from glob import iglob
import os
import pandas as pd
import datetime
from db import dbengine
import .load_globeop_report as load_globeop

import .bbg_helpers

def get_CRT_notional():

    BBG_IP = ['192.168.9.65']
    bbgstartdate = pd.datetime(2011, 1, 1)
    path = '/home/serenitas/edwin/CRT/'
    hist_securities = pd.read_csv(path + 'all_cusips.csv', header=None)
    hist_securities = hist_securities + ' Mtge'
    hist_fields = ['MTG_HIST_FACT']
    orig_ntl_field = ['MTG_ORIG_AMT']

    with bbg_helpers.init_bbg_session(BBG_IP) as session:
        hist_data = bbg_helpers.retrieve_data(session, hist_securities[0].tolist(), hist_fields)

    with bbg_helpers.init_bbg_session(BBG_IP) as session:
        orig_ntl = bbg_helpers.retrieve_data(session, hist_securities[0].tolist(), orig_ntl_field)

    hist_data1 = pd.DataFrame()
    for cusip in hist_data:
        new_df= pd.DataFrame()
        new_df['notional'] = hist_data[cusip]['MTG_HIST_FACT']['Factor'] * orig_ntl[cusip]['MTG_ORIG_AMT']
        new_df['date'] = hist_data[cusip]['MTG_HIST_FACT']['Payment Date']
        new_df['cusip'] = cusip
        hist_data1 = hist_data1.append(new_df)

    hist_data1.to_hdf(path + 'crt_notional.hdf','notionals')

def calc_CRT_notional():
    path = '/home/serenitas/edwin/CRT/'
    hist_data1 = pd.read_hdf(path + 'crt_notional.hdf')
    hist_data1 = hist_data1.set_index('date')
    return hist_data1.groupby(pd.TimeGrouper('M')).sum()