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Build a Real-Time Crypto Trading Bot in Python: Live Prices, RSI Signals, and Telegram Alerts

Build a Real-Time Crypto Trading Bot in Python: Live Prices, RSI Signals, and Telegram Alerts

Crypto prices update every second. Retail traders need tools that spot overbought signals before the crowd. This tutorial builds a Python bot that pulls live Binance prices via CCXT, calculates RSI with TA-Lib, and sends Telegram alerts when RSI hits extremes.

No fluff. You get a working script in 30 minutes. Deploy it on a VPS for 24/7 monitoring.

Why RSI for Trading?

RSI measures momentum on a 0-100 scale. Above 70: overbought, sell signal. Below 30: oversold, buy signal. False signals happen in trends, so pair it with price action.

This bot checks BTC/USDT every minute. Alerts fire on crossovers.

Prerequisites

  • Python 3.10+
  • Binance account (read-only API key optional for public data)
  • Telegram bot token (create via @botfather)

Install libraries:

pip install ccxt pandas TA-Lib telebot
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TA-Lib needs binary install. On Ubuntu:

sudo apt update
wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
tar -xzf ta-lib-0.4.0-src.tar.gz
cd ta-lib/
./configure --prefix=/usr
make
sudo make install
pip install TA-Lib
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Step 1: Fetch Real-Time Prices

CCXT unifies 100+ exchanges. Public data needs no API key.

import ccxt
import pandas as pd
from datetime import datetime

exchange = ccxt.binance()
symbol = 'BTC/USDT'

def fetch_ohlcv():
    ohlcv = exchange.fetch_ohlcv(symbol, timeframe='1m', limit=100)
    df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
    return df
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fetch_ohlcv grabs 100 candles. Each row: open, high, low, close, volume.

Step 2: Calculate RSI

TA-Lib handles indicators. RSI(14) is standard.

import talib

def calculate_rsi(df, period=14):
    df['rsi'] = talib.RSI(df['close'], timeperiod=period)
    return df
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NaN on first 14 periods. Ignore them.

Step 3: Send Telegram Alerts

Create a bot, get token and chat_id.

import telebot

TELEGRAM_TOKEN = 'your_bot_token'
CHAT_ID = 'your_chat_id'
bot = telebot.TeleBot(TELEGRAM_TOKEN)

def send_alert(message):
    bot.send_message(CHAT_ID, message)
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Step 4: Trading Logic

Buy if RSI < 30 and rising. Sell if RSI > 70 and falling.

def check_signals(df):
    latest_rsi = df['rsi'].iloc[-1]
    prev_rsi = df['rsi'].iloc[-2]

    if latest_rsi < 30 and latest_rsi > prev_rsi:
        send_alert(f"🚀 BTC/USDT OVERSOLD: RSI {latest_rsi:.1f} (rising from {prev_rsi:.1f}) at {datetime.now()}")
    elif latest_rsi > 70 and latest_rsi < prev_rsi:
        send_alert(f"🔴 BTC/USDT OVERBOUGHT: RSI {latest_rsi:.1f} (falling from {prev_rsi:.1f}) at {datetime.now()}")
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Full Bot Script

Combine it. Runs forever, sleeps 60s.

import time
import ccxt
import pandas as pd
import talib
import telebot
from datetime import datetime

# Config
TELEGRAM_TOKEN = 'your_bot_token_here'
CHAT_ID = 'your_chat_id_here'
SYMBOL = 'BTC/USDT'
exchange = ccxt.binance()

bot = telebot.TeleBot(TELEGRAM_TOKEN)

def fetch_data():
    ohlcv = exchange.fetch_ohlcv(SYMBOL, '1m', 100)
    df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
    df['rsi'] = talib.RSI(df['close'])
    return df

def send_alert(message):
    try:
        bot.send_message(CHAT_ID, message)
    except:
        print("Alert failed")

while True:
    try:
        df = fetch_data()
        latest_rsi = df['rsi'].dropna().iloc[-1]
        prev_rsi = df['rsi'].dropna().iloc[-2]

        price = df['close'].iloc[-1]

        if latest_rsi < 30 and latest_rsi > prev_rsi:
            send_alert(f"🚀 BUY SIGNAL {SYMBOL}: RSI {latest_rsi:.1f}↑ Price ${price:,.0f}")
        elif latest_rsi > 70 and latest_rsi < prev_rsi:
            send_alert(f"🔴 SELL SIGNAL {SYMBOL}: RSI {latest_rsi:.1f}↓ Price ${price:,.0f}")

        print(f"Checked at {datetime.now()}: RSI {latest_rsi:.1f}, Price ${price:,.0f}")

    except Exception as e:
        print(f"Error: {e}")

    time.sleep(60)
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Test and Deploy

Run locally: python bot.py

Expect output like: "Checked at 2026-05-05 08:30: RSI 45.2, Price $95,420"

Deploy: VPS with screen or systemd. Use python -u bot.py > bot.log 2>&1 &

Add MACD or volume filter to reduce noise.

Next Level

This bot scratches the surface. For 2,500+ coins, chart patterns, AI setups, and paper trading: check Market Masters AI. Free tier screens signals across Binance/Bybit stocks. Start your 30-day Premium trial: https://marketmasters.ai

Build, test, trade smarter.

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