from thefirstock import thefirstock import os import time import pandas as pd import logging from datetime import datetime, timedelta import pytz import stat import requests import urllib.parse # Set IST timezone ist = pytz.timezone('Asia/Kolkata') # Custom formatter to convert time to IST class ISTFormatter(logging.Formatter): def formatTime(self, record, datefmt=None): # Set timezone to IST 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') # Set up global logger logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) logger.propagate = False formatter = ISTFormatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') # Console handler console_handler = logging.StreamHandler() console_handler.setLevel(logging.INFO) console_handler.setFormatter(formatter) logger.addHandler(console_handler) def login(client): userId = client[0] password = client[1] TOTP = client[2] vendorCode = client[3] apiKey = client[4] logger.info("Attempting to login") login_response = thefirstock.firstock_login( userId=userId, password=password, TOTP=TOTP, vendorCode=vendorCode, apiKey=apiKey ) if login_response['status'] == 'success': logger.info("Login successful") else: logger.error("Login failed: %s", login_response) def adjust_intv(row): if row['into'] > row['intc']: return -abs(row['intv']) elif row['into'] < row['intc']: return abs(row['intv']) else: return 0 def fetch_time_price_series(exchange, tradingSymbol, start_time, end_time, userId, interval): ''' exchange='NSE' tradingSymbol='Nifty 50' ''' # Tracing: Print all input parameters logger.info(f"fetch_time_price_series called with params: exchange={exchange}, tradingSymbol={tradingSymbol}, " f"start_time={start_time}, end_time={end_time}, userId={userId}, interval={interval}") try: response = thefirstock.firstock_TimePriceSeries( userId=userId, exchange=exchange, tradingSymbol=tradingSymbol, startTime=start_time, endTime=end_time, interval=interval ) if response.get("status") == "success": data = response.get("data", []) return pd.DataFrame(data) else: logger.error(f"Error: {response.get('status')} {response}") return pd.DataFrame() except Exception as e: logger.error(f"Error fetching time price series: {e}") return pd.DataFrame() def main(userId, clientRootFolder): # Specify the day, month, and year day = 16 month = 10 year = 2024 # Create the fixed start time with the specified date and time start_time_fixed = datetime(year, month, day, 9, 15, 0, 0, tzinfo=ist) trading_end_time = datetime(year, month, day, 15, 30, 0, 0, tzinfo=ist) symbols = [ 'NFO:BANKNIFTY16OCT24P51300', 'NFO:BANKNIFTY16OCT24P51400', 'NFO:BANKNIFTY16OCT24P51500', 'NFO:BANKNIFTY16OCT24P51600', 'NFO:BANKNIFTY16OCT24P51700', 'NFO:BANKNIFTY16OCT24P51800', 'NFO:BANKNIFTY16OCT24P51900', 'NFO:BANKNIFTY16OCT24P52000', 'NFO:BANKNIFTY16OCT24P52100', 'NFO:BANKNIFTY16OCT24C51500', 'NFO:BANKNIFTY16OCT24C51600', 'NFO:BANKNIFTY16OCT24C51700', 'NFO:BANKNIFTY16OCT24C51800', 'NFO:BANKNIFTY16OCT24C51900', 'NFO:BANKNIFTY16OCT24C52000', 'NFO:BANKNIFTY16OCT24C52100', 'NFO:BANKNIFTY16OCT24C52200', 'NFO:BANKNIFTY16OCT24C52300', 'NFO:BANKNIFTY16OCT24C52400', 'NFO:NIFTY17OCT24P24750', 'NFO:NIFTY17OCT24P24800', 'NFO:NIFTY17OCT24P24850', 'NFO:NIFTY17OCT24P24900', 'NFO:NIFTY17OCT24P24950', 'NFO:NIFTY17OCT24P25000', 'NFO:NIFTY17OCT24P25050', 'NFO:NIFTY17OCT24P25100', 'NFO:NIFTY17OCT24P25150', 'NFO:NIFTY17OCT24C24850', 'NFO:NIFTY17OCT24C24900', 'NFO:NIFTY17OCT24C24950', 'NFO:NIFTY17OCT24C25000', 'NFO:NIFTY17OCT24C25050', 'NFO:NIFTY17OCT24C25100', 'NFO:NIFTY17OCT24C25150', 'NFO:NIFTY17OCT24C25200', 'NFO:NIFTY17OCT24C25250', 'NFO:NIFTY17OCT24C25300', 