admin d78bd1864e feat(ui): URL week selector + aisle-migration 0015 cast fix (Sprint 5 F5)
F5 — Persistent week selector in URL (the audit's F5 / H7 finding).

Backend:
- GET /api/meals and GET /api/shopping-list now accept an optional
  ?week_start=YYYY-MM-DD query param. When set, the response is the
  MealPlan for that week (any status). When omitted, behaviour is
  unchanged: meals returns the latest plan; shopping-list returns
  the latest approved/locked plan with fallback to latest.
- No new dependencies; uses FastAPI's Optional[date] Query type
  which auto-validates the YYYY-MM-DD format.
- Files: backend/app/api/meals.py:30-57, shopping_list.py:27-60.

Frontend:
- New week helpers in lib/utils.ts: isoMonday(), parseIsoDate(),
  shiftIsoDate(), formatIsoDate(). All UTC-based to match the
  backend's date column. isoMonday returns the ISO date of the
  Monday of a given date's week.
- api/index.ts: meals.getPlanned(weekStart?) and
  shoppingList.get(weekStart?) take an optional ISO date string.
  Axios drops undefined params, so callers can omit them.
- Dashboard: useSearchParams('week') reads the URL; if absent or
  invalid, falls back to this week's Monday (so the default URL is
  empty). The queryKey now includes weekStart, so navigating weeks
  fetches the right plan. A new segmented control in the header
  (chevron-left | 'This week' / 'Current' jump button | chevron-
  right) lets the user step weeks; the jump button highlights
  primary-50 when the displayed week IS the current week. 'This
  week' clears the ?week param. Mutations (move/approve/deny/
  delete/generate) now invalidate ['mealPlan', weekStart] so the
  right week refetches.
- ShoppingList: same URL sync, same segmented control, same
  weekStart in queryKey. The 'no plan' empty state branches on
  isCurrentWeek: 'No shopping list yet' (current) vs 'No plan for
  that week' (any other week). The local-storage check-state key
  naturally isolates per week (it uses shoppingList.week_start_date
  which is the server's view of the current plan's week).

Migration 0015 cast fix:
- Discovered while smoke-testing on the local dev DB: the
  CASE expression in 0015_normalize_pantry_aisles.py failed
  with 'operator does not exist: text = boolean' on the
  varchar(100) aisle column. Root cause: the CASE branches were
  inferred as different types (string vs NULL) so the SET
  target type couldn't be unified.
- Fix: explicit ::varchar(100) cast on the CASE expression.
  Also simplified the WHEN '' branch (was NULLIF(...) IS NULL
  with implicit bool comparison). Tested on local dev DB:
  alembic upgrade head now succeeds; the 21196 rows that the
  Sprint 2 dry-run predicted actually normalize correctly.
  This means Sprint 2's deploy was blocked on the same bug
  (the deployment host would have hit the same error).
- Verified via curl: /api/shopping-list?week_start=2026-05-15
  returns 25 items with aisles 'Meat & Seafood', 'Pantry',
  'Produce', 'Dairy & Eggs' (the canonical labels the migration
  produces). Pre-migration aisles like 'meat_seafood' are gone.

Build: tsc 0 errors, vite 0 errors. 7 files, +196/-22.
2026-06-04 12:30:49 -07:00

Meal Planner

Self-hosted meal planning system that integrates with Lucky California grocery store, sends weekly meal proposals via email to family members, generates shopping lists, and learns from feedback.

Background

This project was born out of frustration with meal kit services (Blue Apron → EveryPlate → HungryRoot → Sunbasket) that:

  • Escalate costs to 3x ingredient markup
  • Fall into repetitive meal rhythms
  • Force users to log into apps to manage selections
  • Don't integrate with home pantry items

Features

  • Grocery Integration: Scrapes Lucky California weekly ads and sales
  • Family Approval Workflow: Email proposals with approve/deny; one denial swaps the meal
  • Shopping List Generation: Weekly list grouped by store aisles, highlighting sales, with interactive checkboxes to track purchased items
  • Pantry Integration: Specify home items to incorporate into suggestions
  • Web UI: Modern interface for the whole family
  • Learning: Feedback-based meal recommendations, with weekly auto-discovery of new recipes from external APIs when family preferences are signaled
  • Recipe Images: Scraped from public recipe sites, AI fallback available
  • Unit Conversion: Converts recipe quantities (cups, tbsp, lb) to grocery units for accurate cost estimates

Architecture

  • Backend: Python/FastAPI
  • Database: PostgreSQL
  • Frontend: React + Tailwind CSS
  • Email: SendGrid
  • Hosting: Docker Compose with nginx reverse proxy

Documentation

Quick Start

# Clone and start
docker-compose up -d

# View logs
docker-compose logs -f

# Stop
docker-compose down

Family Profile

Household: 2 adults, 2 children

  • One adult likes mushrooms, one child OK with them
  • Three family members do NOT like mushrooms
  • No allergies
  • Calorie, budget, and health conscious eating

Approval Workflow

  1. System generates 7-day meal plan based on sales, dietary constraints, budget, variety
  2. Email sent to both adults with meal previews
  3. One denial = meal swapped; no denials = auto-approved
  4. Shopping list generated after approval

Tech Stack

Component Technology
Backend Python 3.11, FastAPI
Database PostgreSQL 15
Frontend React 18, TypeScript, Tailwind
Scraping Playwright, BeautifulSoup
Email SendGrid
Hosting Docker Compose, nginx
S
Description
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TypeScript 25.9%
JavaScript 0.5%
PLpgSQL 0.4%
CSS 0.3%
Other 0.2%