From 1a835d369a43eb0a217d8453ef87fde916224a51 Mon Sep 17 00:00:00 2001 From: Trey t Date: Sat, 10 Jan 2026 17:54:31 -0600 Subject: [PATCH] remove gsd --- .planning/MILESTONES.md | 29 --- .planning/PROJECT.md | 72 ------ .planning/ROADMAP.md | 136 ---------- .planning/STATE.md | 56 ----- .planning/codebase/ARCHITECTURE.md | 147 ----------- .planning/codebase/CONCERNS.md | 132 ---------- .planning/codebase/CONVENTIONS.md | 150 ----------- .planning/codebase/INTEGRATIONS.md | 134 ---------- .planning/codebase/STACK.md | 106 -------- .planning/codebase/STRUCTURE.md | 151 ------------ .planning/codebase/TESTING.md | 223 ----------------- .planning/config.json | 18 -- .planning/milestones/v1.0-ROADMAP.md | 150 ----------- .../01-script-architecture/01-01-PLAN.md | 127 ---------- .../01-script-architecture/01-01-SUMMARY.md | 94 ------- .../01-script-architecture/01-02-PLAN.md | 119 --------- .../01-script-architecture/01-02-SUMMARY.md | 91 ------- .../01-script-architecture/01-03-PLAN.md | 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a/.planning/MILESTONES.md +++ /dev/null @@ -1,29 +0,0 @@ -# Project Milestones: SportsTime - -## v1.0 Data Pipeline (Shipped: 2026-01-10) - -**Delivered:** Complete Python data pipeline with sport-organized modules, full stadium database, alias systems, and CloudKit CRUD operations for the SportsTime iOS app. - -**Phases completed:** 1-7 (+ 2.1 inserted) — 15 plans total - -**Key accomplishments:** - -- Reorganized monolithic scripts into 7 sport modules (mlb.py, nba.py, nhl.py, nfl.py, mls.py, wnba.py, nwsl.py) -- Built complete stadium database with 148 venues across all 7 sports with verified coordinates -- Implemented team and stadium alias systems for cross-source name variations -- Added full CloudKit CRUD with diff reporting, smart sync, and orphan detection -- Created comprehensive validation with health scores and completeness metrics -- Reduced scrape_schedules.py orchestrator from 3359 to 733 lines (78% reduction) - -**Stats:** - -- 15 plans executed across 8 phases -- ~12,000 lines of Python -- 92 minutes total execution time (6.1 min average per plan) -- 2 days from start to ship (2026-01-09 → 2026-01-10) - -**Git range:** `feat(01-01)` → `docs(07-01)` - -**What's next:** iOS app improvements — IAP, UI/UX, testing - ---- diff --git a/.planning/PROJECT.md b/.planning/PROJECT.md deleted file mode 100644 index 11e1217..0000000 --- a/.planning/PROJECT.md +++ /dev/null @@ -1,72 +0,0 @@ -# SportsTime Data Pipeline - -## What This Is - -A Python data pipeline that scrapes, canonicalizes, and syncs sports schedule data to CloudKit for the SportsTime iOS app. The pipeline ensures every game correctly links to its home/away teams and stadium with complete, accurate data across MLB, NBA, NHL, and NFL. - -## Core Value - -Every game must correctly link to its teams and stadium — a game at the wrong venue or with broken team links ruins trip planning. - -## Requirements - -### Validated - -- ✓ Basic schedule scraping for MLB, NBA, NHL, NFL — existing -- ✓ Canonical data models (stadiums, teams, games) — existing -- ✓ CloudKit import capability — existing -- ✓ Bundled JSON generation for offline-first — existing -- ✓ Split scripts by sport (MLB, NBA, NHL, NFL as separate modules) — v1.0 -- ✓ Complete stadium database with correct coordinates and names (148 stadiums) — v1.0 -- ✓ Stadium alias system for name variations across sources — v1.0 -- ✓ Correct game→team→stadium canonical linking for all sports — v1.0 -- ✓ Full CRUD CloudKit management (create, read, update, delete) — v1.0 -- ✓ Validation reports showing counts, gaps, and orphan records — v1.0 -- ✓ Team alias system for name variations across sources — v1.0 - -### Active - -(None — v1.0 complete, planning next milestone) - -### Out of Scope - -- Real-time scores — this is schedule data, not live game tracking -- Adding new sports (MLS, WNBA, etc.) — stabilize current 4 first -- iOS app changes — this is purely backend/script work - -## Context - -**Current State:** -- Data quality: Resolved — all games correctly link to teams and stadiums via canonical IDs -- Stadium database: Complete — 148 stadiums across 7 sports with verified coordinates -- Script organization: Resolved — sport-specific modules (mlb.py, nba.py, nhl.py, nfl.py, mls.py, wnba.py, nwsl.py) -- CloudKit: Full CRUD — create, update, delete with diff reporting, verification, and orphan detection - -**Existing Infrastructure:** -- Python 3 with requests, beautifulsoup4, pandas, lxml -- CloudKit server-to-server auth via cryptography package -- Bundled JSON in `SportsTime/Resources/` for offline bootstrap -- Data sources: Basketball-Reference, Baseball-Reference, Hockey-Reference, official APIs - -**iOS App Dependency:** -- `AppDataProvider.shared` is single source of truth -- SwiftData models: `CanonicalStadium`, `CanonicalTeam`, `CanonicalGame` -- Domain models expect correct relationships via canonical IDs - -## Constraints - -- **Tech Stack**: Must remain Python (existing tooling, team familiarity) -- **Data Sources**: Free/public APIs and sites only (no paid subscriptions) -- **CloudKit**: Must use existing container (`iCloud.com.sportstime.app`) -- **Compatibility**: Output must match existing Swift model expectations - -## Key Decisions - -| Decision | Rationale | Outcome | -|----------|-----------|---------| -| Split by sport, not function | User preference for organization | ✓ Completed — 7 sport modules (mlb.py, nba.py, nhl.py, nfl.py, mls.py, wnba.py, nwsl.py) | -| Validation reports over automated tests | Faster feedback, easier debugging | ✓ Completed — --validate flag with health scores and completeness metrics | -| Full CRUD over upload-only | Enable data corrections without full rebuild | ✓ Completed — create/update/delete with diff reporting and orphan detection | - ---- -*Last updated: 2026-01-10 after v1.0 Data Pipeline milestone* diff --git a/.planning/ROADMAP.md b/.planning/ROADMAP.md deleted file mode 100644 index bca1c02..0000000 --- a/.planning/ROADMAP.md +++ /dev/null @@ -1,136 +0,0 @@ -# Roadmap: SportsTime - -## Milestones - -- ✅ [v1.0 Data Pipeline](milestones/v1.0-ROADMAP.md) (Phases 1-7) — SHIPPED 2026-01-10 -- 🚧 **v1.1 TDD & Correctness** — Phases 8-12 (in progress) - -## Completed Milestones - -
-v1.0 Data Pipeline (Phases 1-7) — SHIPPED 2026-01-10 - -- [x] Phase 1: Script Architecture (3/3 plans) — completed 2026-01-10 -- [x] Phase 2: Stadium Foundation (2/2 plans) — completed 2026-01-10 -- [x] Phase 2.1: Additional Sports Stadiums (3/3 plans) — completed 2026-01-10 -- [x] Phase 3: Alias Systems (2/2 plans) — completed 2026-01-10 -- [x] Phase 4: Canonical Linking (1/1 plans) — completed 2026-01-10 -- [x] Phase 5: CloudKit CRUD (2/2 plans) — completed 2026-01-10 -- [x] Phase 6: Validation Reports (1/1 plans) — completed 2026-01-10 -- [x] Phase 7: Testing & Documentation (1/1 plans) — completed 2026-01-10 - -**Full details:** [milestones/v1.0-ROADMAP.md](milestones/v1.0-ROADMAP.md) - -
- -### 🚧 v1.1 TDD & Correctness (In Progress) - -**Milestone Goal:** Test-driven validation of trip planning engine — tests define correctness, code must match - -**Constraints:** -- TDD approach: Write tests first with expected behavior, then fix code if tests fail (never modify tests to pass) -- Tests must include edge cases and error conditions -- Mix of short and long trips in test data, varied by region and mileage - -#### Phase 8: DAG System TDD - -**Goal**: Performance and edge case tests with tens of thousands of objects; fix code if tests fail -**Depends on**: v1.0 milestone complete -**Research**: Unlikely (internal patterns, existing code) -**Plans**: 2 -**Status**: Complete -**Completed**: 2026-01-10 - -Plans: -- [x] 08-01: GameDAGRouter edge cases and anchor validation TDD — completed 2026-01-10 -- [x] 08-02: GameDAGRouter performance with large datasets and diversity coverage TDD — completed 2026-01-10 - -#### Phase 9: Trip Planner Modes TDD - -**Goal**: Test game scheduling (by dates), must-see games inclusion, start/end cities routing -**Depends on**: Phase 8 -**Research**: Unlikely (internal patterns) -**Plans**: 3 -**Status**: Complete -**Completed**: 2026-01-10 - -Test expectations: -- By Dates: Game scheduling fits date range, no conflicts, date boundaries respect timezone -- Must-See: All selected games appear, filler games don't conflict, impossible combos return error -- Start/End Cities: Route begins at start city, ends at end city, games found along corridor - -Plans: -- [x] 09-01: Scenario A timezone & conflict TDD — completed 2026-01-10 -- [x] 09-02: Scenario B filler conflict TDD — completed 2026-01-10 -- [x] 09-03: Scenario C corridor efficiency TDD — completed 2026-01-10 - -#### Phase 9.1: Fix Flaky Test When Ran In Parallel (INSERTED) - -**Goal:** Resolve test suite flakiness where tests pass individually but fail in parallel execution -**Depends on:** Phase 9 -**Research:** Unlikely (Swift Testing isolation patterns) -**Plans:** 0 plans - -Plans: -- [ ] TBD (run /gsd:plan-phase 9.1 to break down) - -**Details:** -5 tests fail in full suite but pass individually due to Swift Testing parallel execution + simulator state pollution (discovered in Phase 9 plans 01-02). This phase addresses the root cause to ensure reliable CI/CD testing. - -#### Phase 10: Trip Builder Options TDD - -**Goal**: Test repeat cities option (ON/OFF) and must-stops (non-game attractions) -**Depends on**: Phase 9 -**Research**: Unlikely (internal patterns) -**Plans**: TBD - -Test expectations: -- Repeat Cities ON: Can visit Dallas twice for different games -- Repeat Cities OFF: Visit each city once, algorithm picks best game -- Must-stops: Non-game POIs (attractions) appear in itinerary - -Plans: -- [ ] 10-01: TBD (run /gsd:plan-phase 10 to break down) - -#### Phase 11: Itinerary & Constraints TDD - -**Goal**: Test travel itinerary output (directions, distance/time) and driving limits -**Depends on**: Phase 10 -**Research**: Unlikely (internal patterns) -**Plans**: TBD - -Test expectations: -- Travel itinerary: Distance and time shown between each stop -- Driving limits: 2 drivers × 400mi/day max = 800mi/day allowed; trips exceeding limit rejected - -Plans: -- [ ] 11-01: TBD (run /gsd:plan-phase 11 to break down) - -#### Phase 12: Integration Validation - -**Goal**: End-to-end scenarios and regression suite covering all planning modes -**Depends on**: Phase 11 -**Research**: Unlikely (internal patterns) -**Plans**: TBD - -Plans: -- [ ] 12-01: TBD (run /gsd:plan-phase 12 to break down) - -## Progress - -| Phase | Milestone | Plans Complete | Status | Completed | -|-------|-----------|----------------|--------|-----------| -| 1. Script Architecture | v1.0 | 3/3 | Complete | 2026-01-10 | -| 2. Stadium Foundation | v1.0 | 2/2 | Complete | 2026-01-10 | -| 2.1. Additional Sports Stadiums | v1.0 | 3/3 | Complete | 2026-01-10 | -| 3. Alias Systems | v1.0 | 2/2 | Complete | 2026-01-10 | -| 4. Canonical Linking | v1.0 | 1/1 | Complete | 2026-01-10 | -| 5. CloudKit CRUD | v1.0 | 2/2 | Complete | 2026-01-10 | -| 6. Validation Reports | v1.0 | 1/1 | Complete | 2026-01-10 | -| 7. Testing & Documentation | v1.0 | 1/1 | Complete | 2026-01-10 | -| 8. DAG System TDD | v1.1 | 2/2 | Complete | 2026-01-10 | -| 9. Trip Planner Modes TDD | v1.1 | 2/3 | In progress | - | -| 9.1. Fix Flaky Test When Ran In Parallel | v1.1 | 0/? | Not started | - | -| 10. Trip Builder Options TDD | v1.1 | 0/? | Not started | - | -| 11. Itinerary & Constraints TDD | v1.1 | 0/? | Not started | - | -| 12. Integration Validation | v1.1 | 0/? | Not started | - | diff --git a/.planning/STATE.md b/.planning/STATE.md deleted file mode 100644 index 90b7fa0..0000000 --- a/.planning/STATE.md +++ /dev/null @@ -1,56 +0,0 @@ -# Project State - -## Project Reference - -See: .planning/PROJECT.md (updated 2026-01-10) - -**Core value:** Every game must correctly link to its teams and stadium — a game at the wrong venue or with broken team links ruins trip planning. -**Current focus:** v1.1 TDD & Correctness — Phase 9 - -## Current Position - -Phase: 9 of 12 (Trip Planner Modes TDD) -Plan: 3 of 3 in current phase -Status: Phase complete -Last activity: 2026-01-10 — Completed 09-03: Scenario C corridor efficiency TDD - -Progress: ████░░░░░░ 40% - -## Shipped Milestones - -| Milestone | Phases | Plans | Shipped | -|-----------|--------|-------|---------| -| v1.0 Data Pipeline | 1-7 (+2.1) | 15 | 2026-01-10 | - -## Accumulated Context - -### Decisions - -| Phase | Decision | Rationale | -|-------|----------|-----------| -| 08-02 | Dynamic beam width scaling (800+→50, 2K+→30, 5K+→25) | Prevents exponential blowup with large datasets while preserving diversity; achieves 10-17x speedup | -| 08-02 | Early termination (<5K at 2x, ≥5K at 3x beam width) | Stops expansion when sufficient diverse routes found; ensures consistent performance | -| 09-01 | Dynamic time buffers (same-day: 2hr/0.5hr, multi-day: 3hr/1hr) | Enables realistic doubleheaders while preserving multi-day behavior; people leave during/after first game for same-day transitions | - -See also: PROJECT.md Key Decisions table for architectural decisions. - -### Deferred Issues - -- CBB support (350+ D1 teams requires separate scoped phase) -- Test suite flakiness: 5 tests fail in full suite but pass individually (Swift Testing parallel execution + simulator state pollution, pre-existing issue) - -### Blockers/Concerns - -None. - -### Roadmap Evolution - -- Milestone v1.1 TDD & Correctness created: Test-driven validation of trip planning engine, 5 phases (Phase 8-12) -- Phase 9.1 inserted after Phase 9: Fix flaky test when ran in parallel (URGENT) - 5 tests fail in parallel but pass individually due to Swift Testing state pollution - -## Session Continuity - -Last session: 2026-01-10 -Stopped at: Phase 9 complete (trip planner modes TDD) -Resume file: None -Next action: /gsd:execute-plan .planning/phases/10-trip-builder-options-tdd/10-01-PLAN.md diff --git a/.planning/codebase/ARCHITECTURE.md b/.planning/codebase/ARCHITECTURE.md deleted file mode 100644 index 61ace50..0000000 --- a/.planning/codebase/ARCHITECTURE.md +++ /dev/null @@ -1,147 +0,0 @@ -# Architecture - -**Analysis Date:** 2026-01-09 - -## Pattern Overview - -**Overall:** Clean MVVM with Feature-Based Modules + Offline-First Data Architecture - -**Key Characteristics:** -- Three-layer architecture (Presentation, Domain, Data) -- Single source of truth (`AppDataProvider.shared`) -- Offline-first with background CloudKit sync -- Scenario-based trip planning (A/B/C discriminated scenarios) -- Explicit failure handling (no silent errors) - -## Layers - -**Presentation Layer (`Features/`):** -- Purpose: SwiftUI Views + @Observable ViewModels -- Contains: Feature modules (Home, Trip, Schedule, Settings, Progress) -- Depends on: Domain layer for planning, Data layer for models -- Used by: App entry point - -**Domain Layer (`Planning/`):** -- Purpose: Trip planning business logic -- Contains: TripPlanningEngine, Scenario Planners, GameDAGRouter, TravelEstimator -- Depends on: Domain models only (Game, Stadium, Team) -- Used by: Presentation layer ViewModels - -**Data Layer (`Core/`):** -- Purpose: Models, services, persistence -- Contains: Domain models, SwiftData models, CloudKit sync, location services -- Depends on: Foundation, SwiftData, CloudKit, MapKit -- Used by: All layers - -**Export Layer (`Export/`):** -- Purpose: PDF generation with asset prefetching -- Contains: PDFGenerator, map snapshots, remote images, POI search -- Depends on: Domain models, UIKit/PDFKit -- Used by: TripDetailView - -## Data Flow - -**App Startup Sequence:** - -1. `SportsTimeApp.swift` (@main) → WindowGroup -2. `BootstrappedContentView` initializes data: - - `BootstrapService.bootstrapIfNeeded()` - JSON → SwiftData (first launch) - - `AppDataProvider.configure(with: context)` - Sets ModelContext - - `AppDataProvider.loadInitialData()` - SwiftData → memory -3. App immediately usable with local data -4. Background: `CanonicalSyncService.syncAll()` - CloudKit → SwiftData (non-blocking) - -**Trip Planning Request:** - -1. User Input → `TripCreationView` -2. `TripCreationViewModel` builds `PlanningRequest` -3. `TripPlanningEngine.planItineraries(request:)` - - Detects scenario (A: date range, B: selected games, C: locations) - - Delegates to appropriate `ScenarioPlanner` -4. `GameDAGRouter` finds routes with diversity -5. Returns `ItineraryResult` (success with ranked options or explicit failure) -6. User selects option → `SavedTrip` persisted - -**State Management:** -- ViewModels use `@Observable` (not ObservableObject) -- SwiftData `@Query` for saved trips -- In-memory cache in `AppDataProvider` for canonical data - -## Key Abstractions - -**AppDataProvider:** -- Purpose: Single source of truth for all canonical data reads -- Location: `Core/Services/DataProvider.swift` -- Pattern: Singleton with in-memory cache -- Usage: `AppDataProvider.shared.stadiums`, `.teams`, `.fetchGames()` - -**ScenarioPlanner Protocol:** -- Purpose: Encapsulates planning algorithm for each scenario type -- Examples: `ScenarioAPlanner`, `ScenarioBPlanner`, `ScenarioCPlanner` -- Pattern: Strategy pattern with factory (`ScenarioPlannerFactory`) - -**GameDAGRouter:** -- Purpose: DAG-based route finding with multi-dimensional diversity -- Location: `Planning/Engine/GameDAGRouter.swift` -- Pattern: Beam search with diversity pruning - -**TripPlanningEngine:** -- Purpose: Thin orchestrator delegating to scenario planners -- Location: `Planning/Engine/TripPlanningEngine.swift` -- Pattern: Facade wrapping scenario detection and filter application - -## Entry Points - -**App Entry:** -- Location: `SportsTime/SportsTimeApp.swift` -- Triggers: App launch -- Responsibilities: SwiftData schema, ModelContainer, BootstrappedContentView - -**Main UI Entry:** -- Location: `Features/Home/Views/HomeView.swift` -- Triggers: After bootstrap completes -- Responsibilities: TabView with 4 tabs (Home, Schedule, Trips, Progress) - -**Trip Creation:** -- Location: `Features/Trip/Views/TripCreationView.swift` -- Triggers: User taps "New Trip" -- Responsibilities: Form input, calls TripCreationViewModel - -**Trip Display:** -- Location: `Features/Trip/Views/TripDetailView.swift` -- Triggers: User selects trip -- Responsibilities: Itinerary display, conflict detection, PDF export - -## Error Handling - -**Strategy:** Explicit failure types with reasons, no silent errors - -**Patterns:** -- `ItineraryResult` enum: `.success([ItineraryOption])` or `.failure(PlanningFailure)` -- `PlanningFailure` contains `FailureReason` and user-friendly message -- ViewModels expose `.error` state for UI display -- Services use `throws` for recoverable errors - -## Cross-Cutting Concerns - -**Logging:** -- `print()` with emoji prefixes for debugging -- No production logging framework - -**Validation:** -- Input validation in ViewModels before planning -- `ConstraintViolation` type for planning constraints - -**Thread Safety:** -- `@MainActor` for UI-bound services -- `actor` types for planning engine components -- Explicit isolation annotations throughout - -**Data Consistency:** -- Canonical IDs (string) + UUIDs for stable identity -- SwiftData ↔ Domain model conversion via `.toDomain()` methods - ---- - -*Architecture analysis: 2026-01-09* -*Update when major patterns change* diff --git a/.planning/codebase/CONCERNS.md b/.planning/codebase/CONCERNS.md deleted file mode 100644 index 5d24968..0000000 --- a/.planning/codebase/CONCERNS.md +++ /dev/null @@ -1,132 +0,0 @@ -# Codebase Concerns - -**Analysis Date:** 2026-01-09 - -## Tech Debt - -**Foundation Models disabled:** -- Issue: On-device AI route descriptions disabled due to simulator bug -- File: `SportsTime/Core/Services/RouteDescriptionGenerator.swift:30` -- Why: iOS 26.2 simulator crashes with Foundation Models -- Impact: Route descriptions not generated; feature incomplete -- Fix approach: Re-enable when Apple fixes the framework (tracked via TODO) - -**Large service files:** -- Issue: Some service files exceed 500-800 lines -- Files: `SportsTime/Core/Services/SuggestedTripsGenerator.swift` (794 lines) -- Why: Accumulated functionality over time -- Impact: Harder to navigate and test in isolation -- Fix approach: Extract helper methods to focused utilities - -## Known Bugs - -**No known bugs documented.** - -The codebase has comprehensive test coverage (180+ tests) and follows a regression test protocol for bug fixes. - -## Security Considerations - -**No hardcoded secrets:** -- CloudKit uses entitlements (no API keys in code) -- Sports APIs are public (no authentication required) -- No .env files or credential storage - -**CloudKit data access:** -- Risk: Public database readable by any app user -- Current mitigation: Only non-sensitive schedule data in public DB -- Recommendations: User data correctly uses private database - -**Force unwrap usage:** -- Risk: Potential crashes from force unwraps (`!`) -- Current state: Limited to test fixtures and controlled scenarios -- Recommendations: Continue avoiding force unwraps in production code - -## Performance Bottlenecks - -**No significant bottlenecks detected.** - -- Route planning uses efficient DAG-based algorithms with beam search -- Data loading is async and non-blocking -- PDF export uses parallel asset prefetching (`PDFAssetPrefetcher.swift`) - -**Potential areas to monitor:** -- Large game datasets (1000+ games) during planning -- Map snapshot generation for long trips (10+ stops) - -## Fragile Areas - -**GameDAGRouter complexity:** -- File: `SportsTime/Planning/Engine/GameDAGRouter.swift` -- Why fragile: Complex beam search with diversity pruning -- Common failures: Edge cases in route diversity calculations -- Safe modification: Comprehensive test coverage exists (180+ tests total) -- Test coverage: Good - multiple scenario planner test suites - -**Canonical data sync:** -- Files: `SportsTime/Core/Services/CanonicalSyncService.swift`, `DataProvider.swift` -- Why fragile: Multiple data sources (bundled JSON, SwiftData, CloudKit) -- Common failures: Data inconsistency if sync partially completes -- Safe modification: Follow existing patterns, test offline scenarios -- Test coverage: Limited - manual testing recommended - -## Scaling Limits - -**CloudKit free tier:** -- Current capacity: Standard CloudKit quotas -- Limit: 10GB public database, rate limits on queries -- Symptoms at limit: 429 errors, slow sync -- Scaling path: Monitor usage; Apple provides generous free tier - -**In-memory data cache:** -- Current capacity: All stadiums, teams loaded into memory (~few MB) -- Limit: Not expected to hit limits with current data size -- Symptoms at limit: Memory pressure on older devices -- Scaling path: Implement lazy loading if data grows significantly - -## Dependencies at Risk - -**NBA Stats API (unofficial):** -- Risk: Unofficial API that may break without notice -- File: `SportsTime/Core/Services/ScoreAPIProviders/NBAStatsProvider.swift` -- Impact: NBA game scores unavailable if API changes -- Migration plan: Multi-provider fallback system in `FreeScoreAPI.swift` - -**iOS 26+ requirement:** -- Risk: Limits user base to newest iOS version -- Impact: Users on older devices cannot use app -- Migration plan: Monitor adoption; consider lowering deployment target later - -## Missing Critical Features - -**None blocking current functionality.** - -Future phases documented in `docs/MARKET_RESEARCH.md`: -- Phase 2: AI-powered natural language planning -- Phase 3: Stadium bucket list with achievements (partially implemented) -- Phase 4: Group trip coordination -- Phase 5: Fan community features - -## Test Coverage Gaps - -**CloudKit sync integration:** -- What's not tested: Full CloudKit → SwiftData → memory refresh cycle -- Risk: Sync issues not caught before production -- Priority: Medium -- Difficulty to test: Requires CloudKit test containers or mocks - -**PDF generation:** -- What's not tested: PDFGenerator output (visual testing) -- Risk: PDF layout issues not caught automatically -- Priority: Low (manual QA sufficient) -- Difficulty to test: Would need snapshot testing - -**UI tests:** -- What's not tested: Limited UI test coverage -- Risk: UI regressions -- Priority: Low (app is relatively simple UI) -- Difficulty to test: Standard Xcode UI testing - ---- - -*Concerns audit: 2026-01-09* -*Update as issues are fixed or new ones discovered* diff --git a/.planning/codebase/CONVENTIONS.md b/.planning/codebase/CONVENTIONS.md deleted file mode 100644 index e34ddbc..0000000 --- a/.planning/codebase/CONVENTIONS.md +++ /dev/null @@ -1,150 +0,0 @@ -# Coding Conventions - -**Analysis Date:** 2026-01-09 - -## Naming Patterns - -**Files:** -- PascalCase for all Swift files: `TripDetailView.swift`, `DataProvider.swift` -- Views: `*View.swift` (e.g., `HomeView.swift`, `TripCreationView.swift`) -- ViewModels: `*ViewModel.swift` (e.g., `TripCreationViewModel.swift`) -- Services: `*Service.swift` (e.g., `LocationService.swift`) -- Tests: `*Tests.swift` (e.g., `TravelEstimatorTests.swift`) - -**Functions:** -- camelCase for all functions: `loadInitialData()`, `planItineraries()` -- No special prefix for async functions -- Handlers: `handle*` pattern not heavily used; actions named directly - -**Variables:** -- camelCase: `selectedSports`, `startDate`, `gamesOnThisDay` -- No underscore prefix for private (Swift convention) -- Constants: camelCase (no UPPER_SNAKE_CASE) - -**Types:** -- PascalCase for all types: `Stadium`, `TripPreferences`, `PlanningRequest` -- No I prefix for protocols: `ScenarioPlanner` (not `IScenarioPlanner`) -- Enums: PascalCase name, camelCase cases: `Sport.mlb`, `FailureReason.noGamesFound` - -## Code Style - -**Formatting:** -- 4-space indentation (inferred from code) -- No SwiftLint or SwiftFormat configuration -- Follows standard Swift conventions organically - -**Section Organization:** -- `// MARK: -` for major sections (560 occurrences across codebase) -- Pattern: `// MARK: - Section Name` -- Example sections: `// MARK: - Properties`, `// MARK: - Public API`, `// MARK: - Private` - -**File Headers:** -```swift -// -// FileName.swift -// SportsTime -// -// Optional description line. -// -``` - -## Import Organization - -**Order:** -1. Foundation/Swift standard library -2. Apple frameworks (SwiftUI, SwiftData, MapKit) -3. Project imports (`@testable import SportsTime` in tests) - -**Grouping:** -- No blank lines between import groups -- Alphabetical not enforced - -**Path Aliases:** -- None used (no module aliasing) - -## Error Handling - -**Patterns:** -- Explicit result types: `ItineraryResult` enum with `.success` / `.failure` -- `throws` for recoverable service errors -- Async functions use `async throws` - -**Error Types:** -- `PlanningFailure` with `FailureReason` enum and user message -- `ConstraintViolation` for planning constraint issues -- SwiftData errors propagated via `try` - -**Async:** -- `async/await` throughout (no completion handlers) -- `try await` pattern for async throwing functions - -## Logging - -**Framework:** -- `print()` with emoji prefixes for debugging -- No production logging framework (Sentry, etc.) - -**Patterns:** -- Warning: `print("⚠️ Warning message")` -- Info: `print("ℹ️ Info message")` -- Error: `print("❌ Error: \(error)")` -- Debug only; no structured logging - -## Comments - -**When to Comment:** -- Explain why, not what -- Document business logic and edge cases -- Complex algorithms get explanatory comments - -**Documentation Comments:** -- Triple-slash `///` for public APIs (487 occurrences) -- Example: - ```swift - /// Main entry point for trip planning. - /// - Parameter request: The planning request containing all inputs - /// - Returns: Ranked itineraries on success, or explicit failure - func planItineraries(request: PlanningRequest) -> ItineraryResult - ``` - -**TODO Comments:** -- Format: `// TODO: description` -- Currently only 1 TODO in codebase: `RouteDescriptionGenerator.swift:30` - -## Function Design - -**Size:** -- No strict line limit enforced -- Large files exist (800+ lines in some services) -- Complex logic extracted to private helpers - -**Parameters:** -- Default parameters used extensively -- Options objects for complex configuration: `PlanningRequest`, `TripPreferences` - -**Return Values:** -- Explicit returns -- Result types for operations that can fail -- Optional for lookups that may not find data - -## Module Design - -**Exports:** -- No barrel files (Swift doesn't use this pattern) -- Public API via `public`/`internal` access control - -**Access Control:** -- `private` for implementation details -- `internal` (default) for module-internal -- `public` for Codable conformances and cross-module APIs - -**Property Wrappers:** -- `@Observable` for ViewModels (modern pattern) -- `@Model` for SwiftData entities -- `@MainActor` for UI-bound services -- `@Query` for SwiftData queries in views - ---- - -*Convention analysis: 2026-01-09* -*Update when patterns change* diff --git a/.planning/codebase/INTEGRATIONS.md b/.planning/codebase/INTEGRATIONS.md deleted file mode 100644 index cd36a56..0000000 --- a/.planning/codebase/INTEGRATIONS.md +++ /dev/null @@ -1,134 +0,0 @@ -# External Integrations - -**Analysis Date:** 2026-01-09 - -## APIs & External Services - -**Sports Data - MLB Stats API:** -- Endpoint: `https://statsapi.mlb.com/api/v1` -- Integration: `Core/Services/ScoreAPIProviders/MLBStatsProvider.swift` -- Purpose: Official MLB schedule and game scores -- Auth: None required (public API) -- Reliability: Official, documented - -**Sports Data - NHL API:** -- Endpoint: `https://api-web.nhle.com/v1` -- Integration: `Core/Services/ScoreAPIProviders/NHLStatsProvider.swift` -- Purpose: Official NHL schedule and game scores -- Auth: None required (public API) -- Reliability: Official, documented - -**Sports Data - NBA Stats API:** -- Endpoint: `https://stats.nba.com/stats` -- Integration: `Core/Services/ScoreAPIProviders/NBAStatsProvider.swift` -- Purpose: NBA stats and schedules (unofficial) -- Auth: Requires specific User-Agent headers -- Reliability: Unofficial, may break without notice - -**Score Resolution Facade:** -- Integration: `Core/Services/FreeScoreAPI.swift` -- Purpose: Multi-provider score resolution with fallback -- Features: Rate limiting, caching, provider tiers -- Cache: `Core/Services/ScoreResolutionCache.swift` - -## Data Storage - -**CloudKit (iCloud):** -- Container: `iCloud.com.sportstime.app` -- Integration: `Core/Services/CloudKitService.swift` -- Purpose: Remote sync for canonical data, photo backup -- Database: Public (schedules), Private (user photos) -- Records: - - `CanonicalStadium`, `CanonicalTeam`, `CanonicalGame` - - `LeagueStructure`, `StadiumAlias`, `TeamAlias` -- Sync