import os
import os.path
import pandas as pd
from intex_scenarios import dealname_from_cusip
from zipfile import ZipFile
import re
import datetime
import pdb
from db import query_db
import yaml

if os.name =='nt':
    root = "//WDsentinel/share/CorpCDOs"
elif os.name == 'posix':
    root = '/home/share/CorpCDOs'

def sanitize_float(string):
    if isinstance(string, float):
        return string
    else:
        string = string.replace(",","")
        if "(" in string:
            return - float(string[1:-1])
        else:
            return float(string)

def processzipfiles(workdate=datetime.date.today()):
    pricesdir = os.path.join(root, "Scenarios", "Prices_" + str(workdate))
    zipfiles = [os.path.join(pricesdir, f) for f in os.listdir(pricesdir) \
                if f.endswith(".zip")]
    zipfiles = sorted(zipfiles, key=lambda x: os.stat(x).st_ctime)
    cusips_dict = {}
    dealnames_dict = {}
    for i, zip in enumerate(zipfiles):
        with ZipFile(zip) as myzip:
            allfiles = set([f.filename.split("-")[0] for f in myzip.infolist()])
            allfiles = allfiles - {"Total"}
            dealnames = set([f.filename.split("-")[0] for f in myzip.infolist() \
                             if re.search("COLLAT.*Scen100", f.filename)])
            cusips = allfiles - dealnames
            dealnames = [d.lower() for d in dealnames]
            cusips_dict.update((cusip, i) for cusip in cusips)
            dealnames_dict.update((dealname, i) for dealname in dealnames)
    return {"dealnames": dealnames_dict, "cusips":cusips_dict, "zipfiles": zipfiles}


def get_configfile(dealname, workdate):
    configfile = os.path.join(root, "Scenarios", "_".join(["Intex curves", str(workdate)]),
                              "csv", dealname + ".config")
    try:
        with open(configfile) as fh:
            config = yaml.load(fh)
    except FileNotFoundError:
        config = {"reinvflag": True}
    return config

def getdealcf(dealnames, cusips, zipfiles, workdate = datetime.date.today()):
    fiels = ["Cashflow", "Principal", "Interest"]
    n_scenarios = 100
    for dealname, i in dealnames.items():
        zip = zipfiles[i]
        mv = query_db("select marketvalue from latest_deal_model_numbers where dealname = %s",
                      (dealname,))[0]
        sqlstr = "select \"Curr Collat Bal\", \"Reinv End Date\", \"Deal Next Pay Date\"," \
                 "maturity, \"Principal Bal\" from historical_clo_universe(%s, %s)"
        sqldata = query_db(sqlstr, (dealname, str(workdate)))
        pdb.set_trace()
        config = get_configfile(dealname, workdate)
        if (not sqldate or config["reinvflag"]):
            tranches = ["COLLAT"]
        else:
            tranches = ["COLLAT_INITIAL", "COLLAT_REINVEST"]
        for tranche in tranches:
            cfdata[dealname][tranche]

# fields = ["Price", "WAL", "Market Value", "Modified Duration"]
# dealdata = {}
# workdate = '2013-01-09'
# for dealname in ["abcl071", "ammcclo5"]:
#     tranches = os.listdir(os.path.join(root, "Scenarios", "Prices_" + workdate, dealname))
#     d  = {}
#     for tranche in tranches:
#         data = pd.read_table(os.path.join(root, "Scenarios", "Prices_" + workdate, dealname, tranche))
#         datamod = data[data.columns[2:-1]].T
#         datamod.columns = data[data.columns[1]]
#         for field in fields:
#             datamod[field] = datamod[field].apply(sanitize_float)
#         d[tranche[:-7]] = datamod[fields]
#     dealdata[dealname] = pd.concat(d)

# dealdata = pd.concat(dealdata)

if __name__=="__main__":
    pomme = processzipfiles()
    getdealcf(**pomme)