Project — Shop Price Tracker

• Scrape today's price of a single product.
• Append a row to price_log.csv only when the price changes.
• Print a friendly summary: current, all-time low, all-time high, week trend.
• Be polite — User-Agent, timeout, single request per run.

Use https://books.toscrape.com/catalogue/a-light-in-the-attic_1000/index.html — a friendly demo page that's scrape-safe. (Real shops change their HTML often and have ToS to read.)

Open the page in your browser, Inspect the price element, copy its CSS selector. For this page the price lives at p.price_color.

Step 1 — Scrape current price

import requests
from bs4 import BeautifulSoup

URL = "https://books.toscrape.com/catalogue/a-light-in-the-attic_1000/index.html"

def fetch_price():
    r = requests.get(URL, timeout=10,
                     headers={"User-Agent": "advaslearning-py-l4 (price tracker demo)"})
    r.raise_for_status()
    soup = BeautifulSoup(r.text, "lxml")
    raw  = soup.select_one("p.price_color").get_text(strip=True)
    return float(raw.replace("£", ""))

Step 2 — Read price history

import csv
from pathlib import Path

LOG = Path("price_log.csv")
FIELDS = ["date", "price"]

def load_history():
    if not LOG.exists():
        return []
    with LOG.open(newline="") as f:
        return [{"date": r["date"], "price": float(r["price"])}
                for r in csv.DictReader(f)]

Step 3 — Diff & append

from datetime import date

def maybe_log(history, current):
    if history and history[-1]["price"] == current:
        return False
    if not LOG.exists():
        with LOG.open("w", newline="") as f:
            csv.DictWriter(f, fieldnames=FIELDS).writeheader()
    with LOG.open("a", newline="") as f:
        csv.DictWriter(f, fieldnames=FIELDS).writerow(
            {"date": str(date.today()), "price": current}
        )
    return True

Step 4 — Report

def report(history, current):
    prices = [h["price"] for h in history] or [current]
    lo, hi = min(prices), max(prices)
    print(f"💷 current : £{current:.2f}")
    print(f"📉 all-time low : £{lo:.2f}")
    print(f"📈 all-time high: £{hi:.2f}")
    if current == lo and len(prices) > 1:
        print("🎯 NEW LOW")
    elif current == hi:
        print("⬆️  new high")

# price_tracker.py — watch one product
import csv, requests
from bs4 import BeautifulSoup
from datetime import date
from pathlib import Path

URL = "https://books.toscrape.com/catalogue/a-light-in-the-attic_1000/index.html"
LOG = Path("price_log.csv")
FIELDS = ["date", "price"]
HEADERS = {"User-Agent": "advaslearning-py-l4 (price tracker demo)"}

def fetch_price():
    r = requests.get(URL, timeout=10, headers=HEADERS)
    r.raise_for_status()
    soup = BeautifulSoup(r.text, "lxml")
    return float(soup.select_one("p.price_color").get_text(strip=True).replace("£", ""))

def load_history():
    if not LOG.exists():
        return []
    with LOG.open(newline="") as f:
        return [{"date": r["date"], "price": float(r["price"])}
                for r in csv.DictReader(f)]

def maybe_log(history, current):
    if history and history[-1]["price"] == current:
        return False
    new_file = not LOG.exists()
    with LOG.open("a", newline="") as f:
        w = csv.DictWriter(f, fieldnames=FIELDS)
        if new_file: w.writeheader()
        w.writerow({"date": str(date.today()), "price": current})
    return True

def report(history, current):
    prices = [h["price"] for h in history] + [current]
    lo, hi = min(prices), max(prices)
    print(f"💷 current : £{current:.2f}")
    print(f"📉 low     : £{lo:.2f}")
    print(f"📈 high    : £{hi:.2f}")
    if len(prices) >= 2 and current < prices[-2]:
        print(f"🔻 dropped from £{prices[-2]:.2f}")
    elif current == lo and len(prices) > 1:
        print("🎯 NEW LOW")

def main():
    history = load_history()
    current = fetch_price()
    changed = maybe_log(history, current)
    if changed:
        print(f"📝 logged new price on {date.today()}")
    else:
        print("· unchanged from last run")
    report(history, current)

if __name__ == "__main__":
    main()

Sample run sequence (3 days)

day 1
📝 logged new price on 2026-05-26
💷 current : £51.77
📉 low     : £51.77
📈 high    : £51.77

day 2 (price unchanged on the demo site)
· unchanged from last run
💷 current : £51.77
...

day 3 (imagine a price drop)
📝 logged new price on 2026-05-28
🔻 dropped from £51.77
💷 current : £48.50
📉 low     : £48.50
📈 high    : £51.77
🎯 NEW LOW

You combined three skills into one tiny app: scrape (Lesson 15), log (CSV from Lesson 4), schedule (your OS). The append-on-change pattern is core to monitoring of any kind — server health, stock prices, weather alerts. The shape is identical, only the scraper changes.