✔ Professional ✔ GitHub-friendly ✔ Includes screenshots placeholder ✔ Installation guide ✔ Features list ✔ Tech stack ✔ File structure ✔ Future roadmap ✔ License (MIT)
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✅ Your Complete README.md
(You can copy-paste directly into GitHub)
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🧪 PantryClean — Recipe Ingredient Normalizer PantryClean is a client-side recipe parsing tool that converts messy ingredient text into a structured format. It automatically detects quantities, units, ingredient names, health alternatives, and ambiguity flags — while keeping everything stored locally in the browser.
⚡ No backend. No database. No tracking. Everything happens locally.
🍽️ What PantryClean Does Feature Status Parse free-text recipe ingredients ✅ Unit normalization (ml/g/cups/oz/etc.) ✅ Detect ambiguous instructions (like "pinch", "to taste") ✅ Autofill common interpretations (eggs, onions, cloves, bunches) ✅ Editable ingredient corrections ✅ Export to CSV, JSON, clipboard ✅ Built-in sample recipes ✅ Settings for unit system & precision ✅ LocalStorage persistence (no server) ✅ Responsive UI with dark/light theme ✅ 🏗️ Tech Stack Layer Technology UI HTML5 + CSS (custom styling, no framework) Logic Vanilla JavaScript Storage LocalStorage UX Tooltip parsing, modals, keyboard shortcuts CSS Features CSS variables, accessibility rules, responsive layout 📁 Project Structure PantryClean/ │ ├── index.html # Landing page ├── app.html # Main recipe normalizing app ├── styles.css # Full UI styling (~500 lines) ├── app.js # Core parsing engine + UI logic └── README.md # You’re reading this 😄
🚀 Getting Started 1️⃣ Clone the repository: git clone https://github.com/yourusername/PantryClean.git cd PantryClean
2️⃣ Run locally:
No build step needed — just open:
index.html
in your browser.
3️⃣ (Optional) Run with a local server:
npx serve
or:
python3 -m http.server
Then visit:
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🧠 How Parsing Works
PantryClean uses multiple detection layers: • Unicode fraction handling • Regex quantity extraction • Unit synonym mapping (e.g., tbsp, tablespoon, T → tablespoon) • Ingredient cleanup • Ambiguity scoring • Conversion rules based on user settings • Local corrections override future parsing
Example:
"2 tbsp chopped fresh coriander" ↓ Qty: 30 ml Unit: ml Ingredient: coriander Flags: none
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⚙️ Settings
Users can customize: • Metric / Imperial formats • Preferred volume unit (ml, cups, tablespoon, etc.) • Preferred weight (g, oz, lb, etc.) • Decimal precision • Handling tiny measurements (pinch, <15ml, etc.)
All preferences are saved automatically.
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💾 Data Persistence • Saved parsing corrections are stored under:
localStorage.pantryClean_corrections
• Settings are stored under:
localStorage.pantryClean_settings
No backend is used — everything lives on the user’s device.
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🧰 Keyboard Shortcuts
Shortcut Action Ctrl + Enter Parse ingredients Esc Close active modal S Open Settings
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📤 Export Options
Format Example Use CSV Meal planning, spreadsheets JSON Grocery apps, automation Clipboard text Quick sharing or notes
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🧩 Future Improvements (Roadmap) • AI category tagging (vegetable, protein, spice, dairy, etc.) • Shopping list grouping by aisle • OCR support for printed recipes • Multi-language ingredient dictionary • Nutrition estimation API mode
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📸 Screenshots
(Add images here after deployment)
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🧑💻 Contributing
Pull requests are welcome! Open an issue for bugs, enhancements, or new feature proposals.
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📜 License
MIT License — free to use, modify, and distribute.
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🌟 Credits
Built by Shridhar Panigrahi Designed for clean cooking workflows, automation, and digital recipe storage.
- Generate a live GitHub description
- Create a logo + favicon
- Make a deployment script for Netlify/Vercel
- Convert this to a PWA offline app
Just say: