Tamari

Tamari

Self-hosted recipe manager with meal planning and shopping lists

113stars
6forks
Last commit: 1d ago
Repo age: 2y old
Tamari screenshot

Tamari is a web-based recipe manager built with Python and the Flask framework. It provides tools to store, organize, search, import, and share recipes along with meal planning and shopping list functionality.

Key Features

  • User accounts with email/password login and optional password reset via mail
  • Save detailed recipes (title, category, time, servings, ingredients, instructions, nutrition, photo) and mark favorites
  • Real-time search-as-you-type and browse by category
  • Explore and import recipes from a large indexed collection of external sites with one-click import
  • Meal Planner to schedule recipes up to 30 days in advance
  • Per-store shopping lists; add all recipe ingredients to a list and check items off; barcode scanning supported
  • REST API to manage recipes, shopping lists, and meal plans programmatically
  • Customization options: themes (light/dark), accent colors, photo size, items per page, and profile settings
  • Docker image and manual installation instructions; includes database migrations and Gunicorn-based deployment
  • Data export/import via ZIP for backups and migration

Use Cases

  • Maintain a personal, searchable collection of family recipes with photos and nutrition info
  • Plan weekly meals and generate shopping lists populated directly from chosen recipes
  • Import recipes found online into a private collection for later use or sharing with friends

Limitations and Considerations

  • Recipe import/parsing may fail on some websites due to varied HTML structures; imported content quality varies by source
  • The default deployment uses a simple SQL database configuration; production setups may require custom DB tuning and reverse proxy configuration

Tamari is a practical, feature-rich option for individuals or households who want a private, self-hosted recipe management solution with programmatic access and mobile-friendly UI. It is suitable for local deployments via Docker or a standard Python/Flask stack.

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