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import logging
import pandas as pd
import PyPDF2
from . import DAILY_DIR
logger = logging.getLogger(__name__)
paths = {
"Serenitas": ["NYops", "Margin Calls Barclays"],
"Selene": ["SeleneOps", "Margin Barclays"],
}
def load_file(d, fund, pattern):
file_mapping = {
"Serenitas": "Serenitas Credit Gamma Master Fund LP",
"Selene": "Iso Selene Inc",
}
if fund not in file_mapping:
raise FileNotFoundError(f"No ISDA with Barclays for {fund}")
try:
fname = next(
(DAILY_DIR / fund / "BARCLAYS_reports").glob(
f"{pattern}*{file_mapping[fund]} - Regulatory as at {d:%d %b %Y}*"
)
)
except StopIteration:
raise FileNotFoundError(f"BARCLAYS file not found for date {d}")
if fname.name.endswith("xls"):
return pd.read_excel(fname, skiprows=3, skipfooter=24)
else:
return fname
def get_total_collateral(d, fund):
with open(load_file(d, fund, "CreditSupportStatement"), "rb") as pdf_file:
pdf_reader = PyPDF2.PdfFileReader(pdf_file)
first_page = pdf_reader.getPage(0)
page_text = first_page.extractText()
csb_pos = page_text.find("Credit Support Balance")
next_word_pos = page_text.find(" ", csb_pos + len("Credit Support Balance") + 1)
collateral_balance = page_text[
csb_pos + len("Credit Support Balance") + 1 : next_word_pos
]
return float(collateral_balance.split("\n")[0].replace(",", ""))
def download_files(em, count=20, *, fund="Serenitas", **kwargs):
if fund not in paths:
return
emails = em.get_msgs(path=paths[fund], count=count)
DATA_DIR = DAILY_DIR / fund / "BARCLAYS_reports"
for msg in emails:
for attach in msg.attachments:
fname = attach.name
if fname.startswith("CreditSupport") or fname.startswith("Exposure"):
p = DATA_DIR / fname
if not p.exists():
p.write_bytes(attach.content)
def collateral(d, dawn_trades, *, fund="Serenitas", **kwargs):
collateral = get_total_collateral(d, fund)
df = load_file(d, fund, "Exposure Report")
df = df[["Trade Reference", "Exposure (USD)", "Ind Amt (USD)"]]
df["Trade Reference"] = df["Trade Reference"].astype(str)
df = df.merge(
dawn_trades, how="left", left_on="Trade Reference", right_on="cpty_id"
)
missing_ids = df.loc[df.cpty_id.isnull(), "Trade Reference"]
if not missing_ids.empty:
raise ValueError(f"{missing_ids.tolist()} not in the database for {fund}")
df = df[["folder", "Exposure (USD)", "Ind Amt (USD)"]]
df = df.groupby("folder", dropna=False).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.loc[len(df.index)] = ["M_CSH_CASH", -collateral - df.Amount.sum(), "USD"]
df["date"] = d
return df.set_index("Strategy")
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