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Web Scraping & Bots · 강의

가격 추적 봇 만들기

전자상거래 사이트에서 상품 가격을 모니터링하고 가격이 내려가면 알림을 보내는 봇을 개발합니다.

가격 추적 봇 만들기은(는) CoddyKit의 무료 Web Scraping & Bots 강의입니다. 이것은 4개 중 1번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Web Scraping & Bots 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Web Scraping & Bots 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

What's a Price Tracker Bot?

Have you ever wanted to know when a product's price drops? A price tracker bot does exactly that!

It's an automated program that regularly checks the price of items on e-commerce websites.

When it detects a price change, especially a drop, it can notify you.

Bot's Core Tasks

Building a price tracker involves several key steps:

  • Fetch: Get the product page content.
  • Parse: Extract the price and product details.
  • Store: Keep track of the last known price.
  • Compare: Check if the current price is lower.
  • Notify: Send an alert if a drop is found.

Spotting Product Details

Before we write code, we need to know where the information is on the page.

Using browser developer tools, you'd identify the HTML elements that contain the product's:

  • Name
  • Current Price
  • Product URL

These are crucial for your bot to find the right data.

Getting the Web Page

The first step is to download the web page content. We'll use the requests library for this.

It sends an HTTP GET request to the product URL and retrieves the HTML.

Try running this simple example:

import requests

def fetch_page(url):
    try:
        response = requests.get(url)
        response.raise_for_status() # Check for HTTP errors
        return response.text
    except requests.exceptions.RequestException as e:
        print(f"Error fetching page: {e}")
        return None

if __name__ == "__main__":
    # Example URL (replace with a real product page for testing)
    example_url = "https://example.com/product"
    print(f"Fetching content from: {example_url}")
    # In a real bot, you'd parse this content
    # page_content = fetch_page(example_url)
    # if page_content:
    #     print("Page content fetched successfully (first 200 chars):")
    #     print(page_content[:200])
    # else:
    #     print("Failed to fetch page content.")
    print("Page content fetching logic demonstrated.")

Parsing the Price

Once you have the HTML, you'll use a library like BeautifulSoup to parse it and find the price.

Prices often come with currency symbols or extra text, so we'll need to clean the extracted string to get a numeric value.

Here's a snippet to illustrate:

from bs4 import BeautifulSoup

html_doc = """
<html><body>
  <span class="product-price">$199.99</span>
  <div id="item-name">Cool Gadget</div>
</body></html>
"""

soup = BeautifulSoup(html_doc, 'html.parser')
price_element = soup.find('span', class_='product-price')

if price_element:
    price_string = price_element.get_text()
    # Clean the string to get a float
    cleaned_price = float(price_string.replace('$', '').strip())
    print(f"Extracted Price: {cleaned_price}")
else:
    print("Price element not found.")

Remembering the Price

To track changes, your bot needs to remember the price it last saw. A simple way is to use a file to store this data.

For a basic bot, a JSON file or a simple dictionary in memory can work.

You'll store the product URL and its last known price.

import json

# Example of storing data
product_data = {
    "https://example.com/product1": {
        "name": "Cool Gadget",
        "last_price": 199.99
    },
    "https://example.com/product2": {
        "name": "Awesome Widget",
        "last_price": 49.95
    }
}

# In a real bot, you'd load/save this from a file
# with open('prices.json', 'w') as f:
#     json.dump(product_data, f, indent=2)

print("Product data structure for storage:")
print(json.dumps(product_data, indent=2))

Detecting Price Drops

This is the core logic! After fetching and parsing the new price, you compare it with the stored "last price".

If the new price is lower than the stored price, you've found a deal!

You should also update the stored price with the new one for future comparisons.

current_price = 189.99
stored_price = 199.99
product_name = "Cool Gadget"

if current_price < stored_price:
    print(f"PRICE DROP ALERT! {product_name} is now ${current_price} (was ${stored_price})")
    # Update stored_price = current_price in your data
elif current_price > stored_price:
    print(f"Price increased for {product_name}. Current: ${current_price}, Was: ${stored_price}")
    # Update stored_price = current_price
else:
    print(f"Price for {product_name} remains ${current_price}")

Notifying About Deals

Once a price drop is detected, your bot needs to tell you!

