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from dataclasses import dataclass
import datetime
from typing import ClassVar, Literal
from enum import Enum
from serenitas.utils.db2 import dbconn
FIRMNESS = Literal["FIRM", "INDICATIVE"]
class AssetClass(Enum):
ABS = "ABS"
CD = "CD"
TRS = "TRS"
TR = "TR"
def maturity_dt(d):
try:
return datetime.date(
int(d["maturityyear"]), int(d["maturitymonth"]), int(d["maturityday"])
)
except (
ValueError,
KeyError,
): # Sometimes maturity isn't included but we still have tenor
return
class MarkitQuote:
_conn: ClassVar
_registry: ClassVar[dict] = {}
_table_name: ClassVar[str | None]
_sql_insert: ClassVar[str]
_insert_queue: ClassVar[list]
@classmethod
def init_dbconn(cls, conn=None):
cls._conn = conn or dbconn(
"serenitasdb", application_name="markit_quotes", autocommit=True
)
def __init_subclass__(cls, asset_class, table_name: str):
cls._registry[asset_class] = cls
cls._table_name = table_name
place_holders = ",".join(["%s"] * len(cls.__annotations__))
cls._sql_insert = f"INSERT INTO {table_name}({','.join(cls.__annotations__)}) VALUES({place_holders}) ON CONFLICT DO NOTHING"
cls._insert_queue = []
def __class_getitem__(cls, asset_class: AssetClass):
return cls._registry[asset_class]
@classmethod
def enrich_dict(cls, d):
return d | {
"msg_id": d["message"]["id"],
"quotedate": datetime.datetime.fromtimestamp(d["receiveddatetime"] / 1000),
"quotesource": d["sourceshortname"],
}
@classmethod
def from_markit_line(cls, d):
return cls.from_dict(cls.enrich_dict(d))
@classmethod
def from_dict(cls, d):
return cls(**{k: d[k] for k in cls.__annotations__ if k in d})
@classmethod
def already_uploaded(cls):
with cls._conn.cursor(binary=True) as c:
c.execute(f"SELECT distinct msg_id AS msg_id FROM {cls._table_name}")
return set(row.msg_id for row in c)
def stage(self):
self._insert_queue.append(
tuple([getattr(self, col) for col in self.__annotations__])
)
@classmethod
def commit(cls):
with cls._conn.cursor() as c:
c.executemany(cls._sql_insert, cls._insert_queue)
cls._conn.commit()
cls._insert_queue.clear()
# TODO
# @property
# def message(self):
# return QuoteDetails.from_tradeid(self.msg_id)
@dataclass
class SingleNameQuote(
MarkitQuote, asset_class=AssetClass.CD, table_name="markit_singlename_quotes"
):
quoteid: int
msg_id: str
quotesource: str
confidence: int
redcode: str = None
ticker: str = None
maturity: datetime.date = None
tenor: int = None
runningcoupon: int = None
bidconventionalspread: float = None
bidupfront: float = None
bidsize: float = None
askconventionalspread: float = None
askupfront: float = None
asksize: float = None
firmness: FIRMNESS = None
quotedate: datetime.datetime = None
@classmethod
def enrich_dict(cls, d):
return {
"maturity": maturity_dt(d),
"tenor": f"{d['tenor']}Y",
} | super().enrich_dict(d)
@dataclass
class BondQuote(
MarkitQuote, asset_class=AssetClass.ABS, table_name="markit_bond_quotes"
):
quoteid: int
msg_id: str
quotesource: str
confidence: int
identifier: str = None
cusip: str = None
bidprice: float = None
bidsize: float = None
askprice: float = None
asksize: float = None
pricelevel: float = None
subtype: str = None
quotetype: str = None
firmness: FIRMNESS = None
quotedate: datetime.datetime = None
@classmethod
def enrich_dict(cls, d):
return {
"identifier": d["internalinstrumentidentifier"],
"pricelevel": d.get("pricelevelnormalized"),
} | super().enrich_dict(d)
@dataclass
class TRSQuote(MarkitQuote, asset_class=AssetClass.TRS, table_name="markit_trs_quotes"):
quoteid: int
msg_id: str
quotesource: str
confidence: int
maturity: datetime.date
identifier: str = None
bidlevel: float = None
asklevel: float = None
nav: float = None
ref: float = None
firmness: FIRMNESS = None
funding_benchmark: str = None
quotedate: datetime.datetime = None
@classmethod
def enrich_dict(cls, d):
return {
"identifier": d["ticker"],
"ref": d.get("reference"),
"nav": d.get("inavparsed"),
"funding_benchmark": d.get("parsedbenchmark"),
"maturity": maturity_dt(d),
} | super().enrich_dict(d)
@dataclass
class TrancheQuote(
MarkitQuote, asset_class=AssetClass.TR, table_name="markit_tranche_quotes"
):
quoteid: int
msg_id: str
quotesource: str
confidence: int
maturity: datetime.date
identifier: str = None
bidlevel: float = None
asklevel: float = None
nav: float = None
ref: float = None
attach: int = None
detach: int = None
tenor: int = 5
firmness: FIRMNESS = None
quotedate: datetime.datetime = None
@classmethod
def enrich_dict(cls, d):
return {
"identifier": d["ticker"],
"ref": d.get("reference"),
"nav": d.get("inavparsed"),
"funding_benchmark": d.get("parsedbenchmark"),
"maturity": maturity_dt(d),
} | super().enrich_dict(d)
|
