#
# Copyright 2012 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


from datetime import datetime

import csv

from StringIO import StringIO
from functools import partial

import requests

from loader_utils import (
    date_conversion,
    source_to_records
)

from loader_utils import Mapping

from zipline.finance.risk import DailyReturn

_BENCHMARK_MAPPING = {
    # Need to add 'symbol' and GSPC as a constant
    'volume': (int, 'Volume'),
    'open': (float, 'Open'),
    'close': (float, 'Close'),
    'high': (float, 'High'),
    'low': (float, 'Low'),
    'adj_close': (float, 'Adj Close'),
    'date': (partial(date_conversion, date_pattern='%Y-%m-%d'), 'Date')
}


def benchmark_mappings():
    return {key: Mapping(*value)
            for key, value
            in _BENCHMARK_MAPPING.iteritems()}


def get_raw_benchmark_data(start_date, end_date):

    # create benchmark files
    # ^GSPC 19500103
    params = {
        # the s&p 500
        's': '^GSPC',
        # end_date month, zero indexed
        'd': end_date.month - 1,
        # end_date day str(int(todate[6:8])) #day
        'e': end_date.day,
        # end_date year str(int(todate[0:4]))
        'f': end_date.year,
        # daily frequency
        'g': 'd',
        # start_date month, zero indexed
        'a': start_date.month - 1,
        # start_date day
        'b': start_date.day,
        # start_date year
        'c': start_date.year
    }

    res = requests.get('http://ichart.yahoo.com/table.csv',
                       params=params)

    return csv.DictReader(StringIO(res.content))


def get_benchmark_data():
    """
    Benchmarks from Yahoo's GSPC source.
    """
    start_date = datetime(year=1950, month=1, day=3)
    end_date = datetime.utcnow()

    raw_benchmark_data = get_raw_benchmark_data(start_date, end_date)
    # Reverse data so we can load it in reverse chron order.
    benchmarks_source = reversed(list(raw_benchmark_data))

    mappings = benchmark_mappings()

    return source_to_records(mappings, benchmarks_source)


def get_benchmark_returns():

    benchmark_returns = []

    for data_point in get_benchmark_data():
        returns = (data_point['close'] - data_point['open']) / \
            data_point['open']
        daily_return = DailyReturn(date=data_point['date'], returns=returns)
        benchmark_returns.append(daily_return)

    return benchmark_returns