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binance api trading bot python

Last updated on 29 days ago
C
caaSuper Admin
Posted 29 days ago
To create a trading bot for Binance in Python, you can use Binance’s official API and the **python-binance** library. Here’s a step-by-step guide to building a basic bot that can place orders, monitor balances, and fetch price data.

### Requirements:
1. **Binance Account**: Sign up and enable API access for your account.
2. **API Key and Secret**: Obtain your API key and secret from the Binance API Management section.
3. **python-binance Library**: This is the official library for interacting with the Binance API.

### Step 1: Install the python-binance Library
Install the required library via pip:
bash
pip install python-binance


### Step 2: Set Up API Keys and Security
To keep your API key and secret safe, consider storing them in environment variables or a configuration file instead of hardcoding them.

python
import os
from binance.client import Client

# Replace with your actual API key and secret or store in environment variables
API_KEY = os.getenv("BINANCE_API_KEY")
API_SECRET = os.getenv("BINANCE_API_SECRET")

client = Client(API_KEY, API_SECRET)
C
caaSuper Admin
Posted 29 days ago
### Step 3: Fetch Market Data

Fetching the latest prices and other market data is a key component of any trading bot. Here’s how to get the latest price of a specific symbol, such as BTC/USDT.

python
# Get current price for a symbol
symbol = "BTCUSDT"
ticker = client.get_symbol_ticker(symbol=symbol)
print(f"Current price of {symbol}: {ticker['price']}")


### Step 4: Place Orders
The bot can execute orders such as market orders and limit orders. Here’s how you can place a **market order** for a symbol.

#### Market Order Example
A market order buys or sells immediately at the best available price.

python
# Example of a market order
def place_market_order(symbol, quantity, side):
 try:
 order = client.order_market(
 symbol=symbol,
 side=side, # "BUY" or "SELL"
 quantity=quantity
 )
 print("Order placed:", order)
 except Exception as e:
 print("An error occurred:", e)

# Example usage
place_market_order(symbol="BTCUSDT", quantity=0.001, side="BUY")
C
caaSuper Admin
Posted 29 days ago
#### Limit Order Example
A limit order buys or sells at a specified price or better.

python
# Example of a limit order
def place_limit_order(symbol, quantity, price, side):
 try:
 order = client.order_limit(
 symbol=symbol,
 side=side, # "BUY" or "SELL"
 quantity=quantity,
 price=price
 )
 print("Order placed:", order)
 except Exception as e:
 print("An error occurred:", e)

# Example usage
place_limit_order(symbol="BTCUSDT", quantity=0.001, price="30000", side="BUY")
C
caaSuper Admin
Posted 29 days ago
### Step 5: Monitor Account Balance

To check available balance and track funds, use the following code.

python
# Get account balance
def get_balance(asset):
 balance = client.get_asset_balance(asset=asset)
 print(f"Balance for {asset}: {balance['free']}")

# Example usage
get_balance("BTC")
get_balance("USDT")


### Step 6: Example Strategy (Moving Average Crossover)
Here’s a simple moving average crossover strategy that buys when the short-term moving average crosses above the long-term moving average and sells when it crosses below.

1. Fetch historical price data.
2. Calculate moving averages.
3. Place buy/sell orders based on the crossover.
C
caaSuper Admin
Posted 29 days ago
python
import numpy as np
import pandas as pd

# Fetch historical price data
def get_historical_data(symbol, interval, limit):
 klines = client.get_klines(symbol=symbol, interval=interval, limit=limit)
 data = 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'
 ])
 data['close'] = data['close'].astype(float)
 return data['close']

# Calculate moving averages and place orders
def moving_average_strategy(symbol, short_window, long_window):
 data = get_historical_data(symbol, interval="1m", limit=long_window)
 short_ma = data.rolling(window=short_window).mean()
 long_ma = data.rolling(window=long_window).mean()

 # Check for crossover
 if short_ma.iloc[-1] > long_ma.iloc[-1] and short_ma.iloc[-2] <= long_ma.iloc[-2]:
 print("Buy signal")
 place_market_order(symbol, quantity=0.001, side="BUY")
 elif short_ma.iloc[-1] < long_ma.iloc[-1] and short_ma.iloc[-2] >= long_ma.iloc[-2]:
 print("Sell signal")
 place_market_order(symbol, quantity=0.001, side="SELL")
 else:
 print("No signal")

# Example usage
moving_average_strategy("BTCUSDT", short_window=5, long_window=20)
C
caaSuper Admin
Posted 29 days ago
### Step 7: Automate the Bot
To run the bot continuously, you can use a loop with a delay (e.g., 60 seconds for 1-minute data) or schedule it with a tool like **cron** (Linux) or **Task Scheduler** (Windows).

python
import time

def run_bot():
 while True:
 try:
 moving_average_strategy("BTCUSDT", short_window=5, long_window=20)
 time.sleep(60) # Delay of 1 minute between checks
 except Exception as e:
 print("Error in bot loop:", e)
 time.sleep(60) # Retry after a delay if an error occurs

# Start the bot
run_bot()


### Important Considerations

1. **Paper Trading**: Test your bot with paper trading before using real funds to prevent potential losses.
2. **API Rate Limits**: Binance imposes rate limits, so avoid frequent API calls within a short period.
3. **Error Handling**: Implement error handling and logging to troubleshoot issues easily.
4. **Risk Management**: Include risk management, such as stop-loss orders or position sizing, to protect your capital.

This basic bot demonstrates a moving average strategy and allows you to place orders and monitor your balance with Python and the Binance API. For a more advanced bot, consider adding features like technical indicators, stop-loss settings, and real-time WebSocket data.
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