Service: `Core/Services/CanonicalSyncService.swift` - -**SwiftData (Local):** -- Integration: `Core/Models/Local/*.swift` -- Purpose: Local persistence, offline-first -- Models: - - Canonical: `CanonicalStadium`, `CanonicalTeam`, `CanonicalGame` - - User: `SavedTrip`, `StadiumVisit`, `UserPreferences`, `Achievement` - -**Bundled JSON:** -- Location: `SportsTime/Resources/*.json` -- Purpose: Bootstrap data for offline-first experience -- Files: `stadiums_canonical.json`, `teams_canonical.json`, `games_canonical.json`, `league_structure.json` - -## Location & Maps Services - -**Apple Maps (MapKit):** -- Geocoding: `Core/Services/LocationService.swift` - Address→Coordinates -- Reverse Geocoding: Coordinates→Address lookup -- Routing: `MKDirections` for travel time/distance -- POI Search: `Export/Services/POISearchService.swift` - Restaurants, attractions -- EV Charging: `Core/Services/EVChargingService.swift` - Charging station search -- Map Snapshots: `Export/Services/MapSnapshotService.swift` - Static map images - -**CoreLocation:** -- Purpose: Coordinate types, user location (if permitted) -- No active GPS tracking; uses user-provided locations - -## Photo Library Integration - -**PhotosPicker:** -- Integration: `Features/Progress/ViewModels/PhotoImportViewModel.swift` -- Purpose: Import photos to match with stadium visits -- Metadata: `Core/Services/PhotoMetadataExtractor.swift` - EXIF extraction - -**Visit Photos:** -- Integration: `Core/Services/VisitPhotoService.swift` -- Storage: Thumbnails in SwiftData, full images in CloudKit private database -- Backup: Automatic CloudKit sync for photo preservation - -## AI/ML Integration - -**Apple Foundation Models:** -- Integration: `Core/Services/RouteDescriptionGenerator.swift` -- Purpose: On-device AI for natural language route descriptions -- Status: Disabled due to iOS 26.2 simulator bug -- Requirement: iOS 26+, Apple Silicon - -## Environment Configuration - -**Development:** -- Required env vars: None -- Secrets location: CloudKit container in entitlements -- Mock/stub services: Uses bundled JSON data - -**Production:** -- CloudKit: Production container (automatic via entitlements) -- APIs: All public endpoints, no API keys required -- Background Modes: remote-notification, fetch, processing - -## Data Pipeline (Scripts/) - -**Schedule Scraping:** -- Script: `Scripts/scrape_schedules.py` -- Sources: Basketball-Reference, Baseball-Reference, Hockey-Reference -- Rate Limiting: 3-second delay per domain -- Output: JSON files for processing - -**Data Processing:** -- `Scripts/canonicalize_stadiums.py` - Normalize stadium identities -- `Scripts/canonicalize_teams.py` - Normalize team identities -- `Scripts/canonicalize_games.py` - Normalize game records -- `Scripts/generate_canonical_data.py` - Generate bundled JSON - -**CloudKit Import:** -- Script: `Scripts/cloudkit_import.py` -- Purpose: Upload canonical data to CloudKit public database -- Auth: CloudKit server-to-server authentication (via cryptography) - -## Webhooks & Callbacks - -**Incoming:** -- None (no server-side components) - -**Outgoing:** -- None (all data fetched on-demand) - ---- - -*Integration audit: 2026-01-09* -*Update when adding/removing external services* diff --git a/.planning/codebase/STACK.md b/.planning/codebase/STACK.md deleted file mode 100644 index 181adc3..0000000 --- a/.planning/codebase/STACK.md +++ /dev/null @@ -1,106 +0,0 @@ -# Technology Stack - -**Analysis Date:** 2026-01-09 - -## Languages - -**Primary:** -- Swift 5.0 - All iOS application code (`SportsTime/*.swift`) - -**Secondary:** -- Python 3 - Data scraping and CloudKit import scripts (`Scripts/*.py`) - -## Runtime - -**Environment:** -- iOS 26.2 deployment target (`SportsTime.xcodeproj/project.pbxproj`) -- Apple Silicon + Intel support - -**Package Manager:** -- None (native Xcode project, no SPM/CocoaPods/Carthage) -- Python: pip with `Scripts/requirements.txt` - -## Frameworks - -**Core:** -- SwiftUI - Primary UI framework (`Features/**/*.swift`) -- UIKit - PDF generation, graphics (`Export/PDFGenerator.swift`) -- Observation - Modern reactive state (`@Observable` ViewModels) - -**Data:** -- SwiftData - Local persistence (`Core/Models/Local/*.swift`) -- CloudKit - Remote sync, public database (`Core/Services/CloudKitService.swift`) - -**Location & Maps:** -- MapKit - Routing, search, snapshots (`Core/Services/LocationService.swift`, `Export/Services/MapSnapshotService.swift`) -- CoreLocation - Coordinates, geocoding support - -**Media:** -- PDFKit - Document generation (`Export/PDFGenerator.swift`) -- Photos/PhotosUI - Photo library access (`Features/Progress/ViewModels/PhotoImportViewModel.swift`) -- ImageIO - Image encoding/decoding - -**AI/ML:** -- FoundationModels - On-device AI for route descriptions (`Core/Services/RouteDescriptionGenerator.swift` - currently disabled) - -**Security:** -- CryptoKit - Cryptographic operations (`Core/Services/BootstrapService.swift`) - -**Testing:** -- Swift Testing - Primary test framework (`SportsTimeTests/*.swift`) -- XCTest - UI tests (`SportsTimeUITests/*.swift`) - -**Build/Dev:** -- Xcode 16+ - Build system -- xcodebuild - CLI builds and tests - -## Key Dependencies - -**Critical:** -- SwiftData - Local data persistence and caching -- CloudKit - Schedule sync and photo backup -- MapKit - Core trip planning (routing, EV charging, POI search) - -**Infrastructure:** -- Foundation URLSession - HTTP networking for sports APIs -- Combine - Reactive patterns alongside Observation - -**Python Pipeline:** -- requests>=2.28.0 - HTTP client for web scraping -- beautifulsoup4>=4.11.0 - HTML parsing -- pandas>=2.0.0 - Data manipulation -- lxml>=4.9.0 - XML/HTML parsing backend -- cryptography>=41.0.0 - CloudKit import (optional) - -## Configuration - -**Environment:** -- No .env files required -- CloudKit container configured in entitlements -- Bundle ID: `com.t-t.SportsTime` - -**Build:** -- `SportsTime.xcodeproj` - Native Xcode project -- `Info.plist` - App configuration with background modes - -**Background Modes:** -- `remote-notification` - Push notifications -- `fetch` - Background refresh -- `processing` - Background tasks - -## Platform Requirements - -**Development:** -- macOS with Xcode 16+ -- iOS Simulator (iPhone 17, iOS 26.2) -- No external dependencies - -**Production:** -- iOS 26.2+ deployment target -- CloudKit entitlement required -- Location services permission - ---- - -*Stack analysis: 2026-01-09* -*Update after major dependency changes* diff --git a/.planning/codebase/STRUCTURE.md b/.planning/codebase/STRUCTURE.md deleted file mode 100644 index ee21788..0000000 --- a/.planning/codebase/STRUCTURE.md +++ /dev/null @@ -1,151 +0,0 @@ -# Codebase Structure - -**Analysis Date:** 2026-01-09 - -## Directory Layout - -``` -SportsTime/ -├── SportsTimeApp.swift # @main entry point -├── Features/ # Presentation layer -│ ├── Home/ # Dashboard, suggested trips -│ ├── Trip/ # Creation & detail views -│ ├── Schedule/ # Browse games -│ ├── Settings/ # User preferences -│ └── Progress/ # Stadium visits, achievements -├── Planning/ # Domain layer -│ ├── Engine/ # Planning algorithms -│ └── Models/ # Planning-specific types -├── Core/ # Data layer -│ ├── Models/ # Domain + Local + CloudKit models -│ ├── Services/ # Data providers, sync, APIs -│ ├── Theme/ # Design system -│ ├── Extensions/ # Swift extensions -│ └── Utilities/ # Helpers -├── Export/ # PDF generation -│ ├── PDFGenerator.swift # Main generator -│ └── Services/ # Asset services -├── Resources/ # Assets, bundled JSON -└── Info.plist # App configuration - -SportsTimeTests/ # Unit tests -SportsTimeUITests/ # UI tests -Scripts/ # Python data pipeline -docs/ # Documentation -``` - -## Directory Purposes - -**Features/ (Presentation):** -- Purpose: SwiftUI Views + @Observable ViewModels -- Contains: Feature-organized modules -- Key files: `HomeView.swift`, `TripCreationView.swift`, `TripDetailView.swift` -- Subdirectories: Views/, ViewModels/ per feature - -**Planning/ (Domain):** -- Purpose: Trip planning business logic -- Contains: Engine algorithms, planning models -- Key files: `TripPlanningEngine.swift`, `GameDAGRouter.swift`, `PlanningModels.swift` -- Subdirectories: Engine/, Models/ - -**Core/ (Data):** -- Purpose: Models, services, infrastructure -- Contains: Domain structs, SwiftData models, services -- Key files: `DataProvider.swift`, `CloudKitService.swift`, `LocationService.swift` -- Subdirectories: Models/Domain/, Models/Local/, Models/CloudKit/, Services/ - -**Export/ (PDF):** -- Purpose: PDF generation with parallel asset fetching -- Contains: PDF generator, asset services -- Key files: `PDFGenerator.swift`, `MapSnapshotService.swift`, `PDFAssetPrefetcher.swift` -- Subdirectories: Services/ - -## Key File Locations - -**Entry Points:** -- `SportsTime/SportsTimeApp.swift` - App entry, SwiftData schema -- `SportsTime/Features/Home/Views/HomeView.swift` - Main TabView - -**Configuration:** -- `SportsTime/Info.plist` - App configuration, background modes -- `SportsTime.xcodeproj/project.pbxproj` - Build settings - -**Core Logic:** -- `SportsTime/Core/Services/DataProvider.swift` - Single source of truth -- `SportsTime/Planning/Engine/TripPlanningEngine.swift` - Planning orchestrator -- `SportsTime/Planning/Engine/GameDAGRouter.swift` - Route finding - -**Testing:** -- `SportsTimeTests/TravelEstimatorTests.swift` - 50+ tests -- `SportsTimeTests/ScenarioAPlannerSwiftTests.swift` - Scenario A tests -- `SportsTimeTests/ScenarioBPlannerTests.swift` - Scenario B tests -- `SportsTimeTests/ScenarioCPlannerTests.swift` - Scenario C tests - -**Documentation:** -- `CLAUDE.md` - Project instructions for Claude Code -- `docs/MARKET_RESEARCH.md` - Competitive analysis - -## Naming Conventions - -**Files:** -- PascalCase for Swift files: `TripDetailView.swift`, `DataProvider.swift` -- Pattern: `{TypeName}.swift` matches primary type -- Views: `*View.swift` -- ViewModels: `*ViewModel.swift` -- Services: `*Service.swift` - -**Directories:** -- PascalCase for feature directories: `Features/Trip/` -- Plural for collections: `Models/`, `Services/`, `Views/` - -**Special Patterns:** -- `index.ts` equivalent: None (Swift doesn't use barrel files) -- Test files: `*Tests.swift` in `SportsTimeTests/` - -## Where to Add New Code - -**New Feature:** -- Primary code: `Features/{FeatureName}/Views/` and `ViewModels/` -- Tests: `SportsTimeTests/{FeatureName}Tests.swift` -- Config if needed: Update `SportsTimeApp.swift` schema if adding models - -**New Service:** -- Implementation: `Core/Services/{ServiceName}.swift` -- Tests: `SportsTimeTests/{ServiceName}Tests.swift` - -**New Planning Algorithm:** -- Definition: `Planning/Engine/{PlannerName}.swift` -- Protocol: Implement `ScenarioPlanner` protocol -- Tests: `SportsTimeTests/{PlannerName}Tests.swift` - -**New Domain Model:** -- Domain struct: `Core/Models/Domain/{Model}.swift` -- SwiftData model (if persisted): `Core/Models/Local/{Model}.swift` -- Add to `SportsTimeApp.swift` schema - -**Utilities:** -- Shared helpers: `Core/Utilities/` -- Extensions: `Core/Extensions/` - -## Special Directories - -**Resources/ (Bundled Data):** -- Purpose: Bootstrap data for offline-first -- Source: Generated by `Scripts/generate_canonical_data.py` -- Contents: `stadiums_canonical.json`, `teams_canonical.json`, `games_canonical.json` -- Committed: Yes - -**Scripts/ (Python Pipeline):** -- Purpose: Data scraping, canonicalization, CloudKit import -- Contents: `scrape_schedules.py`, `cloudkit_import.py`, `canonicalize_*.py` -- Committed: Yes - -**.planning/ (Project Planning):** -- Purpose: GSD workflow documents -- Contents: STATE.md, PLAN.md, codebase/ -- Committed: Yes - ---- - -*Structure analysis: 2026-01-09* -*Update when directory structure changes* diff --git a/.planning/codebase/TESTING.md b/.planning/codebase/TESTING.md deleted file mode 100644 index 001b0ac..0000000 --- a/.planning/codebase/TESTING.md +++ /dev/null @@ -1,223 +0,0 @@ -# Testing Patterns - -**Analysis Date:** 2026-01-09 - -## Test Framework - -**Runner:** -- Swift Testing (Apple's new testing framework, iOS 26+) -- Config: Built into Xcode, no separate config file - -**Assertion Library:** -- `#expect()` macro (289 occurrences) -- Replaces XCTest's `XCTAssertEqual`, etc. - -**Run Commands:** -```bash -# Run all tests -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' test - -# Run specific test suite -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/TravelEstimatorTests test - -# Run single test -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/TestClassName/testMethodName test -``` - -## Test File Organization - -**Location:** -- `SportsTimeTests/*.swift` - Unit tests -- `SportsTimeUITests/*.swift` - UI tests (XCTest-based) - -**Naming:** -- Unit tests: `{Component}Tests.swift` -- No integration/e2e distinction in filename - -**Structure:** -``` -SportsTimeTests/ -├── TravelEstimatorTests.swift # 50+ tests -├── SportsTimeTests.swift # DayCard tests (11+), regression tests -├── ScenarioAPlannerSwiftTests.swift # 28 tests -├── ScenarioBPlannerTests.swift # 44 tests -├── ScenarioCPlannerTests.swift # 49 tests -└── (total: 180+ unit tests) -``` - -## Test Structure - -**Suite Organization:** -```swift -import Testing -import Foundation -@testable import SportsTime - -@Suite("ScenarioBPlanner Tests") -struct ScenarioBPlannerTests { - - // MARK: - Test Fixtures - - private func makeStadium(...) -> Stadium { ... } - private func makeGame(...) -> Game { ... } - - // MARK: - Tests - - @Test("handles empty game list") - func emptyGameList() { - // arrange - // act - // assert with #expect() - } -} -``` - -**Patterns:** -- `@Suite("Description")` for grouping related tests -- `@Test("Description")` for individual tests (not `func test...`) -- `#expect()` for assertions -- Private `make*` factory functions for test fixtures - -## Mocking - -**Framework:** -- No external mocking framework -- Manual test doubles via protocol conformance - -**Patterns:** -```swift -// Factory functions create test data -private func makeGame( - id: UUID = UUID(), - stadiumId: UUID, - date: Date -) -> Game { - Game( - id: id, - homeTeamId: UUID(), - awayTeamId: UUID(), - stadiumId: stadiumId, - dateTime: date, - sport: .mlb, - season: "2026" - ) -} -``` - -**What to Mock:** -- External services (CloudKit, network) -- Date/time (use fixed dates in tests) - -**What NOT to Mock:** -- Pure functions (TravelEstimator calculations) -- Domain models - -## Fixtures and Factories - -**Test Data:** -```swift -// Factory pattern in test structs -private func makeStadium( - id: UUID = UUID(), - name: String, - city: String, - state: String, - latitude: Double, - longitude: Double, - sport: Sport = .mlb -) -> Stadium { ... } - -private func date(_ string: String) -> Date { - let formatter = DateFormatter() - formatter.dateFormat = "yyyy-MM-dd HH:mm" - formatter.timeZone = TimeZone(identifier: "America/Los_Angeles") - return formatter.date(from: string)! -} - -private func defaultConstraints() -> DrivingConstraints { ... } -``` - -**Location:** -- Factory functions: Defined in each test struct under `// MARK: - Test Fixtures` -- No shared fixtures directory - -## Coverage - -**Requirements:** -- No enforced coverage target -- Focus on critical paths (planning engine, travel estimation) - -**Configuration:** -- Xcode built-in coverage via scheme settings -- No separate coverage tool - -## Test Types - -**Unit Tests (SportsTimeTests/):** -- Test single function/component in isolation -- Pure logic tests (no network, no persistence) -- Fast: milliseconds per test -- Examples: `TravelEstimatorTests`, `ScenarioAPlannerTests` - -**UI Tests (SportsTimeUITests/):** -- XCTest-based (older framework) -- Test user flows end-to-end -- Slower, requires simulator - -## Common Patterns - -**Async Testing:** -```swift -@Test("async operation succeeds") -func asyncOperation() async { - let result = await asyncFunction() - #expect(result == expected) -} -``` - -**Error Testing:** -```swift -@Test("throws on invalid input") -func invalidInput() throws { - #expect(throws: SomeError.self) { - try functionThatThrows() - } -} -``` - -**Known Distance Testing:** -```swift -@Test("LA to SF distance is approximately 350 miles") -func laToSfDistance() { - let distance = TravelEstimator.haversineDistanceMiles( - from: Coordinate(latitude: 34.05, longitude: -118.24), - to: Coordinate(latitude: 37.77, longitude: -122.42) - ) - // Known distance is ~350 miles - #expect(distance > 340 && distance < 360) -} -``` - -**Regression Test Pattern:** -```swift -// Regression test for handling duplicate game IDs without crashing -@Test("deduplicates games with same ID") -func duplicateGameHandling() { - // Setup with duplicate IDs - // Verify first occurrence preserved - // Verify no crash -} -``` - -## Bug Fix Protocol - -From `CLAUDE.md`: -1. Write failing test that reproduces bug -2. Fix the bug -3. Verify test passes along with all existing tests -4. Name tests descriptively: `test_Component_Condition_Expected` - ---- - -*Testing analysis: 2026-01-09* -*Update when test patterns change* diff --git a/.planning/config.json b/.planning/config.json deleted file mode 100644 index ecb5f9e..0000000 --- a/.planning/config.json +++ /dev/null @@ -1,18 +0,0 @@ -{ - "mode": "yolo", - "depth": "standard", - "gates": { - "confirm_project": false, - "confirm_phases": false, - "confirm_roadmap": false, - "confirm_breakdown": false, - "confirm_plan": false, - "execute_next_plan": false, - "issues_review": false, - "confirm_transition": false - }, - "safety": { - "always_confirm_destructive": true, - "always_confirm_external_services": true - } -} diff --git a/.planning/milestones/v1.0-ROADMAP.md b/.planning/milestones/v1.0-ROADMAP.md deleted file mode 100644 index 0c2c63e..0000000 --- a/.planning/milestones/v1.0-ROADMAP.md +++ /dev/null @@ -1,150 +0,0 @@ -# Milestone v1.0: Data Pipeline - -**Status:** SHIPPED 2026-01-10 -**Phases:** 1-7 (+ 2.1 inserted) -**Total Plans:** 15 - -## Overview - -Transform the monolithic data scraping scripts into a maintainable, sport-organized pipeline that ensures every game correctly links to its teams and stadium. Starting with script restructuring, we completed the stadium database, added alias systems for name variations, established correct canonical linking, implemented full CloudKit CRUD operations, and finished with comprehensive validation reports. - -## Phases - -### Phase 1: Script Architecture -**Goal**: Reorganize monolithic scraping scripts into sport-specific modules (MLB, NBA, NHL, NFL) for easier debugging and maintenance -**Depends on**: Nothing (first phase) -**Plans**: 3 plans - -Plans: -- [x] 01-01: Create core.py shared module + mlb.py sport module -- [x] 01-02: Create nba.py + nhl.py sport modules -- [x] 01-03: Create nfl.py + refactor scrape_schedules.py orchestrator - -**Details:** -- Created `core.py` with shared Game/Stadium dataclasses and scraper utilities -- Each sport module exports: {SPORT}_TEAMS, scrape_{sport}_games, {SPORT}_GAME_SOURCES -- Reduced orchestrator from 3359 to 733 lines (78% reduction) - -### Phase 2: Stadium Foundation -**Goal**: Complete stadium database with correct coordinates, names, and venue data for all 4 sports -**Depends on**: Phase 1 -**Plans**: 2 plans - -Plans: -- [x] 02-01: Audit & complete hardcoded stadium data in sport modules -- [x] 02-02: Regenerate canonical data and verify pipeline - -**Details:** -- Audited and completed hardcoded stadium data for MLB, NBA, NHL, NFL -- Used original opening years (not renovation years) for year_opened field -- Regenerated canonical JSON files with complete stadium coverage - -### Phase 2.1: Additional Sports Stadiums (INSERTED) -**Goal**: Add hardcoded stadium data for secondary sports: MLS, WNBA, NWSL -**Depends on**: Phase 2 -**Plans**: 3 plans - -Plans: -- [x] 02.1-01: Create MLS module with 30 hardcoded stadiums -- [x] 02.1-02: Create WNBA module with 13 hardcoded arenas -- [x] 02.1-03: Create NWSL module with 13 hardcoded stadiums - -**Details:** -- Created mls.py with 30 MLS stadiums including shared NFL venues -- Created wnba.py with 13 arenas cross-referenced from NBA/NHL -- Created nwsl.py with 13 stadiums cross-referenced from MLS -- CBB deferred (350+ D1 teams requires separate scoped phase) - -### Phase 3: Alias Systems -**Goal**: Implement alias systems for both stadiums and teams to handle name variations across data sources -**Depends on**: Phase 2.1 -**Plans**: 2 plans - -Plans: -- [x] 03-01: Add NFL to canonicalization pipeline with aliases -- [x] 03-02: Add MLS, WNBA, NWSL to canonicalization pipeline with aliases - -**Details:** -- Added TEAM_ABBREV_ALIASES for cross-source team name variations -- Stadium aliases handle historical names and source-specific variations -- All 7 sports now have alias support - -### Phase 4: Canonical Linking -**Goal**: Ensure every game correctly links to its home/away teams and stadium via canonical IDs -**Depends on**: Phase 3 -**Plans**: 1 plan - -Plans: -- [x] 04-01: Generate canonical games with resolved team/stadium links - -**Details:** -- All games correctly link to teams and stadiums via canonical IDs -- Team abbreviation aliases discovered during canonicalization added iteratively - -### Phase 5: CloudKit CRUD -**Goal**: Implement full create, read, update, delete operations for CloudKit management -**Depends on**: Phase 4 -**Plans**: 2 plans - -Plans: -- [x] 05-01: Smart sync with change detection (diff reporting, differential upload) -- [x] 05-02: Verification and record management (sync verification, individual CRUD) - -**Details:** -- New records use forceReplace; updates use recordChangeTag for conflict detection -- Orphan deletion requires explicit --delete-orphans flag (safe by default) -- Triple lookup fallback: direct recordName -> deterministic UUID -> canonicalId query - -### Phase 6: Validation Reports -**Goal**: Generate validation reports showing record counts, data gaps, orphan records, and relationship integrity -**Depends on**: Phase 5 -**Plans**: 1 plan - -Plans: -- [x] 06-01: Comprehensive validation with orphan listing and completeness metrics - -**Details:** -- Health score formula: avg_completeness - orphan_penalty (max -30) - unknown_penalty (max -10) -- --list-orphans requires CloudKit connection; --validate works offline -- Completeness metrics per sport with expected game counts - -### Phase 7: Testing & Documentation -**Goal**: Complete pipeline documentation and finalize project status -**Depends on**: Phase 6 -**Plans**: 1 plan - -Plans: -- [x] 07-01: Create Scripts/README.md and update PROJECT.md with completion status - -**Details:** -- Created comprehensive Scripts/README.md with usage examples -- Updated PROJECT.md with completion status and validated requirements - ---- - -## Milestone Summary - -**Decimal Phases:** -- Phase 2.1: Additional Sports Stadiums (inserted after Phase 2 for MLS/WNBA/NWSL coverage) - -**Key Decisions:** -- Split by sport, not function (user preference for organization) -- Validation reports over automated tests (faster feedback, easier debugging) -- Full CRUD over upload-only (enable data corrections without full rebuild) -- Each sport module independent with own team abbrev functions -- Non-core sports remain inline with TODO markers for future extraction - -**Issues Resolved:** -- Game linking failures (games now correctly link to teams/stadiums) -- Missing stadium data (148 stadiums complete with coordinates) -- Name variation mismatches (alias systems handle cross-source differences) - -**Issues Deferred:** -- CBB support (350+ D1 teams requires separate scoped phase) - -**Technical Debt Incurred:** -- None significant - ---- - -_For current project status, see .planning/ROADMAP.md_ diff --git a/.planning/phases/01-script-architecture/01-01-PLAN.md b/.planning/phases/01-script-architecture/01-01-PLAN.md deleted file mode 100644 index c4e9b13..0000000 --- a/.planning/phases/01-script-architecture/01-01-PLAN.md +++ /dev/null @@ -1,127 +0,0 @@ ---- -phase: 01-script-architecture -plan: 01 -type: execute ---- - - -Create shared core module and extract MLB scrapers as the first sport module. - -Purpose: Establish the modular pattern that subsequent sports will follow. -Output: `Scripts/core.py` with shared utilities, `Scripts/mlb.py` with MLB scrapers. - - - -@~/.claude/get-shit-done/workflows/execute-phase.md -@~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -**Source file:** -@Scripts/scrape_schedules.py - -**Codebase context:** -@.planning/codebase/CONVENTIONS.md - -**Tech stack:** Python 3, requests, beautifulsoup4, pandas, lxml -**Established patterns:** dataclasses, type hints, docstrings - - - - - - Task 1: Create core.py shared module - Scripts/core.py - -Create `Scripts/core.py` containing: - -1. Imports: argparse, json, time, re, datetime, timedelta, pathlib, dataclasses, typing, requests, BeautifulSoup, pandas - -2. Rate limiting utilities: - - `REQUEST_DELAY` constant (3.0) - - `last_request_time` dict - - `rate_limit(domain: str)` function - - `fetch_page(url: str, domain: str) -> Optional[BeautifulSoup]` function - -3. Data classes: - - `@dataclass Game` with all fields (id, sport, season, date, time, home_team, away_team, etc.) - - `@dataclass Stadium` with all fields (id, name, city, state, latitude, longitude, etc.) - -4. Multi-source fallback system: - - `@dataclass ScraperSource` - - `scrape_with_fallback(sport, season, sources, verbose)` function - - `@dataclass StadiumScraperSource` - - `scrape_stadiums_with_fallback(sport, sources, verbose)` function - -5. ID generation: - - `assign_stable_ids(games, sport, season)` function - -6. Export utilities: - - `export_to_json(games, stadiums, output_dir)` function - - `cross_validate_sources(games_by_source)` function - -Keep exact function signatures and logic from scrape_schedules.py. Use `__all__` to explicitly export public API. - - python3 -c "from Scripts.core import Game, Stadium, ScraperSource, rate_limit, fetch_page, scrape_with_fallback, assign_stable_ids, export_to_json; print('OK')" - core.py exists, imports successfully, exports all shared utilities - - - - Task 2: Create mlb.py sport module - Scripts/mlb.py - -Create `Scripts/mlb.py` containing: - -1. Import from core: - ```python - from core import Game, Stadium, ScraperSource, StadiumScraperSource, fetch_page, scrape_with_fallback, scrape_stadiums_with_fallback - ``` - -2. MLB game scrapers (copy exact logic): - - `scrape_mlb_baseball_reference(season: int) -> list[Game]` - - `scrape_mlb_statsapi(season: int) -> list[Game]` - - `scrape_mlb_espn(season: int) -> list[Game]` - -3. MLB stadium scrapers: - - `scrape_mlb_stadiums_scorebot() -> list[Stadium]` - - `scrape_mlb_stadiums_geojson() -> list[Stadium]` - - `scrape_mlb_stadiums_hardcoded() -> list[Stadium]` - - `scrape_mlb_stadiums() -> list[Stadium]` (combines above with fallback) - -4. Source configurations: - - `MLB_GAME_SOURCES` list of ScraperSource - - `MLB_STADIUM_SOURCES` list of StadiumScraperSource - -5. Convenience function: - - `scrape_mlb_games(season: int) -> list[Game]` - uses fallback system - -Use `__all__` to export public API. Keep all team abbreviation mappings, venue name normalizations, and parsing logic intact. - - python3 -c "from Scripts.mlb import scrape_mlb_games, scrape_mlb_stadiums, MLB_GAME_SOURCES; print('OK')" - mlb.py exists, imports from core.py, exports MLB scrapers and source configs - - - - - -Before declaring plan complete: -- [ ] `Scripts/core.py` exists and imports cleanly -- [ ] `Scripts/mlb.py` exists and imports from core -- [ ] No syntax errors: `python3 -m py_compile Scripts/core.py Scripts/mlb.py` -- [ ] Type hints present on all public functions - - - -- core.py contains all shared utilities extracted from scrape_schedules.py -- mlb.py contains all MLB-specific scrapers -- Both files import without errors -- Original scrape_schedules.py unchanged (we're creating new files first) - - - -After completion, create `.planning/phases/01-script-architecture/01-01-SUMMARY.md` - diff --git a/.planning/phases/01-script-architecture/01-01-SUMMARY.md b/.planning/phases/01-script-architecture/01-01-SUMMARY.md deleted file mode 100644 index cec4b6a..0000000 --- a/.planning/phases/01-script-architecture/01-01-SUMMARY.md +++ /dev/null @@ -1,94 +0,0 @@ ---- -phase: 01-script-architecture -plan: 01 -subsystem: data-pipeline -tags: [python, scrapers, modular-architecture, dataclasses] - -# Dependency graph -requires: [] -provides: - - core.py shared utilities module - - mlb.py MLB-specific scrapers - - Multi-source fallback pattern for scrapers -affects: [01-02, 01-03] - -# Tech tracking -tech-stack: - added: [] - patterns: - - "Sport-specific modules import from core.py" - - "ScraperSource/StadiumScraperSource for fallback configuration" - - "get_{sport}_team_abbrev() in each sport module" - -key-files: - created: - - Scripts/core.py - - Scripts/mlb.py - modified: [] - -key-decisions: - - "Each sport module has its own get_team_abbrev function for independence" - - "Import fallback pattern (try/except) for running from Scripts/ or project root" - -patterns-established: - - "core.py exports shared utilities via __all__" - - "Sport modules import from core, define team mappings, scrapers, source configs" - -issues-created: [] - -# Metrics -duration: 5min -completed: 2026-01-10 ---- - -# Phase 1 Plan 01: Core + MLB Modules Summary - -**Created core.py shared utilities and mlb.py as the first sport module, establishing the modular pattern for subsequent sports** - -## Performance - -- **Duration:** 5 min -- **Started:** 2026-01-10T05:53:50Z -- **Completed:** 2026-01-10T05:59:10Z -- **Tasks:** 2 -- **Files modified:** 2 - -## Accomplishments - -- Created `Scripts/core.py` with all shared utilities (rate limiting, dataclasses, fallback system, export) -- Created `Scripts/mlb.py` with MLB_TEAMS, 3 game scrapers, 3 stadium scrapers, and source configs -- Established modular pattern that NBA, NHL, NFL will follow - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create core.py shared module** - `edbb5db` (feat) -2. **Task 2: Create mlb.py sport module** - `cdf4c77` (feat) - -## Files Created/Modified - -- `Scripts/core.py` - Shared utilities: rate limiting, Game/Stadium dataclasses, fallback system, ID generation, export -- `Scripts/mlb.py` - MLB team mappings, Baseball-Reference/Stats API/ESPN scrapers, stadium scrapers, source configs - -## Decisions Made - -- Each sport module defines its own `get_{sport}_team_abbrev()` function rather than a shared one — keeps modules independent -- Used try/except import pattern to support both direct execution (`python mlb.py`) and import from project root - -## Deviations from Plan - -None - plan executed exactly as written. - -## Issues Encountered - -None - -## Next Phase Readiness - -- core.py and mlb.py pattern established -- Ready for 01-02-PLAN.md (nba.py + nhl.py modules) - ---- -*Phase: 01-script-architecture* -*Completed: 2026-01-10* diff --git a/.planning/phases/01-script-architecture/01-02-PLAN.md b/.planning/phases/01-script-architecture/01-02-PLAN.md deleted file mode 100644 index b2e6fbd..0000000 --- a/.planning/phases/01-script-architecture/01-02-PLAN.md +++ /dev/null @@ -1,119 +0,0 @@ ---- -phase: 01-script-architecture -plan: 02 -type: execute ---- - - -Extract NBA and NHL scrapers to dedicated sport modules. - -Purpose: Continue the modular pattern established in Plan 01. -Output: `Scripts/nba.py` and `Scripts/nhl.py` with respective scrapers. - - - -@~/.claude/get-shit-done/workflows/execute-phase.md -@~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -**Prior work:** -@.planning/phases/01-script-architecture/01-01-SUMMARY.md - -**Source files:** -@Scripts/core.py -@Scripts/scrape_schedules.py - - - - - - Task 1: Create nba.py sport module - Scripts/nba.py - -Create `Scripts/nba.py` following the mlb.py pattern: - -1. Import from core: - ```python - from core import Game, Stadium, ScraperSource, StadiumScraperSource, fetch_page, scrape_with_fallback, scrape_stadiums_with_fallback - ``` - -2. NBA game scrapers: - - `scrape_nba_basketball_reference(season: int) -> list[Game]` - - `scrape_nba_espn(season: int) -> list[Game]` - - `scrape_nba_cbssports(season: int) -> list[Game]` - -3. NBA stadium scrapers: - - `scrape_nba_stadiums() -> list[Stadium]` (from generate_stadiums_from_teams or hardcoded) - -4. Source configurations: - - `NBA_GAME_SOURCES` list of ScraperSource - - `NBA_STADIUM_SOURCES` list of StadiumScraperSource - -5. Convenience functions: - - `scrape_nba_games(season: int) -> list[Game]` - - `get_nba_season_string(season: int) -> str` - returns "2024-25" format - -Copy exact parsing logic including team abbreviations and venue mappings from scrape_schedules.py. - - python3 -c "from Scripts.nba import scrape_nba_games, NBA_GAME_SOURCES; print('OK')" - nba.py exists, imports from core.py, exports NBA scrapers - - - - Task 2: Create nhl.py sport module - Scripts/nhl.py - -Create `Scripts/nhl.py` following the same pattern: - -1. Import from core: - ```python - from core import Game, Stadium, ScraperSource, StadiumScraperSource, fetch_page, scrape_with_fallback, scrape_stadiums_with_fallback - ``` - -2. NHL game scrapers: - - `scrape_nhl_hockey_reference(season: int) -> list[Game]` - - `scrape_nhl_api(season: int) -> list[Game]` - - `scrape_nhl_espn(season: int) -> list[Game]` - -3. NHL stadium scrapers: - - `scrape_nhl_stadiums() -> list[Stadium]` - -4. Source configurations: - - `NHL_GAME_SOURCES` list of ScraperSource - - `NHL_STADIUM_SOURCES` list of StadiumScraperSource - -5. Convenience functions: - - `scrape_nhl_games(season: int) -> list[Game]` - - `get_nhl_season_string(season: int) -> str` - returns "2024-25" format - -Copy exact parsing logic from scrape_schedules.py. - - python3 -c "from Scripts.nhl import scrape_nhl_games, NHL_GAME_SOURCES; print('OK')" - nhl.py exists, imports from core.py, exports NHL scrapers - - - - - -Before declaring plan complete: -- [ ] `Scripts/nba.py` exists and imports cleanly -- [ ] `Scripts/nhl.py` exists and imports cleanly -- [ ] No syntax errors: `python3 -m py_compile Scripts/nba.py Scripts/nhl.py` -- [ ] Both import from core.py (not duplicating shared utilities) - - - -- nba.py contains all NBA-specific scrapers -- nhl.py contains all NHL-specific scrapers -- Both follow the pattern established in mlb.py -- All files import without errors - - - -After completion, create `.planning/phases/01-script-architecture/01-02-SUMMARY.md` - diff --git a/.planning/phases/01-script-architecture/01-02-SUMMARY.md b/.planning/phases/01-script-architecture/01-02-SUMMARY.md deleted file mode 100644 index 9f5ff65..0000000 --- a/.planning/phases/01-script-architecture/01-02-SUMMARY.md +++ /dev/null @@ -1,91 +0,0 @@ ---- -phase: 01-script-architecture -plan: 02 -subsystem: data-pipeline -tags: [python, scrapers, modular-architecture, nba, nhl] - -# Dependency graph -requires: [01-01] -provides: - - nba.py NBA-specific scrapers - - nhl.py NHL-specific scrapers -affects: [01-03] - -# Tech tracking -tech-stack: - added: [] - patterns: - - "get_{sport}_season_string() for cross-calendar-year seasons (2024-25)" - - "Hardcoded stadium data with coordinates as fallback source" - -key-files: - created: - - Scripts/nba.py - - Scripts/nhl.py - modified: [] - -key-decisions: - - "NBA/NHL use season string format (2024-25) for cross-calendar-year seasons" - - "Each module has hardcoded stadium list with coordinates as reliable fallback" - -patterns-established: - - "Sport modules follow identical structure: TEAMS dict, scrapers, sources, convenience function" - -issues-created: [] - -# Metrics -duration: 10min -completed: 2026-01-10 ---- - -# Phase 1 Plan 02: NBA + NHL Modules Summary - -**Extracted NBA and NHL scrapers from monolithic script into dedicated sport modules** - -## Performance - -- **Duration:** 10 min -- **Started:** 2026-01-10T06:03:30Z -- **Completed:** 2026-01-10T06:13:30Z -- **Tasks:** 2 -- **Files created:** 2 - -## Accomplishments - -- Created `Scripts/nba.py` with NBA_TEAMS (30 teams), 3 game scrapers, stadium data with coordinates -- Created `Scripts/nhl.py` with NHL_TEAMS (32 teams including Utah Hockey Club), 3 game scrapers, stadium data -- Both modules follow the mlb.py pattern exactly for consistency - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create nba.py sport module** - `70acfb7` (feat) -2. **Task 2: Create nhl.py sport module** - `c229fa7` (feat) - -## Files Created/Modified - -- `Scripts/nba.py` - NBA team mappings, Basketball-Reference/ESPN/CBS scrapers, 30 arenas with coordinates -- `Scripts/nhl.py` - NHL team mappings, Hockey-Reference/NHL API/ESPN scrapers, 32 arenas with coordinates - -## Decisions Made - -- Used `get_nba_season_string()` and `get_nhl_season_string()` instead of a shared function to maintain module independence -- Included Utah Hockey Club (newest NHL team) in team mappings - -## Deviations from Plan - -None - plan executed exactly as written. - -## Issues Encountered - -None - -## Next Phase Readiness - -- core.py, mlb.py, nba.py, nhl.py all complete -- Ready for 01-03-PLAN.md (nfl.py + orchestrator refactor) - ---- -*Phase: 01-script-architecture* -*Completed: 2026-01-10* diff --git a/.planning/phases/01-script-architecture/01-03-PLAN.md b/.planning/phases/01-script-architecture/01-03-PLAN.md deleted file mode 100644 index 1009edc..0000000 --- a/.planning/phases/01-script-architecture/01-03-PLAN.md +++ /dev/null @@ -1,147 +0,0 @@ ---- -phase: 01-script-architecture -plan: 03 -type: execute ---- - - -Extract NFL scrapers and refactor scrape_schedules.py to be a thin orchestrator. - -Purpose: Complete the modular architecture and update the main entry point. -Output: `Scripts/nfl.py` and refactored `Scripts/scrape_schedules.py`. - - - -@~/.claude/get-shit-done/workflows/execute-phase.md -@~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -**Prior work:** -@.planning/phases/01-script-architecture/01-01-SUMMARY.md -@.planning/phases/01-script-architecture/01-02-SUMMARY.md - -**Source files:** -@Scripts/core.py -@Scripts/mlb.py -@Scripts/nba.py -@Scripts/nhl.py -@Scripts/scrape_schedules.py - - - - - - Task 1: Create nfl.py sport module - Scripts/nfl.py - -Create `Scripts/nfl.py` following the established pattern: - -1. Import from core: - ```python - from core import Game, Stadium, ScraperSource, StadiumScraperSource, fetch_page, scrape_with_fallback, scrape_stadiums_with_fallback - ``` - -2. NFL game scrapers: - - `scrape_nfl_espn(season: int) -> list[Game]` - - `scrape_nfl_pro_football_reference(season: int) -> list[Game]` - - `scrape_nfl_cbssports(season: int) -> list[Game]` - -3. NFL stadium scrapers: - - `scrape_nfl_stadiums_scorebot() -> list[Stadium]` - - `scrape_nfl_stadiums_geojson() -> list[Stadium]` - - `scrape_nfl_stadiums_hardcoded() -> list[Stadium]` - - `scrape_nfl_stadiums() -> list[Stadium]` - -4. Source configurations: - - `NFL_GAME_SOURCES` list of ScraperSource - - `NFL_STADIUM_SOURCES` list of StadiumScraperSource - -5. Convenience functions: - - `scrape_nfl_games(season: int) -> list[Game]` - - `get_nfl_season_string(season: int) -> str` - returns "2025-26" format - -Copy exact parsing logic from scrape_schedules.py. - - python3 -c "from Scripts.nfl import scrape_nfl_games, NFL_GAME_SOURCES; print('OK')" - nfl.py exists, imports from core.py, exports NFL scrapers - - - - Task 2: Refactor scrape_schedules.py to orchestrator - Scripts/scrape_schedules.py - -Rewrite `Scripts/scrape_schedules.py` as a thin orchestrator: - -1. Replace inline scrapers with imports: - ```python - from core import Game, Stadium, assign_stable_ids, export_to_json - from mlb import scrape_mlb_games, scrape_mlb_stadiums, MLB_GAME_SOURCES - from nba import scrape_nba_games, scrape_nba_stadiums, NBA_GAME_SOURCES, get_nba_season_string - from nhl import scrape_nhl_games, scrape_nhl_stadiums, NHL_GAME_SOURCES, get_nhl_season_string - from nfl import scrape_nfl_games, scrape_nfl_stadiums, NFL_GAME_SOURCES, get_nfl_season_string - ``` - -2. Keep the main() function with argparse for CLI - -3. Update sport scraping blocks to use new imports: - - `if args.sport in ['nba', 'all']:` uses `scrape_nba_games(season)` - - `if args.sport in ['mlb', 'all']:` uses `scrape_mlb_games(season)` - - etc. - -4. Keep stadium scraping with the new module imports - -5. For non-core sports (WNBA, MLS, NWSL, CBB), keep them inline for now with a `# TODO: Extract to separate modules` comment - -6. Update file header docstring to explain the modular structure: - ```python - """ - Sports Schedule Scraper Orchestrator - - This script coordinates scraping across sport-specific modules: - - core.py: Shared utilities, data classes, fallback system - - mlb.py: MLB scrapers - - nba.py: NBA scrapers - - nhl.py: NHL scrapers - - nfl.py: NFL scrapers - - Usage: - python scrape_schedules.py --sport nba --season 2026 - python scrape_schedules.py --sport all --season 2026 - """ - ``` - -Target: ~500 lines (down from 3359) for the orchestrator, with sport logic in modules. - - cd Scripts && python3 scrape_schedules.py --help - scrape_schedules.py is thin orchestrator, imports from sport modules, --help works - - - - - -Before declaring phase complete: -- [ ] All sport modules exist: core.py, mlb.py, nba.py, nhl.py, nfl.py -- [ ] `python3 -m py_compile Scripts/*.py` passes for all files -- [ ] `cd Scripts && python3 scrape_schedules.py --help` shows usage -- [ ] scrape_schedules.py is significantly smaller (~500 lines vs 3359) -- [ ] No circular imports between modules - - - -- Phase 1: Script Architecture complete -- All 4 core sports have dedicated modules -- Shared utilities in core.py -- scrape_schedules.py is thin orchestrator -- CLI unchanged (backward compatible) - - - -After completion, create `.planning/phases/01-script-architecture/01-03-SUMMARY.md` with: -- Phase 1 complete -- Ready for Phase 2: Stadium Foundation - diff --git a/.planning/phases/01-script-architecture/01-03-SUMMARY.md b/.planning/phases/01-script-architecture/01-03-SUMMARY.md deleted file mode 100644 index d383beb..0000000 --- a/.planning/phases/01-script-architecture/01-03-SUMMARY.md +++ /dev/null @@ -1,121 +0,0 @@ ---- -phase: 01-script-architecture -plan: 03 -subsystem: data-pipeline -tags: [python, scrapers, modular-architecture, nfl, orchestrator] - -# Dependency graph -requires: [01-01, 01-02] -provides: - - nfl.py NFL-specific scrapers - - Thin orchestrator scrape_schedules.py - - Complete Phase 1 modular architecture -affects: [02-01] - -# Tech tracking -tech-stack: - added: [] - patterns: - - "Sport modules provide convenience functions (scrape_{sport}_games)" - - "Orchestrator imports and calls module functions instead of inline code" - - "Non-core sports marked with TODO for future extraction" - -key-files: - created: - - Scripts/nfl.py - modified: - - Scripts/scrape_schedules.py - -key-decisions: - - "NFL uses cross-calendar-year season format (2025-26) like NBA/NHL" - - "Non-core sports (WNBA, MLS, NWSL, CBB) remain inline with TODO markers" - - "Orchestrator reduced from 3359 to 733 lines (78% reduction)" - -patterns-established: - - "Each sport module exports: {SPORT}_TEAMS, scrape_{sport}_games, {SPORT}_GAME_SOURCES" - - "Orchestrator calls module convenience functions for core sports" - -issues-created: [] - -# Metrics -duration: 8min -completed: 2026-01-10 ---- - -# Phase 1 Plan 03: NFL + Orchestrator Refactor Summary - -**Created NFL sport module and refactored scrape_schedules.py to thin orchestrator, completing Phase 1: Script Architecture** - -## Performance - -- **Duration:** 8 min -- **Started:** 2026-01-10T06:10:46Z -- **Completed:** 2026-01-10T06:18:23Z -- **Tasks:** 2 -- **Files modified:** 2 - -## Accomplishments - -- Created `Scripts/nfl.py` with NFL_TEAMS (32 teams), 3 game scrapers, 3 stadium scrapers -- Refactored `Scripts/scrape_schedules.py` from 3359 to 733 lines (78% reduction) -- All 4 core sports (MLB, NBA, NHL, NFL) now have dedicated modules -- Phase 1: Script Architecture complete - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create nfl.py sport module** - `a6c9230` (feat) -2. **Task 2: Refactor scrape_schedules.py to orchestrator** - `b93205e` (feat) - -## Files Created/Modified - -- `Scripts/nfl.py` - NFL team mappings, ESPN/Pro-Football-Reference/CBS scrapers, stadium scrapers -- `Scripts/scrape_schedules.py` - Thin orchestrator importing from sport modules - -## Decisions Made - -- NFL uses cross-calendar-year season format (2025-26) consistent with NBA/NHL -- Non-core sports kept inline with TODO comments for future extraction phase -- Orchestrator maintains backward-compatible CLI interface - -## Deviations from Plan - -None - plan executed exactly as written. - -## Issues Encountered - -None - -## Phase 1 Complete - -Phase 1: Script Architecture is now complete with all 3 plans executed: -- 01-01: core.py + mlb.py (shared utilities and first sport module) -- 01-02: nba.py + nhl.py (second and third sport modules) -- 01-03: nfl.py + orchestrator refactor (fourth sport module and thin orchestrator) - -### Module Architecture - -``` -Scripts/ - core.py - Shared utilities (385 lines) - mlb.py - MLB scrapers (412 lines) - nba.py - NBA scrapers (412 lines) - nhl.py - NHL scrapers (412 lines) - nfl.py - NFL scrapers (573 lines) - scrape_schedules.py - Orchestrator (733 lines) -``` - -**Total modular code:** 2,927 lines across 6 files -**Original monolithic:** 3,359 lines in 1 file -**Net change:** More organized, testable, maintainable code with clear separation of concerns - -## Next Phase Readiness - -- Phase 1 complete, ready for Phase 2: Stadium Foundation -- All 4 core sports modularized with consistent patterns -- Orchestrator provides clean entry point for all scraping operations - ---- -*Phase: 01-script-architecture* -*Completed: 2026-01-10* diff --git a/.planning/phases/02-stadium-foundation/02-01-PLAN.md b/.planning/phases/02-stadium-foundation/02-01-PLAN.md deleted file mode 100644 index 29eee5a..0000000 --- a/.planning/phases/02-stadium-foundation/02-01-PLAN.md +++ /dev/null @@ -1,153 +0,0 @@ ---- -phase: 02-stadium-foundation -plan: 01 -type: execute ---- - - -Audit and complete hardcoded stadium data across all 4 sport modules. - -Purpose: Ensure all sport modules have complete, accurate stadium data that will flow through the canonicalization pipeline. -Output: All 4 sport modules with complete stadium data (city, state, lat/lng, capacity, year_opened, teams). - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/phases/01-script-architecture/01-03-SUMMARY.md - -**Key files:** -@Scripts/mlb.py -@Scripts/nba.py -@Scripts/nhl.py -@Scripts/nfl.py - -**Current state:** -- MLB, NBA, NHL, NFL modules have hardcoded stadium data with city, state, lat/lng, capacity, teams -- Missing field: year_opened (null in all canonical data) -- NFL module created in Phase 1 Plan 03 with 30 hardcoded stadiums -- Bundled stadiums_canonical.json has incomplete data (state="", capacity=0, missing NFL) - -**Expected stadium counts:** -- MLB: 30 stadiums (30 teams) -- NBA: 30 stadiums (30 teams) -- NHL: 32 stadiums (32 teams) -- NFL: 30 stadiums (32 teams, 2 shared: SoFi Stadium, MetLife Stadium) - -**Stadium data structure:** -Each module has `scrape_{sport}_stadiums_hardcoded()` returning Stadium objects with: -- name, city, state, lat/lng, capacity, teams -- Missing: year_opened for filtering historical/renamed venues - - - - - - Task 1: Audit stadium data completeness across all 4 sport modules - Scripts/mlb.py, Scripts/nba.py, Scripts/nhl.py, Scripts/nfl.py - -1. Read each sport module's hardcoded stadium function -2. Create audit report listing for each sport: - - Stadium count (should match expected) - - Fields present/missing - - Any stadiums with missing lat/lng (should be 0) - - Any stadiums with missing capacity (should be 0) -3. Identify gaps: stadiums missing from lists, incorrect coordinates, missing teams - -Do NOT modify any files in this task - audit only. The goal is to understand current state before making changes. - - Print audit summary showing stadium counts per sport and any data quality issues found - Audit report shows MLB:30, NBA:30, NHL:32, NFL:30 stadiums with all required fields documented - - - - Task 2: Add year_opened to all hardcoded stadiums - Scripts/mlb.py, Scripts/nba.py, Scripts/nhl.py, Scripts/nfl.py - -Add year_opened to each stadium's hardcoded data. Use the actual opening year for each venue: - -**MLB stadiums (sample):** -- Fenway Park: 1912 -- Wrigley Field: 1914 -- Dodger Stadium: 1962 -- Globe Life Field: 2020 - -**NBA arenas (sample):** -- TD Garden: 1995 -- Madison Square Garden: 1968 -- Chase Center: 2019 -- Intuit Dome: 2024 - -**NHL arenas:** Many share with NBA - verify and match - -**NFL stadiums (sample):** -- Lambeau Field: 1957 -- SoFi Stadium: 2020 -- Allegiant Stadium: 2020 - -For each module: -1. Update the hardcoded dict to include 'year_opened' key -2. Update Stadium object creation to include year_opened parameter -3. Ensure Stadium dataclass in core.py has year_opened field (verify first) - -Research actual opening years from Wikipedia if unsure. Use the original opening year, not renovation years. - - Run `python -c "from mlb import scrape_mlb_stadiums; s=scrape_mlb_stadiums(); print(f'MLB: {len(s)} stadiums, year_opened example: {s[0].year_opened if hasattr(s[0], \"year_opened\") else \"MISSING\"}')"` for each sport - All 4 sport modules have year_opened in hardcoded data, Stadium objects include year_opened field - - - - - -Before declaring plan complete: -- [ ] Audit confirms expected stadium counts: MLB:30, NBA:30, NHL:32, NFL:30 -- [ ] All 4 modules have year_opened in hardcoded stadium data -- [ ] No Python syntax errors in any module -- [ ] Stadium dataclass supports year_opened field - - - - -- Task 1: Audit complete with documented counts and any gaps identified -- Task 2: year_opened added to all hardcoded stadiums in all 4 modules -- No import errors when loading modules -- Ready for Plan 02 (pipeline regeneration) - - - -After completion, create `.planning/phases/02-stadium-foundation/02-01-SUMMARY.md`: - -# Phase 2 Plan 01: Stadium Data Audit & Completion Summary - -**[Substantive one-liner]** - -## Accomplishments - -- [Stadium counts verified] -- [year_opened added to all modules] - -## Files Created/Modified - -- `Scripts/mlb.py` - Added year_opened -- `Scripts/nba.py` - Added year_opened -- `Scripts/nhl.py` - Added year_opened -- `Scripts/nfl.py` - Added year_opened - -## Decisions Made - -[Any gaps found and how resolved] - -## Issues Encountered - -[Any data issues discovered] - -## Next Step - -Ready for 02-02-PLAN.md (pipeline regeneration) - diff --git a/.planning/phases/02-stadium-foundation/02-01-SUMMARY.md b/.planning/phases/02-stadium-foundation/02-01-SUMMARY.md deleted file mode 100644 index f41e30e..0000000 --- a/.planning/phases/02-stadium-foundation/02-01-SUMMARY.md +++ /dev/null @@ -1,34 +0,0 @@ -# Phase 2 Plan 01: Stadium Data Audit & Completion Summary - -**Added year_opened field to all 122 hardcoded stadiums across MLB, NBA, NHL, and NFL modules.** - -## Accomplishments - -- Audited all 4 sport modules confirming expected stadium counts: - - MLB: 30 stadiums - - NBA: 30 stadiums - - NHL: 32 stadiums - - NFL: 30 stadiums (includes 2 shared: SoFi Stadium, MetLife Stadium) -- Verified Stadium dataclass in core.py already has `year_opened: Optional[int] = None` -- Added year_opened to all hardcoded stadium dictionaries -- Updated Stadium object creation in all 4 modules to pass year_opened - -## Files Modified - -- `Scripts/mlb.py` - Added year_opened to 30 ballparks, updated Stadium creation -- `Scripts/nba.py` - Added year_opened to 30 arenas, updated Stadium creation -- `Scripts/nhl.py` - Added year_opened to 32 arenas, updated Stadium creation -- `Scripts/nfl.py` - Added year_opened to 30 stadiums, updated Stadium creation - -## Decisions Made - -- Used original opening years (not renovation years) for historical accuracy -- Stadium dataclass already supported year_opened field - no changes needed to core.py - -## Issues Encountered - -None - all expected stadium counts matched, all fields present. - -## Next Step - -Ready for 02-02-PLAN.md (pipeline regeneration) diff --git a/.planning/phases/02-stadium-foundation/02-02-PLAN.md b/.planning/phases/02-stadium-foundation/02-02-PLAN.md deleted file mode 100644 index 888ae7a..0000000 --- a/.planning/phases/02-stadium-foundation/02-02-PLAN.md +++ /dev/null @@ -1,161 +0,0 @@ ---- -phase: 02-stadium-foundation -plan: 02 -type: execute ---- - - -Regenerate canonical stadium data and verify the complete pipeline flow. - -Purpose: Ensure hardcoded stadium data flows correctly through canonicalization to bundled JSON. -Output: Updated bundled stadiums_canonical.json with complete data for all 4 sports. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md -~/.claude/get-shit-done/references/checkpoints.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/phases/02-stadium-foundation/02-01-SUMMARY.md - -**Key files:** -@Scripts/scrape_schedules.py -@Scripts/run_canonicalization_pipeline.py -@Scripts/canonicalize_stadiums.py - -**Pipeline flow:** -1. `scrape_schedules.py --stadiums-update` calls `scrape_all_stadiums()` → `data/stadiums.json` -2. `run_canonicalization_pipeline.py` reads stadiums.json → canonicalizes → `data/stadiums_canonical.json` -3. Copy to `SportsTime/Resources/stadiums_canonical.json` - -**Expected output:** -- stadiums_canonical.json with all fields populated: canonical_id, name, city, state, latitude, longitude, capacity, sport, primary_team_abbrevs, year_opened -- stadium_aliases.json with historical name mappings -- Stadium counts: MLB:30, NBA:30, NHL:32, NFL:30 = 122 core stadiums - -**Pre-requisites:** -- Plan 02-01 complete (year_opened added to all modules) - - - - - - Task 1: Run stadium scraping and canonicalization pipeline - data/stadiums.json, data/stadiums_canonical.json, data/stadium_aliases.json - -1. Navigate to Scripts directory -2. Run: `python scrape_schedules.py --stadiums-update` - - This calls scrape_all_stadiums() which invokes each sport module's scraper - - Output: data/stadiums.json with raw stadium data -3. Run: `python run_canonicalization_pipeline.py --verbose` - - Or run canonicalize_stadiums.py directly if pipeline is complex -4. Verify output files exist in data/ directory - -If errors occur, debug and fix before proceeding. Common issues: -- Import errors: Check module paths and __init__.py -- Missing fields: Verify Stadium dataclass in core.py - - ls -la data/stadiums*.json && cat data/stadiums_canonical.json | python3 -c "import json,sys; d=json.load(sys.stdin); print(f'Total: {len(d)}'); sports={}; [sports.__setitem__(s['sport'], sports.get(s['sport'],0)+1) for s in d]; print(sports)" - stadiums_canonical.json exists with MLB:30, NBA:30, NHL:32, NFL:30 stadiums - - - - Task 2: Copy canonical data to bundled resources and verify completeness - SportsTime/Resources/stadiums_canonical.json, SportsTime/Resources/stadium_aliases.json - -1. Copy generated canonical files to app bundle: - - cp data/stadiums_canonical.json SportsTime/Resources/stadiums_canonical.json - - cp data/stadium_aliases.json SportsTime/Resources/stadium_aliases.json - -2. Verify data completeness by checking sample records: - - All state fields populated (not empty string) - - All capacity fields > 0 - - All year_opened fields not null - - All lat/lng reasonable (US coordinates: lat 24-49, lng -125 to -66) - -3. If any fields empty, trace back to source: - - Check raw stadiums.json has the field - - Check canonicalize_stadiums.py preserves the field - - Fix the break in the chain - - cat SportsTime/Resources/stadiums_canonical.json | python3 -c "import json,sys; d=json.load(sys.stdin); empty_state=sum(1 for s in d if not s.get('state')); zero_cap=sum(1 for s in d if not s.get('capacity')); null_year=sum(1 for s in d if s.get('year_opened') is None); print(f'Empty state: {empty_state}, Zero capacity: {zero_cap}, Null year: {null_year}')" - Bundled JSON has 0 empty states, 0 zero capacities, 0 null year_opened values - - - - Regenerated and updated bundled stadium data for all 4 core sports - -1. Open `SportsTime/Resources/stadiums_canonical.json` -2. Verify stadium counts by sport: - - MLB: 30 stadiums - - NBA: 30 stadiums - - NHL: 32 stadiums - - NFL: 30 stadiums (2 shared: SoFi, MetLife) -3. Spot check data quality: - - Pick any stadium, verify state is 2-letter code (e.g., "CA", "NY") - - Pick any stadium, verify capacity is realistic (15000-100000) - - Pick any stadium, verify year_opened is reasonable (1900-2025) -4. Verify no non-core sports included (MLS, WNBA, NWSL, CBB should NOT be in bundled JSON - or if present, that's intentional) - - Type "approved" if data looks correct, or describe issues to fix - - - - - -Before declaring plan complete: -- [ ] Pipeline runs without errors -- [ ] data/stadiums_canonical.json has 122 core sport stadiums -- [ ] Bundled JSON updated with complete data -- [ ] Human verified data quality - - - - -- Pipeline completes successfully -- All stadium fields populated (no empty state, zero capacity, or null year_opened) -- Bundled JSON has correct stadium counts for MLB, NBA, NHL, NFL -- Phase 2 complete: Stadium Foundation established - - - -After completion, create `.planning/phases/02-stadium-foundation/02-02-SUMMARY.md`: - -# Phase 2 Plan 02: Pipeline Regeneration & Verification Summary - -**[Substantive one-liner]** - -## Accomplishments - -- [Pipeline executed successfully] -- [Bundled JSON updated with complete data] - -## Files Created/Modified - -- `data/stadiums.json` - Raw stadium data -- `data/stadiums_canonical.json` - Canonical output -- `data/stadium_aliases.json` - Historical aliases -- `SportsTime/Resources/stadiums_canonical.json` - Bundled canonical data -- `SportsTime/Resources/stadium_aliases.json` - Bundled aliases - -## Decisions Made - -[Any decisions about included sports, data sources] - -## Issues Encountered - -[Any pipeline issues and fixes] - -## Phase 2 Complete - -Phase 2: Stadium Foundation is complete: -- All 4 core sports have complete stadium data -- Data includes: canonical_id, name, city, state, lat/lng, capacity, year_opened, teams -- Historical aliases in place for renamed stadiums -- Ready for Phase 3: Alias Systems - diff --git a/.planning/phases/02-stadium-foundation/02-02-SUMMARY.md b/.planning/phases/02-stadium-foundation/02-02-SUMMARY.md deleted file mode 100644 index 305ae84..0000000 --- a/.planning/phases/02-stadium-foundation/02-02-SUMMARY.md +++ /dev/null @@ -1,54 +0,0 @@ -# Phase 2 Plan 02: Pipeline Regeneration & Verification Summary - -**Regenerated canonical stadium data for all 4 core sports (122 stadiums) with complete data quality validation.** - -## Accomplishments - -- Ran stadium scraping pipeline (`scrape_schedules.py --stadiums-update`) collecting 152 stadiums (including MLS) -- Ran canonicalization pipeline (`canonicalize_stadiums.py`) generating canonical IDs and aliases -- Filtered bundled JSON to core 4 sports only (122 stadiums, 165 aliases) -- Verified data quality: 0 empty states, 0 zero capacities, 0 null year_opened values - -## Files Created/Modified - -- `Scripts/data/stadiums.json` - Raw stadium data (152 stadiums including MLS) -- `Scripts/data/stadiums_canonical.json` - Canonical output (152 stadiums) -- `Scripts/data/stadium_aliases.json` - Historical aliases (200 aliases) -- `SportsTime/Resources/stadiums_canonical.json` - Bundled canonical data (122 core sport stadiums) -- `SportsTime/Resources/stadium_aliases.json` - Bundled aliases (165 aliases for core sports) - -## Decisions Made - -- **MLS excluded from bundled JSON**: MLS stadiums (30) have incomplete data from source (zero capacity, null year_opened). Deferred to Phase 2.1: Additional Sports Stadiums -- **Core 4 sports only**: Bundled JSON contains MLB (30), NBA (30), NFL (30), NHL (32) = 122 stadiums -- **Full data retained in Scripts/data/**: MLS data preserved for Phase 2.1 work - -## Issues Encountered - -- **MLS data quality**: The gavinr GeoJSON source for MLS stadiums lacks capacity and year_opened fields. This is expected - MLS stadiums need manual enrichment in Phase 2.1. - -## Stadium Counts - -| Sport | Scraped | Bundled | -|-------|---------|---------| -| MLB | 30 | 30 | -| NBA | 30 | 30 | -| NFL | 30 | 30 | -| NHL | 32 | 32 | -| MLS | 30 | 0 (deferred) | -| **Total** | **152** | **122** | - -## Commits - -| Hash | Description | -|------|-------------| -| `c2da6a7` | feat(02-02): regenerate stadium data with canonicalization pipeline | -| `1808d2c` | feat(02-02): bundle 122 core stadiums (MLB/NBA/NHL/NFL) | - -## Phase 2 Complete - -Phase 2: Stadium Foundation is complete: -- All 4 core sports have complete stadium data -- Data includes: canonical_id, name, city, state, lat/lng, capacity, year_opened, teams -- Historical aliases in place for renamed stadiums (165 aliases) -- Ready for Phase 2.1: Additional Sports Stadiums (MLS, WNBA, NWSL, CBB) diff --git a/.planning/phases/03-alias-systems/03-01-PLAN.md b/.planning/phases/03-alias-systems/03-01-PLAN.md deleted file mode 100644 index d7539f3..0000000 --- a/.planning/phases/03-alias-systems/03-01-PLAN.md +++ /dev/null @@ -1,191 +0,0 @@ ---- -phase: 03-alias-systems -plan: 01 -type: execute ---- - - -Add NFL to the canonicalization pipeline with complete alias support. - -Purpose: NFL is a core sport but missing from team/game canonicalization, breaking game→team→stadium linking for NFL games. -Output: NFL teams canonicalized with division structure, NFL abbreviation aliases for game resolution, NFL stadium historical aliases. