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import pandas as pd
import re
from pathlib import Path
import pdb
from download_emails import update_emails
import datetime

def makedf(r, indextype):
    if indextype=='IG':
        cols = ['Strike', 'RecBid', 'RecOffer', 'DeltaRec', 'PayBid',
                'PayOffer', 'DeltaPay', 'Vol', 'Gamma']
    else:
        cols = ['Strike', 'RecBid', 'RecOffer', 'DeltaRec', 'PayBid',
                'PayOffer', 'DeltaPay', 'Vol', 'PxVol', 'Gamma']
    df = pd.DataFrame.from_records(r, columns = cols)
    for col in ['DeltaRec', 'DeltaPay', 'Vol', 'PxVol', 'Gamma']:
        if col in df:
            df[col] = df[col].str.strip("%").astype('float')/100
    for k in df:
        if df.dtypes[k]=='object':
            df[k] = pd.to_numeric(df[k])
    df.set_index('Strike', inplace=True)
    return df

def parse_email(email_path):
    with email_path.open("rb") as fh:
        date_received = datetime.datetime.fromtimestamp(int(fh.readline())/1000)
        subject = fh.readline()
        m = re.match("(?:Fwd:){0,2}(?:BAML )?(\w{2})([0-9]{1,2})\s", subject.decode('utf-8'))
        if m:
            indextype, series = m.groups()
            series = int(series)
        else:
            raise RuntimeError("can't parse subject line: {0} for email {1}".format(
                subject.decode("utf-8"), email_path.name))
        flag = False
        option_stack = {}
        fwd_index = []
        for line in fh:
            line = line.decode('utf-8', 'ignore')
            line = line.rstrip()
            if line.startswith("At"):
                for p in ['%m/%d  %H:%M:%S', '%b  %d %Y %H:%M:%S']:
                    try:
                        quotedate = pd.to_datetime(line, format=p, exact=False)
                    except ValueError:
                        continue
                    else:
                        if quotedate.year == 1900:
                            quotedate = quotedate.replace(year=date_received.year)
                        break
                else:
                    raise RuntimeError("can't parse date")
            if line.startswith("Ref"):
                regex = "Ref:(?P<ref>\S+)\s+(?:Fwd Px:(?P<fwdprice>\S+)\s+)?" \
                        "Fwd(?: Spd)?:(?P<fwdspread>\S+)\s+Fwd Bpv:(?P<fwdbpv>\S+)" \
                        "\s+Expiry:(?P<expiry>\S+)"
                m = re.match(regex, line)
                try:
                    d = m.groupdict()
                    d['quotedate'] = quotedate
                    d['indextype'] = indextype
                    d['series'] = series
                    d['expiry'] = pd.to_datetime(d['expiry'], format='%d-%b-%y')
                except AttributeError:
                    print("something wrong with {0}".format(email_path.name))
                continue
            if line.startswith("Strike"):
                flag = True
                r = []
                continue
            if flag:
                if line:
                    line = re.sub("[/|]", " ", line)
                    vals = re.sub(" +", " ", line).rstrip().split(" ")
                    r.append(vals)
                    continue
                else:
                    option_stack[d['expiry']] = makedf(r, indextype)
                    fwd_index.append(d)
                    flag = False
                    r = []
                    continue
        if flag:
            option_stack[d['expiry']] = makedf(r, indextype)
            fwd_index.append(d)
        if option_stack:
            fwd_index = pd.DataFrame.from_records(fwd_index,
                                                  index='quotedate')
            return (quotedate, indextype, series), option_stack, fwd_index
        else:
            raise RuntimeError("empty email: {0}".format(email_path.name))

if __name__=="__main__":
    update_emails()
    emails = [f for f in Path("../../data/swaptions").iterdir() if f.is_file()]
    swaption_stack = {}
    index_data = pd.DataFrame()
    for f in emails:
        try:
            key, option_stack, fwd_index = parse_email(f)
        except RuntimeError as e:
            print(e)
        else:
            swaption_stack[key] = pd.concat(option_stack, names=['expiry', 'Strike'])
            index_data = index_data.append(fwd_index)
    for col in ['fwdbpv', 'fwdprice', 'fwdspread', 'ref']:
        index_data[col] = index_data[col].astype('float')
    index_data['indextype'] = index_data['indextype'].astype('category')
    swaption_stack = pd.concat(swaption_stack, names=['quotedate', 'indextype', 'series'])
    with pd.HDFStore('../../data/swaptions.hdf', mode = 'w', complevel=4,
                     complib='blosc', fletcher32=True) as swaptions:
        swaptions.append('swaptions', swaption_stack)
        swaptions.append('index_data', index_data)