import pandas as pd
import subprocess
from bs4 import BeautifulSoup
from pandas.tseries.offsets import BDay
from . import DAILY_DIR, bus_day


def load_file(d):
    try:
        fname = next(
            (DAILY_DIR / "CITI_reports").glob(
                f"262966_Portfolio_{d.strftime('%Y%m%d')}*"
            )
        )
    except StopIteration:
        raise FileNotFoundError(f"CITI file not found for date {d}")
    return pd.read_excel(fname, skiprows=6, skipfooter=2)


def download_files(count=20):
    from exchange import ExchangeMessage

    em = ExchangeMessage()
    emails = em.get_msgs(
        path=["NYops", "Margin Calls Citi"], count=count, subject__startswith="262966"
    )
    DATA_DIR = DAILY_DIR / "CITI_reports"
    for msg in emails:
        for attach in msg.attachments:
            fname = attach.name
            p = DATA_DIR / fname
            if not p.exists():
                p.write_bytes(attach.content)


def load_pdf(file_path):
    proc = subprocess.run(
        ["pdftohtml", "-xml", "-stdout", "-i", file_path.as_posix()],
        capture_output=True,
    )
    soup = BeautifulSoup(proc.stdout, features="lxml")
    l = soup.findAll("text")
    l = sorted(l, key=lambda x: (int(x["top"]), int(x["left"])))
    return l


def get_col(l, top, bottom, left, right):
    return [
        c.text
        for c in l
        if int(c["left"]) >= left
        and int(c["left"]) < right
        and int(c["top"]) >= top
        and int(c["top"]) < bottom
    ]


def parse_num(s):
    s = s.replace(",", "")
    if s[0] == "(":
        return -float(s[1:-1])
    else:
        return float(s)


def get_df(l, col1, col2, col3):
    df = pd.DataFrame(
        {"amount": get_col(l, *col2), "currency": get_col(l, *col3)},
        index=get_col(l, *col1),
    )
    df.amount = df.amount.apply(parse_num)
    df.index = df.index.str.lstrip()
    return df


def get_total_collateral(d):
    try:
        fname = next(
            (DAILY_DIR / "CITI_reports").glob(
                f"262966_MarginNotice_{d.strftime('%Y%m%d')}_*.pdf"
            )
        )
    except StopIteration:
        raise FileNotFoundError(f"CITI file not found for date {d.date()}")
    l = load_pdf(fname)
    col1 = (370, 500, 70, 100)
    col2 = (370, 500, 100, 500)
    col3 = (370, 500, 500, 600)

    variation_margin = get_df(l, col1, col2, col3)
    anchor = next(c for c in l if c.text == "Non Regulatory Initial Margin")
    top = int(anchor["top"]) + 10
    bottom = top + 150
    col1 = (top, bottom, 70, 100)
    col2 = (top, bottom, 100, 505)
    col3 = (top, bottom, 505, 600)
    initial_margin = get_df(l, col1, col2, col3)
    return (
        variation_margin.loc["VM Total Collateral", "amount"]
        + initial_margin.loc["Non Reg IM Total Collateral", "amount"]
    )


def collateral(d, dawn_trades, *args):
    df = load_file(d)
    collat = get_total_collateral(d - BDay())
    df = df[["Operations File", "Market Value", "BasicAmt"]].dropna(
        subset=["Operations File"]
    )  # missing Operations File means assignment usually
    df = df.merge(
        dawn_trades, how="left", left_on="Operations File", right_on="cpty_id"
    )
    missing_ids = df.loc[df.cpty_id.isnull(), "Operations File"]
    if not missing_ids.empty:
        raise ValueError(f"{missing_ids.tolist()} not in the database")
    df = df.groupby("folder").sum()
    df = df.sum(axis=1).to_frame(name="Amount")
    df["Currency"] = "USD"
    df = df.reset_index()
    df.columns = ["Strategy", "Amount", "Currency"]
    df.Amount *= -1
    df = df.append(
        {
            "Strategy": "M_CSH_CASH",
            "Amount": collat - df.Amount.sum(),
            "Currency": "USD",
        },
        ignore_index=True,
    )
    df["date"] = d - bus_day
    return df.set_index("Strategy")