Building a Resilient Web Scraping & Alert Pipeline in Python

Описание и применение

Построена асинхронная система мониторинга цен с устойчивым к отказам запросом, парсингом и оповещением через Discord/Slack.

Задача

Web scraping tutorials often fail in production due to throttling, network drops, and layout changes.

Результат

The pipeline reliably fetches product pages, handles transient failures, parses prices, and alerts when prices fall below user‑defined thresholds.

Рабочий процесс

• Define Pydantic models for target products and scraped results.
• Set up a virtual environment and install aiohttp, beautifulsoup4, and pydantic.
• Implement an async fetcher with exponential backoff for transient HTTP errors.
• Parse HTML with BeautifulSoup4 and validate data via Pydantic.
• Compare current prices to target thresholds.
• Send formatted alerts to a Discord or Slack webhook when thresholds are met.

Доказательства

Most web scraping tutorials show you how to fetch a static page with requests and print a price to the terminal.

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Fetches multiple target URLs concurrently using aiohttp.

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Handles retries with exponential backoff.

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Dispatches formatted alert notifications to a Discord or Slack webhook when target thresholds are hit.

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