🍳 COOKup Analytics — Home-Cooked Food Price Tracker

Artisanal Food Telemetry, Home Cook Analytics & Dish Price History Platform for Cookups Bangladesh.

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📌 Executive Summary

COOKup Analytics is an interactive telemetry and price analytics platform built for Cookups, Bangladesh's premier marketplace for home-cooked meals and artisanal dishes.

The system ingests dish catalogs, tracks pricing fluctuations across home cooks, calculates price drop trends, and provides interactive modal analytics. Built on a hybrid architecture, COOKup Analytics operates seamlessly via a local Python REST API server or statically through pre-baked JSON datasets deployed to GitHub Pages.

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🚀 Key Features

• 👨‍🍳 Cook & Dish Telemetry: Track active home cooks, dish availability, category distribution, and average dish pricing metrics.
• 📉 Dynamic Price Drop Tracker: Dedicated filter highlighting active price reductions across home-cooked meals.
• 📊 Interactive Chart.js Modals: Detailed price history charts displaying price trends over time per dish.
• ⚡ Hybrid Architecture: Runs as a dynamic HTTP REST API service (server.py) or as a static site backed by exported JSON datasets (export_static_data.py).
• 💾 Relational SQLite Database: Structured storage (cookups.db) maintaining dishes, categories, cooks, and daily price logs.

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🏗️ System Architecture

flowchart TD
    subgraph Data_Collection ["⚡ Ingestion Pipeline"]
        Scraper[scraper.py] -->|Crawl Cookups API| CookupsAPI[Cookups Platform]
        CookupsAPI -->|Parse Dishes & Cooks| DB[(SQLite: cookups.db)]
    end

    subgraph Data_Export ["💾 Static Dataset Generation"]
        DB -->|export_static_data.py| StaticFiles[data/*.json]
        StaticFiles --> Stats[stats.json]
        StaticFiles --> Dishes[dishes.json]
        StaticFiles --> History[history.json]
    end

    subgraph Deployment_Modes ["🌐 Execution Modes"]
        DB -->|server.py REST API| LocalUI[Local Web App :8080]
        StaticFiles -->|GitHub Actions| GHPages[GitHub Pages Deployment]
    end

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📁 Repository Structure

COOKup/
├── scraper.py              # API crawler and SQLite database populator
├── server.py               # Python HTTP server & REST API handler (:8080)
├── export_static_data.py   # Exporter script generating static JSON datasets
├── cookups.db              # SQLite database (dishes, cooks, categories, price history)
├── app.js                  # Frontend interactive SPA (dual REST API / static fallback)
├── index.html              # Responsive dashboard markup
├── style.css               # Modern dashboard layout styling
├── data/                   # Pre-baked static JSON files for GitHub Pages
│   ├── stats.json          # Overall platform statistics summary
│   ├── categories.json     # Category breakdown map
│   ├── dishes.json         # Dish records lookup
│   └── history.json        # Historical price change logs
└── .github/workflows/
    └── deploy.yml          # GitHub Pages automated deployment workflow

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🛠️ Usage & Local Setup

1. Local Server Mode (Dynamic REST API)

To launch the backend API server and web interface:

python server.py

Open http://localhost:8080 in your web browser.

2. Updating Static Data for GitHub Pages

To crawl fresh data and update SQLite database:

python scraper.py

To export updated database records into static JSON datasets:

python export_static_data.py

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📜 License

Distributed under the MIT License. Data rights belong to Cookups. Built for analytical and personal tracking purposes.