Automated Crypto Trading Bot with Python | Step By Step Tutorial

3 min readFeb 3, 2025

Cryptocurrency trading can be both exciting and profitable, but it requires constant monitoring of price movements and quick execution of trades. A trading bot automates this process, making decisions based on predefined strategies. In this tutorial, we’ll guide you through building an automated crypto trading bot using Python.

Prerequisites

Before we start, ensure you have the following:

Basic knowledge of Python
A Binance account (or another exchange that supports API trading)
Installed libraries: ccxt, pandas, ta, requests

Step 1: Install Required Libraries

To interact with an exchange, fetch data, and perform analysis, install the following Python packages:

pip install ccxt pandas ta requests

Step 2: Set Up Exchange API Keys

To allow the bot to place trades, generate API keys from Binance (or your preferred exchange). Store them securely.

API_KEY = 'your_api_key'
API_SECRET = 'your_api_secret'

Step 3: Connect to the Exchange

We’ll use the ccxt library to interface with Binance:

import ccxt

exchange = ccxt.binance({
    'apiKey': API_KEY,
    'secret': API_SECRET,
    'enableRateLimit': True
})

Step 4: Fetch Market Data

We need real-time market data to make trading decisions. Let’s fetch recent price data:

import pandas as pd

def get_data(symbol, timeframe='1h'):
    bars = exchange.fetch_ohlcv(symbol, timeframe, limit=100)
    df = pd.DataFrame(bars, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
    return df

Step 5: Implement a Simple Trading Strategy

We’ll use a Moving Average Crossover strategy, where a trade is made when a short-term moving average crosses a long-term one.

import ta

def apply_strategy(df):
    df['sma_short'] = ta.trend.sma_indicator(df['close'], window=10)
    df['sma_long'] = ta.trend.sma_indicator(df['close'], window=50)
    df['signal'] = df['sma_short'] > df['sma_long']
    return df

Step 6: Place Orders

Once the strategy generates buy/sell signals, execute trades accordingly.

def place_order(symbol, side, amount):
    order = exchange.create_market_order(symbol, side, amount)
    print(f"Placed {side} order for {amount} {symbol}")
    return order

Step 7: Automate the Trading Process

Let’s put everything together into a loop that runs at intervals.

SYMBOL = 'BTC/USDT'
AMOUNT = 0.001  # Adjust as needed

def run_bot():
    df = get_data(SYMBOL)
    df = apply_strategy(df)
    latest_signal = df.iloc[-1]['signal']
    
    if latest_signal:
        place_order(SYMBOL, 'buy', AMOUNT)
    else:
        place_order(SYMBOL, 'sell', AMOUNT)import time
while True:
    run_bot()
    time.sleep(3600)  # Run every hour

Conclusion

You now have a simple automated crypto trading bot using Python! Keep in mind:

Always test strategies with paper trading before risking real funds.
Crypto markets are volatile; risk management is essential.
Consider using more advanced strategies like RSI, MACD, or AI-based models.

Let me know in the comments if you need enhancements to the bot! 🚀

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