File size: 3,986 Bytes
9484d1a c0b3ebc 9484d1a c0b3ebc 9484d1a 522c1ed 9484d1a c0b3ebc 9484d1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 | import time
from datetime import date, datetime, timezone
import pandas as pd
from pandas.errors import EmptyDataError
from loguru import logger
from sqlalchemy import create_engine, text
from src.config import DB_URL, GarchParams
engine = None
if DB_URL:
try:
engine = create_engine(DB_URL)
except Exception:
logger.exception(f"Invalid DB_URL format. Length of DB_URL: {len(DB_URL)}")
engine = None
else:
logger.warning("DB_URL is not set. Database features will be disabled.")
def create_preds_table() -> None:
if engine is None:
logger.warning("Database not configured, skipping table creation.")
return
sql_create = text("""
CREATE TABLE IF NOT EXISTS garch_preds (
id INTEGER GENERATED BY DEFAULT AS IDENTITY PRIMARY KEY,
ticker VARCHAR(10) NOT NULL,
execution_time TIMESTAMP DEFAULT NOW(),
target_date DATE NOT NULL,
model_config VARCHAR(20) NOT NULL,
prediction DOUBLE PRECISION NOT NULL,
CONSTRAINT unique_pred UNIQUE (ticker, target_date, model_config)
);
""")
with engine.begin() as conn:
conn.execute(sql_create)
logger.info("Succesfully created table 'garch_preds' or table exists")
def store_preds(
ticker: str, pred: float, target_date: date, params: GarchParams
) -> None:
if engine is None:
logger.info(f"Skipping DB save for {ticker} (DB not configured)")
return
execution_time = datetime.now(timezone.utc)
pred = float(pred)
model_config = "_".join(str(atr) for atr in vars(params).values())
sql_insert = text("""
INSERT INTO garch_preds (ticker, target_date, prediction, execution_time, model_config)
VALUES (:ticker, :target_date, :prediction, :execution_time, :model_config)
ON CONFLICT (ticker, target_date, model_config)
DO UPDATE SET
prediction = EXCLUDED.prediction,
execution_time = EXCLUDED.execution_time;
""")
with engine.begin() as conn:
conn.execute(
sql_insert,
{
"ticker": ticker,
"target_date": target_date,
"execution_time": execution_time,
"model_config": model_config,
"prediction": pred,
},
)
logger.info(f"Stored prediction for {ticker} (Target: {target_date})")
def get_error_data() -> pd.DataFrame:
error_df = None
if engine is None:
raise Exception("Could not connect to DB")
attempts = 10
for i in range(attempts):
try:
sql_extract = text("""
SELECT p.ticker, p.target_date, p.model_config, gp.error_abs, gp.error_rel, gp.error_sq, gp.error_raw
FROM garch_performance gp
JOIN garch_preds p
ON gp.prediction_id = p.id
WHERE p.target_date < CURRENT_DATE
AND p.target_date >= CURRENT_DATE - INTERVAL '10 days'
""")
with engine.begin() as conn:
error_df = pd.read_sql(sql_extract, conn)
logger.info("Got performance data for last week from DB")
logger.debug(f"Error DF rows: {error_df.count()}")
if error_df is not None and not error_df.empty:
break
logger.debug(
f"Attempt {i + 1}/{attempts}: Could not get data from 'garch_performance' DB. Retrying..."
)
except Exception as e:
logger.debug(
f"Attempt {i + 1}/{attempts}: Exception fetching data: {e}. Retrying..."
)
if i < attempts - 1:
time.sleep(5)
if error_df is None or error_df.empty:
logger.error(
"Could not get data from 'garch_performance' DB\nMax attempt reached\nReturning error page"
)
raise EmptyDataError
return error_df
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