I used your code: import time
from binance.client import Client
from binance.enums import *
from binance.exceptions import BinanceAPIException
from binance.helpers import round_step_size
import pandas as pd
import json
import numpy as np
import pytz
import datetime as dt
import ccxt
from decimal import Decimal
import requests
import hmac
import hashlib
API_KEY = ‘’
API_SECRET = ‘’

client = Client(API_KEY, API_SECRET)

# Set the endpoint and parameters for the request
url = “https://fapi.binance.com/fapi/v2/account”
timestamp = int(time.time() * 1000)
recv_window = 5000

params = {
“timestamp”: timestamp,
“recvWindow”: recv_window
}

# Sign the message using the Client’s secret key
message = ‘&’.join([f"{k}={v}" for k, v in params.items()])
signature = hmac.new(API_SECRET.encode(), message.encode(), hashlib.sha256).hexdigest()
params[‘signature’] = signature
leverage = 100

# Send the request using the requests library
response = requests.get(url, params=params, headers={‘X-MBX-APIKEY’: API_KEY})
account_info = response.json()

# Get the USDT balance and calculate the max trade size based on the leverage
usdt_balance = next((item for item in account_info[‘assets’] if item[“asset”] == “USDT”), {“balance”: 0})
max_trade_size = float(usdt_balance.get(“balance”, 0)) * leverage

# Get the current time and timestamp
now = dt.datetime.now()
date = now.strftime(“%m/%d/%Y %H:%M:%S”)
print(date)

timestamp = int(time.time() * 1000)

STOP_LOSS_PERCENTAGE = -50
TAKE_PROFIT_PERCENTAGE = 100
MAX_TRADE_QUANTITY_PERCENTAGE = 100
POSITION_SIDE_SHORT = ‘SELL’
POSITION_SIDE_LONG = ‘BUY’
quantity = 1
symbol = ‘BTC/USDT’
order_type = ‘market’
leverage = 100
max_trade_quantity_percentage = 1
binance_futures = ccxt.binance({
‘apiKey’: API_KEY,
‘secret’: API_SECRET,
‘enableRateLimit’: True, # enable rate limitation
‘options’: {
‘defaultType’: ‘future’,
‘adjustForTimeDifference’: True
},‘future’: {
‘sideEffectType’: ‘MARGIN_BUY’, # MARGIN_BUY, AUTO_REPAY, etc…
}
})

binance_futures = ccxt.binance({
‘apiKey’: API_KEY,
‘secret’: API_SECRET,
‘enableRateLimit’: True, # enable rate limitation
‘options’: {
‘defaultType’: ‘future’,
‘adjustForTimeDifference’: True
}
})
# Load the market symbols

try:
markets = binance_futures.load_markets()
except ccxt.BaseError as e:
print(f’Error fetching markets: {e}‘)
markets = []

if symbol in markets:
print(f"{symbol} found in the market")
else:
print(f"{symbol} not found in the market")

# Get server time and time difference

def get_server_time(exchange):
server_time = exchange.fetch_currencies()
return server_time[‘timestamp’]

def get_time_difference():
server_time = get_server_time(binance_futures)
local_time = int(time.time() * 1000)
time_difference = local_time - server_time
return time_difference
time.sleep(1)

def get_klines(symbol, interval, lookback):
url = “https://fapi.binance.com/fapi/v1/klines”
end_time = int(time.time() * 1000) # end time is now
start_time = end_time - (lookback * 60 * 1000) # start time is lookback minutes ago
symbol = symbol.replace(“/”, “”) # remove slash from symbol
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(symbol, ‘1m’, 89280)

def signal_generator(df):
if df is None:
return “”
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(symbol, ‘1m’, 89280)
def order_execution(symbol, signal, step_size, leverage, order_type):
# Close any existing positions
current_position = None
positions = binance_futures.fapiPrivateGetPositionRisk()
for position in positions:
if position[“symbol”] == symbol:
current_position = position
if current_position is not None and current_position[“positionAmt”] != 0:
binance_futures.fapiPrivatePostOrder(
symbol=symbol,
side=‘SELL’ if current_position[“positionSide”] == “LONG” else ‘BUY’,
type=‘MARKET’,
quantity=abs(float(current_position[“positionAmt”])),
positionSide=current_position[“positionSide”],
reduceOnly=True
)
time.sleep(1)

# Calculate appropriate order quantity and price based on signal
opposite_position = None
quantity = step_size
position_side = None #initialise to None
price = None

