import pandas as pd
from . import DAILY_DIR

paths = {
    "Serenitas": ["NYops", "Margin calls MS"],
    "Brinker": ["NYops", "Margin Calls MS-Brinker"],
    "BowdSt": ["BowdoinOps", "Margin MS"],
}

subjects = {
    "Serenitas": "SERCX **Daily",
    "Brinker": "061761QY1***BRINKER",
    "BowdSt": "BOSTON PATRIOT BOWDOIN",
}


def download_files(em, count=20, *, fund="Serenitas", **kwargs):
    emails = em.get_msgs(
        path=paths[fund], count=count, subject__contains=subjects[fund],
    )
    DATA_DIR = DAILY_DIR / fund / "MS_reports"
    for msg in emails:
        for attach in msg.attachments:
            if "NETSwaps" in attach.name:
                fname = "Trade_Detail_" + attach.name.split("_")[1]
            elif "NET_Collateral" in attach.name:
                fname = "Collateral_Detail_" + attach.name.rsplit("_", 1)[1]
            else:
                continue
            p = DATA_DIR / fname
            if not p.exists():
                p.write_bytes(attach.content)


def collateral(d, dawn_trades, *, fund="Serenitas", **kwargs):
    df = pd.read_excel(
        DAILY_DIR / fund / "MS_reports" / f"Collateral_Detail_{d:%Y%m%d}.xls"
    )
    collat = df.loc[1, "coll_val_ccy"].replace(",", "")
    if "(" in collat:
        collat = collat[1:-1]
        collat = -float(collat)
    else:
        collat = float(collat)
    df = pd.read_excel(DAILY_DIR / fund / "MS_reports" / f"Trade_Detail_{d:%Y%m%d}.xls")
    df = df.dropna(subset=["trade_ccy"])
    df = df.merge(dawn_trades, how="left", left_on="trade_id", right_on="cpty_id")
    missing_ids = df.loc[df.cpty_id.isnull(), "trade_id"]
    if not missing_ids.empty:
        raise ValueError(f"{missing_ids.tolist()} not in the database for {fund}")
    df = df.groupby("folder")[["collat_req_in_agr_ccy"]].sum()
    df["Currency"] = "USD"
    df = df.reset_index()
    df.columns = ["Strategy", "Amount", "Currency"]
    df = df.append(
        {
            "Strategy": "M_CSH_CASH",
            "Amount": -collat - df.Amount.sum(),
            "Currency": "USD",
        },
        ignore_index=True,
    )
    df["date"] = d
    return df.set_index("Strategy")