strike project django user selected strike file

 import pandas as pd

from django.db import connection

from  multistrikeoi.utlis import utils as u

from datetime import datetime,timedelta

today_string=None

yesterday_string=None

tomorrow_string=None

class UserSelectedPrice:

    def combined_oi_calculation(

        symbol,

        instrument,

        strikeprice,

        option_type,

        expiery,

        today,

        tomorrow,

    ):

        print(today)

        print(tomorrow)

        engine = connection

        df = pd.read_sql_query(

            f"""

            SELECT symbol, expiry_date, strike_price, created_at, ticker, instrument_name, option_type, open_interest FROM indiacharts.fno_prices fp 

            WHERE created_at > '{today}' AND created_at < '{tomorrow}'

            AND symbol = '{symbol}' AND instrument_name = '{instrument}' AND strike_price = {strikeprice}

            AND option_type = '{option_type}'

            ORDER BY created_at ASC

            """,

            con=engine,

        )

        df["created_at_ist"] = df["created_at"].apply(u.convert_utc_to_ist)

        df["created_at_ist"] = pd.to_datetime(df["created_at_ist"])

        df["rounded_created_at_ist"] = df["created_at_ist"].apply(

            u.round_to_nearest_5_minutes

        )

        # Group by rounded_created_at_ist and calculate the sum of open_interest

        oi_sum_df = (

            df.groupby("rounded_created_at_ist")["open_interest"].sum().reset_index()

        )

        df["rounded_created_at_ist"] = pd.to_datetime(df["rounded_created_at_ist"])

        oi_sum_df["rounded_created_at_ist"] = pd.to_datetime(

            oi_sum_df["rounded_created_at_ist"]

        )

        # Merge the DataFrames on 'rounded_created_at_ist'

        merged_df = pd.merge(df, oi_sum_df, on="rounded_created_at_ist", how="left")

        merged_df.rename(columns={"open_interest_y": "Combined OI"}, inplace=True)

        merged_df["expiry_date"] = merged_df["expiry_date"].astype(str)

        merged_df = merged_df[merged_df["expiry_date"] == expiery]

        return merged_df

    def get_historical_eod_data(

        symbol, instrument, strikeprice, option_type, expiery, yesterday_string

    ):

        engine = connection

        print("yesterday_string=",yesterday_string)

        df = pd.read_sql_query(

            f"""select symbol,expiry_date,strike_price,created_at,ticker, instrument_name,option_type,open_interest from indiacharts.fno_price_eod fpe 

            WHERE created_at ='{yesterday_string}'

            AND symbol = '{symbol}' AND instrument_name = '{instrument}' AND strike_price = {strikeprice}

            AND option_type = '{option_type}' 

            ORDER BY created_at ASC

                               """,

            con=engine,

        )

        # Calculate the sum of open_interest and add it as a new column

        combined_oi_eod = df["open_interest"].sum()

        df["Combined OI EOD"] = combined_oi_eod

        return df