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/phases/01-script-architecture/01-03-SUMMARY.md - -# Key source files: -@Scripts/canonicalize_teams.py -@Scripts/canonicalize_games.py -@Scripts/canonicalize_stadiums.py -@Scripts/nfl.py - -**Prior decisions:** -- NFL uses cross-calendar-year season format (2025-26) like NBA/NHL -- Each sport module exports {SPORT}_TEAMS dict with team mappings -- canonicalize_teams.py uses division mappings for conference/division assignment - -**Patterns established:** -- Team canonicalization: import {SPORT}_TEAMS, add {SPORT}_DIVISIONS dict, include in sport_mappings list -- Game resolution: TEAM_ABBREV_ALIASES dict maps alternate abbrevs to canonical team IDs -- Stadium aliases: HISTORICAL_STADIUM_ALIASES dict maps canonical_id to list of historical names with dates - - - - - - Task 1: Add NFL to canonicalize_teams.py - Scripts/canonicalize_teams.py - - 1. Add NFL_TEAMS to import statement: `from scrape_schedules import NBA_TEAMS, MLB_TEAMS, NHL_TEAMS, NFL_TEAMS` - 2. Add NFL_DIVISIONS dict with all 32 teams mapped to (conference_id, division_id): - - AFC East: BUF, MIA, NE, NYJ → ('nfl_afc', 'nfl_afc_east') - - AFC North: BAL, CIN, CLE, PIT → ('nfl_afc', 'nfl_afc_north') - - AFC South: HOU, IND, JAX, TEN → ('nfl_afc', 'nfl_afc_south') - - AFC West: DEN, KC, LV, LAC → ('nfl_afc', 'nfl_afc_west') - - NFC East: DAL, NYG, PHI, WAS → ('nfl_nfc', 'nfl_nfc_east') - - NFC North: CHI, DET, GB, MIN → ('nfl_nfc', 'nfl_nfc_north') - - NFC South: ATL, CAR, NO, TB → ('nfl_nfc', 'nfl_nfc_south') - - NFC West: ARI, LAR, SF, SEA → ('nfl_nfc', 'nfl_nfc_west') - 3. Add ('NFL', NFL_TEAMS) to sport_mappings list in canonicalize_all_teams() - 4. Update canonicalize_teams() to use 'stadium' key for NFL (same as MLB, not 'arena') - 5. Add NFL_DIVISIONS to division_map dict - - Note: NFL_TEAMS uses 'stadium' key (not 'arena' like NBA/NHL), so the arena_key logic already handles this. - - python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "NFL:|Created.*teams" - NFL teams appear in output with 32 teams, no warnings about stadium matches - - - - Task 2: Add NFL team abbreviation aliases to canonicalize_games.py - Scripts/canonicalize_games.py - - Add NFL entries to TEAM_ABBREV_ALIASES dict for common abbreviation variations: - - ```python - # NFL - ('NFL', 'JAC'): 'team_nfl_jax', # Jacksonville (JAC vs JAX) - ('NFL', 'OAK'): 'team_nfl_lv', # Oakland → Las Vegas Raiders (moved 2020) - ('NFL', 'SD'): 'team_nfl_lac', # San Diego → Los Angeles Chargers (moved 2017) - ('NFL', 'STL'): 'team_nfl_lar', # St. Louis → Los Angeles Rams (moved 2016) - ('NFL', 'GNB'): 'team_nfl_gb', # Green Bay alternate - ('NFL', 'KAN'): 'team_nfl_kc', # Kansas City alternate - ('NFL', 'NWE'): 'team_nfl_ne', # New England alternate - ('NFL', 'NOR'): 'team_nfl_no', # New Orleans alternate - ('NFL', 'TAM'): 'team_nfl_tb', # Tampa Bay alternate - ('NFL', 'SFO'): 'team_nfl_sf', # San Francisco alternate - ('NFL', 'WAS'): 'team_nfl_was', # Washington (direct match but include for completeness) - ``` - - These cover: - - Historical relocations (OAK→LV, SD→LAC, STL→LAR) - - Common 3-letter variations used by different data sources - - grep -c "NFL" Scripts/canonicalize_games.py | head -1 - NFL aliases present in TEAM_ABBREV_ALIASES dict (should show 10+ NFL entries) - - - - Task 3: Add NFL stadium historical aliases to canonicalize_stadiums.py - Scripts/canonicalize_stadiums.py - - Add NFL entries to HISTORICAL_STADIUM_ALIASES dict for sponsorship changes and renames: - - ```python - # NFL - 'stadium_nfl_sofi_stadium': [ - # SoFi Stadium opened 2020, no prior name - ], - 'stadium_nfl_allegiant_stadium': [ - # Allegiant Stadium opened 2020, no prior name (Raiders moved from Oakland Coliseum) - ], - 'stadium_nfl_caesars_superdome': [ - {'alias_name': 'mercedes-benz superdome', 'valid_from': '2011-10-01', 'valid_until': '2021-07-01'}, - {'alias_name': 'louisiana superdome', 'valid_from': '1975-08-01', 'valid_until': '2011-09-30'}, - {'alias_name': 'superdome', 'valid_from': '1975-08-01'}, - ], - 'stadium_nfl_paycor_stadium': [ - {'alias_name': 'paul brown stadium', 'valid_from': '2000-08-01', 'valid_until': '2022-09-05'}, - ], - 'stadium_nfl_empower_field_at_mile_high': [ - {'alias_name': 'broncos stadium at mile high', 'valid_from': '2018-09-01', 'valid_until': '2019-08-31'}, - {'alias_name': 'sports authority field at mile high', 'valid_from': '2011-08-01', 'valid_until': '2018-08-31'}, - {'alias_name': 'invesco field at mile high', 'valid_from': '2001-09-01', 'valid_until': '2011-07-31'}, - {'alias_name': 'mile high stadium', 'valid_from': '1960-01-01', 'valid_until': '2001-08-31'}, - ], - 'stadium_nfl_acrisure_stadium': [ - {'alias_name': 'heinz field', 'valid_from': '2001-08-01', 'valid_until': '2022-07-10'}, - ], - 'stadium_nfl_everbank_stadium': [ - {'alias_name': 'tiaa bank field', 'valid_from': '2018-01-01', 'valid_until': '2023-03-31'}, - {'alias_name': 'everbank field', 'valid_from': '2014-01-01', 'valid_until': '2017-12-31'}, - {'alias_name': 'alltel stadium', 'valid_from': '1997-06-01', 'valid_until': '2006-12-31'}, - {'alias_name': 'jacksonville municipal stadium', 'valid_from': '1995-08-01', 'valid_until': '1997-05-31'}, - ], - 'stadium_nfl_northwest_stadium': [ - {'alias_name': 'fedexfield', 'valid_from': '1999-11-01', 'valid_until': '2025-01-01'}, - {'alias_name': 'fedex field', 'valid_from': '1999-11-01', 'valid_until': '2025-01-01'}, - {'alias_name': 'jack kent cooke stadium', 'valid_from': '1997-09-01', 'valid_until': '1999-10-31'}, - ], - 'stadium_nfl_hard_rock_stadium': [ - {'alias_name': 'sun life stadium', 'valid_from': '2010-01-01', 'valid_until': '2016-07-31'}, - {'alias_name': 'land shark stadium', 'valid_from': '2009-01-01', 'valid_until': '2009-12-31'}, - {'alias_name': 'dolphin stadium', 'valid_from': '2005-01-01', 'valid_until': '2008-12-31'}, - {'alias_name': 'pro player stadium', 'valid_from': '1996-04-01', 'valid_until': '2004-12-31'}, - {'alias_name': 'joe robbie stadium', 'valid_from': '1987-08-01', 'valid_until': '1996-03-31'}, - ], - 'stadium_nfl_highmark_stadium': [ - {'alias_name': 'bills stadium', 'valid_from': '2020-03-01', 'valid_until': '2021-03-31'}, - {'alias_name': 'new era field', 'valid_from': '2016-08-01', 'valid_until': '2020-02-29'}, - {'alias_name': 'ralph wilson stadium', 'valid_from': '1998-08-01', 'valid_until': '2016-07-31'}, - {'alias_name': 'rich stadium', 'valid_from': '1973-08-01', 'valid_until': '1998-07-31'}, - ], - 'stadium_nfl_geha_field_at_arrowhead_stadium': [ - {'alias_name': 'arrowhead stadium', 'valid_from': '1972-08-01'}, - ], - 'stadium_nfl_att_stadium': [ - {'alias_name': 'cowboys stadium', 'valid_from': '2009-05-01', 'valid_until': '2013-07-24'}, - ], - 'stadium_nfl_us_bank_stadium': [ - # Opened 2016, no prior name (Vikings moved from Metrodome) - ], - 'stadium_nfl_lumen_field': [ - {'alias_name': 'centurylink field', 'valid_from': '2011-06-01', 'valid_until': '2020-11-18'}, - {'alias_name': 'qwest field', 'valid_from': '2004-06-01', 'valid_until': '2011-05-31'}, - {'alias_name': 'seahawks stadium', 'valid_from': '2002-07-01', 'valid_until': '2004-05-31'}, - ], - ``` - - Only include stadiums with actual historical name changes. Skip stadiums like Soldier Field, Lambeau Field that have kept their names. - - grep -c "stadium_nfl" Scripts/canonicalize_stadiums.py - NFL stadium aliases present in HISTORICAL_STADIUM_ALIASES (should show 10+ entries) - - - - - -Before declaring plan complete: -- [ ] `python Scripts/canonicalize_teams.py --verbose` shows 32 NFL teams with stadium matches -- [ ] `python Scripts/canonicalize_stadiums.py --verbose` runs without error -- [ ] NFL entries exist in all three canonicalization scripts - - - -- All tasks completed -- NFL teams appear in teams_canonical.json output -- NFL stadium aliases added to canonicalization -- NFL abbreviation variations covered for game resolution - - - -After completion, create `.planning/phases/03-alias-systems/03-01-SUMMARY.md` - diff --git a/.planning/phases/03-alias-systems/03-01-SUMMARY.md b/.planning/phases/03-alias-systems/03-01-SUMMARY.md deleted file mode 100644 index cc0a448..0000000 --- a/.planning/phases/03-alias-systems/03-01-SUMMARY.md +++ /dev/null @@ -1,98 +0,0 @@ ---- -phase: 03-alias-systems -plan: 01 -subsystem: data-pipeline -tags: [nfl, canonicalization, aliases, teams, stadiums] - -# Dependency graph -requires: - - phase: 01-script-architecture - provides: NFL_TEAMS dict in nfl.py, canonicalization script patterns - - phase: 02-stadium-foundation - provides: NFL stadium data with coordinates -provides: - - NFL teams canonicalized with division structure (32 teams) - - NFL team abbreviation aliases for game resolution (11 aliases) - - NFL stadium historical aliases for sponsorship/name changes (14 stadiums) -affects: [04-canonical-linking, game-resolution, stadium-matching] - -# Tech tracking -tech-stack: - added: [] - patterns: [team-abbrev-aliases, historical-stadium-aliases, division-mapping] - -key-files: - created: [] - modified: - - Scripts/canonicalize_teams.py - - Scripts/canonicalize_games.py - - Scripts/canonicalize_stadiums.py - -key-decisions: - - "Used same division ID format as other sports: nfl_afc, nfl_afc_east, etc." - - "Included historical relocation aliases (OAK→LV, SD→LAC, STL→LAR) for backward compatibility" - - "Only added stadium aliases for venues with actual name changes (skipped Soldier Field, Lambeau, etc.)" - -patterns-established: - - "NFL follows same canonicalization patterns as MLB, NBA, NHL" - - "Team abbreviation aliases handle both historical relocations and data source variations" - -issues-created: [] - -# Metrics -duration: 4 min -completed: 2026-01-10 ---- - -# Phase 3 Plan 01: NFL Canonicalization Summary - -**NFL added to canonicalization pipeline with 32 teams, 11 abbreviation aliases, and 14 stadium historical aliases** - -## Performance - -- **Duration:** 4 min -- **Started:** 2026-01-10T15:33:15Z -- **Completed:** 2026-01-10T15:36:49Z -- **Tasks:** 3 -- **Files modified:** 3 - -## Accomplishments -- NFL teams canonicalized with full AFC/NFC division structure (32 teams) -- NFL team abbreviation aliases added for game resolution (handles JAC/JAX, relocations, etc.) -- NFL stadium historical aliases added for sponsorship changes (Heinz Field→Acrisure, FedExField→Northwest Stadium, etc.) - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Add NFL to canonicalize_teams.py** - `d4d0d95` (feat) -2. **Task 2: Add NFL team abbreviation aliases to canonicalize_games.py** - `41496b6` (feat) -3. **Task 3: Add NFL stadium historical aliases to canonicalize_stadiums.py** - `90c9cef` (feat) - -**Plan metadata:** (pending) - -## Files Created/Modified -- `Scripts/canonicalize_teams.py` - Added NFL_TEAMS import, NFL_DIVISIONS dict, sport_mappings entry -- `Scripts/canonicalize_games.py` - Added 11 NFL entries to TEAM_ABBREV_ALIASES -- `Scripts/canonicalize_stadiums.py` - Added 14 NFL stadium entries to HISTORICAL_STADIUM_ALIASES - -## Decisions Made -- Used same division ID format as other sports (nfl_afc, nfl_afc_east, etc.) -- Included historical relocation aliases (OAK→LV, SD→LAC, STL→LAR) for backward compatibility with older data -- Only added stadium aliases for venues with actual name changes (skipped Soldier Field, Lambeau Field, etc. that haven't changed) - -## Deviations from Plan - -None - plan executed exactly as written. - -## Issues Encountered - -None - -## Next Phase Readiness -- NFL canonicalization complete, ready for game resolution testing -- Ready for 03-02-PLAN.md (MLS, WNBA, NWSL canonicalization) - ---- -*Phase: 03-alias-systems* -*Completed: 2026-01-10* diff --git a/.planning/phases/03-alias-systems/03-02-PLAN.md b/.planning/phases/03-alias-systems/03-02-PLAN.md deleted file mode 100644 index 37a278f..0000000 --- a/.planning/phases/03-alias-systems/03-02-PLAN.md +++ /dev/null @@ -1,190 +0,0 @@ ---- -phase: 03-alias-systems -plan: 02 -type: execute ---- - - -Add MLS, WNBA, and NWSL to the canonicalization pipeline with alias support. - -Purpose: Secondary sports modules exist (Phase 2.1) but aren't integrated into canonicalization, preventing game→team→stadium linking. -Output: All three secondary sports canonicalized with team and stadium alias support. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/phases/03-alias-systems/03-01-SUMMARY.md - -# Key source files: -@Scripts/canonicalize_teams.py -@Scripts/canonicalize_games.py -@Scripts/canonicalize_stadiums.py -@Scripts/mls.py -@Scripts/wnba.py -@Scripts/nwsl.py - -**Prior decisions:** -- MLS uses soccer configuration capacities for shared NFL stadiums -- WNBA cross-references shared arena coordinates from nba.py and nhl.py -- NWSL cross-references shared stadium coordinates from mls.py - -**Patterns established (from 03-01):** -- Team canonicalization: import {SPORT}_TEAMS, add {SPORT}_DIVISIONS dict, include in sport_mappings list -- Game resolution: TEAM_ABBREV_ALIASES dict maps alternate abbrevs to canonical team IDs -- Stadium aliases: HISTORICAL_STADIUM_ALIASES dict maps canonical_id to list of historical names - - - - - - Task 1: Add MLS to canonicalization pipeline - Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py - - **canonicalize_teams.py:** - 1. Update import: add MLS_TEAMS from mls module - `from mls import MLS_TEAMS` - 2. Add MLS_DIVISIONS dict (MLS uses conferences, not divisions): - - Eastern Conference: ATL, CHI, CIN, CLB, CLT, DCU, FCC, MIA, MTL, NE, NYC, NYR, ORL, PHI, TOR → ('mls_eastern', None) - - Western Conference: AUS, COL, DAL, HOU, LAF, LAG, MIN, NSH, POR, RSL, SEA, SJE, SKC, STL, VAN → ('mls_western', None) - 3. Add ('MLS', MLS_TEAMS) to sport_mappings list - - **canonicalize_games.py:** - Add MLS aliases to TEAM_ABBREV_ALIASES: - ```python - # MLS - ('MLS', 'LA'): 'team_mls_lag', # LA Galaxy - ('MLS', 'LAFC'): 'team_mls_laf', # LAFC (Los Angeles FC) - ('MLS', 'NYCFC'): 'team_mls_nyc', # NYC FC - ('MLS', 'RBNY'): 'team_mls_nyr', # NY Red Bulls - ('MLS', 'SJ'): 'team_mls_sje', # San Jose Earthquakes - ('MLS', 'KC'): 'team_mls_skc', # Sporting KC - ('MLS', 'DC'): 'team_mls_dcu', # DC United - ('MLS', 'FCD'): 'team_mls_dal', # FC Dallas - ('MLS', 'MON'): 'team_mls_mtl', # Montreal - ``` - - **canonicalize_stadiums.py:** - Add MLS stadium historical aliases (recent renames only): - ```python - # MLS - 'stadium_mls_bmw_stadium': [ - {'alias_name': 'adi stadium', 'valid_from': '2021-07-01', 'valid_until': '2024-01-01'}, - ], - 'stadium_mls_shell_energy_stadium': [ - {'alias_name': 'paypal park', 'valid_from': '2021-01-01', 'valid_until': '2024-06-01'}, - {'alias_name': 'earthquakes stadium', 'valid_from': '2015-03-01', 'valid_until': '2020-12-31'}, - {'alias_name': 'avaya stadium', 'valid_from': '2015-03-01', 'valid_until': '2020-12-31'}, - ], - 'stadium_mls_geodis_park': [ - # Opened 2022, no prior name - ], - 'stadium_mls_dignity_health_sports_park': [ - {'alias_name': 'stubhub center', 'valid_from': '2013-06-01', 'valid_until': '2019-01-31'}, - {'alias_name': 'home depot center', 'valid_from': '2003-06-01', 'valid_until': '2013-05-31'}, - ], - ``` - - python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "MLS:|Created.*teams" - MLS teams appear in output (29-30 teams depending on expansion), no critical warnings - - - - Task 2: Add WNBA to canonicalization pipeline - Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py - - **canonicalize_teams.py:** - 1. Update import: add WNBA_TEAMS from wnba module - `from wnba import WNBA_TEAMS` - 2. Add WNBA_DIVISIONS dict (no divisions, just conferences, but map to None): - - Single key mapping per team to ('wnba', None) - - 13 teams: ATL, CHI, CON, DAL, IND, LVA, LAS, MIN, NYL, PHO, SEA, WAS, GSV - 3. Add ('WNBA', WNBA_TEAMS) to sport_mappings list - - **canonicalize_games.py:** - Add WNBA aliases to TEAM_ABBREV_ALIASES: - ```python - # WNBA - ('WNBA', 'LA'): 'team_wnba_las', # LA Sparks - ('WNBA', 'LV'): 'team_wnba_lva', # Las Vegas Aces - ('WNBA', 'NY'): 'team_wnba_nyl', # New York Liberty - ('WNBA', 'PHX'): 'team_wnba_pho', # Phoenix Mercury - ('WNBA', 'CONN'): 'team_wnba_con', # Connecticut Sun - ('WNBA', 'WSH'): 'team_wnba_was', # Washington Mystics - ``` - - **canonicalize_stadiums.py:** - WNBA shares arenas with NBA/NHL, so most aliases already exist. Add WNBA-specific entries if any: - ```python - # WNBA (most share NBA arenas, which have existing aliases) - 'stadium_wnba_gateway_center_arena': [ - # College Park Center - no historical renames - ], - ``` - - python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "WNBA:|Created.*teams" - WNBA teams appear in output (13 teams), no critical warnings - - - - Task 3: Add NWSL to canonicalization pipeline - Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py - - **canonicalize_teams.py:** - 1. Update import: add NWSL_TEAMS from nwsl module - `from nwsl import NWSL_TEAMS` - 2. Add NWSL_DIVISIONS dict (no divisions in NWSL): - - 14 teams all map to ('nwsl', None): ANG, CHI, HOU, KC, LOU, NCC, NJY, ORL, POR, RAC, SD, SEA, UTA, WAS - 3. Add ('NWSL', NWSL_TEAMS) to sport_mappings list - - **canonicalize_games.py:** - Add NWSL aliases to TEAM_ABBREV_ALIASES: - ```python - # NWSL - ('NWSL', 'LA'): 'team_nwsl_ang', # Angel City FC (Los Angeles) - ('NWSL', 'NC'): 'team_nwsl_ncc', # North Carolina Courage - ('NWSL', 'GOTHAM'): 'team_nwsl_njy', # NJ/NY Gotham FC - ('NWSL', 'NY'): 'team_nwsl_njy', # NJ/NY Gotham FC alt - ('NWSL', 'LOU'): 'team_nwsl_lou', # Louisville (Racing Louisville) - ('NWSL', 'RLC'): 'team_nwsl_lou', # Racing Louisville alt - ``` - - **canonicalize_stadiums.py:** - NWSL shares stadiums with MLS, so most aliases already exist. Add NWSL-specific: - ```python - # NWSL - 'stadium_nwsl_cpkc_stadium': [ - # Opened 2024, no prior name (first soccer-specific stadium built for NWSL team) - ], - ``` - - python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "NWSL:|Created.*teams" - NWSL teams appear in output (13-14 teams), no critical warnings - - - - - -Before declaring plan complete: -- [ ] `python Scripts/canonicalize_teams.py --verbose` shows MLS, WNBA, NWSL teams -- [ ] All three secondary sports have abbreviation aliases in canonicalize_games.py -- [ ] Stadium aliases added where applicable -- [ ] Total team count increased to ~180 (90 core + ~90 secondary) - - - -- All tasks completed -- MLS, WNBA, NWSL teams appear in teams_canonical.json output -- Game resolution can handle common abbreviation variations for all sports -- Phase 3 complete (all 7 sports have alias support) - - - -After completion, create `.planning/phases/03-alias-systems/03-02-SUMMARY.md`: -Include final team count by sport, note any warnings or issues encountered. - diff --git a/.planning/phases/03-alias-systems/03-02-SUMMARY.md b/.planning/phases/03-alias-systems/03-02-SUMMARY.md deleted file mode 100644 index c72b226..0000000 --- a/.planning/phases/03-alias-systems/03-02-SUMMARY.md +++ /dev/null @@ -1,102 +0,0 @@ ---- -phase: 03-alias-systems -plan: 02 -subsystem: data-pipeline -tags: [mls, wnba, nwsl, canonicalization, aliases, teams, stadiums] - -# Dependency graph -requires: - - phase: 02.1-additional-sports-stadiums - provides: MLS_TEAMS, WNBA_TEAMS, NWSL_TEAMS dicts with stadium data - - phase: 03-alias-systems/03-01 - provides: NFL canonicalization patterns, division mapping approach -provides: - - MLS teams canonicalized (30 teams in Eastern/Western conferences) - - WNBA teams canonicalized (13 teams) - - NWSL teams canonicalized (13 teams) - - Team abbreviation aliases for all secondary sports - - Stadium historical aliases for all secondary sports -affects: [04-canonical-linking, game-resolution, stadium-matching] - -# Tech tracking -tech-stack: - added: [] - patterns: [conference-only-divisions, shared-venue-aliases] - -key-files: - created: [] - modified: - - Scripts/canonicalize_teams.py - - Scripts/canonicalize_games.py - - Scripts/canonicalize_stadiums.py - -key-decisions: - - "MLS/WNBA/NWSL use conference-only structure (no divisions) - mapped to (conference, None)" - - "WNBA/NWSL share venues with NBA/MLS - minimal new stadium aliases needed" - - "Added arena_key='arena' for WNBA to match venue field naming" - -patterns-established: - - "All 7 sports now follow consistent canonicalization patterns" - - "Conference-only sports use (conference_id, None) for division mapping" - -issues-created: [] - -# Metrics -duration: 5 min -completed: 2026-01-10 ---- - -# Phase 3 Plan 02: Secondary Sports Canonicalization Summary - -**MLS, WNBA, NWSL added to canonicalization pipeline with 56 total new teams, 23 abbreviation aliases, and 15 stadium aliases** - -## Performance - -- **Duration:** 5 min -- **Started:** 2026-01-10T15:38:30Z -- **Completed:** 2026-01-10T15:43:56Z -- **Tasks:** 3 -- **Files modified:** 3 - -## Accomplishments -- MLS canonicalized with 30 teams (Eastern/Western conferences) + 10 aliases + 8 stadium aliases -- WNBA canonicalized with 13 teams + 6 aliases + 4 stadium aliases -- NWSL canonicalized with 13 teams + 7 aliases + 3 stadium aliases -- Total team count now 180 across all 7 sports (NBA: 30, MLB: 30, NHL: 32, NFL: 32, MLS: 30, WNBA: 13, NWSL: 13) - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Add MLS to canonicalization pipeline** - `b6a913d` (feat) -2. **Task 2: Add WNBA to canonicalization pipeline** - `285bc07` (feat) -3. **Task 3: Add NWSL to canonicalization pipeline** - `81f620d` (feat) - -**Plan metadata:** (pending) - -## Files Created/Modified -- `Scripts/canonicalize_teams.py` - Added imports, division dicts, sport_mappings for MLS, WNBA, NWSL -- `Scripts/canonicalize_games.py` - Added 23 team abbreviation aliases across 3 sports -- `Scripts/canonicalize_stadiums.py` - Added 15 stadium historical aliases across 3 sports - -## Decisions Made -- MLS/WNBA/NWSL use conference-only structure (no divisions) - mapped to (conference_id, None) -- WNBA/NWSL share venues with NBA/MLS - only added sport-specific aliases where needed -- Added arena_key='arena' for WNBA to match venue field naming convention - -## Deviations from Plan - -None - plan executed exactly as written. - -## Issues Encountered - -None - -## Next Phase Readiness -- Phase 3 complete - all 7 sports now have alias support -- 180 teams canonicalized with full conference/division structure -- Ready for Phase 4: Canonical Linking - ---- -*Phase: 03-alias-systems* -*Completed: 2026-01-10* diff --git a/.planning/phases/04-canonical-linking/04-01-PLAN.md b/.planning/phases/04-canonical-linking/04-01-PLAN.md deleted file mode 100644 index d03c0ab..0000000 --- a/.planning/phases/04-canonical-linking/04-01-PLAN.md +++ /dev/null @@ -1,209 +0,0 @@ ---- -phase: 04-canonical-linking -plan: 01 -type: execute ---- - - -Generate canonical games with correct team and stadium links for all 7 sports. - -Purpose: Complete the data pipeline by resolving raw game data to canonical team/stadium IDs, enabling the iOS app to correctly display game→team→stadium relationships. -Output: `games_canonical.json` with all games linked to canonical teams and stadiums, validated and ready for CloudKit upload. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -# Prior phase summaries (dependency graph): -@.planning/phases/03-alias-systems/03-01-SUMMARY.md -@.planning/phases/03-alias-systems/03-02-SUMMARY.md - -# Key files: -@Scripts/canonicalize_games.py -@Scripts/validate_canonical.py - -**Tech stack available:** Python canonicalization pipeline, team/stadium aliases -**Established patterns:** 3-stage canonicalization (stadiums → teams → games), sport-scoped resolution -**Constraining decisions:** -- Phase 03-01: Team abbreviation aliases handle relocations and data source variations -- Phase 03-02: All 7 sports (NBA, MLB, NHL, NFL, MLS, WNBA, NWSL) canonicalized with 180 total teams - -**Current state:** -- `games.json`: 2.2MB raw game data -- `games_canonical.json`: Empty `[]` - needs to be generated -- `teams_canonical.json`: 180 teams across 7 sports -- `stadiums_canonical.json`: Complete stadium data -- `stadium_aliases.json`: Historical name aliases - - - - - - Task 1: Run game canonicalization pipeline - Scripts/data/games_canonical.json, Scripts/data/game_resolution_warnings.json - -Run the game canonicalization to generate canonical games: - -```bash -cd Scripts && python canonicalize_games.py --games data/games.json --teams data/teams_canonical.json --aliases data/stadium_aliases.json --output data/ --verbose -``` - -This will: -1. Load raw games from games.json -2. Resolve team abbreviations to canonical IDs using TEAM_ABBREV_ALIASES -3. Resolve venues to stadium canonical IDs (preferring home team stadium) -4. Generate canonical game IDs with doubleheader handling -5. Output games_canonical.json and any warnings - -Expected output: ~10,000+ canonical games across all sports with home_team_canonical_id, away_team_canonical_id, and stadium_canonical_id populated. - - -- games_canonical.json exists and is non-empty -- File size > 1MB (indicates substantial data) -- Sample game has all three canonical ID fields populated - - games_canonical.json generated with canonical team/stadium links for all games - - - - Task 2: Validate canonical links - Scripts/data/canonicalization_validation.json - -Run validation to ensure all game→team→stadium references resolve: - -```bash -cd Scripts && python validate_canonical.py --data-dir data/ --verbose -``` - -Check validation output for: -1. **ERROR-level issues**: Must be zero (blocks CloudKit upload) -2. **Unknown teams**: Any team_canonical_id not found in teams_canonical.json -3. **Unknown stadiums**: Any stadium_canonical_id starting with "stadium_unknown" -4. **Game count warnings**: Teams with unusual game counts per EXPECTED_GAMES config - -If validation passes with no errors, the linking is complete. - - -- validate_canonical.py exits with code 0 -- No ERROR-level issues reported -- All teams and stadiums resolve to known entities - - All canonical games validated - no broken team or stadium links - - - - Task 3: Fix resolution issues (if any) - Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py - -Review game_resolution_warnings.json and fix any issues: - -**If "Unknown home/away team" warnings:** -- Add missing team abbreviation alias to TEAM_ABBREV_ALIASES in canonicalize_games.py -- Format: `('SPORT', 'ABBREV'): 'team_sport_canonical',` - -**If "Unknown stadium" warnings:** -- Check if venue name needs alias in HISTORICAL_STADIUM_ALIASES in canonicalize_stadiums.py -- Or verify home team has correct stadium_canonical_id in sport module - -**After fixes:** -1. Re-run canonicalization: `python canonicalize_games.py --verbose` -2. Re-run validation: `python validate_canonical.py --verbose` - -If no warnings exist, mark this task as complete with "No resolution issues found." - - -- game_resolution_warnings.json is empty or contains only acceptable warnings -- Re-run canonicalization produces no new warnings - - All resolution issues fixed, or no issues found - - - - - -Before declaring phase complete: -- [ ] `games_canonical.json` exists with >1MB of data -- [ ] All games have valid `home_team_canonical_id` (no "team_unknown_*") -- [ ] All games have valid `away_team_canonical_id` (no "team_unknown_*") -- [ ] All games have valid `stadium_canonical_id` (no "stadium_unknown_*") -- [ ] `validate_canonical.py` passes with 0 errors -- [ ] Game counts per team within expected ranges - - - - -- All tasks completed -- All verification checks pass -- games_canonical.json ready for CloudKit upload -- No broken team or stadium links in any game - - - -After completion, create `.planning/phases/04-canonical-linking/04-01-SUMMARY.md` with: - -```markdown ---- -phase: 04-canonical-linking -plan: 01 -subsystem: data-pipeline -tags: [games, canonicalization, linking, validation] - -# Dependency graph -requires: - - phase: 03-alias-systems - provides: Team/stadium aliases for all 7 sports -provides: - - Canonical games with resolved team/stadium links - - Validated game→team→stadium relationships -affects: [05-cloudkit-crud, ios-app-data] - -# Tech tracking -tech-stack: - added: [] - patterns: [game-canonicalization, link-validation] - -key-files: - created: - - Scripts/data/games_canonical.json - modified: [] - -key-decisions: - - [Any decisions made during execution] - -patterns-established: - - [Any new patterns] - -issues-created: [] - -# Metrics -duration: X min -completed: YYYY-MM-DD ---- - -# Phase 4 Plan 01: Canonical Linking Summary - -**[One-liner: X games canonicalized with Y% resolution rate]** - -## Accomplishments -- [Key outcomes] - -## Files Created/Modified -- [List with descriptions] - -## Decisions Made -- [Or "None"] - -## Issues Encountered -- [Or "None"] - -## Next Phase Readiness -- Ready for Phase 5: CloudKit CRUD -``` - diff --git a/.planning/phases/04-canonical-linking/04-01-SUMMARY.md b/.planning/phases/04-canonical-linking/04-01-SUMMARY.md deleted file mode 100644 index f02723a..0000000 --- a/.planning/phases/04-canonical-linking/04-01-SUMMARY.md +++ /dev/null @@ -1,105 +0,0 @@ ---- -phase: 04-canonical-linking -plan: 01 -subsystem: data-pipeline -tags: [games, canonicalization, linking, validation] - -requires: - - phase: 03-alias-systems - provides: Team/stadium aliases for all 7 sports - -provides: - - Canonical games with resolved team/stadium links - - Validated game-team-stadium relationships - -affects: [05-cloudkit-crud, ios-app-data] - -tech-stack: - added: [] - patterns: [game-canonicalization, link-validation, team-abbreviation-aliases] - -key-files: - created: - - Scripts/data/games_canonical.json - - Scripts/data/game_resolution_warnings.json - modified: - - Scripts/canonicalize_games.py - -key-decisions: - - Added 3 missing team abbreviation aliases discovered during canonicalization (WSH->WAS for NFL, NY->NYRB and ATX->AUS for MLS) - - NFL playoff placeholder games (TBD/AFC/NFC) are expected warnings and do not require fixes - -patterns-established: - - Team abbreviation alias discovery during canonicalization run - - Iterative alias refinement based on resolution warnings - -issues-created: [] - -duration: 4 min -completed: 2026-01-10 ---- - -# Phase 4 Plan 01: Canonical Linking Summary - -**5760 games canonicalized with 100% team/stadium resolution rate (excluding 8 expected NFL playoff placeholders)** - -## Performance - -- Duration: ~4 minutes -- Start: 2026-01-10 09:54 -- End: 2026-01-10 09:58 -- Tasks completed: 3 of 3 - -## Accomplishments - -1. **Game Canonicalization Pipeline**: Generated `games_canonical.json` with 5760 canonical games across 5 sports - - NBA: 1230 games - - MLB: 2430 games - - NHL: 1312 games - - NFL: 278 games - - MLS: 510 games - -2. **Team Alias Resolution**: Added 3 missing team abbreviation aliases to handle data source variations: - - `('NFL', 'WSH'): 'team_nfl_was'` - Washington Commanders alternate - - `('MLS', 'NY'): 'team_mls_nyrb'` - NY Red Bulls short form - - `('MLS', 'ATX'): 'team_mls_aus'` - Austin FC alternate - -3. **Validation**: All canonical links validated successfully - - 0 errors, 0 warnings - - All 5760 games have valid `home_team_canonical_id` - - All 5760 games have valid `away_team_canonical_id` - - All 5760 games have valid `stadium_canonical_id` - - No `team_unknown_*` or `stadium_unknown_*` references - -4. **Expected Warnings**: 8 NFL playoff placeholder games excluded (TBD/AFC/NFC teams will be updated when playoffs begin) - -## Files Created/Modified - -| File | Description | -|------|-------------| -| `Scripts/data/games_canonical.json` | 2.0MB - 5760 canonical games with resolved team/stadium links | -| `Scripts/data/game_resolution_warnings.json` | 8 expected NFL playoff placeholder warnings | -| `Scripts/canonicalize_games.py` | Added 3 team abbreviation aliases | - -## Task Commits - -| Task | Commit | Files | -|------|--------|-------| -| Task 1: Run game canonicalization | b628611 | canonicalize_games.py, games_canonical.json, game_resolution_warnings.json | -| Task 2: Validate canonical links | (validation only) | No file changes | -| Task 3: Fix resolution issues | (no issues found) | No changes needed | - -## Deviations from Plan - -- **Auto-fix applied**: During Task 1, discovered 3 missing team aliases (WSH, NY, ATX) that caused 85 games to fail resolution. Fixed immediately by adding aliases to TEAM_ABBREV_ALIASES and re-running canonicalization. This is consistent with Task 3's purpose but was handled proactively. - -## Issues Encountered - -None. All tasks completed successfully. - -## Next Phase Readiness - -Ready for **Phase 5: CloudKit CRUD** -- `games_canonical.json` contains 5760 games with complete team/stadium linking -- All canonical IDs resolve to valid entries -- Data validated and ready for CloudKit upload diff --git a/.planning/phases/05-cloudkit-crud/05-01-PLAN.md b/.planning/phases/05-cloudkit-crud/05-01-PLAN.md deleted file mode 100644 index 7f4e51a..0000000 --- a/.planning/phases/05-cloudkit-crud/05-01-PLAN.md +++ /dev/null @@ -1,151 +0,0 @@ ---- -phase: 05-cloudkit-crud -plan: 01 -type: execute -domain: data-pipeline ---- - - -Add smart sync with change detection to cloudkit_import.py. - -Purpose: Enable differential uploads that only sync new/changed records, reducing CloudKit API calls and sync time. -Output: Enhanced cloudkit_import.py with --diff, --smart-sync, and --changes-only flags. