turns-00003.parquet:40881
2510d7ffb078a1c686b671f8degenerate_repetitionAbsentFinal dense release
USER
Give me right type of this code
ASSISTANT
Here's the corrected code with changes to the 'order_execution' function for defining the 'order_quantity' variable in both the 'long_position' and 'short_position' blocks:
```
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
date = dt.datetime.now().strftime("%m/%d/%Y %H:%M:%S")
print(date)
url = "https://api.binance.com/api/v1/time"
t = time.time()*1000
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 = 0.27
order_type = 'MARKET'
leverage = 125
max_trade_quantity_percentage = 10
client = Client(API_KEY, API_SECRET)
def getminutedata(symbol, interval, lookback):
frame = pd.DataFrame(client.get_historical_klines(symbol, interval, lookback+'min ago UTC'))
frame = frame.iloc[:60,:6]
frame.columns = ['Time','Open','High','Low','Close','Volume']
frame = frame.set_index('Time')
today = dt.date.today()
frame.index = pd.to_datetime(frame.index, unit='ms').tz_localize('UTC').tz_convert('Etc/GMT+3').strftime(f"{today} %H:%M:%S")
frame = frame.astype(float)
return frame
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 = getminutedata('BTCUSDT', '5m', '44640')
signal = ["" for i in range(len(df))] # initialize signal as a list of empty strings
for i in range(1, len(df)):
df_temp = df[i-1:i+1]
signal[i] = signal_generator(df_temp)
df["signal"] = signal
def order_execution(symbol, signal, max_trade_quantity_percentage):
max_trade_quantity_percentage = 10
buy = signal == "buy"
sell = signal == "sell"
signal = buy or sell
symbol = 'BTCUSDT'
account_balance = client.futures_account_balance()
usdt_balance = float([x['balance'] for x in account_balance if x['asset'] == 'USDT'][0])
max_trade_quantity = usdt_balance * max_trade_quantity_percentage/100
STOP_LOSS_PERCENTAGE = -50
TAKE_PROFIT_PERCENTAGE = 100
POSITION_SIDE_SHORT = SIDE_SELL
POSITION_SIDE_LONG = SIDE_BUY
long_position = POSITION_SIDE_LONG
short_position = POSITION_SIDE_SHORT
symbol = 'BTCUSDT'
positions = client.futures_position_information(symbol=symbol)
long_position = next((p for p in positions if p['symbol'] == symbol and p['positionSide'] == 'LONG'), None)
if long_position:
# Close long position if signal is opposite
if signal == "sell":
order = client.futures_create_order(
symbol=symbol,
side=SIDE_SELL,
type=ORDER_TYPE_MARKET,
quantity=long_position['positionAmt'],
reduceOnly=True
)
print(f"Closed long position with order ID {order['orderId']}")
time.sleep(1)
else:
if long_position is not None:
order_quantity = min(max_trade_quantity, abs(float(long_position['positionAmt'])))
else:
print("No long position found")
order = client.futures_create_order(
symbol=symbol,
side=SIDE_SELL,
type=ORDER_TYPE_MARKET,
quantity=order_quantity,
reduceOnly=False,
timeInForce=TIME_IN_FORCE_GTC,
positionSide=POSITION_SIDE_SHORT,
leverage=leverage
)
print(f"Placed short order with order ID {order['orderId']} and quantity {order_quantity}")
time.sleep(1)
# Set stop loss and take profit orders
stop_loss_price = order['avgPrice'] * (1 + STOP_LOSS_PERCENTAGE / 100)
take_profit_price = order['avgPrice'] * (1 + TAKE_PROFIT_PERCENTAGE / 100)
client.futures_create_order(
symbol=symbol,
side=SIDE_BUY,
type=ORDER_TYPE_STOP_LOSS,
quantity=order_quantity,
stopPrice=stop_loss_price,
reduceOnly=True,
timeInForce=TIME_IN_FORCE_GTC,
positionSide=POSITION_SIDE_SHORT
)
client.futures_create_order(
symbol=symbol,
side=SIDE_BUY,
type=ORDER_TYPE_LIMIT,
quantity=order_quantity,
price=take_profit_price,
reduceOnly=True,
timeInForce=TIME_IN_FORCE_GTC,
positionSide=POSITION_SIDE_SHORT
)
print(f"Set stop loss at {stop_loss_price} and take profit at {take_profit_price}")
time.sleep(1)
short_position = next((p for p in positions if p['symbol'] == symbol and p['positionSide'] == 'SHORT'), None)
if short_position:
# Close short position if signal is opposite
if signal == "buy":
order = client.futures_create_order(
symbol=symbol,
side=SIDE_BUY,
type=ORDER_TYPE_MARKET,
quantity=short_position['positionAmt'],
reduceOnly=True
)
print(f"Closed short position with order ID {order['orderId']}")
time.sleep(1)
else:
order_quantity = min(max_trade_quantity, float(short_position['maxNotionalValue']) / leverage)
order = client.futures_create_order(
symbol=symbol,
side=SIDE_BUY,
type=ORDER_TYPE_MARKET,
quantity=order_quantity,
reduceOnly=False,
timeInForce=TIME_IN_FORCE_GTC,
positionSide=POSITION_SIDE_LONG,
leverage=leverage
)
print(f"Placed long order with order ID {order['orderId']} and quantity {order_quantity}")
time.sleep(1)
# Set stop loss and take profit orders
stop_loss_price = order['avgPrice'] * (1 - STOP_LOSS_PERCENTAGE / 100)
take_profit_price = order['avgPrice'] * (1 - TAKE_PROFIT_PERCENTAGE / 100)
client.futures_create_order(
symbol=symbol,
side=SIDE_SELL,
type=ORDER_TYPE_STOP_LOSS,
quantity=order_quantity,
stopPrice=stop_loss_price,
reduceOnly=True,
timeInForce=TIME_IN_FORCE_GTC,
positionSide=POSITION_SIDE_LONG
)
client.futures_create_order(
symbol=symbol,
side=SIDE_SELL,
type=ORDER_TYPE_LIMIT,
quantity=order_quantity,
price=take_profit_price,
reduceOnly=True,
timeInForce=TIME_IN_FORCE_GTC,
positionSide=POSITION_SIDE_LONG
)
print(f"Set stop loss at {stop_loss_price} and take profit at {take_profit_price}")
time.sleep(1)
while True:
current_time = dt.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
current_signal = signal_generator(df)
print(f"The signal time is: {current_time} :{current_signal}")
if current_signal:
order_execution(symbol, current_signal, max_trade_quantity_percentage)
time.sleep(1) # Add a delay of 1 second
```