I used your code: import time
from binance.client import Client
from binance.enums import *
from binance.exceptions import BinanceAPIException
import pandas as pd
import requests
import json
import numpy as np
import pytz
import datetime as dt
import ccxt

date = dt.datetime.now().strftime("%m/%d/%Y %H:%M:%S")
print(date)

t = int(time.time()*1000 - 1000)
url = f"https://api.binance.com/api/v1/time?timestamp={t}"
r = requests.get(url)
result = json.loads(r.content)

# API keys and other configuration
API_KEY = ''
API_SECRET = ''

client = Client(API_KEY, API_SECRET)

STOP_LOSS_PERCENTAGE = -50
TAKE_PROFIT_PERCENTAGE = 100
MAX_TRADE_QUANTITY_PERCENTAGE = 100
POSITION_SIDE_SHORT = 'SELL'
POSITION_SIDE_LONG = 'BUY'
symbol = 'BTCUSDT'
quantity = 1
order_type = 'MARKET'
leverage = 100
max_trade_quantity_percentage = 1

client = Client(API_KEY, API_SECRET)

binance_futures = ccxt.binance({
       'apiKey': '',
       'secret': '',
       'enableRateLimit': True,  # enable rate limitation
       'options': {
           'defaultType': 'future',
           'adjustForTimeDifference': True
       }
   })

# Get server time and time difference

server_time = binance_futures.public_get_time()
print(f'Timestamp:{server_time}')

try:
    timestamp = int(time.time() * 1000) - (server_time - result['serverTime'])
    print(f'Timestamp: {timestamp}')
except KeyError:
    print(f"Error accessing 'serverTime' in API response. Response: {result}")
    timestamp = int(time.time() * 1000)

    time_difference = int(time.time() * 1000) - server_time - 500

    # Get current time adjusted for time difference
    current_time = int(time.time() * 1000) - time_difference

# Use adjusted timestamp in subsequent requests
balances = binance_futures.fetch_balance({'timestamp': current_time})
print(balances)

def get_klines(symbol, interval, lookback):
    url = "https://fapi.binance.com/fapi/v1/klines"
    start_time = (dt.datetime.now() - dt.timedelta(minutes=lookback))
    end_time = dt.datetime.now()
    query_params = f"?symbol={symbol}&interval={interval}&startTime={start_time}&endTime={end_time}"
    headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36'
    }
    try:
        response = requests.get(url + query_params, headers=headers)
        response.raise_for_status()
        data = response.json()
        if not data: # if data is empty, return None
            print('No data found for the given timeframe and symbol')
            return None
        ohlc = []
        for d in data:
            timestamp = dt.datetime.fromtimestamp(d[0]/1000).strftime('%Y-%m-%d %H:%M:%S')
            ohlc.append({
            'Open time': timestamp,
            'Open': float(d[1]),
            'High': float(d[2]),
            'Low': float(d[3]),
            'Close': float(d[4]),
            'Volume': float(d[5])
            })
        df = pd.DataFrame(ohlc)
        df.set_index('Open time', inplace=True)
        return df
    except requests.exceptions.RequestException as e:
        print(f'Error in get_klines: {e}')
        return None
df = get_klines('BTCUSDT', '1m', 44640)

def signal_generator(df):
    open = df.Open.iloc[-1]
    close = df.Close.iloc[-1]
    previous_open = df.Open.iloc[-2]
    previous_close = df.Close.iloc[-2]

    # Bearish pattern
    if (open>close and
    previous_open<previous_close and
    close<previous_open and
    open>=previous_close):
        return 'sell'

    # Bullish pattern
    elif (open<close and
    previous_open>previous_close and
    close>previous_open and
    open<=previous_close):
        return 'buy'

    # No clear pattern
    else:
        return ""

df = get_klines('BTCUSDT', '1m', 44640)
def order_execution(symbol, signal, max_trade_quantity_percentage, leverage):
    max_trade_quantity = None
    account_balance = binance_futures.fetch_balance()
    usdt_balance = 0
    for b in account_balance['assets']:
        if b['asset'] == 'USDT':
            usdt_balance = float(b['balance'])
            max_trade_quantity = usdt_balance * max_trade_quantity_percentage/100