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/phases/04-canonical-linking/04-01-SUMMARY.md - -**Relevant source files:** -@Scripts/cloudkit_import.py - -**Tech stack available:** Python 3, requests, cryptography, CloudKit server-to-server API -**Established patterns:** forceReplace for create/update, query() for read, delete_all() for deletion, batch operations with BATCH_SIZE=200 - -**Constraining decisions:** -- Phase 04-01: 5760 games canonicalized with 100% team/stadium resolution -- Existing CloudKit import uses forceReplace (creates or replaces) for all operations -- recordChangeTag must be used for conflict detection in updates - - - - - - Task 1: Add change detection with diff reporting - Scripts/cloudkit_import.py - -Add change detection capability to compare local canonical data against CloudKit records. - -1. Add `query_all(record_type, verbose)` method to CloudKit class: - - Query with pagination (use continuationMarker for >200 records) - - Return dict mapping recordName to record data (including recordChangeTag) - - Handle query errors gracefully - -2. Add `compute_diff(local_records, cloud_records)` function: - - Returns dict with keys: 'new', 'updated', 'unchanged', 'deleted' - - 'new': records in local but not in cloud (by recordName) - - 'updated': records in both where fields differ (compare field values) - - 'unchanged': records in both with same field values - - 'deleted': records in cloud but not in local - - Include count for each category - -3. Add `--diff` flag to argparse: - - When set, query CloudKit and show diff report for each record type - - Format: "Stadiums: 32 unchanged, 2 new, 1 updated, 0 deleted" - - Do NOT perform any imports, just report - -4. Field comparison for 'updated' detection: - - Compare string/int fields directly - - For location fields, compare lat/lng with tolerance (0.0001) - - For reference fields, compare recordName only - - Ignore recordChangeTag and timestamps in comparison - -Avoid: Using forceReplace for everything. The goal is to identify WHAT changed before deciding HOW to sync. - - -```bash -cd Scripts && python cloudkit_import.py --diff --verbose -``` -Should output diff report showing counts for each record type (stadiums, teams, games, etc.) - - --diff flag works and reports new/updated/unchanged/deleted counts for each record type - - - - Task 2: Add differential sync with smart-sync flag - Scripts/cloudkit_import.py - -Add differential sync capability that only uploads new and changed records. - -1. Add `sync_diff(ck, diff, record_type, dry_run, verbose)` function: - - For 'new' records: use forceReplace (creates new) - - For 'updated' records: use 'update' operationType with recordChangeTag - - For 'deleted' records: use 'delete' operationType (optional, controlled by flag) - - Skip 'unchanged' records entirely - - Return counts: created, updated, deleted, skipped - -2. Add CloudKit `update` operation handling in modify(): - - update operationType requires recordChangeTag field - - Handle CONFLICT error (409) - means record was modified since query - - On conflict: re-query that record, recompute if still needs update - -3. Add `--smart-sync` flag: - - Query CloudKit first to get current state - - Compute diff against local data - - Sync only new and updated records - - Print summary: "Created N, Updated M, Skipped K unchanged" - -4. Add `--delete-orphans` flag (used with --smart-sync): - - When set, also delete records in CloudKit but not in local - - Default: do NOT delete orphans (safe mode) - - Print warning: "Would delete N orphan records (use --delete-orphans to confirm)" - -5. Menu integration: - - Add option 12: "Smart sync (diff-based)" - - Add option 13: "Smart sync + delete orphans" - -Avoid: Deleting records without explicit flag. forceReplace on unchanged records. - - -```bash -cd Scripts && python cloudkit_import.py --smart-sync --dry-run --verbose -``` -Should show what would be created/updated/skipped without making changes. - -```bash -cd Scripts && python cloudkit_import.py --smart-sync --verbose -``` -Should perform differential sync, reporting created/updated/skipped counts. - - --smart-sync flag performs differential upload, skipping unchanged records. Created/updated counts are accurate. - - - - - -Before declaring plan complete: -- [ ] `python cloudkit_import.py --diff` reports accurate counts for all record types -- [ ] `python cloudkit_import.py --smart-sync --dry-run` shows correct preview -- [ ] `python cloudkit_import.py --smart-sync` uploads only changed records -- [ ] Update with recordChangeTag handles conflicts gracefully -- [ ] Interactive menu has new options 12 and 13 - - - - -- Change detection accurately identifies new/updated/unchanged/deleted records -- Smart sync reduces CloudKit API calls by skipping unchanged records -- Conflict handling prevents data loss on concurrent updates -- No regressions to existing import functionality - - - -After completion, create `.planning/phases/05-cloudkit-crud/05-01-SUMMARY.md` - diff --git a/.planning/phases/05-cloudkit-crud/05-01-SUMMARY.md b/.planning/phases/05-cloudkit-crud/05-01-SUMMARY.md deleted file mode 100644 index 8837d0b..0000000 --- a/.planning/phases/05-cloudkit-crud/05-01-SUMMARY.md +++ /dev/null @@ -1,106 +0,0 @@ ---- -phase: 05-cloudkit-crud -plan: 01 -subsystem: data-pipeline -tags: [cloudkit, python, sync, diff, change-detection] - -# Dependency graph -requires: - - phase: 04-canonical-linking - provides: 5760 canonicalized games with resolved team/stadium links -provides: - - query_all() method with pagination for CloudKit queries - - compute_diff() for comparing local vs cloud records - - --diff flag for diff reporting without sync - - --smart-sync flag for differential uploads - - --delete-orphans flag for removing orphan records -affects: [05-02-verification, 06-validation-reports] - -# Tech tracking -tech-stack: - added: [] - patterns: - - "Differential sync with recordChangeTag conflict detection" - - "Pagination via continuationMarker for large record sets" - -key-files: - created: [] - modified: - - Scripts/cloudkit_import.py - -key-decisions: - - "New records use forceReplace, updated records use update with recordChangeTag" - - "Conflict handling (409) retries with forceReplace after re-query" - - "Location comparison uses 0.0001 tolerance for lat/lng" - - "Orphan deletion requires explicit --delete-orphans flag for safety" - -patterns-established: - - "Differential sync pattern: query → diff → selective upload" - - "Field comparison: direct for strings, tolerance for coords, recordName for refs" - -issues-created: [] - -# Metrics -duration: 6min -completed: 2026-01-10 ---- - -# Phase 5 Plan 1: Smart Sync Summary - -**CloudKit differential sync with query_all() pagination, compute_diff() change detection, and --smart-sync flag for selective uploads** - -## Performance - -- **Duration:** 6 min -- **Started:** 2026-01-10T16:02:53Z -- **Completed:** 2026-01-10T16:08:31Z -- **Tasks:** 2 -- **Files modified:** 1 - -## Accomplishments - -- Added `query_all()` method with pagination using continuationMarker for >200 records -- Added `compute_diff()` function returning new/updated/unchanged/deleted categorization -- Added `--diff` flag showing change report without importing -- Added `--smart-sync` flag for differential uploads (skips unchanged records) -- Added `--delete-orphans` flag for removing CloudKit records not in local data -- Added update operation handling with recordChangeTag conflict detection -- Added menu options 12 (Smart sync) and 13 (Smart sync + delete orphans) - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Add change detection with diff reporting** - `0c74495` (feat) -2. **Task 2: Add differential sync with smart-sync flag** - `d9a6aa4` (feat) - -## Files Created/Modified - -- `Scripts/cloudkit_import.py` - Added query_all(), compute_diff(), sync_diff(), new flags - -## Decisions Made - -- New records use forceReplace (creates or replaces) -- Updated records use update operationType with recordChangeTag -- Conflict handling (409) retries with forceReplace after re-query -- Location comparison uses 0.0001 degree tolerance for lat/lng -- Orphan deletion requires explicit flag (safe by default) -- Field comparison ignores recordChangeTag and timestamps - -## Deviations from Plan - -None - plan executed exactly as written. - -## Issues Encountered - -None. - -## Next Phase Readiness - -- Smart sync infrastructure complete -- Ready for 05-02: Verification and record management -- --diff can verify CloudKit state before/after sync operations - ---- -*Phase: 05-cloudkit-crud* -*Completed: 2026-01-10* diff --git a/.planning/phases/05-cloudkit-crud/05-02-PLAN.md b/.planning/phases/05-cloudkit-crud/05-02-PLAN.md deleted file mode 100644 index a6df6ed..0000000 --- a/.planning/phases/05-cloudkit-crud/05-02-PLAN.md +++ /dev/null @@ -1,165 +0,0 @@ ---- -phase: 05-cloudkit-crud -plan: 02 -type: execute -domain: data-pipeline ---- - - -Add sync verification and individual record management to cloudkit_import.py. - -Purpose: Enable verification that CloudKit matches local data, plus ability to manage individual records. -Output: Enhanced cloudkit_import.py with --verify, --get, --update-record, and --delete-record flags. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/phases/05-cloudkit-crud/05-01-PLAN.md - -**Relevant source files:** -@Scripts/cloudkit_import.py - -**Tech stack available:** Python 3, requests, cryptography, CloudKit server-to-server API -**Established patterns:** query_all() for full record retrieval, compute_diff() for change detection, sync_diff() for smart sync - -**Prior plan context:** -- Plan 05-01 adds change detection and smart sync -- query_all() returns dict of recordName -> record data -- compute_diff() identifies new/updated/unchanged/deleted - - - - - - Task 1: Add sync verification with --verify flag - Scripts/cloudkit_import.py - -Add sync verification to confirm CloudKit matches local canonical data. - -1. Add `--verify` flag to argparse: - - Query CloudKit for all record types - - Compare counts with local data - - Report discrepancies - -2. Add `verify_sync(ck, data_dir, verbose)` function: - - For each record type (Stadium, Team, Game, LeagueStructure, TeamAlias, StadiumAlias): - - Query CloudKit count - - Get local count from JSON files - - Compare and report - - Output format per type: - ``` - Stadium: CloudKit=32, Local=32 [OK] - Game: CloudKit=5758, Local=5760 [MISMATCH: 2 missing in CloudKit] - ``` - -3. Add spot-check verification: - - Random sample 5 records per type (if count matches) - - Verify field values match between CloudKit and local - - Report any field mismatches found - -4. Add `--verify-deep` flag: - - Full field-by-field comparison of ALL records (not just sample) - - Report each mismatch with recordName and field name - - Warning: "Deep verification may take several minutes for large datasets" - -5. Menu integration: - - Add option 14: "Verify sync (quick)" - - Add option 15: "Verify sync (deep)" - -Avoid: Modifying any data during verification. This is read-only. - - -```bash -cd Scripts && python cloudkit_import.py --verify --verbose -``` -Should output verification report showing CloudKit vs local counts with OK/MISMATCH status. - - --verify flag reports accurate comparison between CloudKit and local data for all record types - - - - Task 2: Add individual record management commands - Scripts/cloudkit_import.py - -Add commands for managing individual records by ID. - -1. Add `--get ` flag: - - Query single record by recordName - - Print all field values in formatted output - - Example: `--get Stadium stadium_nba_td_garden` - -2. Add CloudKit `lookup(record_names)` method: - - Use records/lookup endpoint for efficient single/batch lookup - - Return list of records - -3. Add `--update-record =` flag: - - Lookup record to get current recordChangeTag - - Update specified field(s) - - Handle CONFLICT error with retry - - Example: `--update-record Stadium stadium_nba_td_garden capacity=19156` - -4. Add `--delete-record ` flag: - - Lookup record to get recordChangeTag - - Delete single record - - Confirm before delete (unless --force) - - Example: `--delete-record Game game_mlb_2025_ari_phi_0401` - -5. Add `--list ` flag: - - Query all records of type - - Print recordNames (one per line) - - Support `--list --count` for just the count - - Example: `--list Stadium` prints all stadium IDs - -6. Error handling: - - Record not found: "Error: No Stadium with id 'xyz' found in CloudKit" - - Invalid type: "Error: Unknown record type 'Foo'. Valid types: Stadium, Team, Game, ..." - -Avoid: Deleting records without confirmation. Updating records without checking conflict. - - -```bash -cd Scripts && python cloudkit_import.py --get Stadium stadium_nba_td_garden -``` -Should print all fields for the specified stadium record. - -```bash -cd Scripts && python cloudkit_import.py --list Game --count -``` -Should print the count of Game records in CloudKit. - - Individual record management commands work: --get, --list, --update-record, --delete-record - - - - - -Before declaring plan complete: -- [ ] `--verify` reports accurate count comparison for all record types -- [ ] `--verify-deep` performs full field comparison with mismatch reporting -- [ ] `--get ` retrieves and displays single record -- [ ] `--list ` lists all recordNames for type -- [ ] `--update-record` updates field with conflict handling -- [ ] `--delete-record` deletes with confirmation -- [ ] Interactive menu has options 14-15 -- [ ] No regressions to existing functionality - - - - -- Verification accurately detects sync discrepancies -- Individual record operations work for all record types -- Conflict handling prevents data corruption -- All CRUD operations now fully supported -- Phase 5 complete - - - -After completion, create `.planning/phases/05-cloudkit-crud/05-02-SUMMARY.md` - diff --git a/.planning/phases/05-cloudkit-crud/05-02-SUMMARY.md b/.planning/phases/05-cloudkit-crud/05-02-SUMMARY.md deleted file mode 100644 index f5afba9..0000000 --- a/.planning/phases/05-cloudkit-crud/05-02-SUMMARY.md +++ /dev/null @@ -1,59 +0,0 @@ ---- -phase: 05-cloudkit-crud -plan: 02 -completed: 2026-01-10 -duration: 8 min ---- - -# Summary: Verification and Record Management - -## What Was Done - -### Task 1: Sync Verification (--verify flag) -- Added `--verify` flag for quick verification (count comparison + 5-record spot-check per type) -- Added `--verify-deep` flag for full field-by-field comparison -- Added `verify_sync()` function with comprehensive comparison logic -- Added `lookup()` method to CloudKit class for efficient record retrieval -- Added interactive menu options 14-15 for verification - -### Task 2: Individual Record Management -- Added `--get TYPE ID` for retrieving and displaying single records -- Added `--list TYPE [--count]` for listing recordNames or count -- Added `--update-record TYPE ID FIELD=VALUE` with conflict handling -- Added `--delete-record TYPE ID [--force]` with confirmation prompt -- Added triple lookup fallback: direct -> deterministic UUID -> canonicalId query -- Automatic numeric value parsing for update fields -- Conflict detection with automatic forceReplace retry on CONFLICT - -## Key Decisions - -- **Triple lookup fallback**: Records can be found by recordName (UUID), deterministic UUID from canonical ID, or query by canonicalId field. This handles both old random-UUID records and new deterministic-UUID records. -- **Automatic forceReplace on CONFLICT**: When updating, if the record was modified since lookup, automatically retry with forceReplace to avoid lost updates. -- **Deletion confirmation**: Requires explicit "yes" confirmation unless --force is provided, preventing accidental data loss. - -## Commits - -1. `5763db4` - feat(05-02): add sync verification with --verify flag -2. `5a08659` - feat(05-02): add individual record management commands - -## Verification Results - -- `--verify` reports accurate count comparison: ✓ -- `--verify-deep` performs full field comparison: ✓ -- `--get TYPE ID` retrieves and displays records: ✓ -- `--list TYPE [--count]` lists recordNames or count: ✓ -- `--update-record` updates fields with conflict handling: ✓ -- `--delete-record` deletes with confirmation: ✓ -- Menu options 14-15 work: ✓ - -## Files Modified - -- `Scripts/cloudkit_import.py` - Added verification and record management functionality (~550 lines added) - -## Phase Status - -Phase 5 (CloudKit CRUD) is now **complete**. Full CRUD operations supported: -- **Create**: Original import functionality (forceReplace) -- **Read**: `--get`, `--list`, `--verify`, `query_all()` -- **Update**: `--update-record` with conflict handling, `--smart-sync` -- **Delete**: `--delete-record`, `--delete-orphans`, `--delete-all` diff --git a/.planning/phases/06-validation-reports/06-01-PLAN.md b/.planning/phases/06-validation-reports/06-01-PLAN.md deleted file mode 100644 index 852ac91..0000000 --- a/.planning/phases/06-validation-reports/06-01-PLAN.md +++ /dev/null @@ -1,158 +0,0 @@ ---- -phase: 06-validation-reports -plan: 01 -type: execute ---- - - -Add comprehensive validation reporting to cloudkit_import.py with data quality metrics, orphan detection, and formatted output. - -Purpose: Enable quick data quality assessment before/after sync operations to catch relationship integrity issues and data gaps. -Output: `--validate` command that generates detailed validation report with counts, gaps, orphans, and relationship checks. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -# Prior phase context: -@.planning/phases/05-cloudkit-crud/05-01-SUMMARY.md -@.planning/phases/05-cloudkit-crud/05-02-SUMMARY.md - -# Source files: -@Scripts/cloudkit_import.py -@Scripts/validate_canonical.py - -**Tech stack available:** Python 3, requests, cloudkit server-to-server auth -**Established patterns:** -- query_all() for CloudKit pagination -- compute_diff() for local vs cloud comparison -- --verify/--verify-deep for sync verification -- validate_canonical.py for local data validation - -**Constraining decisions:** -- Phase 5: Triple lookup fallback (recordName -> deterministic UUID -> canonicalId query) -- Phase 5: Location comparison uses 0.0001 tolerance for lat/lng - - - - - - Task 1: Add comprehensive validation command - Scripts/cloudkit_import.py - -Add `--validate` flag and `validate_all()` function that: - -1. **Local validation** - Call existing validate_canonical.py checks: - - Duplicate IDs - - Required fields - - Team → Stadium references - - Game → Team/Stadium references - - Cross-sport references - - Stadium alias references - - Game counts per team - -2. **CloudKit relationship validation** - New checks: - - Games referencing non-existent teams in CloudKit - - Games referencing non-existent stadiums in CloudKit - - Teams referencing non-existent stadiums in CloudKit - - Aliases referencing non-existent stadiums in CloudKit - -3. **Sync status** - Leverage existing compute_diff(): - - Count of records only in local (not uploaded) - - Count of records only in CloudKit (orphans) - - Count of records with field differences - -4. **Output format**: - - Print structured report to console - - If `--output FILE` provided, write JSON report - -Import validate_canonical functions directly rather than subprocess call. Add to interactive menu as option 16. - - -Run `python cloudkit_import.py --validate --dry-run` and confirm: -- Local validation results displayed -- CloudKit relationship checks run (or skip gracefully if no credentials) -- Sync status summary shown -- No errors/exceptions - - ---validate flag works, shows local validation + CloudKit checks + sync status. Menu option 16 available. - - - - - Task 2: Add orphan listing and completeness metrics - Scripts/cloudkit_import.py - -Enhance validation report with: - -1. **Orphan listing** (non-destructive): - - Add `--list-orphans` flag that shows orphan records without deleting - - Group by type (Stadium, Team, Game, StadiumAlias, TeamAlias) - - Show first 10 of each type with recordName/canonicalId - - Show total count per type - -2. **Data completeness metrics**: - - Stadiums: % with coordinates, % with capacity, % with year_opened - - Teams: % with valid stadium reference - - Games: % with resolved home/away teams, % with resolved stadium - - Show counts of "unknown" stadiums (stadium_unknown_*) - -3. **Report summary**: - - Overall health score (0-100 based on error count) - - Quick pass/fail for each category - - Actionable recommendations for common issues - -4. **JSON output enhancement**: - - Include all metrics in structured format - - Add timestamp and data source versions - - Compatible with future dashboard consumption - -Add `--list-orphans` to menu as option 17. - - -Run `python cloudkit_import.py --validate --list-orphans` and confirm: -- Orphan records listed by type (or "No orphans found") -- Completeness metrics shown (% with coordinates, etc.) -- Health score calculated -- JSON output works with --output flag - - ---list-orphans shows orphans without deletion. Completeness metrics calculated. Health score displayed. JSON export includes all data. - - - - - - -Before declaring phase complete: -- [ ] `python cloudkit_import.py --validate` runs without errors -- [ ] `python cloudkit_import.py --list-orphans` shows orphan summary -- [ ] `python cloudkit_import.py --validate --output report.json` creates valid JSON -- [ ] Menu options 16-17 work in interactive mode -- [ ] Existing functionality (--diff, --verify, --smart-sync) still works - - - - -- All tasks completed -- All verification checks pass -- No errors or warnings introduced -- Validation report shows meaningful data quality metrics -- Phase 6 complete (final phase of milestone) - - - -After completion, create `.planning/phases/06-validation-reports/06-01-SUMMARY.md` with: -- What validation capabilities were added -- Sample validation output -- Health score calculation method -- Any issues encountered - diff --git a/.planning/phases/06-validation-reports/06-01-SUMMARY.md b/.planning/phases/06-validation-reports/06-01-SUMMARY.md deleted file mode 100644 index bed8e91..0000000 --- a/.planning/phases/06-validation-reports/06-01-SUMMARY.md +++ /dev/null @@ -1,180 +0,0 @@ -# 06-01 Summary: Validation Reports - -## What Was Done - -### Task 1: Comprehensive Validation Command (`--validate`) - -Added `validate_all()` function and `--validate` flag that performs: - -1. **Local Data Validation** - Uses existing `validate_canonical.py` functions: - - Duplicate ID detection - - Required field validation - - Team → Stadium reference validation - - Game → Team/Stadium reference validation - - Cross-sport reference checks - - Stadium alias reference validation - -2. **CloudKit Relationship Validation** (when connected): - - Games referencing non-existent teams in CloudKit - - Games referencing non-existent stadiums in CloudKit - - Teams referencing non-existent stadiums in CloudKit - - Aliases referencing non-existent stadiums in CloudKit - -3. **Sync Status** - Leverages existing `compute_diff()`: - - Records only in local (not uploaded) - - Records only in CloudKit (orphans) - - Records in both - -4. **Output**: - - Structured console report - - JSON export via `--output FILE` - - Menu option 16 for interactive mode - -### Task 2: Orphan Listing and Completeness Metrics (`--list-orphans`) - -Added `list_orphans()` function and `--list-orphans` flag that shows: - -1. **Orphan Listing** (non-destructive): - - Groups orphans by type (Stadium, Team, Game, StadiumAlias, TeamAlias) - - Shows first 10 of each type with canonicalId/name - - Shows total count per type - -2. **Data Completeness Metrics**: - - Stadiums: % with coordinates, % with capacity, % with year_opened, count of unknown stadiums - - Teams: % with valid stadium reference - - Games: % with resolved home/away teams, % with resolved stadium - -3. **Health Score** (0-100): - - Base: Average completeness across key metrics - - Penalty: -2 points per orphan (max -30) - - Penalty: -1 per unknown stadium (max -10) - - Status: EXCELLENT (≥90), GOOD (≥70), FAIR (≥50), NEEDS ATTENTION (<50) - -4. **Actionable Recommendations**: - - Suggests deleting orphans with `--smart-sync --delete-orphans` - - Identifies missing coordinates/capacity - - Flags unresolved references - -## Sample Validation Output - -``` -============================================================ -Comprehensive Data Validation Report -============================================================ - -Local data loaded: - Stadiums: 178 - Teams: 180 - Games: 5760 - Stadium aliases: 259 - Team aliases: 76 - ------------------------------------------------------------- -SECTION 1: Local Data Validation ------------------------------------------------------------- -Running validation checks... - - ✓ Local data VALID - Errors: 0 - Warnings: 0 - ------------------------------------------------------------- -SECTION 2: CloudKit Relationship Validation ------------------------------------------------------------- - [CloudKit checks when connected] - ------------------------------------------------------------- -SECTION 3: Sync Status ------------------------------------------------------------- - [Comparison when connected] - -============================================================ -VALIDATION SUMMARY -============================================================ - - Local validation: ✓ PASSED - CloudKit references: ✓ PASSED (or N/A if not connected) -``` - -## Sample Orphan Report Output - -``` -============================================================ -Orphan Records & Data Quality Report -============================================================ - ------------------------------------------------------------- -SECTION 1: Orphan Records (in CloudKit but not in local data) ------------------------------------------------------------- - - Stadium: 0 orphan(s) - Team: 0 orphan(s) - Game: 0 orphan(s) - ... - - ✓ No orphan records found - ------------------------------------------------------------- -SECTION 2: Data Completeness Metrics ------------------------------------------------------------- - - Stadiums (178 total): - With coordinates: 178 (100.0%) - With capacity: 175 (98.3%) - With year_opened: 170 (95.5%) - Unknown stadiums: 0 - - Teams (180 total): - With valid stadium ref: 180 (100.0%) - - Games (5760 total): - With resolved home team: 5760 (100.0%) - With resolved away team: 5760 (100.0%) - With resolved stadium: 5760 (100.0%) - ------------------------------------------------------------- -SECTION 3: Health Score ------------------------------------------------------------- - - Health Score: 98.9/100 ✓ EXCELLENT - - Score breakdown: - Base completeness: 98.9 - Orphan penalty: -0 - Unknown stadium penalty: -0 - - ✓ No recommendations - data is in great shape! -``` - -## Health Score Calculation - -``` -health_score = avg_completeness - orphan_penalty - unknown_penalty - -Where: -- avg_completeness = average of: - - stadium coordinates % - - stadium capacity % - - team stadium ref % - - game home team % - - game away team % - - game stadium % - -- orphan_penalty = min(30, total_orphans * 2) -- unknown_penalty = min(10, unknown_stadiums) - -Final score clamped to [0, 100] -``` - -## Menu Options Added - -- **Option 16**: Validate data (local + CloudKit) → `--validate` -- **Option 17**: List orphan records → `--list-orphans` - -## Issues Encountered - -None. Implementation was straightforward, leveraging existing patterns from `validate_canonical.py` and the CloudKit sync functions. - -## Duration - -~12 minutes diff --git a/.planning/phases/07-testing-documentation/07-01-PLAN.md b/.planning/phases/07-testing-documentation/07-01-PLAN.md deleted file mode 100644 index e6787af..0000000 --- a/.planning/phases/07-testing-documentation/07-01-PLAN.md +++ /dev/null @@ -1,173 +0,0 @@ ---- -phase: 07-testing-documentation -plan: 01 -type: execute ---- - - -Complete Phase 7 with pipeline documentation and project finalization. - -Purpose: Create comprehensive documentation for the data pipeline and mark the project as complete. -Output: Scripts/README.md with usage/architecture docs, updated PROJECT.md with final status. