import os import time import pandas as pd import pandas_ta as ta import logging from datetime import datetime, timedelta import pytz from thefirstock import thefirstock from typing import List import numpy as np import requests import sys class StockDataFetcher: def __init__(self, client_details: List[str]): self.client_details = client_details self.user_id = client_details[0] self.ist = pytz.timezone('Asia/Kolkata') self.logger = self.setup_logger() print("\n\n\n\n") self.logger.info("**************************") def setup_logger(self) -> logging.Logger: logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) if not logger.handlers: formatter = self.ISTFormatter('%(asctime)s - %(levelname)s - %(message)s') console_handler = logging.StreamHandler() console_handler.setFormatter(formatter) logger.addHandler(console_handler) logging.getLogger().handlers.clear() return logger class ISTFormatter(logging.Formatter): def formatTime(self, record, datefmt=None): ist = pytz.timezone('Asia/Kolkata') record_time = datetime.fromtimestamp(record.created, tz=ist) return record_time.strftime(datefmt or '%Y-%m-%d %H:%M:%S') def login(self): try: response = thefirstock.firstock_login(*self.client_details) if response.get("status") == "success": self.logger.info("Login successful") else: self.logger.error(f"Login failed: {response}") except Exception as e: self.logger.error(f"Login error: {e}") def fetch_time_price_series( self, exchange: str, trading_symbol: str, start_time: str, end_time: str, interval: str ) -> pd.DataFrame: print('\n') self.logger.info(f"----------------------------------") self.logger.info(f"Fetching data for {trading_symbol}") self.logger.info(f"----------------------------------") try: response = thefirstock.firstock_TimePriceSeries( userId=self.user_id, exchange=exchange, tradingSymbol=trading_symbol, startTime=start_time, endTime=end_time, interval=interval, ) if response.get("status") == "success": return pd.DataFrame(response.get("data", [])) else: self.logger.error(f"Fetch failed: {response}") return pd.DataFrame() except Exception as e: self.logger.error(f"Error fetching series: {e}") return pd.DataFrame() def getStepValueAndShortSymbol(self, symbol): tmp_symbol=symbol if symbol == 'NSE:Nifty 50': step_value = 50 tmp_symbol='NIFTY' elif symbol == 'NSE:Nifty Bank': step_value = 100 tmp_symbol='BANKNIFTY' elif symbol == 'NSE:NIFTY MID SELECT': step_value = 25 tmp_symbol='MIDCPNIFTY' elif symbol == 'NSE:Nifty Fin Service': step_value = 50 tmp_symbol='FINNIFTY' elif symbol == 'BSE:SENSEX': step_value = 100 tmp_symbol='SENSEX' else: step_value = 50 return step_value, tmp_symbol def calculate_supertrend(self, df: pd.DataFrame, atr_period: int, multiplier: float) -> pd.DataFrame: df[['high', 'low', 'close']] = df[['inth', 'intl', 'intc']].apply(pd.to_numeric, errors='coerce') supertrend = df.ta.supertrend(high='high', low='low', close='close', length=atr_period, multiplier=multiplier) supertrend['ST_Signal'] = supertrend['SUPERTd_21_6.3'].apply(lambda x: 'Buy' if x == 1 else 'Sell') #supertrend['ST_Signal'] = supertrend['SUPERTd_6_13.0'].apply(lambda x: 'Buy' if x == 1 else 'Sell') return pd.concat([df, supertrend], axis=1) def process_symbol_data(self, symbol: str, interval: int, start_time: datetime, end_time: datetime): step_value, tmp_symbol = self.getStepValueAndShortSymbol(symbol) exchange, trading_symbol = symbol.split(":") # Fetch Data if exchange == 'NSE' and trading_symbol == 'Nifty 50': exchange = 'NFO' trading_symbol = 'NIFTY27FEB25F' df = self.fetch_time_price_series( exchange, trading_symbol, start_time.strftime("%d/%m/%Y %H:%M:%S"), end_time.strftime("%d/%m/%Y %H:%M:%S"), str(interval), ) else: df = self.fetch_time_price_series( exchange, trading_symbol, start_time.strftime("%d/%m/%Y %H:%M:%S"), end_time.strftime("%d/%m/%Y %H:%M:%S"), str(interval), ) if df.empty: self.logger.warning(f"No data for {trading_symbol}") return # Preprocess timestamps and ensure data integrity #df['time'] = pd.to_datetime(df['time']).dt.tz_localize(self.ist) df['time'] = pd.to_datetime(df['time'], errors='coerce', dayfirst=True) if not df['time'].dt.tz: df['time'] = df['time'].dt.tz_localize(self.ist) df = df[~((df['time'].dt.hour == 9) & (df['time'].dt.minute < 15))] df = df[~(((df['time'].dt.hour == 15) & (df['time'].dt.minute >= 31)) | ((df['time'].dt.hour > 