Python

Build a Cryptocurrency Price Tracker in Python

Cryptocurrency markets run 24/7, making automated tracking essential. In this tutorial, we build a crypto price tracker that fetches live prices from the free CoinGecko API, calculates your portfolio value, and sends alerts when prices cross thresholds.

Prerequisites

✓Basic Python
✓pip installed
✓No API key needed (CoinGecko free tier)

Step 1.Install dependencies

requests for API calls, pandas for data, tabulate for pretty terminal output.

pip install requests pandas tabulate

Step 2.Fetch live crypto prices

CoinGecko provides free crypto data without authentication. We get price, 24h change, and market cap in one call.

import requests
import pandas as pd
from datetime import datetime

def get_crypto_prices(coins: list, currency: str = "gbp") -> dict:
    ids = ",".join(coins)
    url = "https://api.coingecko.com/api/v3/simple/price"
    params = {
        "ids": ids,
        "vs_currencies": currency,
        "include_24hr_change": "true",
        "include_market_cap": "true"
    }
    r = requests.get(url, params=params, timeout=10)
    r.raise_for_status()
    return r.json()

coins = ["bitcoin", "ethereum", "solana", "cardano", "polkadot"]
prices = get_crypto_prices(coins)
for coin, data in prices.items():
    print(f'{coin}: pounds {data["gbp"]:,.2f} ({data["gbp_24h_change"]:.1f}%)')

Step 3.Track your portfolio

Multiply your holdings by live prices to see current portfolio value.

portfolio = {
    "bitcoin": 0.5,
    "ethereum": 4.0,
    "solana": 25.0,
}

total = 0
rows = []
for coin, amount in portfolio.items():
    price = prices[coin]["gbp"]
    value = amount * price
    total += value
    rows.append({
        "Coin": coin.title(),
        "Amount": amount,
        "Price": price,
        "Value": value,
        "Change 24h": f'{prices[coin]["gbp_24h_change"]:.1f}%'
    })

df = pd.DataFrame(rows)
print(df.to_string(index=False))
print(f"Total portfolio value: pounds {total:,.2f}")

Step 4.Set up price alerts

Define price thresholds and check them against live data. In production, you would send email or push notifications.

ALERTS = {
    "bitcoin": {"above": 100000, "below": 40000},
    "ethereum": {"above": 5000, "below": 2000},
}

def check_alerts(prices: dict, alerts: dict):
    triggered = []
    for coin, thresholds in alerts.items():
        if coin in prices:
            price = prices[coin]["gbp"]
            if price > thresholds["above"]:
                triggered.append(f"{coin.title()} above {thresholds['above']:,}")
            if price < thresholds["below"]:
                triggered.append(f"{coin.title()} below {thresholds['below']:,}")
    return triggered

alerts = check_alerts(prices, ALERTS)
if alerts:
    for a in alerts:
        print(f"ALERT: {a}")
else:
    print("No alerts triggered")

Step 5.Get historical data

Historical data lets you plot trends and calculate moving averages.

def get_price_history(coin: str, days: int = 30) -> pd.DataFrame:
    url = f"https://api.coingecko.com/api/v3/coins/{coin}/market_chart"
    params = {"vs_currency": "gbp", "days": days}
    r = requests.get(url, params=params, timeout=10)
    data = r.json()
    df = pd.DataFrame(data["prices"], columns=["timestamp", "price"])
    df["date"] = pd.to_datetime(df["timestamp"], unit="ms")
    return df[["date", "price"]]

btc_history = get_price_history("bitcoin", 30)
print(f'BTC 30-day range: pounds {btc_history["price"].min():,.0f} - pounds {btc_history["price"].max():,.0f}')

Expected Output

     Coin  Amount  Price     Value  Change 24h
  Bitcoin     0.5  84250  42125.00       2.3%
 Ethereum     4.0   3180  12720.00       1.8%
   Solana    25.0    142   3562.50       4.1%

Total portfolio value: pounds 58,407.50

Next Steps

→Add email notifications using smtplib
→Store historical portfolio values in a database
→Build a Streamlit dashboard