Binance-Crypto-Trader

import os import math from binance.client import Client import pandas as pd import time

Set your Binance API key and secret

api_key = '' api_secret = '' client = Client(api_key, api_secret)

Set trading parameters

symbol = 'BTCBRL' interval = '1m' short_window = 10 long_window = 30 fee_percentage = 0.001 # Assuming a 0.1% fee, adjust as needed

def get_historical_data(): # Fetch historical klines klines = client.get_klines(symbol=symbol, interval=interval)

# Convert klines to DataFrame for analysis
df = pd.DataFrame(klines, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time', 'quote_asset_volume', 'number_of_trades', 'taker_buy_base_asset_volume', 'taker_buy_quote_asset_volume', 'ignore'])

# Convert timestamp to datetime
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')

return df

def calculate_moving_averages(df): # Calculate short and long-term moving averages df['short_mavg'] = df['close'].rolling(window=short_window, min_periods=1, center=False).mean() df['long_mavg'] = df['close'].rolling(window=long_window, min_periods=1, center=False).mean()

def execute_trade_action(balance, current_price, position): if position == 'none': return 'buy' if balance > 0 else 'none' elif position == 'long' and current_price < df['short_mavg'].iloc[-1]: return 'sell' elif position == 'none' and current_price > df['long_mavg'].iloc[-1]: return 'buy' else: return 'none'

Main trading loop

balance = 95 # Updated balance in BRL position = 'none' # Initial position while True: df = get_historical_data() calculate_moving_averages(df)

current_price = float(df['close'].iloc[-1])

action = execute_trade_action(balance, current_price, position)

if action == 'buy' and balance > 0:
    # Get the lot size filter from the exchange info
    lot_size_filter = next((filter for filter in client.get_symbol_info(symbol)['filters'] if filter['filterType'] == 'LOT_SIZE'), None)
    if lot_size_filter:
        step_size = float(lot_size_filter['stepSize'])
        quantity_to_buy = round(balance / current_price, int(-1 * round(math.log10(step_size))))
    else:
        # Default rounding to 6 decimal places if lot size information is not available
        quantity_to_buy = round(balance / current_price, 6)
    
    order = client.order_market_buy(symbol=symbol, quantity=quantity_to_buy)
    print(f"Buying {quantity_to_buy} BTC at {current_price} BRL")
    balance = 0
    position = 'long'
elif action == 'sell':
    quantity_to_sell = round(balance / current_price, int(-1 * round(math.log10(step_size))))
    quantity_to_sell_after_fee = quantity_to_sell * (1 - fee_percentage)
    quantity_to_sell_after_fee = max(quantity_to_sell_after_fee, 0)  # Ensure quantity is not negative
    order = client.order_market_sell(symbol=symbol, quantity=quantity_to_sell_after_fee)
    balance = current_price * quantity_to_sell_after_fee
    position = 'none'
    print(f"Selling {quantity_to_sell_after_fee} BTC at {current_price} BRL after fees")

time.sleep(60)  # Wait for 1 minute before the next iteration