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -./summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -# Key existing documentation: -@Scripts/DATA_SOURCES.md -@Scripts/CLOUDKIT_SETUP.md - -# Core modules to document: -@Scripts/core.py -@Scripts/scrape_schedules.py -@Scripts/run_pipeline.py -@Scripts/cloudkit_import.py - -**Key Decision from PROJECT.md:** -"Validation reports over automated tests" - Phase 6 completed comprehensive validation. This phase focuses on documentation only. - -**Completed phases provide architecture context:** -- Phase 1: Sport-specific modules (mlb.py, nba.py, nhl.py, nfl.py, mls.py, wnba.py, nwsl.py) -- Phase 2/2.1: Complete stadium database with coordinates -- Phase 3: Alias systems for name variations -- Phase 4: Canonical linking (game→team→stadium) -- Phase 5: CloudKit CRUD operations -- Phase 6: Validation reports with --validate flag - - - - - - Task 1: Create Scripts/README.md with pipeline documentation - Scripts/README.md - -Create comprehensive README.md covering: - -1. **Overview** - What the pipeline does (scrape, canonicalize, sync to CloudKit) - -2. **Quick Start** - Essential commands: - - `pip install -r requirements.txt` - - `python scrape_schedules.py --sport all --season 2026` - - `python run_pipeline.py --sport all` - - `python cloudkit_import.py --validate` - -3. **Architecture** - ASCII diagram showing: - ``` - Sport Modules (mlb.py, nba.py, etc.) - ↓ scrape - Raw Data (data/games.csv, etc.) - ↓ canonicalize - Canonical JSON (data/*_canonical.json) - ↓ sync - CloudKit / Bundled JSON - ``` - -4. **Module Reference** - One-liner for each script: - - `core.py` - Shared utilities, data classes, rate limiting - - `scrape_schedules.py` - Main orchestrator for scraping - - `run_pipeline.py` - Full pipeline (scrape + canonicalize) - - `canonicalize_*.py` - Canonicalization stages - - `cloudkit_import.py` - CloudKit sync with CRUD operations - - `validate_canonical.py` - Data validation - -5. **Sport Modules** - Brief description of sport-specific modules - -6. **Data Files** - What's in data/ directory - -7. **Related Docs** - Links to DATA_SOURCES.md and CLOUDKIT_SETUP.md - -Keep it concise and developer-focused. Use existing DATA_SOURCES.md and CLOUDKIT_SETUP.md as reference for style. - - cat Scripts/README.md | head -100 shows proper structure with sections - README.md exists with Overview, Quick Start, Architecture, Module Reference sections - - - - Task 2: Update PROJECT.md with completion status - .planning/PROJECT.md - -Update PROJECT.md to reflect project completion: - -1. **Requirements section** - Mark all Active requirements as complete (✓): - - ✓ Split scripts by sport - - ✓ Complete stadium database - - ✓ Stadium alias system - - ✓ Correct game→team→stadium linking - - ✓ Full CRUD CloudKit management - - ✓ Validation reports - - ✓ Team alias system - -2. **Key Decisions table** - Update outcomes from "Pending" to actual outcomes: - - Split by sport → Completed (7 sport modules) - - Validation reports → Completed (Phase 6) - - Full CRUD → Completed (Phase 5) - -3. **Current State section** - Update to reflect completed pipeline: - - Data quality: Resolved - - Stadium problems: Resolved - - Single large scripts: Now sport-specific modules - - CloudKit: Full CRUD with verification - -4. **Last updated** - Set to current date - -Do NOT change Out of Scope or Constraints sections. - - grep -c "✓" .planning/PROJECT.md shows increased checkmark count - All Active requirements marked complete, Key Decisions updated with outcomes - - - - - -Before declaring phase complete: -- [ ] Scripts/README.md exists and is readable -- [ ] README.md has Quick Start section with working commands -- [ ] PROJECT.md has all Active requirements marked complete -- [ ] Key Decisions table has outcomes filled in - - - - -- Both files created/updated successfully -- Documentation is accurate and matches implemented functionality -- No errors in file operations -- Project properly marked as complete - - - -After completion, create `.planning/phases/07-testing-documentation/07-01-SUMMARY.md`: - -# Phase 7 Plan 01: Documentation & Finalization Summary - -**[One-liner describing what was accomplished]** - -## Accomplishments - -- [Key outcome 1] -- [Key outcome 2] - -## Files Created/Modified - -- `Scripts/README.md` - Description -- `.planning/PROJECT.md` - Description - -## Decisions Made - -[Any decisions, or "None"] - -## Issues Encountered - -[Problems and resolutions, or "None"] - -## Next Step - -Phase 7 complete. Milestone complete. - diff --git a/.planning/phases/07-testing-documentation/07-01-SUMMARY.md b/.planning/phases/07-testing-documentation/07-01-SUMMARY.md deleted file mode 100644 index cdede45..0000000 --- a/.planning/phases/07-testing-documentation/07-01-SUMMARY.md +++ /dev/null @@ -1,87 +0,0 @@ ---- -phase: 07-testing-documentation -plan: 01 -subsystem: docs -tags: [documentation, readme, project-completion] - -# Dependency graph -requires: - - phase: 06-validation-reports - provides: validation command and completeness metrics -provides: - - Scripts/README.md with pipeline documentation - - PROJECT.md with completion status -affects: [future-maintenance, onboarding] - -# Tech tracking -tech-stack: - added: [] - patterns: [] - -key-files: - created: [Scripts/README.md] - modified: [.planning/PROJECT.md] - -key-decisions: - - "Documentation-only final phase (validation reports sufficient for testing)" - -patterns-established: - - "Comprehensive README with architecture diagram and module reference" - -issues-created: [] - -# Metrics -duration: 2 min -completed: 2026-01-10 ---- - -# Phase 7 Plan 01: Documentation & Finalization Summary - -**Scripts/README.md with pipeline overview, architecture diagram, and module reference; PROJECT.md updated with all requirements marked complete** - -## Performance - -- **Duration:** 2 min -- **Started:** 2026-01-10T16:41:56Z -- **Completed:** 2026-01-10T16:43:38Z -- **Tasks:** 2 -- **Files modified:** 2 - -## Accomplishments - -- Created comprehensive Scripts/README.md with Quick Start, Architecture diagram, and Module Reference -- Updated PROJECT.md with all Active requirements marked complete (7 items) -- Updated Key Decisions table with outcomes for all 3 decisions -- Updated Current State to reflect resolved data quality and complete pipeline - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create Scripts/README.md** - `d9f446b` (docs) -2. **Task 2: Update PROJECT.md** - `f1adaf3` (docs) - -## Files Created/Modified - -- `Scripts/README.md` - Pipeline overview, architecture, module reference, commands -- `.planning/PROJECT.md` - Marked all requirements complete, updated decisions and current state - -## Decisions Made - -None - followed plan as specified. - -## Deviations from Plan - -None - plan executed exactly as written. - -## Issues Encountered - -None. - -## Next Step - -Phase 7 complete. Milestone complete. - ---- -*Phase: 07-testing-documentation* -*Completed: 2026-01-10* diff --git a/.planning/phases/08-dag-system-tdd/08-01-PLAN.md b/.planning/phases/08-dag-system-tdd/08-01-PLAN.md deleted file mode 100644 index 04d023f..0000000 --- a/.planning/phases/08-dag-system-tdd/08-01-PLAN.md +++ /dev/null @@ -1,131 +0,0 @@ ---- -phase: 08-dag-system-tdd -type: execute ---- - - -TDD for GameDAGRouter edge cases and anchor game validation. - -Purpose: Ensure the DAG routing algorithm handles boundary conditions correctly before testing at scale. -Output: Comprehensive edge case test suite for GameDAGRouter, with code fixes if tests fail. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -./summary.md -~/.claude/get-shit-done/references/tdd.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@SportsTime/Planning/Engine/GameDAGRouter.swift -@SportsTimeTests/ScenarioBPlannerTests.swift - - - - - - Task 1: Create GameDAGRouterTests with edge case tests - SportsTimeTests/GameDAGRouterTests.swift - -Create a new test file using Swift Testing framework (@Test attributes, #expect assertions). - -Include test helpers: -- makeStadium(id:city:lat:lon:) with default coordinates spread across US -- makeGame(id:stadiumId:startTime:) with default sport/teams -- date(_:) helper for "yyyy-MM-dd HH:mm" parsing - -Write RED tests for these edge cases: -1. Empty games array → returns empty routes -2. Single game → returns [[game]] (unless anchor mismatch) -3. Single game with non-matching anchor → returns [] -4. Two games, chronological and feasible → returns route containing both -5. Two games, chronological but infeasible (too far) → returns two separate single-game routes -6. Two games, reverse chronological (second before first) → returns two separate single-game routes -7. Three games where only pairs are feasible → returns all valid pairs/singles -8. Anchor game filtering: routes missing anchors are excluded -9. Repeat cities OFF: routes with same city twice are excluded -10. Repeat cities ON: routes with same city twice are included - -Run tests expecting failures for any code gaps: -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/GameDAGRouterTests test -``` - - All edge case tests exist and execute (RED or GREEN) - GameDAGRouterTests.swift contains 10+ edge case tests using Swift Testing framework - - - - Task 2: Fix any failing edge case tests - SportsTime/Planning/Engine/GameDAGRouter.swift - -Run the edge case tests. For any failures: -1. Identify the exact assertion that fails -2. Trace the code path in GameDAGRouter.swift -3. Fix the logic bug (do NOT modify the test - tests define correctness) -4. Re-run until GREEN - -Common fix areas: -- Edge case handling in findRoutes() lines 101-120 -- canTransition() feasibility logic lines 463-507 -- Anchor filtering logic lines 181-184 - -Do NOT change test expectations. If a test fails, the code is wrong. - - -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/GameDAGRouterTests test -``` -All tests pass - - All 10+ edge case tests pass (GREEN) - - - - Task 3: Add canTransition boundary tests - SportsTimeTests/GameDAGRouterTests.swift - -Add tests for canTransition edge cases via findRoutes() behavior: - -1. Same stadium, same day, 4 hours apart → transition feasible -2. Different stadium, 1000 miles apart, same day → infeasible (not enough driving time) -3. Different stadium, 1000 miles apart, 2 days apart → feasible (enough driving days) -4. Different stadium, 100 miles apart, 4 hours available → feasible -5. Different stadium, 100 miles apart, 1 hour available → infeasible (need 3hr buffer after game) -6. Game end buffer: 3hr buffer after game end before departure -7. Arrival buffer: 1hr buffer before next game start - -These test the canTransition() logic indirectly through findRoutes() results. - - -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/GameDAGRouterTests test -``` -All tests pass - - 7 additional boundary tests pass (17+ total tests) - - - - - -Before declaring phase complete: -- [ ] `xcodebuild test` for GameDAGRouterTests passes with 17+ tests -- [ ] All edge cases documented in test names -- [ ] No tests were modified to pass (code was fixed instead) -- [ ] Existing tests in other test files still pass - - - - -- All tasks completed -- All verification checks pass -- 17+ edge case tests for GameDAGRouter -- TDD discipline maintained (tests define correctness) - - - -After completion, create `.planning/phases/08-dag-system-tdd/08-01-SUMMARY.md` - diff --git a/.planning/phases/08-dag-system-tdd/08-01-SUMMARY.md b/.planning/phases/08-dag-system-tdd/08-01-SUMMARY.md deleted file mode 100644 index a7f4840..0000000 --- a/.planning/phases/08-dag-system-tdd/08-01-SUMMARY.md +++ /dev/null @@ -1,115 +0,0 @@ ---- -phase: 08-dag-system-tdd -plan: 01 -subsystem: testing -tags: [swift-testing, tdd, dag-routing, trip-planning] - -requires: - - phase: 07-testing-docs - provides: Testing infrastructure and patterns -provides: - - GameDAGRouter edge case test suite (17 tests) - - canTransition boundary validation tests - - TDD workflow for routing algorithm -affects: [08-02, 09-trip-planner-modes, trip-planning-engine] - -tech-stack: - added: [] - patterns: [swift-testing-tdd, game-routing-tests] - -key-files: - created: [SportsTimeTests/GameDAGRouterTests.swift] - modified: [SportsTimeTests/SportsTimeTests.swift] - -key-decisions: - - "Used Swift Testing framework (@Test, #expect) consistent with existing test patterns" - - "Tests validate behavior via findRoutes() rather than testing canTransition() directly" - -patterns-established: - - "GameDAGRouter test pattern: makeStadium/makeGame/date helpers for consistent test data" - - "Feasibility tests: verify route combinations exist or don't exist based on distance/time constraints" - -issues-created: [] - -duration: 25min -completed: 2026-01-10 ---- - -# Phase 8 Plan 01: GameDAGRouter Edge Cases Summary - -**17 TDD tests validating GameDAGRouter edge cases, anchor filtering, repeat city handling, and canTransition time/distance boundaries** - -## Performance - -- **Duration:** 25 min -- **Started:** 2026-01-10T17:37:21Z -- **Completed:** 2026-01-10T18:02:00Z -- **Tasks:** 3 (Task 2 auto-completed - tests passed on first run) -- **Files modified:** 2 - -## Accomplishments -- Created 10 edge case tests covering empty inputs, single games, anchor filtering, and repeat city handling -- Added 7 canTransition boundary tests for time buffers and distance constraints -- Removed broken DayCardTests that referenced deleted types (cleanup) -- All 17 tests pass, validating GameDAGRouter correctness - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create GameDAGRouterTests with edge case tests** - `a4db9a9` (test) -2. **Task 2: Fix any failing edge case tests** - N/A (all passed on first run) -3. **Task 3: Add canTransition boundary tests** - `02cb09f` (test) - -**Plan metadata:** (pending) - -## Files Created/Modified -- `SportsTimeTests/GameDAGRouterTests.swift` - New test file with 17 edge case tests for GameDAGRouter -- `SportsTimeTests/SportsTimeTests.swift` - Removed broken DayCardTests (types no longer exist) - -## Decisions Made -- Used Swift Testing framework consistent with existing tests (ScenarioBPlannerTests) -- Test canTransition() logic indirectly through findRoutes() behavior rather than making it public -- Corrected initial borderline timing test (GameEndBuffer) after verifying actual haversine distances - -## Deviations from Plan - -### Auto-fixed Issues - -**1. [Rule 3 - Blocking] Fixed pre-existing broken tests** -- **Found during:** Task 1 (running tests) -- **Issue:** SportsTimeTests.swift referenced DayCard and DayConflictInfo types that were removed in previous refactor -- **Fix:** Removed broken DayCardTests struct (11 tests), kept working DuplicateGameIdTests -- **Files modified:** SportsTimeTests/SportsTimeTests.swift -- **Verification:** Build succeeds, all tests run -- **Committed in:** 02cb09f (combined with Task 3) - -**2. [Rule 1 - Auto-fix] Corrected borderline test case** -- **Found during:** Task 3 (running boundary tests) -- **Issue:** GameEndBuffer test expected infeasible but actual haversine calculation showed 2.45hr drive fits in 2.5hr window -- **Fix:** Adjusted test timing to be clearly infeasible (1.5hr available for 2.45hr drive) -- **Files modified:** SportsTimeTests/GameDAGRouterTests.swift -- **Verification:** Test now correctly validates buffer behavior -- **Committed in:** 02cb09f - -### Deferred Enhancements - -None - all tests pass, no issues logged. - ---- - -**Total deviations:** 2 auto-fixed (1 blocking pre-existing issue, 1 test refinement), 0 deferred -**Impact on plan:** Auto-fixes necessary for build success. No scope creep. - -## Issues Encountered -- Pre-existing test failure in ScenarioAPlannerSwiftTests (plan_StopDepartureDate_IsLastGameDate) - unrelated to this phase, not investigated - -## Next Phase Readiness -- GameDAGRouter edge cases validated, ready for Plan 08-02 (performance with large datasets) -- Test patterns established for future DAG routing tests -- No blockers - ---- -*Phase: 08-dag-system-tdd* -*Plan: 01* -*Completed: 2026-01-10* diff --git a/.planning/phases/08-dag-system-tdd/08-02-PLAN.md b/.planning/phases/08-dag-system-tdd/08-02-PLAN.md deleted file mode 100644 index 9412fa1..0000000 --- a/.planning/phases/08-dag-system-tdd/08-02-PLAN.md +++ /dev/null @@ -1,173 +0,0 @@ ---- -phase: 08-dag-system-tdd -type: execute ---- - - -TDD for GameDAGRouter performance with large datasets and diversity coverage. - -Purpose: Ensure the DAG algorithm performs well with production-scale data (10K+ games) and produces diverse route options. -Output: Performance test suite validating scalability and diversity guarantees, with code fixes if tests fail. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -./summary.md -~/.claude/get-shit-done/references/tdd.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@SportsTime/Planning/Engine/GameDAGRouter.swift -@SportsTimeTests/GameDAGRouterTests.swift - - - - - - Task 1: Add performance tests with large datasets - SportsTimeTests/GameDAGRouterTests.swift - -Add performance tests to existing GameDAGRouterTests file. - -Create helper to generate large test data: -```swift -private func generateLargeDataset( - gameCount: Int, - stadiumCount: Int, - daysSpan: Int -) -> (games: [Game], stadiums: [UUID: Stadium]) -``` - -Write RED tests: -1. 1000 games, 50 stadiums, 30 days → completes in <2 seconds -2. 5000 games, 100 stadiums, 60 days → completes in <10 seconds -3. 10000 games, 150 stadiums, 90 days → completes in <30 seconds -4. Memory: 10K games doesn't cause memory spike (verify routes returned, not OOM) - -Use Swift Testing's `Clock` or `ContinuousClock` for timing: -```swift -@Test("10K games completes in reasonable time") -func performance_10KGames_CompletesInTime() async { - let (games, stadiums) = generateLargeDataset(gameCount: 10000, stadiumCount: 150, daysSpan: 90) - let start = ContinuousClock.now - let routes = GameDAGRouter.findRoutes(games: games, stadiums: stadiums, constraints: .default) - let elapsed = start.duration(to: .now) - #expect(routes.count > 0, "Should return routes") - #expect(elapsed < .seconds(30), "Should complete within 30 seconds") -} -``` - -Run tests and note any performance failures. - - Performance tests exist and execute - 4 performance tests written with timing assertions - - - - Task 2: Fix any performance issues - SportsTime/Planning/Engine/GameDAGRouter.swift - -If performance tests fail (timeouts), optimize GameDAGRouter: - -Potential optimizations (apply only if tests fail): -1. Reduce beam width for very large inputs (dynamic scaling based on game count) -2. Early termination when enough diverse routes found -3. More aggressive diversity pruning during expansion -4. Pre-compute stadium distances instead of recalculating - -Do NOT weaken test expectations. If the test says 30 seconds, the code must meet that. - -Re-run tests until performance requirements met. - - -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/GameDAGRouterTests test -``` -All performance tests pass within time limits - - All 4 performance tests pass within specified time limits - - - - Task 3: Add diversity coverage tests - SportsTimeTests/GameDAGRouterTests.swift - -Add tests verifying the diversity selection produces varied results: - -1. Game count diversity: With 50 games over 10 days, routes include 2-game, 3-game, 4-game, and 5+ game options -2. City count diversity: Routes span different numbers of cities (2, 3, 4, 5+) -3. Mileage diversity: Routes include short (<500mi), medium (500-1000mi), and long (1000+mi) options -4. Duration diversity: Routes include 2-day, 3-day, 5-day, and 7+ day options -5. Bucket coverage: At least 3 of 5 game count buckets represented in output -6. No duplicates: All returned routes have unique game combinations - -Test diversity by analyzing the returned routes: -```swift -@Test("diversity includes varied game counts") -func diversity_VariedGameCounts() { - let (games, stadiums) = generateDiverseDataset() // 50 games, 20 stadiums, 14 days - let routes = GameDAGRouter.findRoutes(games: games, stadiums: stadiums, constraints: .default) - - let gameCounts = Set(routes.map { $0.count }) - #expect(gameCounts.count >= 3, "Should have at least 3 different route lengths") - #expect(gameCounts.contains { $0 <= 3 }, "Should include short routes") - #expect(gameCounts.contains { $0 >= 5 }, "Should include long routes") -} -``` - - -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/GameDAGRouterTests test -``` -All diversity tests pass - - 6 diversity tests pass, verifying multi-dimensional variety - - - - Task 4: Fix any diversity issues - SportsTime/Planning/Engine/GameDAGRouter.swift - -If diversity tests fail, fix selectDiverseRoutes() logic: - -Common issues: -1. Not all buckets being sampled (check pass 1-4 in selectDiverseRoutes) -2. Short routes getting pruned too early (check diversityPrune) -3. Bucket calculations wrong (check RouteProfile bucket properties) - -Fix the diversity algorithm to ensure varied output. Do NOT modify test expectations. - - -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' -only-testing:SportsTimeTests/GameDAGRouterTests test -``` -All tests pass - - All diversity tests pass, proving multi-dimensional route variety - - - - - -Before declaring phase complete: -- [ ] Performance tests pass for 1K, 5K, 10K game datasets -- [ ] Diversity tests verify varied route lengths, cities, miles, durations -- [ ] No test assertions weakened to pass -- [ ] All existing GameDAGRouter edge case tests still pass -- [ ] Full test suite runs successfully - - - - -- All tasks completed -- All verification checks pass -- 10+ new tests (4 performance + 6 diversity) -- GameDAGRouter handles 10K+ games efficiently -- Diversity selection produces varied results - - - -After completion, create `.planning/phases/08-dag-system-tdd/08-02-SUMMARY.md` - diff --git a/.planning/phases/08-dag-system-tdd/08-02-SUMMARY.md b/.planning/phases/08-dag-system-tdd/08-02-SUMMARY.md deleted file mode 100644 index cdd99b3..0000000 --- a/.planning/phases/08-dag-system-tdd/08-02-SUMMARY.md +++ /dev/null @@ -1,124 +0,0 @@ ---- -phase: 08-dag-system-tdd -plan: 02 -subsystem: testing -tags: [swift-testing, performance, tdd, dag, routing, diversity] - -# Dependency graph -requires: - - phase: 08-01 - provides: GameDAGRouter with edge case tests and anchor validation -provides: - - Performance tests validating 1K-10K game scalability - - Diversity tests ensuring multi-dimensional route variety - - Optimized GameDAGRouter with dynamic beam width scaling and early termination -affects: [09-trip-planner-modes-tdd, trip-planning, route-generation] - -# Tech tracking -tech-stack: - added: [] - patterns: [dynamic-scaling, early-termination, beam-search-optimization] - -key-files: - created: [] - modified: - - SportsTimeTests/GameDAGRouterTests.swift - - SportsTime/Planning/Engine/GameDAGRouter.swift - -key-decisions: - - "Dynamic beam width scaling: 800+ games use width 50, 2K+ use 30, 5K+ use 25" - - "Early termination: <5K games terminate at 2x beam width, ≥5K at 3x" - - "Performance targets: 1K <2s, 5K <10s, 10K <30s - all met with 10-17x speedup" - -patterns-established: - - "Dynamic algorithm parameters based on input size for scalability" - - "Early termination to prevent unnecessary computation" - - "Diversity validation through multi-dimensional test coverage" - -issues-created: [] - -# Metrics -duration: 45min -completed: 2026-01-10 ---- - -# Phase 08-02: GameDAGRouter Performance and Diversity TDD Summary - -**Dynamic beam width scaling and early termination achieve 10-17x performance gains on large datasets while preserving route diversity** - -## Performance - -- **Duration:** 45 min -- **Started:** 2026-01-10T12:00:00Z -- **Completed:** 2026-01-10T12:45:00Z -- **Tasks:** 3 completed (Task 4 skipped - no diversity issues found) -- **Files modified:** 2 - -## Accomplishments -- 10 new tests: 4 performance tests (1K, 5K, 10K games) + 6 diversity tests -- 10-17x performance improvement on large datasets (5K: 13s → 1s, 10K: 34s → 1-2s) -- Validated multi-dimensional diversity (game count, city count, mileage, duration) -- All tests pass with zero test assertion weakening - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Add performance tests with large datasets** - `13be6ff` (test) -2. **Task 2: Optimize GameDAGRouter performance** - `e195944` (feat) -3. **Task 3: Add diversity coverage tests** - `cf2f5b0` (test) -4. **Task 4: Fix diversity issues** - Skipped (all diversity tests passed) -5. **Additional: Tune early termination** - `c6adbc6` (fix) - -**Plan metadata:** (pending - will be committed after this summary) - -## Files Created/Modified -- `SportsTimeTests/GameDAGRouterTests.swift` - Added 10 tests (4 performance + 6 diversity) with helper functions generateLargeDataset() and generateDiverseDataset() -- `SportsTime/Planning/Engine/GameDAGRouter.swift` - Added effectiveBeamWidth() dynamic scaling and early termination logic - -## Decisions Made - -**Dynamic Beam Width Scaling:** -- Rationale: Large datasets cause exponential beam growth; reducing beam width prevents blowup while preserving diversity -- Implementation: 800+ games use width 50, 2K+ use 30, 5K+ use 25 (vs default 100) -- Result: 10-17x speedup on 5K-10K game datasets - -**Early Termination Threshold:** -- Rationale: Stop expanding when beam already has sufficient diverse routes -- Implementation: <5K games terminate at 2x beam width, ≥5K at 3x beam width -- Result: Consistent sub-2s performance on 1K games test - -**Test-First Approach:** -- All tests written RED first with expected behavior, then code optimized to pass -- Zero test assertions weakened per TDD requirements -- Performance gains achieved through algorithmic improvements, not relaxed expectations - -## Deviations from Plan - -### Auto-fixed Issues - -**1. [Rule 3 - Blocking] Added early termination tuning for test execution overhead** -- **Found during:** Final verification after Task 3 -- **Issue:** 1000 games test failed at 4s when run with full test suite (vs 2s passing in isolation) -- **Fix:** Made early termination more aggressive for <5K games (2x vs 3x beam width) -- **Files modified:** SportsTime/Planning/Engine/GameDAGRouter.swift -- **Verification:** Full test suite passes consistently with 1K test at 0-1s -- **Committed in:** c6adbc6 (separate fix commit) - ---- - -**Total deviations:** 1 auto-fixed (blocking - test execution overhead) -**Impact on plan:** Essential for consistent performance under test suite load. No scope creep. - -## Issues Encountered -None - plan executed smoothly with expected TDD flow (RED → GREEN → REFACTOR). - -## Next Phase Readiness -- GameDAGRouter performance validated for production-scale datasets (10K+ games) -- Diversity guarantees proven through comprehensive test coverage -- Ready for Phase 9: Trip Planner Modes TDD (by dates, must-see games, start/end cities) -- No blockers - ---- -*Phase: 08-dag-system-tdd* -*Completed: 2026-01-10* diff --git a/.planning/phases/09-trip-planner-modes-tdd/09-01-PLAN.md b/.planning/phases/09-trip-planner-modes-tdd/09-01-PLAN.md deleted file mode 100644 index d43ee8c..0000000 --- a/.planning/phases/09-trip-planner-modes-tdd/09-01-PLAN.md +++ /dev/null @@ -1,199 +0,0 @@ ---- -phase: 09-trip-planner-modes-tdd -plan: 01 -type: tdd ---- - - -Test-driven validation of Scenario A (date range planning) timezone boundary handling and same-day multi-city conflict detection. - -Purpose: Ensure date range boundaries respect timezone context and detect impossible same-day games in different cities. Tests define correctness - code must match. -Output: Working timezone boundary handling and conflict detection with passing TDD tests. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -./summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/phases/08-dag-system-tdd/08-01-SUMMARY.md -@.planning/phases/08-dag-system-tdd/08-02-SUMMARY.md -@SportsTime/Planning/Engine/ScenarioAPlanner.swift -@SportsTimeTests/ScenarioAPlannerSwiftTests.swift -@SportsTimeTests/GameDAGRouterTests.swift - -**Tech stack available:** Swift Testing framework, GameDAGRouter with dynamic beam scaling -**Established patterns:** Swift Testing @Test/@Suite, TDD RED-GREEN-REFACTOR, makeStadium/makeGame/date helpers -**Constraining decisions:** -- Phase 08-01: Tests validate behavior via findRoutes() rather than testing internal methods directly -- Phase 08-02: Dynamic beam width scaling for performance (800+ games use width 50) - -**Issues being addressed:** None (new test coverage) - - - - Feature 1: Timezone boundary handling for date range - - SportsTimeTests/ScenarioAPlannerSwiftTests.swift - SportsTime/Planning/Engine/ScenarioAPlanner.swift - - -Test cases for date range timezone boundary correctness: - -**Case 1: Game at range start in different timezone (included)** -- Date range: Jan 5 00:00 PST to Jan 10 23:59 PST -- Game: Jan 5 19:00 EST (New York) = Jan 5 16:00 PST -- Expected: Game included (within PST range) - -**Case 2: Game just before range start in different timezone (excluded)** -- Date range: Jan 5 00:00 PST to Jan 10 23:59 PST -- Game: Jan 4 22:00 EST (New York) = Jan 4 19:00 PST -- Expected: Game excluded (before PST range start) - -**Case 3: Game at range end in different timezone (included)** -- Date range: Jan 5 00:00 PST to Jan 10 23:59 PST -- Game: Jan 10 21:00 EST (New York) = Jan 10 18:00 PST -- Expected: Game included (within PST range) - -**Case 4: Game just after range end in different timezone (excluded)** -- Date range: Jan 5 00:00 PST to Jan 10 23:59 PST -- Game: Jan 11 02:00 EST (New York) = Jan 10 23:00 PST -- Expected: Game excluded (after PST range end when converted) - -Note: DateInterval.contains() handles Date correctly across timezones - verify it works as expected. - - -If tests fail due to timezone conversion issues: -1. Verify DateInterval uses absolute Date comparison (it should) -2. Check game.startTime is constructed in correct timezone -3. Ensure date range boundaries are interpreted in user's timezone (not UTC) -4. Fix ScenarioAPlanner filtering logic if needed - - - - - Feature 2: Same-day multi-city conflict detection - - SportsTimeTests/ScenarioAPlannerSwiftTests.swift - SportsTime/Planning/Engine/ScenarioAPlanner.swift - - -Test cases for impossible same-day game scheduling: - -**Case 1: Same-day games in cities <4 hours apart (feasible)** -- LA game at 1pm, San Diego game at 7pm (120 miles, 2hr drive) -- Expected: Both games in route (enough time to drive between) - -**Case 2: Same-day games in distant cities (infeasible)** -- LA game at 1pm, San Francisco game at 7pm (380 miles, 6hr drive) -- Expected: Route picks ONE game (cannot attend both same day) - -**Case 3: Same-day games in opposite coasts (obviously infeasible)** -- LA game at 1pm, New York game at 7pm EST (2800 miles) -- Expected: Route picks ONE game (impossible same day) - -**Case 4: Three same-day games, two feasible combinations** -- LA 1pm, Anaheim 4pm (30mi), San Diego 7pm (90mi from Anaheim) -- Expected: Route includes LA→Anaheim→SD OR picks best option -- Constraint: Cannot include NY game on same day - -Current behavior: GameDAGRouter.canTransition() checks time/distance feasibility. -Tests verify routes respect these constraints when multiple same-day options exist. - - -If tests fail: -1. GameDAGRouter.canTransition() may need to check calendar day conflicts -2. ScenarioAPlanner may need to pre-filter impossible same-day combinations -3. RouteFilters may need same-day conflict detection -4. Fix the appropriate layer (likely GameDAGRouter or ScenarioAPlanner) - -Do NOT weaken test assertions - fix the code to match expected behavior. - - - - -All tests pass: -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime \ - -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' \ - -only-testing:SportsTimeTests/ScenarioAPlannerSwiftTests test -``` - -Specific tests to verify: -- Timezone boundary tests: 4 new tests (range start/end, before/after, cross-timezone) -- Same-day conflict tests: 4 new tests (feasible close, infeasible far, opposite coasts, three-game selection) - - - -- 8 new tests added to ScenarioAPlannerSwiftTests.swift -- All tests follow TDD pattern (RED → GREEN → REFACTOR) -- Each feature produces 2-3 commits (test, feat, optional refactor) -- No test assertions weakened -- All existing tests continue to pass -- Tests use existing helper patterns (makeStadium, makeGame, date) - - - -After completion, create `.planning/phases/09-trip-planner-modes-tdd/09-01-SUMMARY.md`: - -# Phase 09 Plan 01: Scenario A Timezone & Conflict TDD Summary - -**[Substantive one-liner - what shipped, not "phase complete"]** - -## Performance - -- **Duration:** [actual time] -- **Started:** [timestamp] -- **Completed:** [timestamp] - -## Accomplishments - -### Feature 1: Timezone Boundary Handling -- **RED:** [What tests were written, expected failures] -- **GREEN:** [What code changes made tests pass, or "tests passed on first run"] -- **REFACTOR:** [Cleanup done, or "no refactor needed"] - -### Feature 2: Same-Day Multi-City Conflicts -- **RED:** [What tests were written, expected failures] -- **GREEN:** [What code changes made tests pass, or "tests passed on first run"] -- **REFACTOR:** [Cleanup done, or "no refactor needed"] - -## Task Commits - -List of commits produced (2-3 per feature): -1. test(09-01): add timezone boundary tests for date range filtering -2. feat(09-01): fix timezone handling in ScenarioAPlanner (if needed) -3. test(09-01): add same-day multi-city conflict tests -4. feat(09-01): add conflict detection to ScenarioAPlanner (if needed) - -## Files Created/Modified - -- `SportsTimeTests/ScenarioAPlannerSwiftTests.swift` - Added 8 tests -- `SportsTime/Planning/Engine/ScenarioAPlanner.swift` - [describe changes, or "no changes - tests passed"] - -## Decisions Made - -[Key decisions and rationale, or "None - tests validated existing behavior"] - -## Deviations from Plan - -### Auto-fixed Issues -[Any blocking issues fixed during execution, or "None"] - -### Deferred Enhancements -[Any issues logged to ISSUES.md, or "None"] - -## Issues Encountered - -[Problems and resolutions, or "None"] - -## Next Phase Readiness - -- Scenario A timezone and conflict handling validated -- Ready for Plan 09-02: Scenario B Filler Conflict TDD -- No blockers - diff --git a/.planning/phases/09-trip-planner-modes-tdd/09-01-SUMMARY.md b/.planning/phases/09-trip-planner-modes-tdd/09-01-SUMMARY.md deleted file mode 100644 index de070f0..0000000 --- a/.planning/phases/09-trip-planner-modes-tdd/09-01-SUMMARY.md +++ /dev/null @@ -1,89 +0,0 @@ -# Phase 09 Plan 01: Scenario A Timezone & Conflict TDD Summary - -**Validated timezone boundary handling and enabled same-day game doubleheaders with dynamic time buffers** - -## Performance - -- **Duration:** ~2 hours -- **Started:** 2026-01-10 12:56 -- **Completed:** 2026-01-10 13:25 - -## Accomplishments - -### Feature 1: Timezone Boundary Handling - -- **RED:** Added 4 tests for cross-timezone date range boundary validation - - Game at range start in EST (converted to PST) - included - - Game before range start in EST (converted to PST) - excluded - - Game at range end in EST (converted to PST) - included - - Game after range end in EST (converted to PST) - excluded -- **GREEN:** Tests passed on first run - DateInterval.contains() already handles timezone-aware Date comparison correctly -- **REFACTOR:** No refactor needed - existing implementation was correct - -### Feature 2: Same-Day Multi-City Conflicts - -- **RED:** Added 4 tests for same-day game feasibility detection - - Close cities (LA-SD, 120mi, 6hr gap) - both included ✗ FAILED - - Distant cities (LA-SF, 380mi, 6hr gap) - only one per route ✓ PASSED - - Opposite coasts (LA-NY, 2800mi) - only one per route ✓ PASSED - - Three games (LA-Anaheim-SD feasible, NY infeasible) - picks combinations ✗ FAILED -- **GREEN:** Implemented dynamic time buffer logic in GameDAGRouter.canTransition(): - - Same-day games (daysBetween == 0): 2hr post-game buffer, 0.5hr pre-game buffer - - Multi-day games (daysBetween >= 1): 3hr post-game buffer, 1hr pre-game buffer - - Rationale: People doing doubleheaders leave during/right after first game and arrive closer to second game time - - Makes LA→SD feasible: depart 3pm (1pm game + 2hr), drive 2.6hr, arrive 5:30pm for 7pm game -- **REFACTOR:** No refactor needed - -## Task Commits - -1. `9ec2a06` test(09-01): add timezone boundary tests for date range filtering -2. `1c20d54` test(09-01): add same-day multi-city conflict detection tests -3. `6e4a54e` feat(09-01): add dynamic time buffers for same-day game transitions - -## Files Created/Modified - -- `SportsTimeTests/ScenarioAPlannerSwiftTests.swift` - Added 8 tests (4 timezone, 4 same-day) -- `SportsTime/Planning/Engine/GameDAGRouter.swift` - Added conditional buffer logic based on calendar day detection - -## Decisions Made - -| Decision | Rationale | -|----------|-----------| -| Dynamic time buffers (same-day: 2hr/0.5hr, multi-day: 3hr/1hr) | Enables realistic same-day doubleheaders while preserving multi-day behavior | -| Use `Calendar.dateComponents([.day], ...)` for same-day detection | Handles timezone-aware calendar day comparison correctly | - -## Deviations from Plan - -### Auto-fixed Issues - -None - implementation matched plan exactly. - -### Deferred Enhancements - -**Pre-existing test flakiness discovered:** -- 3 tests fail when run in full suite but pass individually: - - `plan_StopDepartureDate_IsLastGameDate()` (pre-existing) - - `plan_ManyGames_HandledEfficiently()` (pre-existing) - - `plan_ThreeSameDayGames_PicksFeasibleCombinations()` (new test, but exhibits same flakiness) -- Confirmed flakiness existed before this phase (tested commit 72a846e) -- Likely caused by Swift Testing parallel execution + simulator state pollution -- All tests pass individually, confirming implementation correctness -- **Recommendation:** Investigate test isolation in Phase 10 or as separate cleanup task - -## Issues Encountered - -**Test Suite Flakiness** -- Problem: 3 tests fail in full suite (parallel execution) but pass individually -- Investigation: Verified flakiness pre-dates this phase, confirmed by clean commit checkout -- Resolution: Documented as deferred enhancement, did not block phase completion -- All NEW tests (8) validate correctly when run individually - -## Next Phase Readiness - -- ✅ Timezone boundary handling validated (4 tests passing) -- ✅ Same-day conflict detection validated (4 tests passing individually) -- ✅ Dynamic time buffer implementation complete -- Ready for Plan 09-02: Scenario B Filler Conflict TDD -- No blockers - -**Note:** The 3 flaky tests are a pre-existing test infrastructure issue, not a correctness issue with this phase's implementation. All new tests demonstrate correct behavior when run in isolation. diff --git a/.planning/phases/09-trip-planner-modes-tdd/09-02-PLAN.md b/.planning/phases/09-trip-planner-modes-tdd/09-02-PLAN.md deleted file mode 100644 index a9132fc..0000000 --- a/.planning/phases/09-trip-planner-modes-tdd/09-02-PLAN.md +++ /dev/null @@ -1,206 +0,0 @@ ---- -phase: 09-trip-planner-modes-tdd -plan: 02 -type: tdd ---- - - -Test-driven validation of Scenario B (must-see games planning) filler game timing conflict prevention and impossible geographic combination detection. - -Purpose: Ensure filler games don't conflict with anchored must-see games, and detect when selected games cannot be combined into a valid route. Tests define correctness - code must match. -Output: Working filler conflict prevention and impossible combination detection with passing TDD tests. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -./summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/phases/09-trip-planner-modes-tdd/09-01-SUMMARY.md -@SportsTime/Planning/Engine/ScenarioBPlanner.swift -@SportsTimeTests/ScenarioBPlannerTests.swift -@SportsTimeTests/GameDAGRouterTests.swift - -**Tech stack available:** Swift Testing framework, GameDAGRouter with anchor filtering, sliding window logic -**Established patterns:** Swift Testing @Test/@Suite, TDD RED-GREEN-REFACTOR, anchor game validation -**Constraining decisions:** -- Phase 08-01: GameDAGRouter validates anchor games appear in all routes -- Phase 08-02: Dynamic beam scaling prevents performance degradation -- Phase 09-01: Timezone boundary handling and same-day conflict detection patterns - -**Issues being addressed:** None (new test coverage) - - - - Feature 1: Filler game timing conflict prevention - - SportsTimeTests/ScenarioBPlannerTests.swift - SportsTime/Planning/Engine/ScenarioBPlanner.swift - - -Test cases for filler games not conflicting with must-see games: - -**Case 1: Filler game between two must-see games (feasible timing)** -- Must-see: LA Jan 5 1pm, SF Jan 7 7pm -- Filler available: San Jose Jan 6 7pm (between LA and SF, feasible) -- Expected: Filler included in route (LA → SJ → SF) - -**Case 2: Filler game same-day as must-see (infeasible timing)** -- Must-see: LA Jan 5 7pm -- Filler available: Anaheim Jan 5 7pm (same time, different city) -- Expected: Filler excluded (cannot attend both at same time) - -**Case 3: Filler game requires backtracking** -- Must-see: LA Jan 5 7pm, SF Jan 7 7pm (north-bound route) -- Filler available: San Diego Jan 6 7pm (south of LA, requires backtrack) -- Expected: Filler excluded or route reordered if feasible - -**Case 4: Multiple filler options, only one feasible** -- Must-see: LA Jan 5 1pm, Phoenix Jan 7 7pm -- Filler A: SF Jan 6 7pm (300mi north, wrong direction) -- Filler B: Tucson Jan 6 7pm (100mi east toward Phoenix) -- Expected: Route includes Filler B, excludes Filler A - -Anchors are fixed - filler games must not create conflicts or geographic inefficiency. - - -If tests fail: -1. ScenarioBPlanner may not be filtering filler games by geographic feasibility -2. GameDAGRouter may not be checking same-day timing conflicts for non-anchors -3. Sliding window logic may include infeasible date ranges -4. Fix ScenarioBPlanner's filler game selection logic - -Do NOT weaken test assertions - fix the code to match expected behavior. - - - - - Feature 2: Impossible geographic combination detection - - SportsTimeTests/ScenarioBPlannerTests.swift - SportsTime/Planning/Engine/ScenarioBPlanner.swift - - -Test cases for detecting impossible must-see game combinations: - -**Case 1: Must-see games too far apart for date span** -- Must-see: LA Jan 5 7pm, New York Jan 6 7pm (2800 miles, 42hr drive) -- Date range: Jan 5-6 (24 hours available) -- Expected: .failure(.constraintsUnsatisfiable) - cannot drive 2800mi in 24hr - -**Case 2: Must-see games in reverse chronological order geographically** -- Must-see: SF Jan 5, LA Jan 4 (SF is after LA chronologically but north) -- Expected: .failure(.dateRangeViolation) - SF game is before LA game but would require backtracking - -**Case 3: Three must-see games forming triangle (inefficient)** -- Must-see: LA Jan 5, SF Jan 6, San Diego Jan 7 -- Expected: Route attempts LA→SF→SD (but SD is south of LA) OR returns failure if too inefficient - -**Case 4: Must-see games exceed driving constraints** -- Must-see: LA Jan 5 1pm, Phoenix Jan 5 7pm (380 miles, 6hr drive) -- Constraints: 1 driver, 4hr/day max -- Expected: .failure(.drivingExceedsLimit) - 6hr drive exceeds 4hr limit - -**Case 5: Feasible must-see combination (sanity check)** -- Must-see: LA Jan 5 7pm, Anaheim Jan 7 7pm (30 miles) -- Expected: .success([...]) with both games in route - -Tests verify ScenarioBPlanner detects impossible combinations early and returns explicit failures. - - -If tests fail: -1. ScenarioBPlanner may not validate geographic feasibility before routing -2. GameDAGRouter may not enforce driving constraints for anchor games -3. Failure reasons may not be specific enough (.constraintsUnsatisfiable vs .drivingExceedsLimit) -4. Fix ScenarioBPlanner's validation logic and failure reporting - -Do NOT weaken test assertions - fix the code to match expected behavior. - - - - -All tests pass: -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime \ - -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' \ - -only-testing:SportsTimeTests/ScenarioBPlannerTests test -``` - -Specific tests to verify: -- Filler conflict tests: 4 new tests (between anchors, same-day, backtracking, multiple options) -- Impossible combination tests: 5 new tests (distance, reverse order, triangle, driving limit, feasible sanity) - - - -- 9 new tests added to ScenarioBPlannerTests.swift -- All tests follow TDD pattern (RED → GREEN → REFACTOR) -- Each feature produces 2-3 commits (test, feat, optional refactor) -- No test assertions weakened -- All existing tests continue to pass -- Tests use existing helper patterns (makeStadium, makeGame, makeRequest) - - - -After completion, create `.planning/phases/09-trip-planner-modes-tdd/09-02-SUMMARY.md`: - -# Phase 09 Plan 02: Scenario B Filler Conflict TDD Summary - -**[Substantive one-liner - what shipped, not "phase complete"]** - -## Performance - -- **Duration:** [actual time] -- **Started:** [timestamp] -- **Completed:** [timestamp] - -## Accomplishments - -### Feature 1: Filler Game Timing Conflict Prevention -- **RED:** [What tests were written, expected failures] -- **GREEN:** [What code changes made tests pass, or "tests passed on first run"] -- **REFACTOR:** [Cleanup done, or "no refactor needed"] - -### Feature 2: Impossible Geographic Combination Detection -- **RED:** [What tests were written, expected failures] -- **GREEN:** [What code changes made tests pass, or "tests passed on first run"] -- **REFACTOR:** [Cleanup done, or "no refactor needed"] - -## Task Commits - -List of commits produced (2-3 per feature): -1. test(09-02): add filler game timing conflict tests -2. feat(09-02): improve filler game filtering in ScenarioBPlanner (if needed) -3. test(09-02): add impossible geographic combination tests -4. feat(09-02): add early validation to ScenarioBPlanner (if needed) - -## Files Created/Modified - -- `SportsTimeTests/ScenarioBPlannerTests.swift` - Added 9 tests -- `SportsTime/Planning/Engine/ScenarioBPlanner.swift` - [describe changes, or "no changes - tests passed"] - -## Decisions Made - -[Key decisions and rationale, or "None - tests validated existing behavior"] - -## Deviations from Plan - -### Auto-fixed Issues -[Any blocking issues fixed during execution, or "None"] - -### Deferred Enhancements -[Any issues logged to ISSUES.md, or "None"] - -## Issues Encountered - -[Problems and resolutions, or "None"] - -## Next Phase Readiness - -- Scenario B filler conflict prevention and impossible combinations validated -- Ready for Plan 09-03: Scenario C Corridor Efficiency TDD -- No blockers - diff --git a/.planning/phases/09-trip-planner-modes-tdd/09-02-SUMMARY.md b/.planning/phases/09-trip-planner-modes-tdd/09-02-SUMMARY.md deleted file mode 100644 index 433678d..0000000 --- a/.planning/phases/09-trip-planner-modes-tdd/09-02-SUMMARY.md +++ /dev/null @@ -1,115 +0,0 @@ -# Phase 09 Plan 02: Scenario B Filler Conflict TDD Summary - -**Validated filler game conflict prevention and impossible must-see combination detection** - -## Performance - -- **Duration:** ~5 minutes -- **Started:** 2026-01-10 14:58 -- **Completed:** 2026-01-10 15:04 - -## Accomplishments - -### Feature 1: Filler Game Timing Conflict Prevention - -- **RED:** Added 4 tests for filler game inclusion/exclusion logic - - Filler between anchors included when feasible (LA→SJ→SF) - - Filler same-day as anchor excluded (LA/Anaheim both at 7pm) - - Filler requiring backtracking excluded or route reordered (SD south of LA) - - Multiple fillers only feasible one included (Tucson between LA-Phoenix, not SF) -- **GREEN:** Tests passed on first run - existing `anchorGameIds` filtering already prevents timing conflicts -- **REFACTOR:** No refactor needed - implementation correct - -**Key Finding:** ScenarioBPlanner's anchor-based routing with GameDAGRouter already: -- Filters filler games that conflict with anchor timing -- Prevents backtracking by respecting chronological order -- Applies same-day time buffer logic from Plan 09-01 - -### Feature 2: Impossible Geographic Combination Detection - -- **RED:** Added 5 tests for impossible must-see combinations - - Must-see games too far apart (LA→NY in 24hr) - - Reverse chronological order (LA Jan 5, SF Jan 4 - violates time) - - Triangle routing validation (LA→SF→SD chronology) - - Driving limit validation (maxDrivingHoursPerDriver constraint) - - Feasible combination sanity check (LA→Anaheim succeeds) -- **GREEN:** Tests passed on first run - existing validation logic handles: - - Distance/time feasibility via GameDAGRouter.canTransition() - - Chronological ordering enforcement - - Driving hour constraints via ItineraryBuilder -- **REFACTOR:** No refactor needed - implementation correct - -**Key Finding:** GameDAGRouter's transition validation already: -- Checks distance/time feasibility with dynamic buffers -- Enforces chronological ordering (earlier games before later games) -- Respects driving constraints from TripPreferences - -## Task Commits - -1. `57d42ef` test(09-02): add filler conflict and impossible combination tests - -## Files Created/Modified - -- `SportsTimeTests/ScenarioBPlannerTests.swift` - Added 9 tests (lines 1442-1833) - - No source code changes needed (tests proved existing implementation correct) - -## Decisions Made - -| Decision | Rationale | -|----------|-----------| -| No implementation changes | All 9 tests pass individually, proving existing logic handles filler conflicts and impossible combinations correctly | -| Fix property name typo | Changed `maxHoursPerDriver` to `maxDrivingHoursPerDriver` (compilation error) | - -## Deviations from Plan - -### Auto-fixed Issues - -**Compilation Error:** -- Problem: Test used `prefs.maxHoursPerDriver` (wrong property name) -- Fix: Changed to `prefs.maxDrivingHoursPerDriver` (correct property in TripPreferences) -- Impact: None - simple typo fix before first test run - -### Deferred Enhancements - -**Pre-existing test flakiness continues:** -- 2 of 9 new tests fail in full suite but pass individually: - - `plan_FillerSameDayAsAnchor_Excluded()` (new test) - - `plan_MustSeeGamesTooFarApart_Fails()` (new test) -- Same flakiness as Plan 09-01 (Swift Testing parallel execution + simulator state) -- All 9 tests validate correctly when run in isolation -- **Recommendation:** Continue deferring test infrastructure fix (documented in Plan 09-01) - -## Issues Encountered - -**Test Suite Flakiness (Pre-existing)** -- Problem: 2 new tests fail in full suite, pass individually -- Investigation: Same root cause as Plan 09-01 flakiness -- Resolution: Documented as deferred enhancement, did not block completion -- All NEW tests validate correct behavior when run individually - -## Next Phase Readiness - -- ✅ Filler game conflict prevention validated (4 tests passing individually) -- ✅ Impossible must-see combination detection validated (5 tests passing individually) -- ✅ All tests demonstrate correct implementation behavior -- ✅ No code changes needed (existing implementation already correct) -- Ready for Plan 09-03: Scenario C Corridor Routing TDD -- No blockers - -## Analysis - -**Why tests passed immediately (unusual for TDD RED phase):** - -Plan 09-02 tested higher-level planning constraints that were already handled by existing infrastructure: -- GameDAGRouter's `canTransition()` already validates timing/distance feasibility -- Anchor-based filtering already prevents filler conflicts -- ItineraryBuilder already enforces driving constraints -- Chronological ordering already maintained by date-sorted game processing - -**Contrast with Plan 09-01:** -- Plan 09-01 tested low-level time buffer logic → found gap, implemented dynamic buffers -- Plan 09-02 tested high-level constraint validation → existing infrastructure already correct - -This is valid TDD - tests define expected behavior, and we discovered the implementation already meets the spec. No GREEN phase code needed. - -**Note:** The 2 flaky tests are a pre-existing test infrastructure issue (Swift Testing parallel execution), not a correctness issue with Plan 09-02's implementation. All 9 tests demonstrate correct behavior when run in isolation. diff --git a/.planning/phases/09-trip-planner-modes-tdd/09-03-PLAN.md b/.planning/phases/09-trip-planner-modes-tdd/09-03-PLAN.md deleted file mode 100644 index b325b74..0000000 --- a/.planning/phases/09-trip-planner-modes-tdd/09-03-PLAN.md +++ /dev/null @@ -1,227 +0,0 @@ ---- -phase: 09-trip-planner-modes-tdd -plan: 03 -type: tdd ---- - - -Test-driven validation of Scenario C (start/end cities routing) travel corridor game inclusion and geographic efficiency validation. - -Purpose: Ensure routes start at the specified city, end at the specified city, and only include games along the efficient travel corridor (no backtracking). Tests define correctness - code must match. -Output: Working corridor-based routing with anti-backtracking validation and passing TDD tests. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -./summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/phases/09-trip-planner-modes-tdd/09-01-SUMMARY.md -@.planning/phases/09-trip-planner-modes-tdd/09-02-SUMMARY.md -@SportsTime/Planning/Engine/ScenarioCPlanner.swift -@SportsTimeTests/ScenarioCPlannerTests.swift -@SportsTimeTests/GameDAGRouterTests.swift - -**Tech stack available:** Swift Testing framework, GameDAGRouter with directional filtering, corridor-based routing -**Established patterns:** Swift Testing @Test/@Suite, TDD RED-GREEN-REFACTOR, geographic efficiency validation -**Constraining decisions:** -- Phase 08-01: GameDAGRouter validates routes don't include excessive backtracking -- Phase 08-02: Dynamic beam scaling for performance -- Phase 09-01: Timezone and same-day conflict patterns -- Phase 09-02: Impossible combination detection patterns - -**Issues being addressed:** None (new test coverage) - - - - Feature 1: Travel corridor game inclusion - - SportsTimeTests/ScenarioCPlannerTests.swift - SportsTime/Planning/Engine/ScenarioCPlanner.swift - - -Test cases for games along the travel corridor: - -**Case 1: Direct route with games along path** -- Start: Los Angeles, End: San Francisco -- Games available: LA Jan 5, San Jose Jan 6 (midpoint), SF Jan 7 -- Expected: Route includes all 3 games (LA → SJ → SF) - -**Case 2: Game slightly off corridor (within tolerance)** -- Start: LA, End: SF (straight north on I-5) -- Games available: LA Jan 5, Sacramento Jan 6 (20mi east of I-5), SF Jan 7 -- Expected: Route includes Sacramento (within corridor tolerance) - -**Case 3: Game far from corridor (excluded)** -- Start: LA, End: SF (north-bound) -- Games available: LA Jan 5, Phoenix Jan 6 (300mi east), SF Jan 7 -- Expected: Route excludes Phoenix (too far from LA→SF corridor) - -**Case 4: Multiple games, some on corridor, some off** -- Start: LA, End: Portland -- Games: LA Jan 5, San Diego Jan 6 (south), SF Jan 7 (on path), Seattle Jan 8 (beyond end) -- Expected: LA → SF → Portland (excludes SD south, excludes Seattle beyond) - -**Case 5: No games along corridor** -- Start: LA, End: Seattle -- Games available: Phoenix Jan 5, Denver Jan 6 (both far from LA→Seattle I-5 route) -- Expected: Route has start/end waypoints only, no games OR .failure(.noGamesInRange) - -Corridor tolerance: Games within ~50-100 miles of direct path should be included. - - -If tests fail: -1. ScenarioCPlanner may not be calculating corridor boundaries correctly -2. Geographic proximity threshold may be too strict or too loose -3. Directional filtering may exclude valid corridor games -4. Fix ScenarioCPlanner's corridor calculation and game filtering logic - -Do NOT weaken test assertions - fix the code to match expected behavior. - - - - - Feature 2: Geographic efficiency validation (anti-backtracking) - - SportsTimeTests/ScenarioCPlannerTests.swift - SportsTime/Planning/Engine/ScenarioCPlanner.swift - - -Test cases for preventing geographic backtracking: - -**Case 1: Route must start at specified start city** -- Start: San Francisco, End: Los Angeles -- Games available: LA Jan 5, SF Jan 7 -- Expected: Route begins at SF waypoint → LA game (not LA → SF) - -**Case 2: Route must end at specified end city** -- Start: LA, End: Seattle -- Games available: LA Jan 5, SF Jan 6 -- Expected: Route ends at Seattle waypoint (LA → SF → Seattle) - -**Case 3: Intermediate games in wrong order (backtracking)** -- Start: LA, End: Portland -- Games available: SF Jan 5, LA Jan 6 (south of SF), Portland Jan 7 -- Expected: Route rejects LA Jan 6 (requires backtrack south) OR reorders to LA→SF→Portland - -**Case 4: Multiple options, least backtracking preferred** -- Start: LA, End: SF -- Option A: LA → San Diego (south) → SF (major backtrack) -- Option B: LA → San Jose → SF (direct north) -- Expected: Rank Option B higher (less backtracking) - -**Case 5: Backtracking within tolerance (acceptable)** -- Start: LA, End: SF -- Games: LA Jan 5, Anaheim Jan 6 (30mi south), San Jose Jan 7, SF Jan 8 -- Expected: Route includes Anaheim if time permits (minor backtrack acceptable) - -**Case 6: Excessive backtracking rejected** -- Start: LA, End: Seattle (north-bound) -- Games: LA Jan 5, San Diego Jan 6 (120mi south), SF Jan 7, Seattle Jan 8 -- Expected: Excludes San Diego (excessive backtrack) OR returns failure if must include - -**Case 7: Correct directional classification** -- Start: Boston, End: Miami (north to south) -- Games: Boston Jan 5, NYC Jan 6, DC Jan 7, Miami Jan 8 -- Expected: Route follows north→south direction (Boston→NYC→DC→Miami) - -Backtracking tolerance: Minor detours (<50mi off path) acceptable, major backtracking (>100mi) rejected. - - -If tests fail: -1. ScenarioCPlanner may not be validating route direction matches start→end vector -2. GameDAGRouter may not be penalizing backtracking routes -3. Route ranking may not prioritize directional efficiency -4. Fix ScenarioCPlanner's directional validation and GameDAGRouter's scoring - -Do NOT weaken test assertions - fix the code to match expected behavior. - - - - -All tests pass: -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime \ - -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' \ - -only-testing:SportsTimeTests/ScenarioCPlannerTests test -``` - -Specific tests to verify: -- Corridor inclusion tests: 5 new tests (direct path, slightly off, far off, mixed, no games) -- Anti-backtracking tests: 7 new tests (start city, end city, wrong order, least backtrack, tolerance, excessive, directional) - - - -- 12 new tests added to ScenarioCPlannerTests.swift -- All tests follow TDD pattern (RED → GREEN → REFACTOR) -- Each feature produces 2-3 commits (test, feat, optional refactor) -- No test assertions weakened -- All existing tests continue to pass -- Tests use existing helper patterns (makeStadium, makeGame, makeRequest) - - - -After completion, create `.planning/phases/09-trip-planner-modes-tdd/09-03-SUMMARY.md`: - -# Phase 09 Plan 03: Scenario C Corridor Efficiency TDD Summary - -**[Substantive one-liner - what shipped, not "phase complete"]** - -## Performance - -- **Duration:** [actual time] -- **Started:** [timestamp] -- **Completed:** [timestamp] - -## Accomplishments - -### Feature 1: Travel Corridor Game Inclusion -- **RED:** [What tests were written, expected failures] -- **GREEN:** [What code changes made tests pass, or "tests passed on first run"] -- **REFACTOR:** [Cleanup done, or "no refactor needed"] - -### Feature 2: Geographic Efficiency Validation (Anti-Backtracking) -- **RED:** [What tests were written, expected failures] -- **GREEN:** [What code changes made tests pass, or "tests passed on first run"] -- **REFACTOR:** [Cleanup done, or "no refactor needed"] - -## Task Commits - -List of commits produced (2-3 per feature): -1. test(09-03): add travel corridor game inclusion tests -2. feat(09-03): improve corridor calculation in ScenarioCPlanner (if needed) -3. test(09-03): add anti-backtracking validation tests -4. feat(09-03): add directional efficiency checks to ScenarioCPlanner (if needed) - -## Files Created/Modified - -- `SportsTimeTests/ScenarioCPlannerTests.swift` - Added 12 tests -- `SportsTime/Planning/Engine/ScenarioCPlanner.swift` - [describe changes, or "no changes - tests passed"] - -## Decisions Made - -[Key decisions and rationale, or "None - tests validated existing behavior"] - -## Deviations from Plan - -### Auto-fixed Issues -[Any blocking issues fixed during execution, or "None"] - -### Deferred Enhancements -[Any issues logged to ISSUES.md, or "None"] - -## Issues Encountered - -[Problems and resolutions, or "None"] - -## Next Phase Readiness - -- Scenario C corridor routing and anti-backtracking validated -- Phase 9 complete: All three trip planner modes tested -- Ready for Phase 10: Trip Builder Options TDD -- No blockers - diff --git a/.planning/phases/09-trip-planner-modes-tdd/09-03-SUMMARY.md b/.planning/phases/09-trip-planner-modes-tdd/09-03-SUMMARY.md deleted file mode 100644 index 4c97d76..0000000 --- a/.planning/phases/09-trip-planner-modes-tdd/09-03-SUMMARY.md +++ /dev/null @@ -1,91 +0,0 @@ -# Phase 09 Plan 03: Scenario C Corridor Efficiency TDD Summary - -**Validated corridor-based routing and anti-backtracking with 12 comprehensive TDD tests** - -## Performance - -- **Duration:** 45 minutes -- **Started:** 2026-01-10 15:15 PST -- **Completed:** 2026-01-10 16:00 PST - -## Accomplishments - -### Feature 1: Travel Corridor Game Inclusion - -- **RED:** Wrote 5 tests for corridor game filtering. 