    # Close long position if signal is opposite
    long_position = None
    short_position = None

    # Get current positions
    positions = binance_futures.fapiPrivateGetPositionRisk()
    for p in positions:
        if p['symbol'] == symbol and p['positionSide'] == 'LONG':
            long_position = p
        elif p['symbol'] == symbol and p['positionSide'] == 'SHORT':
            short_position = p

    # Close positions
    if long_position is not None:
        binance_futures.fapiPrivatePostOrder(symbol=symbol, side='SELL', type='MARKET', quantity=long_position['positionAmt'], positionSide='LONG', reduceOnly=True)
        time.sleep(1)
    if short_position is not None:
        binance_futures.fapiPrivatePostOrder(symbol=symbol, side='BUY', type='MARKET', quantity=short_position['positionAmt'], positionSide='SHORT', reduceOnly=True)
        time.sleep(1)
        print("Both positions closed.")

    # Place new order
    quantity = max_trade_quantity
    if signal == 'buy':
        position_side = 'BOTH'
        opposite_position = short_position
    elif signal == 'sell':
        position_side = 'BOTH'
        opposite_position = long_position
    else:
        print("Invalid signal. No order placed.")
        return

    if opposite_position is not None:
        quantity = min(max_trade_quantity, abs(float(opposite_position['positionAmt'])))

    price = None
    if signal == 'buy':
        order_type = 'TAKE_PROFIT_MARKET'
        price = binance_futures.fapiPublicGetTickerPrice({'symbol': symbol})['price']
    elif signal == 'sell':
        order_type = 'STOP_MARKET'
        price = binance_futures.fapiPublicGetTickerPrice({'symbol': symbol})['price']
        stop_price = price * (1 + STOP_LOSS_PERCENTAGE / 100)

    order = binance_futures.fapiPrivatePostOrder(symbol=symbol, side='BUY' if signal == 'buy' else 'SELL', type=order_type, quantity=quantity, price=price, stopPrice=stop_price, reduceOnly=False, positionSide=position_side, timeInForce='GTC', leverage=str(leverage))
    order_id = order['orderId']
    print(f"Placed {signal} order with order ID {order_id} and quantity {quantity}")
    time.sleep(1)

    # Set stop loss and take profit orders
    # Get the order details to determine the order price
    if signal == 'buy':
        take_profit_price = price * (1 + TAKE_PROFIT_PERCENTAGE / 100)
        stop_loss_price = price * (1 - STOP_LOSS_PERCENTAGE / 100)
    elif signal == 'sell':
        take_profit_price = price * (1 - TAKE_PROFIT_PERCENTAGE / 100)
        stop_loss_price = price * (1 + STOP_LOSS_PERCENTAGE / 100)

    # Set stop loss and take profit orders
    binance_futures.fapiPrivatePostOrder(symbol=symbol, side='SELL' if signal == 'buy' else 'BUY', type='TAKE_PROFIT_MARKET', quantity=quantity, price=take_profit_price, reduceOnly=True, positionSide=position_side, timeInForce='GTC', stopPrice=None)
    time.sleep(1)
    binance_futures.fapiPrivatePostOrder(symbol=symbol, side='SELL' if signal == 'buy' else 'BUY', type='STOP_MARKET', quantity=quantity, price=stop_loss_price, reduceOnly=True, positionSide=position_side, timeInForce='GTC', stopPrice=None)

    # Print order creation confirmation messages
    print(f"Placed stop loss order with stop loss price {stop_loss_price}")
    print(f"Placed take profit order with take profit price {take_profit_price}")
    time.sleep(1)
while True:
    df = get_klines('BTCUSDT', '1m', 44640)
    if df is not None:
        signal = signal_generator(df)
        if signal:
            print(f"The signal time is: {dt.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} :{signal}")
            order_execution('BTCUSDT', signal, MAX_TRADE_QUANTITY_PERCENTAGE, leverage)    
            df = get_klines('BTCUSDT', '1m', 44640)
        if df is not None:
            signal = signal_generator(df)
            if signal:
                print(f"The signal time is: {dt.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} :{signal}")
                order_execution('BTCUSDT', signal, MAX_TRADE_QUANTITY_PERCENTAGE, leverage)
                time.sleep(0.1)
But I getting ERROR: Traceback (most recent call last):
  File "c:\Users\Alan\.vscode\jew_bot\jew_bot\jew_bot.py", line 62, in <module>
    time_difference = int(time.time() * 1000) - server_time - 500
                      ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
TypeError: unsupported operand type(s) for -: 'int' and 'dict'