Can I vibe code Competera?

Build a lightweight dynamic pricing engine in Python (FastAPI) with PostgreSQL and Next.js.

1. DATA MODEL:
- Products: id, sku, title, cost_price, base_price, current_price, min_margin_percent, shopify_variant_id.
- CompetitorTrackers: id, product_id, competitor_name, target_url, CSS_selector, current_competitor_price, last_scraped_at.
- PriceRules: id, product_id, rule_type (cost_plus, match_competitor, undercut), value, active_status.
- PriceHistory: id, product_id, old_price, new_price, trigger_reason, created_at.

2. CORE FUNCTIONALITY:
- Scheduled Scraper: Runs a background job using Playwright and residential proxy headers to scrape target_url and update current_competitor_price.
- Pricing Engine: Evaluates rules whenever competitor prices change or on a cron schedule. Computes proposed_price based on rule_type. Enforces hard constraint: proposed_price >= cost_price * (1 + min_margin_percent / 100).
- Platform Sync: Pushes validated price updates directly to the Shopify Admin REST/GraphQL API and records changes in PriceHistory.
- Web Dashboard: Next.js UI showing live competitor prices, margin health, price change logs, and a manual override toggle.

3. FAILURE MODES & HANDLERS:
- Handle anti-bot blocking (HTTP 403/429) by logging failures, alerting via Slack, and keeping the existing price unchanged.
- Handle missing CSS selectors or structural changes on scraped pages by throwing parsing alerts without crashing the worker.
- Enforce strict ceiling and floor rules to prevent unexpected zero or hyper-inflated prices.

4. OUT OF SCOPE:
- ML price elasticity models, cross-category cannibalization, multi-currency conversion, and complex enterprise ERP batch syncing.

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