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MEAL_PLANNER_FEATURE.md

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🍽️ Meal Planner Feature

Overview

A comprehensive meal planning system that allows users to:

  • Create and manage weekly meal plans
  • Add specific recipes to planned meals with serving sizes
  • Auto-generate shopping lists from meal plans
  • Track nutritional information for planned meals
  • Share meal plans with others

New Features Added

Backend Components

1. Database Models (app/models/meal_plan.py)

  • MealPlan: Core meal plan with name, description, date range, and public/private settings
  • PlannedMeal: Individual meals in a plan (breakfast, lunch, dinner, snack) with recipe links
  • ShoppingList: Auto-generated shopping lists from meal plans
  • ShoppingListItem: Individual items in shopping lists with purchase tracking

2. API Schemas (app/schemas/meal_plan.py)

  • Pydantic models for request/response validation
  • Support for CRUD operations on meal plans and planned meals
  • Shopping list and nutrition summary schemas

3. Service Layer (app/services/meal_plan_service.py)

  • Business logic for meal plan management
  • Shopping list generation with ingredient aggregation
  • Nutrition calculation (mock implementation ready for real data)
  • Permission-based access control

4. API Endpoints (app/api/v1/meal_plans.py)

  • POST /meal-plans - Create new meal plan
  • GET /meal-plans - List user's meal plans
  • GET /meal-plans/{id} - Get specific meal plan
  • PUT /meal-plans/{id} - Update meal plan
  • DELETE /meal-plans/{id} - Delete meal plan
  • POST /meal-plans/{id}/meals - Add meal to plan
  • POST /meal-plans/{id}/shopping-list - Generate shopping list
  • GET /meal-plans/{id}/nutrition - Get nutrition summary

Frontend Components

1. Meal Planner Dashboard (src/components/MealPlannerDashboard.tsx)

  • Complete meal planning interface
  • Calendar-based meal scheduling
  • Shopping list management with purchase tracking
  • Nutrition summary display
  • Responsive design with Tailwind CSS

2. API Integration (src/lib/meal-plan-api.ts)

  • TypeScript API client for all meal planning endpoints
  • Type-safe request/response handling
  • Authentication support

3. Updated Main App (src/App.tsx)

  • Added navigation to meal planner
  • Feature showcase on home page

Key Features

1. Meal Planning

  • Create weekly/custom date range meal plans
  • Add recipes to specific days and meal types
  • Specify serving sizes for accurate shopping lists
  • Add notes for meal customizations

2. Smart Shopping Lists

  • Automatically aggregate ingredients from all planned meals
  • Group items by category (Produce, Dairy, Meat, etc.)
  • Track purchase status
  • Prevent duplicate ingredients

3. Nutrition Tracking

  • Calculate total calories, protein, carbs, and fat
  • Per-meal and total plan summaries
  • Visual nutrition dashboard

4. Social Features

  • Make meal plans public to share with community
  • Private meal plans for personal use

Technical Implementation

Database Schema

-- Core tables for meal planning
meal_plans (id, name, description, user_id, start_date, end_date, is_public, created_at, updated_at)
planned_meals (id, meal_plan_id, recipe_id, meal_date, meal_type, servings, notes, created_at)
shopping_lists (id, meal_plan_id, name, created_at, updated_at)
shopping_list_items (id, shopping_list_id, ingredient_name, quantity, unit, category, is_purchased, notes)

API Architecture

  • RESTful API design
  • JWT authentication
  • Input validation with Pydantic
  • Error handling and proper HTTP status codes

Frontend Architecture

  • React with TypeScript
  • Component-based architecture
  • State management with React hooks
  • Responsive design with Tailwind CSS

Future Enhancements

  1. Recipe Integration: Connect with actual recipe database for ingredient extraction
  2. Grocery Store Integration: Map ingredients to store locations/prices
  3. Meal Plan Templates: Pre-made meal plans for different dietary preferences
  4. Collaborative Planning: Family/household meal planning features
  5. Mobile App: React Native implementation
  6. AI Suggestions: ML-powered meal recommendations based on preferences

Installation Notes

The feature requires:

  • Backend: FastAPI, SQLAlchemy, Pydantic
  • Frontend: React, TypeScript, Tailwind CSS, Lucide React icons
  • Database: PostgreSQL or SQLite

This feature significantly enhances the Recipe Hub platform by adding practical meal planning functionality that goes beyond simple recipe sharing, making it a comprehensive cooking and meal management solution.