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from serenitas.utils.env import DAILY_DIR
from serenitas.utils.exchange import ExchangeMessage
import datetime
from collateral.baml_isda import download_from_secure_id
from bs4 import BeautifulSoup
from urllib.parse import urlsplit, parse_qs, urlunsplit
import logging
import argparse
from collateral.common import load_pdf
from pathlib import Path
import pandas as pd
from collections import defaultdict
import shutil
from interest_statement import export_data
from dateutil.relativedelta import relativedelta
logger = logging.getLogger(__name__)
def download_messages(em, counterparty, start, end, auto=False):
for msg in em.get_msgs(
20,
path=["Interest", counterparty],
):
if not auto:
if counterparty == "CITI":
base_dir = DAILY_DIR / f"{counterparty}_reports" / "Interest Statements"
elif counterparty == "BAML":
base_dir = (
DAILY_DIR / "Serenitas" / f"BoA_reports" / "Interest Statements"
)
else:
base_dir = (
DAILY_DIR
/ "Serenitas"
/ f"{counterparty}_reports"
/ "Interest Statements"
)
else:
base_dir = (
DAILY_DIR / "Serenitas" / "MonthlyInterest" / f"{counterparty}_reports"
)
if (msg.datetime_sent.date() >= datetime.date.fromisoformat(start)) and (
msg.datetime_sent.date() <= datetime.date.fromisoformat(end)
):
if counterparty == "BAML":
soup = BeautifulSoup(msg.body, features="lxml")
a = soup.find("a")
url = urlsplit(a["href"])
query = parse_qs(url.query)
base_url = urlunsplit(url[:2] + ("",) * 3)
try:
download_from_secure_id(
query["id"][0], query["brand"][0], base_dir, base_url
)
except ValueError as e:
logging.error(e)
continue
continue
for attach in msg.attachments:
fname = attach.name
if (counterparty == "CS") and not ("Interest" in fname):
continue
p = base_dir / fname
if not p.parent.exists():
p.parent.mkdir(parents=True)
if not p.exists():
p.write_bytes(attach.content)
def get_CS(g):
for e in g:
if "This interest, margin" in e.text:
return float(value)
value = e.text
def get_BNP(g):
for e in g:
if "Due to" in e.text:
value = next(g).text.replace(",", "")
return -float(value)
def get_CITI(path):
df = pd.read_excel(path)
for row in df.itertuples():
if "Net Interest Due To CP" in row:
return -row._6
def get_GS(g):
for e in g:
if "TOTAL INTEREST" in e.text:
next(g)
return float(next(g).text.replace("USD", "").replace(",", ""))
def get_MS(path):
df = pd.read_excel(path)
return -round(df["LOCAL_ACCRUAL"].sum(), 2)
def get_BAML(g):
for e in g:
if "Net interest Amount" in e.text:
return -float(next(g).text.replace("(", "-").replace(")", ""))
def start_end(year, month):
start = datetime.date(year, month, 1)
end = start + relativedelta(months=1)
end -= datetime.timedelta(days=1)
return start, end
def get_interest(delete=False):
interest_amounts = defaultdict(float)
counterparties = ["BNP", "CITI", "CS", "GS", "MS", "BAML"]
for cp in counterparties:
try:
func = globals()[f"get_{cp}"]
except KeyError:
continue
if cp in ("CITI", "MS"):
for file in Path(
f"/home/serenitas/Daily/Serenitas/MonthlyInterest/{cp}_reports"
).glob("*.xls*"):
amount = func(file)
interest_amounts[cp] = interest_amounts[cp] + amount
else:
for file in Path(
f"/home/serenitas/Daily/Serenitas/MonthlyInterest/{cp}_reports"
).glob("*.pdf"):
g = iter(load_pdf(file))
amount = func(g)
interest_amounts[cp] = interest_amounts[cp] + amount
if delete:
try:
shutil.rmtree(
f"/home/serenitas/Daily/Serenitas/MonthlyInterest/{cp}_reports"
)
except FileNotFoundError:
pass
return pd.DataFrame(interest_amounts, index=[0]).T.rename(
index={"BAML": "BAML_ISDA"}, columns={0: "monthly_statement"}
)
em = ExchangeMessage()
counterparties = ["BNP", "CITI", "CS", "GS", "MS", "BAML"]
parser = argparse.ArgumentParser(description="determine sender destination")
parser.add_argument("start")
parser.add_argument("end", default=datetime.date.today())
parser.add_argument("--auto", action="store_true", help="for automation or for monthly")
parser.add_argument(
"--delete", action="store_true", default=True, help="for automation or for monthly"
)
args = parser.parse_args()
for cp in counterparties:
if args.auto:
download_messages(em, cp, args.start, args.end, auto=args.auto)
else:
download_messages(em, cp, args.start, args.end)
if args.auto:
df = get_interest(delete=args.delete)
start, end = start_end(
datetime.datetime.today().year, datetime.datetime.today().month - 1
)
new_df = pd.merge(
export_data(start, end).groupby("broker").sum(),
df,
how="outer",
left_index=True,
right_index=True,
)
new_df["difference"] = new_df["amount"] - new_df["monthly_statement"]
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