pd

from catalyst.testing import test_resource_path, write_compressed
from catalyst.utils.calendars import get_calendar


def zipfile_path(symbol, ext):
    return test_resource_path('yahoo_samples', symbol + ext + '.gz')


def pricing_for_sid(sid):
    modifier = {
        'Low': 0,
        'Open': 1,
        'Close': 2,
        'High': 3,
        'Volume': 0,
    }

    def column(name):
        return np.arange(252) + 1 + sid * 10000 + modifier[name] * 1000

    trading_days = get_calendar('NYSE').all_sessions

    return pd.DataFrame(
        data={
            'Date': trading_days[
                (trading_days >= pd.Timestamp('2014')) &
                (trading_days < pd.Timestamp('2015'))
            ],
            'Open': column('Open'),
            'High': column('High'),
            'Low': column('Low'),
            'Close': column('Close'),
            'Volume': column('Volume'),
            'Adj Close': 0,
        },
        columns=[
            'Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'Adj Close',
        ],
    ).to_csv(index=False, date_format='%Y-%m-%d').encode('ascii')


def adjustments_for_sid(sid):
    """This is not exactly a csv... thanks yahoo.
    """
    return dedent(
        """\
        Date,Dividends
        DIVIDEND, 20140403,0.{p1}00000
        SPLIT, 20140703,{p2}:1
        DIVIDEND, 20141002,0.{p2}00000
        STARTDATE, 20140102
        ENDDATE, 20141231
        TOTALSIZE, 2
        """.format(p1=sid + 1, p2=sid + 2),
    ).encode('ascii')


def main():
    symbols = 'AAPL', 'IBM', 'MSFT'

    for sid, symbol in enumerate(symbols):
        write_compressed(
            zipfile_path(symbol, '.csv'),
            pricing_for_sid(sid),
        )
        write_compressed(
            zipfile_path(symbol, '.adjustments'),
            adjustments_for_sid(sid),
        )

if __name__ == '__main__':
    main()