from analytics.cms_spread import CmsSpread
from pathlib import Path
import os
import pandas as pd

DAILY_DIR = Path(os.environ["DAILY_DIR"])
r = []
today = pd.Timestamp.today()
trade = CmsSpread.from_tradeid(1)
dr = pd.bdate_range("2018-01-19", today, closed="left", normalize=True)
for d in dr:
    trade.value_date = d
    r.append(trade.pv)

def gs_navs(trade_id='LTAAB4ZN3333L6TTSH7.0.0.0'):
    # load gs navs for a given trade
    dates = []
    r = []
    for fname in (DAILY_DIR / "GS_reports").glob("Trade_Detail*.xls"):
        m = re.match("[^\d]*(\d{2}_.{3}_\d{4})", fname.name)
        if m:
            date_string, = m.groups()
            dates.append(datetime.datetime.strptime(date_string, "%d_%b_%Y"))
        df = pd.read_excel(fname, skiprows=9, skipfooter=77)
        r.append(df.set_index('Trade Id').loc[trade_id, 'NPV (USD)'])
    s = pd.Series(r, dates)
    s = s.sort_index()
    #remove the IA until it settled
    s[:2] -= 68750.00
    return -s