15) & (df['time'].dt.hour < 23)))] current_time = datetime.now(self.ist) df = df.sort_values(by='time', ascending=True) df['intc'] = pd.to_numeric(df['intc'], errors='coerce') df = self.calculate_supertrend(df, 21, 6.3) #df = self.calculate_supertrend(df, 6, 13) df['SUPERTd_21_6.3'] = pd.to_numeric(df['SUPERTd_21_6.3'], errors='coerce') #df['SUPERTd_6_13.0'] = pd.to_numeric(df['SUPERTd_6_13.0'], errors='coerce') latest_date = df['time'].dt.date.max() df = df[df['time'].dt.date == latest_date] ft_high = df.iloc[0]['inth'] ft_low = df.iloc[0]['intl'] df['FT_High'] = ft_high df['FT_Low'] = ft_low df['FT_High'] = pd.to_numeric(df['FT_High'], errors='coerce') df['FT_Low'] = pd.to_numeric(df['FT_Low'], errors='coerce') df = df.loc[:, ['time', 'intc', 'ST_Signal', 'FT_High', 'FT_Low']] current_time_ist = datetime.now(self.ist).strftime('%H:%M') cutoff_time = "09:16" if current_time_ist <= cutoff_time: print(f"Current Time {current_time_ist} is less than or equal to {cutoff_time}. Do Nothing.") return current_time = datetime.now(self.ist) df['elapsedTime'] = (current_time - df['time']).dt.total_seconds() // 60 df = df[df['elapsedTime'] >= interval] if symbol == 'NSE:Nifty 50': step_value = 50 margin = 20 tmp_symbol='NIFTY' elif symbol == 'NSE:Nifty Bank': step_value = 100 margin = 50 tmp_symbol='BANKNIFTY' elif symbol == 'NSE:NIFTY MID SELECT': step_value = 25 margin = 10 tmp_symbol='MIDCPNIFTY' elif symbol == 'NSE:Nifty Fin Service': step_value = 50 margin = 20 tmp_symbol='FINNIFTY' elif symbol == 'BSE:SENSEX': step_value = 100 margin = 50 tmp_symbol='SENSEX' else: step_value = 50 margin = 10 tmp_symbol='XXX' df['instrument'] = df['intc'].apply(lambda x: int((int(x / step_value) * step_value))) #print(df) # Initialize flags and variables st_signal = df.iloc[1]['ST_Signal'] st_instrument = df.iloc[1]['instrument'] st_time = df.iloc[1]['time'] tickTime_str = st_time.strftime("%Y-%m-%d_%H:%M:%S") first_buy_order_placed = False first_sell_order_placed = False if st_signal == 'Buy': print(f"Place first Buy order. Instrument {st_instrument}. Time {st_time}. Close Price {df.iloc[1]['intc']}") first_buy_order_placed = True buy_order_time = st_time instrument = str(tmp_symbol)+str(st_instrument) + 'CE' closePrice = str(df.iloc[1]['intc']) signal = st_signal.upper() orderType = 'first' #self.createEntry(tickTime_str, instrument, closePrice, signal, orderType) elif st_signal == 'Sell': st_instrument = step_value + st_instrument print(f"Place first Sell order. Instrument {st_instrument}. Time {st_time}. Close Price {df.iloc[1]['intc']}") first_sell_order_placed = True sell_order_time = st_time instrument = str(tmp_symbol)+str(st_instrument) + 'PE' closePrice = str(df.iloc[1]['intc']) signal = st_signal.upper() orderType = 'first' #self.createEntry(tickTime_str, instrument, closePrice, signal, orderType) # Initialize flags for top-up orders topup_buy_order_placed = False topup_sell_order_placed = False topup_buy_order_price = 0.0 topup_sell_order_price = 0.0 new_buy_topup_allowed = True new_sell_topup_allowed = True # Iterate over the DataFrame starting from the 3rd row (index 2) for i in range(2, len(df)): row = df.iloc[i] current_signal = row['ST_Signal'] current_instrument = row['instrument'] current_time = row['time'] current_intc = row['intc'] current_FT_Low = row['FT_Low'] current_FT_High = row['FT_High'] tickTime_str = current_time.strftime("%Y-%m-%d_%H:%M:%S") #print(f"Tick Time: {tickTime_str}, Signal: {current_signal}, Instrument: {current_instrument}, Time: {current_time}, INTC: {current_intc}, FT Low: {current_FT_Low}, FT High: {current_FT_High}") # Detect change in ST_Signal and place first order accordingly if current_signal != st_signal: # Check if signal has changed if current_signal == 'Buy' and not first_buy_order_placed: #print(f"Place first Buy order. Instrument {current_instrument}. Time {current_time}. Close Price {current_intc}") first_buy_order_placed = True first_sell_order_placed = False topup_buy_order_placed = False topup_sell_order_placed = False buy_order_time = current_time instrument = str(tmp_symbol)+str(current_instrument) + 'CE' closePrice = str(current_intc) signal = current_signal.upper() orderType = 'first' self.createEntry(tickTime_str, instrument, closePrice, signal, orderType) elif current_signal == 'Sell' and not first_sell_order_placed: current_instrument = step_value + current_instrument #print(f"Place first Sell order. Instrument {current_instrument}. Time {current_time}. Close Price {current_intc}") first_sell_order_placed = True first_buy_order_placed = False topup_buy_order_placed = False topup_sell_order_placed = False sell_order_time = current_time instrument = str(tmp_symbol)+str(current_instrument) + 'PE' closePrice = str(current_intc) signal = current_signal.upper() orderType = 'first' self.createEntry(tickTime_str, instrument, closePrice, signal, orderType) # Update the signal for the next iteration st_signal = current_signal if topup_buy_order_price != 0.0 and current_intc > (topup_buy_order_price + margin) and not new_buy_topup_allowed: new_buy_topup_allowed = True #print(i, current_time, current_intc) continue if topup_sell_order_price != 0.0 and current_intc < (topup_sell_order_price - margin) and not new_sell_topup_allowed: new_sell_topup_allowed = True #print(i, current_time, current_intc) continue # Place top-up Buy or Sell orders based on the conditions if topup_buy_order_placed or topup_sell_order_placed: # If intc is within FT_Low and FT_High, reset the flag to allow new orders if current_intc >= current_FT_Low and current_intc <= current_FT_High: if new_buy_topup_allowed: topup_buy_order_placed = False if new_sell_topup_allowed: topup_sell_order_placed = False else: continue # Skip this row if a top-up order has already been placed # Check if the current row's ST_Signal is 'Buy' and place a top-up Buy order if current_signal == 'Buy' and first_buy_order_placed and buy_order_time != current_time: if current_intc < current_FT_Low or current_intc > current_FT_High: if not topup_buy_order_placed and new_buy_topup_allowed: #print(f"Top-up Buy order placed for row {i} at time {current_time}. Instrument {current_instrument}. Close Price {current_intc}") topup_buy_order_placed = True topup_buy_order_price = current_intc new_buy_topup_allowed = False instrument = str(tmp_symbol)+str(current_instrument) + 'CE' closePrice = str(current_intc) signal = current_signal.upper() orderType = 'topUp' self.createEntry(tickTime_str, instrument, closePrice, signal, orderType) # Check if the current row's ST_Signal is 'Sell' and place a top-up Sell order elif current_signal == 'Sell' and first_sell_order_placed and sell_order_time != current_time: if current_intc < current_FT_Low or current_intc > current_FT_High: if not topup_sell_order_placed and new_sell_topup_allowed: current_instrument = step_value + current_instrument #print(f"Top-up Sell order placed for row {i} at time {current_time}. Instrument {current_instrument}. Close Price {current_intc}") topup_sell_order_placed = True topup_sell_order_price = current_intc new_sell_topup_allowed = False instrument = str(tmp_symbol)+str(current_instrument) + 'PE' closePrice = str(current_intc) signal = current_signal.upper() orderType = 'topUp' self.createEntry(tickTime_str, instrument, closePrice, signal, orderType) def createEntry(self, tickTime_str, instrument, closePrice, signal, orderType): url = "http://143.244.141.41/php/createEntry.php" # Replace with your actual URL # Define the parameters params = { 'tickTime': str(tickTime_str), 'instrument': str(instrument), 'closePrice': str(closePrice), 'signal': str(signal), 'orderType': str(orderType) } # Perform the GET request self.logger.info(f"Get Request with params: {params}") response = requests.get(url, params=params) if response.status_code != 200: self.logger.error(f"Request failed with status code: {response.status_code}") if response.text != '': self.logger.error(response.text + "\n") # Print error message if available else: self.logger.info(f"Request success: {response.text}\n") def fetch_all_data(self): symbols = { "NSE:Nifty 50": 7, "NSE:Nifty Bank": 7, "NSE:NIFTY MID SELECT": 7, "NSE:Nifty Fin Service": 7, "BSE:SENSEX": 7 } for interval in [1]: for symbol, days in symbols.items(): time.sleep(1) start_time = datetime.now(self.ist) - timedelta(days=days) end_time = datetime.now(self.ist).replace(hour=15, minute=30) self.process_symbol_data(symbol, interval, start_time, end_time) if __name__ == "__main__": client_details = ['GA0810', 'O9i8u7y6$$', '08101994', 'GA0810_API', 'ada14c5f73f182ca724b90c5dde1e72d'] stock_fetcher = StockDataFetcher(client_details) stock_fetcher.login() stock_fetcher.fetch_all_data()