'BFO:SENSEX24O1881400PE', 'BFO:SENSEX24O1881500PE', 'BFO:SENSEX24O1881600PE', 'BFO:SENSEX24O1881700PE', 'BFO:SENSEX24O1881800PE', 'BFO:SENSEX24O1881900PE', 'BFO:SENSEX24O1882000PE', 'BFO:SENSEX24O1882100PE', 'BFO:SENSEX24O1882200PE', 'BFO:SENSEX24O1881600CE', 'BFO:SENSEX24O1881700CE', 'BFO:SENSEX24O1881800CE', 'BFO:SENSEX24O1881900CE', 'BFO:SENSEX24O1882000CE', 'BFO:SENSEX24O1882100CE', 'BFO:SENSEX24O1882200CE', 'BFO:SENSEX24O1882300CE', 'BFO:SENSEX24O1882400CE', 'BFO:SENSEX24O1882500CE', 'NFO:MIDCPNIFTY21OCT24P13000', 'NFO:MIDCPNIFTY21OCT24P13025', 'NFO:MIDCPNIFTY21OCT24P13050', 'NFO:MIDCPNIFTY21OCT24P13075', 'NFO:MIDCPNIFTY21OCT24P13100', 'NFO:MIDCPNIFTY21OCT24P13125', 'NFO:MIDCPNIFTY21OCT24P13150', 'NFO:MIDCPNIFTY21OCT24P13175', 'NFO:MIDCPNIFTY21OCT24P13200', 'NFO:MIDCPNIFTY21OCT24C13050', 'NFO:MIDCPNIFTY21OCT24C13075', 'NFO:MIDCPNIFTY21OCT24C13100', 'NFO:MIDCPNIFTY21OCT24C13125', 'NFO:MIDCPNIFTY21OCT24C13150', 'NFO:MIDCPNIFTY21OCT24C13175', 'NFO:MIDCPNIFTY21OCT24C13200', 'NFO:MIDCPNIFTY21OCT24C13225', 'NFO:MIDCPNIFTY21OCT24C13250', 'NFO:MIDCPNIFTY21OCT24C13275', 'NFO:FINNIFTY22OCT24P23550', 'NFO:FINNIFTY22OCT24P23600', 'NFO:FINNIFTY22OCT24P23650', 'NFO:FINNIFTY22OCT24P23700', 'NFO:FINNIFTY22OCT24P23750', 'NFO:FINNIFTY22OCT24P23800', 'NFO:FINNIFTY22OCT24P23850', 'NFO:FINNIFTY22OCT24P23900', 'NFO:FINNIFTY22OCT24P23950', 'NFO:FINNIFTY22OCT24C23650', 'NFO:FINNIFTY22OCT24C23700', 'NFO:FINNIFTY22OCT24C23750', 'NFO:FINNIFTY22OCT24C23800', 'NFO:FINNIFTY22OCT24C23850', 'NFO:FINNIFTY22OCT24C23900', 'NFO:FINNIFTY22OCT24C23950', 'NFO:FINNIFTY22OCT24C24000', 'NFO:FINNIFTY22OCT24C24050', 'NFO:FINNIFTY22OCT24C24100' ] #symbols = ["NFO:NIFTY05SEP24C25300" ] #symbols = ["BFO:SENSEX24AUG81400PE", "NFO:NIFTY05SEP24C25300"] intervalList = [ 5 , 10 , 15, 30 ] intervalList = [ 5 ] for interval in intervalList: for symbol in symbols: time.sleep(1) logger.info(f"symbol = {symbol} ") exchange, tradingSymbol = symbol.split(':') start_time_str = start_time_fixed.strftime("%d/%m/%Y %H:%M:%S") end_time_str = trading_end_time.strftime("%d/%m/%Y %H:%M:%S") interval_str = str(interval) df = fetch_time_price_series(exchange, tradingSymbol, start_time_str, end_time_str, userId, interval_str) if not df.empty: srcfolderName = os.path.join( clientRootFolder , 'input' ) if not os.path.exists(srcfolderName): os.makedirs(srcfolderName) os.chmod(srcfolderName, stat.S_IRWXU | stat.S_IRWXG | stat.S_IRWXO) srcFileName = os.path.join(srcfolderName, f"{tradingSymbol}_{interval_str}.csv") df.to_csv(srcFileName, index=False) # Logging the filtered and updated DataFrame logger.debug(f"{tradingSymbol} {interval_str} data:\n{df}") encoded_file_path = urllib.parse.quote(srcFileName) # Construct the URL with the encoded file argument url = f"http://143.244.141.41/php/data.php?file={encoded_file_path}" # Make the GET request try: response = requests.get(url) # Log the status code or response logger.debug(f"Request made to {url} - Status Code: {response.status_code}") except requests.exceptions.RequestException as e: logger.error(f"Failed to make request to {url} - Error: {e}") time.sleep(1) if __name__ == "__main__": #clientDetails = ['RA1383', 'O9i8u7y6##', '13061983', 'RA1383_API', '491bf9166cfe0e7c419ac071f3fca6e1'] #clientDetails = ['DB1485', '$L10n-one', '14121985', 'DB1485_API', 'e64881301306ce087b1108a74e174e82'] clientDetails = ['TT1582', 'O9i8u7y6##', '15111982', 'TT1582_API', 'ed87fa73888bc882c5d79bf832c0f9eb'] userId = clientDetails[0] clientRootFolder = f"/var/www/html/clientData/{userId}" os.chdir(clientRootFolder) login(clientDetails) main(userId, clientRootFolder)