# Set default take profit price
take_profit_price = None
stop_loss_price = None

if signal == ‘buy’:
position_side = ‘BOTH’
opposite_position = current_position if current_position and current_position[‘positionSide’] == ‘SHORT’ else None
order_type = ‘TAKE_PROFIT_MARKET’
ticker = binance_futures.fetch_ticker(symbol)
price = 0 # default price
if ‘askPrice’ in ticker:
price = ticker[‘askPrice’]
# perform rounding and other operations on price
else:
# handle the case where the key is missing (e.g. raise an exception, skip this signal, etc.)
take_profit_percentage = TAKE_PROFIT_PERCENTAGE
stop_loss_percentage = STOP_LOSS_PERCENTAGE

elif signal == ‘sell’:
position_side = ‘BOTH’
opposite_position = current_position if current_position and current_position[‘positionSide’] == ‘LONG’ else None
order_type = ‘STOP_MARKET’
ticker = binance_futures.fetch_ticker(symbol)
price = 0 # default price
if ‘askPrice’ in ticker:
price = ticker[‘askPrice’]
# perform rounding and other operations on price
else:
# handle the case where the key is missing (e.g. raise an exception, skip this signal, etc.)
take_profit_percentage = TAKE_PROFIT_PERCENTAGE
stop_loss_percentage = STOP_LOSS_PERCENTAGE

# Set stop loss price
stop_loss_price = None
if price is not None:
try:
price = round_step_size(price, step_size=step_size)
if signal == ‘buy’:
# Calculate take profit and stop loss prices for a buy signal
take_profit_price = round_step_size(price * (1 + TAKE_PROFIT_PERCENTAGE / 100), step_size=step_size)
stop_loss_price = round_step_size(price * (1 - STOP_LOSS_PERCENTAGE / 100), step_size=step_size)
elif signal == ‘sell’:
# Calculate take profit and stop loss prices for a sell signal
take_profit_price = round_step_size(price * (1 - TAKE_PROFIT_PERCENTAGE / 100), step_size=step_size)
stop_loss_price = round_step_size(price * (1 + STOP_LOSS_PERCENTAGE / 100), step_size=step_size)
except Exception as e:
print(f"Error rounding price: {e}“)

# Reduce quantity if opposite position exists
if opposite_position is not None:
if abs(opposite_position[‘positionAmt’]) < quantity:
quantity = abs(opposite_position[‘positionAmt’])

# Update position_side based on opposite_position and current_position
if opposite_position is not None:
position_side = opposite_position[‘positionSide’]
elif current_position is not None:
position_side = current_position[‘positionSide’]


# Place stop market order
if order_type == ‘STOP_MARKET’:
try:
response = binance_futures.fapiPrivatePostOrder(
symbol=symbol,
side=‘BUY’ if signal == ‘buy’ else ‘SELL’,
type=‘STOP_MARKET’,
quantity=quantity,
stopPrice=stop_loss_price,
reduceOnly=True
)
print(f"Order details: {response}”)
except BinanceAPIException as e:
print(f"Error in order_execution: {e}“)
time.sleep(1)
return

# Place market or take profit order
elif order_type == ‘market’:
try:
response = binance_futures.create_order(
symbol=symbol,
type=order_type,
side=‘BUY’ if signal == ‘buy’ else ‘SELL’,
amount=quantity,
price=price
)
print(f"Order details: {response}”)
except BinanceAPIException as e:
print(f"Error in order_execution: {e}")
time.sleep(1)
return
signal = signal_generator(df)
while True:
df = get_klines(symbol, ‘1m’, 89280) # await the coroutine function here
if df is not None:
signal = signal_generator(df)
if signal is not None:
print(f"The signal time is: {dt.datetime.now().strftime(’%Y-%m-%d %H:%M:%S’)} :{signal}")
if signal:
order_execution(symbol, signal, MAX_TRADE_QUANTITY_PERCENTAGE, leverage, order_type)
time.sleep(0.1)
But I getting ERROR: The signal time is: 2023-06-08 10:54:02 :sell
Traceback (most recent call last):
File “c:\Users\Alan.vscode\jew_bot\jew_bot\jew_bot.py”, line 295, in <module>
order_execution(symbol, signal, MAX_TRADE_QUANTITY_PERCENTAGE, leverage, order_type)
File “c:\Users\Alan.vscode\jew_bot\jew_bot\jew_bot.py”, line 258, in order_execution
response = binance_futures.fapiPrivatePostOrder(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: Entry.init.<locals>.unbound_method() got an unexpected keyword argument ‘symbol’