For a simple bot, printing a message to the console is enough. For real-world use, you might:

  • Send an email
  • Push a notification to your phone
  • Send a message to a chat app (e.g., Discord, Telegram)
def send_notification(product_name, old_price, new_price):
    message = (
        f"🚨 Price Drop Alert! 🚨\n"
        f"Product: {product_name}\n"
        f"Old Price: ${old_price:.2f}\n"
        f"New Price: ${new_price:.2f}\n"
        f"Check it out now!"
    )
    print(message)
    # In a real app, you'd integrate email/SMS here

if __name__ == "__main__":
    send_notification("Awesome Headphones", 250.00, 225.00)

Your First Price Tracker

Let's combine these pieces into a basic, runnable price tracker. This example simulates fetching and parsing.

Remember, for a real bot, you'd replace the `mock_fetch_and_parse` with actual requests and BeautifulSoup calls.

import json
import random

# Mock functions for demonstration
def mock_fetch_and_parse(product_url):
    # Simulate different prices
    if "gadget" in product_url:
        return random.choice([199.99, 189.99, 205.00])
    return random.choice([49.95, 45.00, 52.00])

def send_notification(product_name, old_price, new_price):
    print(f"🚨 Price Drop! {product_name} is now ${new_price:.2f} (was ${old_price:.2f})")

# Main logic
def check_price(product_url, product_name, stored_prices):
    current_price = mock_fetch_and_parse(product_url)
    last_price = stored_prices.get(product_url)

    if last_price is None:
        print(f"First check for {product_name}: ${current_price:.2f}")
    elif current_price < last_price:
        send_notification(product_name, last_price, current_price)
    elif current_price > last_price:
        print(f"Price for {product_name} increased to ${current_price:.2f}")
    else:
        print(f"Price for {product_name} remains ${current_price:.2f}")
    
    stored_prices[product_url] = current_price # Update price

if __name__ == "__main__":
    # Simulate stored prices (from a file in a real app)
    my_tracked_items = {
        "https://example.com/gadget": 200.00, # Initial price
        "https://example.com/widget": 50.00
    }

    print("--- First Run ---")
    check_price("https://example.com/gadget", "Cool Gadget", my_tracked_items)
    check_price("https://example.com/widget", "Awesome Widget", my_tracked_items)
    print("\n--- Second Run ---")
    check_price("https://example.com/gadget", "Cool Gadget", my_tracked_items)
    check_price("https://example.com/widget", "Awesome Widget", my_tracked_items)
    print("\nFinal tracked prices:", json.dumps(my_tracked_items, indent=2))

Price Logic Check

Consider a price tracker bot. It last recorded a product price of $50.00. On its next run, it fetches the price as $45.00. What should the bot do?

Recap & Next Steps

You've learned the fundamental steps to build a price tracker bot!

  • Fetch HTML with requests.
  • Parse prices with BeautifulSoup.
  • Store prices (e.g., in a JSON file).
  • Compare current vs. stored prices.
  • Notify on price drops.

Next steps include scheduling your bot to run automatically and exploring more advanced notification methods.

자주 묻는 질문

“가격 추적 봇 만들기” 강의는 무료인가요?

네 — “가격 추적 봇 만들기” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Web Scraping & Bots 강의 전체를 잠금 해제할 수 있습니다. Web Scraping & Bots 강의에는 총 4개의 강의가 포함되어 있습니다.

“가격 추적 봇 만들기”에서 뭘 배우나요?

전자상거래 사이트에서 상품 가격을 모니터링하고 가격이 내려가면 알림을 보내는 봇을 개발합니다. 브라우저에서 직접 실행하는 실습 코드로 Web Scraping & Bots을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

Web Scraping & Bots을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 Web Scraping & Bots은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 1번째 강의입니다.

“가격 추적 봇 만들기” 강의는 얼마나 걸리나요?

대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.

이 Web Scraping & Bots 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 Web Scraping & Bots 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

이 강의의 모든 강의

  1. 가격 추적 봇 만들기
  2. 소셜 미디어 모니터 만들기
  3. 클라우드 플랫폼에 봇 배포하기
  4. 경고와 알림 보내기
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