# Define your trading pair and timeframe symbol = 'BTC/USDT' tim

import ccxt
import pandas as pd
import time

# Initialize the Binance exchange API
exchange = ccxt.binance({
'apiKey': BTCUSDT.P 'HrTNX3qb64fYm1k9acw45Qy1bUBPDGHVhH43fESGg3UkysUAc1Yo7wwcLyXAEQT7',
'secret': 'M5vjVCyNaNoblpgMut2hcQwj9dbqfxSmGCL4jR78C5PaSiXrKyQi9MtOIHn3C4Y6',
})

# Define your trading pair and timeframe
symbol = 'BTC/USDT'
timeframe = '1h'

# Bollinger Bands parameters
period = 20 # Lookback period
std_dev = 2 # Standard deviation multiplier

while True:
# Fetch historical OHLCV data
ohlcv = exchange.fetch_ohlcv(symbol, timeframe, limit=period + 1)

# Create a pandas DataFrame
df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])

# Calculate Bollinger Bands
df['sma'] = df['close'].rolling(window=period).mean()
df['std'] = df['close'].rolling(window=period).std()
df['upper_band'] = df['sma'] + (df['std'] * std_dev)
df['lower_band'] = df['sma'] - (df['std'] * std_dev)

# Get the latest data
latest_data = df.iloc[-1]

# Check for buy/sell signals
if latest_data['close'] < latest_data['lower_band']:
# Place a buy order here
print('Bullish Buy Signal - Place Buy Order')

elif latest_data['close'] > latest_data['upper_band']:
# Place a sell order here
print('Bearish Sell Signal - Place Sell Order')

# Add a sleep to avoid overloading the exchange
time.sleep(60) # Sleep for 1 minute (adjust as needed)