Convert WebSocket TickData to Candlesticks(OHLC) with Python

				
					# Initialize a dictionary to store candlestick data for each token
candlestick_data_dict = {}

# Initialize variables for storing LTP values over 60 seconds
ltp_values_dict = {}

# Shared start time for all tokens
start_time_dict = {}

# List of tokens
tokens = ['26000', '26009', '1']  # Add more tokens as needed

# Initialize data structures for each token
for token in tokens:
    candlestick_data_dict[token] = pd.DataFrame(columns=['timestamp', 'open', 'high', 'low', 'close'])
    ltp_values_dict[token] = []
    start_time_dict[token] = get_next_minute_start()

while True:
    for token in tokens:
        # Simulating live data stream (replace this with your actual data retrieval logic)
        # For simplicity, we are using a random value as LTP.
        ltp = float(get_live_data(token))
        ltp_values_dict[token].append(ltp)

        # Check if 60 seconds have passed for the specific token
        if datetime.datetime.now() >= start_time_dict[token] + datetime.timedelta(seconds=60):
            # Calculate OHLC values
            open_price = ltp_values_dict[token][0]
            high_price = max(ltp_values_dict[token])
            low_price = min(ltp_values_dict[token])
            close_price = ltp_values_dict[token][-1]

            # Print OHLC values and current time
            print(f"{format_time(start_time_dict[token])} - Token: {token}, Open: {open_price}, High: {high_price}, Low: {low_price}, Close: {close_price}")

            # Create a new row of data
            new_data = pd.DataFrame({
                'timestamp': [start_time_dict[token]],
                'open': [open_price],
                'high': [high_price],
                'low': [low_price],
                'close': [close_price]
            })

            # Concatenate the new data with the existing candlestick_data for the token
            candlestick_data_dict[token] = pd.concat([candlestick_data_dict[token], new_data], ignore_index=True)

            # Clear the list for the next 60 seconds
            ltp_values_dict[token] = []

            # Update start time for the next 60-second interval for the specific token
            start_time_dict[token] = get_next_minute_start()

    # Wait for the next iteration
    time.sleep(.5)