import pandas as pd
from analytics import CreditIndex, Swaption
import datetime
import sys

from utils.db import dbengine
from contextlib import contextmanager
from itertools import starmap
from functools import partial
from multiprocessing import Pool

serenitas_engine = dbengine("serenitasdb")


def get_data(index, series, date=datetime.date.min):
    df = pd.read_sql_query(
        "SELECT * from swaption_ref_quotes JOIN swaption_quotes "
        "USING (ref_id) WHERE index=%s and series=%s "
        "and quotedate >=%s ORDER BY quotedate",
        serenitas_engine,
        params=(index, series, date),
        parse_dates=["quotedate", "expiry"],
    )
    df.loc[
        (df.quote_source == "GS") & (df["index"] == "HY"),
        ["pay_bid", "pay_offer", "rec_bid", "rec_offer"],
    ] *= 100
    df.quotedate = df.quotedate.dt.tz_convert("America/New_York")
    return df


def get_data_latest():
    df = pd.read_sql_query(
        "SELECT quotedate, index, series, expiry, ref, "
        "quote_source, swaption_quotes.* "
        "FROM swaption_ref_quotes "
        "JOIN swaption_quotes USING (ref_id) "
        "LEFT JOIN swaption_calib USING (quote_id) "
        "WHERE swaption_calib.quote_id is NULL",
        serenitas_engine,
        parse_dates=["quotedate", "expiry"],
    )
    df.loc[
        (df.quote_source == "GS") & (df["index"] == "HY"),
        ["pay_bid", "pay_offer", "rec_bid", "rec_offer"],
    ] *= 100
    df.quotedate = df.quotedate.dt.tz_convert("America/New_York")
    return df


def calib(option, ref, strike, pay_bid, pay_offer, rec_bid, rec_offer):
    option.ref = ref
    option.strike = strike
    r = []
    for price_type in ["price", "price_black"]:
        for option_type in ["pay", "rec"]:
            if option_type == "pay":
                mid = (pay_bid + pay_offer) / 2 * 1e-2
                option.option_type = "payer"
            else:
                mid = (rec_bid + rec_offer) / 2 * 1e-2
                option.option_type = "receiver"
            if mid == 0.0:
                logger.info("0. mid, skipping.")
                r.append(0.0)
                continue
            try:
                setattr(option, price_type, mid)
            except (ValueError, SystemError) as e:
                if "Failed" in str(e):
                    logger.error(e)
                    logger.error("probably data error")
                    sys.exit(0)
                r.append(None)
                logger.error(e)
            else:
                r.append(option.sigma)
    return r


@contextmanager
def MaybePool(nproc):
    yield Pool(nproc) if nproc > 1 else None


def calibrate(index_type=None, series=None, date=None, nproc=4, latest=False):
    sql_str = "INSERT INTO swaption_calib VALUES({}) ON CONFLICT DO NOTHING".format(
        ",".join(["%s"] * 5)
    )
    if latest:
        data = get_data_latest()
    else:
        data = get_data(index_type, series, date)

    with MaybePool(nproc) as pool:
        pstarmap = pool.starmap if pool else starmap
        for k, v in data.groupby([data["quotedate"].dt.date, "index", "series"]):
            trade_date, index_type, series = k
            logger.debug(f"{trade_date} {index_type}{series}")
            index = CreditIndex(index_type, series, "5yr", trade_date)
            for expiry, df in v.groupby(["expiry"]):
                try:
                    option = Swaption(index, expiry.date(), 100)
                except ValueError as e:
                    logger.error(e)
                    continue
                mycalib = partial(calib, option)
                r = pstarmap(
                    mycalib,
                    df[
                        [
                            "ref",
                            "strike",
                            "pay_bid",
                            "pay_offer",
                            "rec_bid",
                            "rec_offer",
                        ]
                    ].itertuples(index=False, name=None),
                )
                to_insert = [[a] + b for a, b in zip(df.quote_id, r)]
                serenitas_engine.execute(sql_str, to_insert)


if __name__ == "__main__":
    import logging
    from utils import SerenitasFileHandler

    logger = logging.getLogger("swaption_calib")
    import argparse

    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--index", required=False, type=lambda s: s.upper(), dest="index_type"
    )
    parser.add_argument("--series", required=False, type=int, default=28)
    parser.add_argument("--date", required=False, default=datetime.date.min)
    parser.add_argument("--latest", required=False, action="store_true")
    parser.add_argument("--nproc", required=False, type=int, default=4)
    parser.add_argument(
        "-d", "--debug", action="store_true", help="more verbose logging"
    )
    args = parser.parse_args()

    logger.setLevel(logging.DEBUG if args.debug else logging.INFO)
    if not args.debug:
        handler = SerenitasFileHandler(f"calib_swaptions_{datetime.date.today()}.log")
    else:
        handler = logging.StreamHandler()
        handler.setFormatter(SerenitasFileHandler._formatter)
    if not logger.handlers:
        logger.addHandler(handler)
    if args.latest:
        calibrate(latest=True, nproc=args.nproc)
    else:
        calibrate(**vars(args))