Manual supplier price verification consumes excessive time for media designers

**Frontend (React + TypeScript + TailwindCSS):** Build a **real-time dashboard** with a **supplier comparison grid** (using `react-virtualized` for large datasets) and **interactive price trend charts** (via `recharts` or `d3.js`). Integrate a **Chrome Extension** (using `puppeteer` for headless scraping fallback) to auto-detect supplier pages and trigger API/webhook syncs. For discrepancy alerts, use **WebSocket** (`socket.io`) to push updates to the UI with **visual urgency indicators** (e.g., red for 10%+ spikes, yellow for 5% drops). Store user notes in **IndexedDB** for offline access, synced via **Firebase/Firestore** for collaboration. **Backend (Python FastAPI + Celery + Redis):** Core logic runs via **Celery workers** to scrape suppliers (using `scrapy` + `selenium` for dynamic pages) or call APIs (e.g., B&H Photo’s undocumented API via `requests` with headers spoofing). Parse structured data with **BeautifulSoup** (HTML) or **lxml** (XML/JSON APIs). For historical tracking, use **DuckDB** (embedded OLAP) to query price trends without a traditional DB. Cache responses in **Redis** to reduce API scrape frequency. Deploy with **Docker** + **Kubernetes** for auto-scaling during peak loads (e.g., Black Friday). **Data Pipeline:** - **Scraping/API Layer:** Rotate user agents (`fake-useragent`) and proxies (`scrapy-proxy-pool`) to avoid blocks. Use **Playwright** for JavaScript-heavy supplier sites. - **Normalization:** Standardize SKUs/items via **fuzzy matching** (`fuzzywuzzy`) against a master catalog (stored in **PostgreSQL**). - **Alerting:** Trigger **Slack/Email webhooks** (via `python-slackclient`) for critical discrepancies, with **rate-limiting** to avoid spam. **Validation:** - **Mock Suppliers:** Seed the system with **scraped historical data** (e.g., Archive.org snapshots) to test discrepancy detection. - **A/B Testing:** Compare manual vs. tool-assisted verification times via **Google Analytics** event tracking.

This tool **eliminates the ‘context-switching tax’** of toggling between supplier tabs, reducing **cognitive load** by surfacing discrepancies **before** purchase decisions. For a **videographer**, it cuts **1–2 hours/week** spent chasing outdated prices, freeing time for creative work. **Historical tracking** prevents **overpaying** (e.g., catching a 20% markup mid-project) and **reduces server costs** by consolidating supplier API calls into a single pipeline. **Supplier notes** replace **Slack/email noise**, while **real-time alerts** prevent **last-minute budget overruns**. The **embedded DuckDB** enables **offline-first** use in remote locations, and **Celery’s async scraping** optimizes cloud spend by batching requests.