Python Binance Robot Tutorial: Building Your First Trading Bot
Binance is one of the world's leading cryptocurrency exchanges, offering a wide range of trading options and high liquidity to its users. Binance also provides an API that allows developers to build bots capable of executing trades automatically. In this tutorial, we will guide you through building your first Python-based trading bot using the Binance Futures API.
What is a Trading Bot?
A trading bot automates repetitive or complex tasks by making real-time decisions based on predefined rules and strategies. These bots can be used for various purposes, such as executing trades in high frequency, optimizing trades, analyzing market trends, or even generating alerts.
Why Python for Binance Trading Bot?
Python is an excellent choice for building trading bots due to its simplicity, versatility, and wide range of libraries that facilitate rapid development and execution. Additionally, the Binance Futures API supports Python, making it a perfect match for creating efficient bots tailored for Binance.
Setting Up Your Development Environment
To get started with your bot project, you'll need to set up a basic Python environment on your computer. You can follow these steps:
1. Install the Anaconda distribution of Python by visiting [anaconda.com/distribution](https://www.anaconda.com/distribution/) and choosing an appropriate installer for your system.
2. Open the Anaconda Prompt (Windows) or Terminal (Mac/Linux) and install necessary packages using the following command: `conda env create -f environment.yml`
3. Activate the created environment with the command: `conda activate binbot_env`
4. Install the required libraries for this project by running the commands:
```python
pip install pandas numpy requests ssl pillow
```
Understanding Binance Futures API
The Binance Futures API allows you to access real-time order book data, trade history, and more without having to manually input credentials. To start using the API, follow these steps:
1. Create a Binance account at [binance.com](https://www.binance.com/) if you haven't already.
2. Navigate to the [Binance Futures API documentation page](https://futuresapi.binance.com/docs) and click "Register your app" to generate an API key and secret pair.
3. Save these credentials securely on your computer or cloud storage, as they are necessary for accessing the Binance Futures API.
Building Your Trading Bot with Python
Now that you have a development environment set up and understand the basics of the Binance Futures API, it's time to start coding. This section will guide you through creating a simple bot that buys Bitcoin (BTC) when its price drops below $10k and sells it once the price rises back above $12k.
Step 1: Importing Necessary Libraries
```python
import requests
import ssl
from PIL import Image
import numpy as np
import pandas as pd
```
Step 2: Setting Up Binance Futures API Connection
Replace `api_key`, `secret_key` with your actual Binance API key and secret pair.
```python
def get_binance(url):
session = requests.Session()
session.headers["apisign"] = f'APIKEY:SECRET'
return session.get(f'https://api.binance.com{url}').json()
```
Step 3: Checking Market Prices and Order Books
This function retrieves the last trade price, 24-hour trading volume, and order book data for Bitcoin.
```python
def get_market_data():
orderbook = get_binance('fapi/depth?symbol=BTCUSDT&limit=50')['result']
ticker = get_binance('fapi/ticker/price?symbol=BTCUSDT')['result']
return orderbook, ticker
```
Step 4: Executing a Trade Based on Price Thresholds
This function checks the market price and decides whether to buy or sell Bitcoin.
```python
def execute_trade(price):
if price < 10000:
buy_quantity = 0.5 # Example quantity
order = {
"symbol": "BTCUSDT",
"side": "BUY",
"type": "LIMIT",
"timeInForce": "GTC",
"quantity": buy_quantity,
"price": price + 10 # Margin for slippage
}
response = get_binance('fapi/order?symbol=' + order['symbol'] + '&side=' + order['side'] + '&type=' + order['type'] + '&timeInForce=' + order['timeInForce'] + '&quantity=' + str(order['quantity']) + '&price=' + str(order['price']))
if response['success']:
print('Bought BTC at', price)
elif price > 12000 and len(open_positions()) > 0:
sell_all()
```
Step 5: Running the Trading Bot
This function runs in an infinite loop and continuously checks for trade opportunities.
```python
def run_bot():
while True:
orderbook, ticker = get_market_data()
price = float(ticker['lastPrice'])
execute_trade(price)
sleep(60) # Wait 1 minute before checking again
```
Step 6: Helper Functions
These functions help in managing open positions and making the bot more flexible.
```python
def open_positions():
positions = get_binance('fapi/open-orders?symbol=BTCUSDT')['result']
return positions
def sell_all():
if len(open_positions()) > 0:
for position in open_positions():
order = {
"symbol": "BTCUSDT",
"side": "SELL",
"type": "LIMIT",
"timeInForce": "GTC",
"quantity": position['origQty'],
"price": float(position['avgPrice']) - 10 # Margin for slippage
}
get_binance('fapi/order?symbol=' + order['symbol'] + '&side=' + order['side'] + '&type=' + order['type'] + '&timeInForce=' + order['timeInForce'] + '&quantity=' + str(order['quantity']) + '&price=' + str(order['price']))
print('Sold all BTC')
```
Step 7: Starting the Trading Bot
Run your bot by executing this line of code in your Python environment.
```python
run_bot()
```
Conclusion
This tutorial has provided you with a solid foundation for building your first Binance trading bot using Python and the Binance Futures API. While this example was relatively simple, remember that the possibilities are endless—you can incorporate more complex strategies, monitor multiple assets or markets, integrate external data sources (e.g., news feeds), or even create sophisticated risk management systems.
The key to successful trading bot development lies in understanding market dynamics and continuously refining your strategy based on performance feedback. Happy trading!