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import logging
import pandas as pd
import time
from . import DAILY_DIR
from paramiko import Transport, SFTPClient
logger = logging.getLogger(__name__)
def get_sftp_client():
transport = Transport(("prmssp.amer.sgcib.com", 22))
transport.connect(username="SerenitasGamma@USA", password="SSqrrLL99")
return SFTPClient.from_transport(transport)
def download_files(
d=None,
report_types=[
"OTC_CASH_ACTIVITY",
"OTC_POSITIONS",
"OTC_MARGIN",
"OTC_MARGIN_EX_DEF",
"OTC_STATEMENT",
],
retry_count=0,
):
if retry_count > 20:
return
DATA_DIR = DAILY_DIR / "SG_reports"
sftp = get_sftp_client()
if d is None:
for f in sftp.listdir("OTC"):
if f.endswith("OTC_STATEMENT.xls"):
print(f)
sftp.get(f"OTC/{f}", localpath=DATA_DIR / f)
else:
for report_type in report_types[:-1]:
if f.endswith(f"{report_type}.csv"):
print(f)
sftp.get(f"OTC/{f}", localpath=DATA_DIR / f)
else:
continue
else:
file_list = sftp.listdir("OTC")
for report_type in report_types:
if report_type == "OTC_STATEMENT":
f = f"{d:%Y%m%d}_{report_type}.xls"
else:
f = f"{d:%Y%m%d}_{report_type}.csv"
if f not in file_list:
logger.info("File not here yet, trying again in 500s...")
logger.info(f"Try count: {retry_count}")
time.sleep(500)
sftp.close()
download_files(d, report_types, retry_count + 1)
else:
sftp.get(f"OTC/{f}", localpath=DATA_DIR / f)
sftp.close()
def collateral(d, engine):
df_activity = pd.read_csv(
DAILY_DIR / "SG_reports" / f"{d:%Y%m%d}_OTC_CASH_ACTIVITY.csv",
usecols=["Ticket Reference", "Record Type", "Currency", "Amount"],
)
df_position = pd.read_csv(
DAILY_DIR / "SG_reports" / f"{d:%Y%m%d}_OTC_POSITIONS.csv",
usecols=["Ticket Reference", "Reference Entity", "Mtm Value"],
)
df_activity = df_activity.loc[df_activity["Record Type"] == "VM"].set_index(
"Ticket Reference"
)
df_margin = pd.read_csv(
DAILY_DIR / "SG_reports" / f"{d:%Y%m%d}_OTC_MARGIN_EX_DEF.csv",
usecols=["Currency", "SG IMR"],
)
df_position = df_position.set_index("Ticket Reference")
# expired_trades
# df_position = df_position.append(
# pd.DataFrame({"Reference Entity": 'CDX-NAIGS29V1-5Y', "Mtm Value": 0.},
# index=['T2201711010000A3K20000045561220U']))
df = df_activity.join(df_position)
# expired trade (need to figure out how to get them from the report)
# df.loc['N201811090000A3K215946925849228U1', 'Mtm Value'] = 0.
# df.loc['N201811090000A3K215946925849228U1', 'Reference Entity'] = 'CDX-NAIGS31V1-5Y'
df["Collateral"] = df["Mtm Value"] - df["Amount"]
ref_entity = df["Reference Entity"].str.split("-", expand=True)
del ref_entity[0]
ref_entity.columns = ["to_split", "tenor"]
ref_entity = ref_entity.join(
ref_entity["to_split"].str.extract(r"(IG|HY|EUROPE)S(\d+)V(\d+)$", expand=True)
)
del ref_entity["to_split"]
ref_entity.columns = ["tenor", "index_type", "series", "version"]
ref_entity.index_type[ref_entity.index_type == "EUROPE"] = "EU"
df = df.join(ref_entity)
df = df.groupby(["index_type", "series", "tenor"])["Collateral"].sum()
positions = pd.read_sql_query(
"SELECT security_desc, folder, notional, currency "
"FROM list_cds_positions_by_strat(%s)",
engine,
params=(d.date(),),
)
instruments = positions.security_desc.str.split(expand=True)[[1, 3, 4]]
instruments.columns = ["index_type", "series", "tenor"]
instruments.series = instruments.series.str.extract(r"S(\d+)")
instruments.index_type[instruments.index_type == "EUR"] = "EU"
positions = positions.join(instruments)
del positions["security_desc"]
positions = positions.set_index(["index_type", "series", "tenor"])
df = positions.join(df)
def f(g):
g.Collateral = g.Collateral * g.notional / g.notional.sum()
return g
df = df.groupby(level=["index_type", "series", "tenor"]).apply(f)
df = df.groupby(["folder"]).agg({"Collateral": "sum", "currency": "first"})
df = df.reset_index("folder")
df = df.rename(
columns={"folder": "Strategy", "currency": "Currency", "Collateral": "Amount"}
)
df.Strategy = df.Strategy.map(
{
"HEDGE_MBS": "MBSCDSCSH",
"SER_ITRXCURVE": "SER_ITRXCVCSH",
"SER_IGCURVE": "SER_IGCVECSH",
"HYOPTDEL": "HYCDSCSH",
"IGOPTDEL": "IGCDSCSH",
}
)
df_margin["account"] = "SGNSCLMASW"
df_margin = df_margin.rename(columns={"SG IMR": "amount", "Currency": "currency"})
df_margin["date"] = d
try:
df_margin.to_sql("fcm_im", engine, if_exists="append", index=False)
except IntegrityError:
pass
df["date"] = d
return df
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