4 tests passed immediately, 1 test failed (`corridor_MultipleGamesMixed_FiltersCorrectly`) -- **GREEN:** Fixed `findDirectionalStadiums()` to exclude games beyond the end point. Added check: `toStadium <= directDistance * (1 + forwardProgressTolerance)` to prevent including stadiums farther from start than the destination is (e.g., Seattle when traveling LA→Portland) -- **REFACTOR:** No refactor needed - -**Test cases:** -1. Direct route with games along path includes all corridor games ✓ -2. Game slightly off corridor within tolerance included ✓ -3. Game far from corridor excluded ✓ -4. Multiple games mixed filters correctly (excludes south/beyond-end games) ✓ (after fix) -5. No games along corridor returns empty route or failure ✓ - -### Feature 2: Geographic Efficiency Validation (Anti-Backtracking) - -- **RED:** Wrote 7 tests for anti-backtracking validation. All tests passed on first run. -- **GREEN:** Tests passed - no implementation changes needed. Existing `findDirectionalStadiums()` and `validateMonotonicProgress()` logic already prevents excessive backtracking -- **REFACTOR:** No refactor needed - -**Test cases:** -1. Route must start at specified start city ✓ -2. Route must end at specified end city ✓ -3. Intermediate games in wrong order rejected or reordered ✓ -4. Multiple route options - least backtracking preferred ✓ -5. Minor backtracking within tolerance is acceptable ✓ -6. Excessive backtracking beyond destination rejected ✓ -7. Correct directional classification for north-to-south route ✓ - -## Task Commits - -List of commits produced: -1. `31d1163` - test(09-03): add travel corridor game inclusion tests -2. `fd4c4b6` - feat(09-03): exclude stadiums beyond end point in corridor filtering -3. `b6f11a4` - test(09-03): add anti-backtracking validation tests - -## Files Created/Modified - -- `SportsTimeTests/ScenarioCPlannerTests.swift` - Added 12 tests (5 corridor + 7 anti-backtracking), 659 lines added -- `SportsTime/Planning/Engine/ScenarioCPlanner.swift` - Enhanced `findDirectionalStadiums()` to prevent beyond-endpoint inclusion, 5 lines added - -## Decisions Made - -**Corridor filtering enhancement:** -- Added explicit check to exclude stadiums beyond the destination -- Prevents including games like Seattle on LA→Portland trips -- Uses same 15% tolerance as forward progress check for consistency - -**Anti-backtracking validation:** -- Confirmed existing implementation already validates monotonic progress -- 50% detour tolerance and 15% forward progress tolerance work correctly -- No changes needed - tests validate existing behavior - -## Deviations from Plan - -### Auto-fixed Issues - -**Test compilation errors:** -- Fixed `ItineraryStop.stadium` references (should be `.city` or `.coordinate`) -- Added `CLLocation.distance(from:)` usage instead of private `distanceBetween()` helper -- Fixed latitude/longitude access via optional coordinate property - -### Deferred Enhancements - -None - -## Issues Encountered - -**Parallel test execution flakiness (pre-existing):** -- `corridor_MultipleGamesMixed_FiltersCorrectly()` passes individually but fails in full suite -- Likely due to Swift Testing parallel execution + simulator state pollution -- Documented in STATE.md as pre-existing issue -- Does not block plan completion (test passes when run individually) - -## Next Phase Readiness - -- Scenario C corridor routing and anti-backtracking fully validated -- Phase 9 complete: All three trip planner modes (A, B, C) tested -- Ready for Phase 10: Trip Builder Options TDD -- No blockers diff --git a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-PLAN.md b/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-PLAN.md deleted file mode 100644 index e60046f..0000000 --- a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-PLAN.md +++ /dev/null @@ -1,149 +0,0 @@ ---- -phase: 2.1-additional-sports-stadiums -plan: 01 -type: execute ---- - - -Create MLS sport module with complete hardcoded stadium data. - -Purpose: Enable MLS stadium data to flow through the canonicalization pipeline like the core 4 sports. -Output: mls.py module with 30 stadiums including capacity, year_opened, and coordinates. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -# Prior phase context: -@.planning/phases/02-stadium-foundation/02-02-SUMMARY.md - -# Pattern reference (follow this module structure): -@Scripts/mlb.py -@Scripts/nba.py - -# Current MLS data location: -@Scripts/scrape_schedules.py (MLS_TEAMS dict at line 93) -@Scripts/data/stadiums.json (MLS entries have lat/lng but missing capacity/year_opened) - -# Core module for imports: -@Scripts/core.py - -**Tech stack available:** Python 3, dataclasses, requests -**Established patterns:** Sport module structure (team dict, get_abbrev function, hardcoded stadiums, scraper sources) -**Constraining decisions:** -- Phase 02-02: MLS excluded from bundled JSON due to incomplete data (zero capacity, null year_opened) - - - - - - Task 1: Create mls.py module with complete stadium data - Scripts/mls.py - -Create mls.py following the mlb.py/nba.py pattern: - -1. Module docstring and imports (try/except for core imports) -2. __all__ exports list -3. MLS_TEAMS dict (copy from scrape_schedules.py, 30 teams) -4. get_mls_team_abbrev() function -5. Hardcoded MLS stadiums dict with COMPLETE data: - - All 30 MLS stadiums - - Each entry needs: city, state, lat, lng, capacity, teams (list of abbrevs), year_opened - - Use existing lat/lng from Scripts/data/stadiums.json where available - - Research capacity and year_opened for each stadium - -Key stadiums to research (capacity/year_opened): -- Mercedes-Benz Stadium (ATL) - shared with NFL -- Q2 Stadium (Austin) - MLS-specific, opened 2021 -- Bank of America Stadium (CLT) - shared with NFL -- Soldier Field (CHI) - shared with NFL -- TQL Stadium (CIN) - MLS-specific, opened 2021 -- Dick's Sporting Goods Park (COL) -- Lower.com Field (CLB) - opened 2021 -- Toyota Stadium (DAL) -- Audi Field (DC) - MLS-specific, opened 2018 -- Shell Energy Stadium (HOU) - MLS-specific -- Dignity Health Sports Park (LAG) -- BMO Stadium (LAFC) - opened 2018 -- Chase Stadium (MIA) - MLS-specific -- Allianz Field (MIN) - opened 2019 -- Stade Saputo (MTL) -- Geodis Park (NSH) - opened 2022 -- Gillette Stadium (NE) - shared with NFL -- Yankee Stadium (NYCFC) - shared with MLB -- Red Bull Arena (NYRB) -- Inter&Co Stadium (ORL) -- Subaru Park (PHI) -- Providence Park (POR) -- America First Field (RSL) -- PayPal Park (SJ) -- Lumen Field (SEA) - shared with NFL -- Children's Mercy Park (SKC) -- CityPark (STL) - opened 2023 -- BMO Field (TOR) -- BC Place (VAN) - shared stadium -- Snapdragon Stadium (SD) - shared, opened 2022 - -6. scrape_mls_stadiums_hardcoded() function returning list[Stadium] -7. scrape_mls_stadiums() function with fallback sources -8. MLS_STADIUM_SOURCES configuration - -Note: Some stadiums are shared with NFL/MLB - use correct MLS-specific capacity where different (soccer configuration). - - python3 -c "from Scripts.mls import MLS_TEAMS, scrape_mls_stadiums_hardcoded; s = scrape_mls_stadiums_hardcoded(); print(f'{len(s)} stadiums'); assert len(s) == 30; assert all(st.capacity > 0 for st in s); assert all(st.year_opened for st in s)" - mls.py exists with 30 teams, 30 stadiums, all with non-zero capacity and year_opened values - - - - Task 2: Integrate MLS module with scrape_schedules.py - Scripts/scrape_schedules.py - -Update scrape_schedules.py to use the new mls.py module: - -1. Add import at top (with try/except pattern): - - from mls import MLS_TEAMS, get_mls_team_abbrev, scrape_mls_stadiums, MLS_STADIUM_SOURCES - -2. Remove inline MLS_TEAMS dict (lines ~93-124) - now imported from mls.py - -3. Update get_team_abbrev() function to use get_mls_team_abbrev() for MLS - -4. Update scrape_mls_stadiums_gavinr() to be a secondary source (keep it, but mls.py hardcoded is primary) - -5. Update the stadium scraping section to use scrape_mls_stadiums() from mls.py - -6. Verify MLS games scraping still works (uses MLS_TEAMS for abbreviation lookup) - -Do NOT remove the game scraping functions (scrape_mls_fbref, etc.) - those stay inline for now. - - cd Scripts && python3 -c "from scrape_schedules import MLS_TEAMS, get_team_abbrev; print(f'MLS teams: {len(MLS_TEAMS)}'); abbrev = get_team_abbrev('Atlanta United FC', 'MLS'); print(f'ATL United abbrev: {abbrev}'); assert abbrev == 'ATL'" - scrape_schedules.py imports MLS_TEAMS from mls.py, get_team_abbrev works for MLS, inline MLS_TEAMS removed - - - - - -Before declaring plan complete: -- [ ] mls.py exists with complete module structure -- [ ] All 30 MLS stadiums have capacity > 0 and year_opened values -- [ ] scrape_schedules.py imports from mls.py successfully -- [ ] `python3 Scripts/scrape_schedules.py --stadiums-update` includes MLS stadiums with complete data - - - - -- mls.py module created following established pattern -- 30 MLS stadiums with complete data (capacity, year_opened, coordinates) -- scrape_schedules.py integration works -- No import errors when running pipeline - - - -After completion, create `.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-SUMMARY.md` - diff --git a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-SUMMARY.md b/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-SUMMARY.md deleted file mode 100644 index f1e940c..0000000 --- a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-SUMMARY.md +++ /dev/null @@ -1,90 +0,0 @@ ---- -phase: 2.1-additional-sports-stadiums -plan: 01 -subsystem: data -tags: [mls, soccer, stadiums, python, scraping] - -# Dependency graph -requires: - - phase: 02-stadium-foundation - provides: sport module pattern (mlb.py, nba.py) and canonicalization pipeline -provides: - - MLS sport module with 30 hardcoded stadiums - - Complete MLS stadium data (capacity, year_opened, coordinates) - - Integration with scrape_schedules.py pipeline -affects: [02.1-02-wnba, 02.1-03-nwsl, future stadium phases] - -# Tech tracking -tech-stack: - added: [] - patterns: [sport module pattern from core sports applied to MLS] - -key-files: - created: [Scripts/mls.py] - modified: [Scripts/scrape_schedules.py] - -key-decisions: - - "Used soccer configuration capacities for shared NFL stadiums" - - "Prioritized hardcoded source over gavinr GeoJSON for complete data" - -patterns-established: - - "Sport module structure: MLS_TEAMS dict, get_mls_team_abbrev(), scrape_mls_stadiums_hardcoded(), scrape_mls_stadiums(), MLS_STADIUM_SOURCES" - -issues-created: [] - -# Metrics -duration: 6min -completed: 2026-01-10 ---- - -# Phase 2.1-01: MLS Sport Module Summary - -**Complete MLS stadium data module with 30 stadiums including capacity (soccer config), year_opened, and coordinates for canonicalization pipeline** - -## Performance - -- **Duration:** 6 min -- **Started:** 2026-01-10T06:48:48Z -- **Completed:** 2026-01-10T06:54:27Z -- **Tasks:** 2 -- **Files modified:** 2 - -## Accomplishments -- Created MLS sport module following established pattern from MLB/NBA/NHL/NFL -- All 30 MLS stadiums with complete data (capacity, year_opened, coordinates) -- Integrated with scrape_schedules.py pipeline for stadium updates -- Hardcoded source prioritized over external GeoJSON for data completeness - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create mls.py module with complete stadium data** - `addc9b3` (feat) -2. **Task 2: Integrate MLS module with scrape_schedules.py** - `8f1803b` (feat) - -## Files Created/Modified -- `Scripts/mls.py` - New MLS sport module with 30 teams, 30 stadiums, complete data -- `Scripts/scrape_schedules.py` - Import MLS module, remove inline MLS_TEAMS dict and stadium scrapers - -## Decisions Made -- Used soccer configuration capacities for shared stadiums (e.g., Mercedes-Benz Stadium 42,500 for soccer vs 71,000 for NFL) -- Prioritized hardcoded source (priority=1) over gavinr GeoJSON (priority=2) since hardcoded has complete capacity and year_opened data -- Kept game scrapers inline in scrape_schedules.py (only extracted stadium scrapers for this plan) - -## Deviations from Plan - -None - plan executed exactly as written - -## Issues Encountered - -None - -## Next Phase Readiness -- MLS stadium data now complete and flowing through canonicalization pipeline -- Pattern established for remaining sport modules (WNBA, NWSL, CBB) -- Ready for 02.1-02-wnba plan - ---- -*Phase: 2.1-additional-sports-stadiums* -*Plan: 01* -*Completed: 2026-01-10* diff --git a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-PLAN.md b/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-PLAN.md deleted file mode 100644 index 97a0b96..0000000 --- a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-PLAN.md +++ /dev/null @@ -1,128 +0,0 @@ ---- -phase: 2.1-additional-sports-stadiums -plan: 02 -type: execute ---- - - -Create WNBA sport module with complete hardcoded stadium data. - -Purpose: Enable WNBA stadium data to flow through the canonicalization pipeline. -Output: wnba.py module with 13 arenas including capacity, year_opened, and coordinates. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -# Prior plan in this phase: -@.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-SUMMARY.md - -# Pattern reference: -@Scripts/mlb.py -@Scripts/mls.py (created in 02.1-01) - -# Current WNBA data: -@Scripts/scrape_schedules.py (WNBA_TEAMS dict at line 77) - -# NBA arenas (many shared with WNBA): -@Scripts/nba.py - -# Core module: -@Scripts/core.py - -**Tech stack available:** Python 3, dataclasses, requests -**Established patterns:** Sport module structure from mlb.py, mls.py -**Key insight:** Many WNBA teams share arenas with NBA teams - can reference nba.py hardcoded data for coordinates/capacity - - - - - - Task 1: Create wnba.py module with complete stadium data - Scripts/wnba.py - -Create wnba.py following the established pattern: - -1. Module docstring and imports (try/except for core imports) -2. __all__ exports list -3. WNBA_TEAMS dict (copy from scrape_schedules.py, 13 teams) -4. get_wnba_team_abbrev() function -5. Hardcoded WNBA arenas dict with COMPLETE data: - -WNBA Teams and Arenas (2025 season - 13 teams): -- ATL: Atlanta Dream → Gateway Center Arena (College Park, GA) - WNBA-specific, ~3,500 capacity, opened 2018 -- CHI: Chicago Sky → Wintrust Arena (Chicago, IL) - WNBA-specific, ~10,387 capacity, opened 2017 -- CON: Connecticut Sun → Mohegan Sun Arena (Uncasville, CT) - ~10,000 capacity, opened 2001 -- DAL: Dallas Wings → College Park Center (Arlington, TX) - ~7,000 capacity, opened 2012 -- GSV: Golden State Valkyries → Chase Center (San Francisco, CA) - shared with NBA Warriors, ~18,064, opened 2019 -- IND: Indiana Fever → Gainbridge Fieldhouse (Indianapolis, IN) - shared with NBA Pacers, ~17,923, opened 1999 -- LVA: Las Vegas Aces → Michelob Ultra Arena (Las Vegas, NV) - ~12,000 capacity, opened 2016 -- LA: Los Angeles Sparks → Crypto.com Arena (Los Angeles, CA) - shared with NBA Lakers/Clippers, ~19,079, opened 1999 -- MIN: Minnesota Lynx → Target Center (Minneapolis, MN) - shared with NBA Timberwolves, ~18,978, opened 1990 -- NY: New York Liberty → Barclays Center (Brooklyn, NY) - shared with NBA Nets, ~17,732, opened 2012 -- PHO: Phoenix Mercury → Footprint Center (Phoenix, AZ) - shared with NBA Suns, ~17,071, opened 1992 -- SEA: Seattle Storm → Climate Pledge Arena (Seattle, WA) - shared with NHL Kraken, ~17,100, opened 1962 (renovated 2021) -- WAS: Washington Mystics → Entertainment & Sports Arena (Washington, DC) - WNBA-specific, ~4,200, opened 2018 - -6. scrape_wnba_stadiums_hardcoded() function returning list[Stadium] -7. scrape_wnba_stadiums() function with fallback sources -8. WNBA_STADIUM_SOURCES configuration - -Note: Use WNBA-specific capacity where different from NBA configuration. -Cross-reference nba.py for shared arena coordinates. - - python3 -c "from Scripts.wnba import WNBA_TEAMS, scrape_wnba_stadiums_hardcoded; s = scrape_wnba_stadiums_hardcoded(); print(f'{len(s)} arenas'); assert len(s) == 13; assert all(st.capacity > 0 for st in s); assert all(st.year_opened for st in s)" - wnba.py exists with 13 teams, 13 arenas, all with non-zero capacity and year_opened values - - - - Task 2: Integrate WNBA module with scrape_schedules.py - Scripts/scrape_schedules.py - -Update scrape_schedules.py to use the new wnba.py module: - -1. Add import at top (with try/except pattern): - - from wnba import WNBA_TEAMS, get_wnba_team_abbrev, scrape_wnba_stadiums, WNBA_STADIUM_SOURCES - -2. Remove inline WNBA_TEAMS dict (lines ~77-91) - now imported from wnba.py - -3. Update get_team_abbrev() function to use get_wnba_team_abbrev() for WNBA - -4. Update scrape_wnba_stadiums() stub function to use the new module's implementation - -5. Verify WNBA games scraping still works - -Do NOT remove the game scraping functions - those stay inline for now. - - cd Scripts && python3 -c "from scrape_schedules import WNBA_TEAMS, get_team_abbrev; print(f'WNBA teams: {len(WNBA_TEAMS)}'); abbrev = get_team_abbrev('Las Vegas Aces', 'WNBA'); print(f'Aces abbrev: {abbrev}'); assert abbrev == 'LVA'" - scrape_schedules.py imports WNBA_TEAMS from wnba.py, get_team_abbrev works for WNBA, inline WNBA_TEAMS removed - - - - - -Before declaring plan complete: -- [ ] wnba.py exists with complete module structure -- [ ] All 13 WNBA arenas have capacity > 0 and year_opened values -- [ ] scrape_schedules.py imports from wnba.py successfully -- [ ] No import errors when running pipeline - - - - -- wnba.py module created following established pattern -- 13 WNBA arenas with complete data (capacity, year_opened, coordinates) -- scrape_schedules.py integration works -- Shared NBA arenas have correct coordinates - - - -After completion, create `.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-SUMMARY.md` - diff --git a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-SUMMARY.md b/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-SUMMARY.md deleted file mode 100644 index ab830da..0000000 --- a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-SUMMARY.md +++ /dev/null @@ -1,109 +0,0 @@ ---- -phase: 2.1-additional-sports-stadiums -plan: 02 -subsystem: data -tags: [wnba, basketball, stadiums, python, scraping] - -# Dependency graph -requires: - - phase: 02.1-01 - provides: sport module pattern (mls.py) and integration pattern -provides: - - WNBA sport module with 13 hardcoded arenas - - Complete WNBA arena data (capacity, year_opened, coordinates) - - Integration with scrape_schedules.py pipeline -affects: [02.1-03-nwsl, 02.1-04-cbb, future stadium phases] - -# Tech tracking -tech-stack: - added: [] - patterns: [sport module pattern from core sports applied to WNBA] - -key-files: - created: [Scripts/wnba.py] - modified: [Scripts/scrape_schedules.py] - -key-decisions: - - "Cross-referenced shared arena coordinates from nba.py and nhl.py" - - "Used WNBA-specific capacities where applicable (differs from NBA configuration)" - - "Included Climate Pledge Arena year_opened as 1962 (original construction, renovated 2021)" - -patterns-established: - - "Sport module structure: WNBA_TEAMS dict, get_wnba_team_abbrev(), scrape_wnba_stadiums_hardcoded(), scrape_wnba_stadiums(), WNBA_STADIUM_SOURCES" - -issues-created: [] - -# Metrics -duration: 4min -completed: 2026-01-10 ---- - -# Phase 2.1-02: WNBA Sport Module Summary - -**Complete WNBA stadium data module with 13 arenas including capacity, year_opened, and coordinates for canonicalization pipeline** - -## Performance - -- **Duration:** 4 min -- **Started:** 2026-01-10T06:56:38Z -- **Completed:** 2026-01-10T07:00:04Z -- **Tasks:** 2 -- **Files modified:** 2 - -## Accomplishments -- Created WNBA sport module following established pattern from MLS/MLB/NBA/NHL/NFL -- All 13 WNBA arenas with complete data (capacity, year_opened, coordinates) -- Cross-referenced shared arena coordinates from nba.py (6 arenas) and nhl.py (1 arena) -- Integrated with scrape_schedules.py pipeline for stadium updates - -## WNBA Arenas Summary - -| Arena | Team | City | Capacity | Year | Shared With | -|-------|------|------|----------|------|-------------| -| Gateway Center Arena | ATL | College Park, GA | 3,500 | 2018 | WNBA-specific | -| Wintrust Arena | CHI | Chicago, IL | 10,387 | 2017 | WNBA-specific | -| Mohegan Sun Arena | CON | Uncasville, CT | 10,000 | 2001 | WNBA-specific | -| College Park Center | DAL | Arlington, TX | 7,000 | 2012 | WNBA-specific | -| Chase Center | GSV | San Francisco, CA | 18,064 | 2019 | GSW Warriors | -| Gainbridge Fieldhouse | IND | Indianapolis, IN | 17,923 | 1999 | IND Pacers | -| Michelob Ultra Arena | LVA | Las Vegas, NV | 12,000 | 2016 | WNBA-specific | -| Crypto.com Arena | LA | Los Angeles, CA | 19,079 | 1999 | LAL Lakers | -| Target Center | MIN | Minneapolis, MN | 18,978 | 1990 | MIN Timberwolves | -| Barclays Center | NY | Brooklyn, NY | 17,732 | 2012 | BRK Nets | -| Footprint Center | PHO | Phoenix, AZ | 17,071 | 1992 | PHO Suns | -| Climate Pledge Arena | SEA | Seattle, WA | 17,100 | 1962 | SEA Kraken | -| Entertainment & Sports Arena | WAS | Washington, DC | 4,200 | 2018 | WNBA-specific | - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create wnba.py module with complete stadium data** - `5a51dab` (feat) -2. **Task 2: Integrate WNBA module with scrape_schedules.py** - `f141136` (feat) - -## Files Created/Modified -- `Scripts/wnba.py` - New WNBA sport module with 13 teams, 13 arenas, complete data -- `Scripts/scrape_schedules.py` - Import WNBA module, remove inline WNBA_TEAMS dict and stadium scrapers - -## Decisions Made -- Cross-referenced shared arena coordinates from nba.py (Chase Center, Gainbridge Fieldhouse, Crypto.com Arena, Target Center, Barclays Center, Footprint Center) and nhl.py (Climate Pledge Arena) -- Used WNBA-specific capacities where teams have their own venues (Gateway Center Arena 3,500, Wintrust Arena 10,387, etc.) -- Kept game scrapers inline in scrape_schedules.py (only extracted stadium scrapers for this plan) - -## Deviations from Plan - -None - plan executed exactly as written - -## Issues Encountered - -None - -## Next Phase Readiness -- WNBA stadium data now complete and flowing through canonicalization pipeline -- Pattern established for remaining sport modules (NWSL, CBB) -- Ready for 02.1-03-nwsl plan - ---- -*Phase: 2.1-additional-sports-stadiums* -*Plan: 02* -*Completed: 2026-01-10* diff --git a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-03-PLAN.md b/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-03-PLAN.md deleted file mode 100644 index 5891923..0000000 --- a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-03-PLAN.md +++ /dev/null @@ -1,140 +0,0 @@ ---- -phase: 2.1-additional-sports-stadiums -plan: 03 -type: execute ---- - - -Create NWSL sport module with complete hardcoded stadium data. - -Purpose: Enable NWSL stadium data to flow through the canonicalization pipeline. -Output: nwsl.py module with 13+ stadiums including capacity, year_opened, and coordinates. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md - -# Prior plans in this phase: -@.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-SUMMARY.md -@.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-02-SUMMARY.md - -# Pattern reference: -@Scripts/mlb.py -@Scripts/mls.py (created in 02.1-01) -@Scripts/wnba.py (created in 02.1-02) - -# Current NWSL data: -@Scripts/scrape_schedules.py (NWSL_TEAMS dict at line 126) - -# MLS stadiums (some shared with NWSL): -@Scripts/mls.py - -# Core module: -@Scripts/core.py - -**Tech stack available:** Python 3, dataclasses, requests -**Established patterns:** Sport module structure from mlb.py, mls.py, wnba.py -**Key insight:** Several NWSL teams share stadiums with MLS teams - can reference mls.py hardcoded data - - - - - - Task 1: Create nwsl.py module with complete stadium data - Scripts/nwsl.py - -Create nwsl.py following the established pattern: - -1. Module docstring and imports (try/except for core imports) -2. __all__ exports list -3. NWSL_TEAMS dict (copy from scrape_schedules.py, 13 teams - verify current roster) -4. get_nwsl_team_abbrev() function -5. Hardcoded NWSL stadiums dict with COMPLETE data: - -NWSL Teams and Stadiums (2025 season - 14 teams as of expansion): -- LA: Angel City FC → BMO Stadium (Los Angeles, CA) - shared with LAFC, ~22,000, opened 2018 -- SJ: Bay FC → PayPal Park (San Jose, CA) - shared with SJ Earthquakes, ~18,000, opened 2015 -- CHI: Chicago Red Stars → SeatGeek Stadium (Bridgeview, IL) - ~20,000 capacity, opened 2006 -- HOU: Houston Dash → Shell Energy Stadium (Houston, TX) - shared with Houston Dynamo, ~22,039, opened 2012 -- KC: Kansas City Current → CPKC Stadium (Kansas City, MO) - NWSL-specific, ~11,500, opened 2024 -- NJ: NJ/NY Gotham FC → Red Bull Arena (Harrison, NJ) - shared with NY Red Bulls, ~25,000, opened 2010 -- NC: North Carolina Courage → WakeMed Soccer Park (Cary, NC) - ~10,000, opened 2002 -- ORL: Orlando Pride → Inter&Co Stadium (Orlando, FL) - shared with Orlando City SC, ~25,500, opened 2017 -- POR: Portland Thorns FC → Providence Park (Portland, OR) - shared with Portland Timbers, ~25,218, opened 1926 (renovated 2019) -- SEA: Seattle Reign FC → Lumen Field (Seattle, WA) - shared with Sounders/Seahawks, ~69,000, opened 2002 -- SD: San Diego Wave FC → Snapdragon Stadium (San Diego, CA) - shared, ~35,000, opened 2022 -- UTA: Utah Royals FC → America First Field (Sandy, UT) - shared with Real Salt Lake, ~20,213, opened 2008 -- WAS: Washington Spirit → Audi Field (Washington, DC) - shared with DC United, ~20,000, opened 2018 -- BOS: Boston Breakers FC (if active - verify current NWSL roster) - -Cross-reference mls.py for shared stadium coordinates and verify current league membership. - -6. scrape_nwsl_stadiums_hardcoded() function returning list[Stadium] -7. scrape_nwsl_stadiums() function with fallback sources -8. NWSL_STADIUM_SOURCES configuration - -Note: NWSL has had expansion and contraction - verify current team roster matches actual 2025 season. - - python3 -c "from Scripts.nwsl import NWSL_TEAMS, scrape_nwsl_stadiums_hardcoded; s = scrape_nwsl_stadiums_hardcoded(); print(f'{len(s)} stadiums'); print(f'{len(NWSL_TEAMS)} teams'); assert all(st.capacity > 0 for st in s); assert all(st.year_opened for st in s)" - nwsl.py exists with current NWSL teams, all stadiums with non-zero capacity and year_opened values - - - - Task 2: Integrate NWSL module and finalize phase - Scripts/scrape_schedules.py - -Update scrape_schedules.py to use the new nwsl.py module: - -1. Add import at top (with try/except pattern): - - from nwsl import NWSL_TEAMS, get_nwsl_team_abbrev, scrape_nwsl_stadiums, NWSL_STADIUM_SOURCES - -2. Remove inline NWSL_TEAMS dict (lines ~126-140) - now imported from nwsl.py - -3. Update get_team_abbrev() function to use get_nwsl_team_abbrev() for NWSL - -4. Update scrape_nwsl_stadiums() stub function to use the new module's implementation - -5. Verify NWSL games scraping still works - -6. Run full stadium update to verify all 3 new sports integrate: - python3 scrape_schedules.py --stadiums-update - -Do NOT remove the game scraping functions - those stay inline for now. - - cd Scripts && python3 -c "from scrape_schedules import NWSL_TEAMS, get_team_abbrev; print(f'NWSL teams: {len(NWSL_TEAMS)}'); abbrev = get_team_abbrev('Portland Thorns FC', 'NWSL'); print(f'Thorns abbrev: {abbrev}'); assert abbrev == 'POR'" - scrape_schedules.py imports NWSL_TEAMS from nwsl.py, get_team_abbrev works for NWSL, all 3 secondary sport modules integrated - - - - - -Before declaring plan complete: -- [ ] nwsl.py exists with complete module structure -- [ ] All NWSL stadiums have capacity > 0 and year_opened values -- [ ] scrape_schedules.py imports from nwsl.py successfully -- [ ] `python3 Scripts/scrape_schedules.py --stadiums-update` includes MLS, WNBA, and NWSL stadiums -- [ ] No import errors when running pipeline - - - - -- nwsl.py module created following established pattern -- All NWSL stadiums with complete data (capacity, year_opened, coordinates) -- scrape_schedules.py integration works for all 3 new sports -- Phase 2.1 complete (MLS, WNBA, NWSL modules created) -- CBB deferred to future phase (documented in summary) - - - -After completion, create `.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-03-SUMMARY.md` with: -- Summary of all 3 plans (MLS, WNBA, NWSL modules) -- Note that CBB was deferred (350+ D1 teams requires separate scoped phase) -- Phase 2.1 complete status - diff --git a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-03-SUMMARY.md b/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-03-SUMMARY.md deleted file mode 100644 index 9ed6515..0000000 --- a/.planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-03-SUMMARY.md +++ /dev/null @@ -1,130 +0,0 @@ ---- -phase: 2.1-additional-sports-stadiums -plan: 03 -subsystem: data -tags: [nwsl, soccer, stadiums, python, scraping] - -# Dependency graph -requires: - - phase: 02.1-01 - provides: MLS sport module pattern and shared stadium coordinates - - phase: 02.1-02 - provides: WNBA sport module pattern confirmation -provides: - - NWSL sport module with 13 hardcoded stadiums - - Complete NWSL stadium data (capacity, year_opened, coordinates) - - Integration with scrape_schedules.py pipeline - - Phase 2.1 complete (all secondary sport stadium modules created) -affects: [future stadium phases, canonicalization pipeline] - -# Tech tracking -tech-stack: - added: [] - patterns: [sport module pattern from MLS applied to NWSL] - -key-files: - created: [Scripts/nwsl.py] - modified: [Scripts/scrape_schedules.py] - -key-decisions: - - "Cross-referenced shared stadium coordinates from mls.py (10 of 13 stadiums shared)" - - "CPKC Stadium (Kansas City Current) is NWSL-specific, newest stadium opened 2024" - - "CBB deferred to future phase (350+ D1 teams requires separate scoped phase)" - -patterns-established: - - "Sport module structure: NWSL_TEAMS dict, get_nwsl_team_abbrev(), scrape_nwsl_stadiums_hardcoded(), scrape_nwsl_stadiums(), NWSL_STADIUM_SOURCES" - -issues-created: [] - -# Metrics -duration: 7min -completed: 2026-01-10 ---- - -# Phase 2.1-03: NWSL Sport Module Summary - -**Complete NWSL stadium data module with 13 stadiums including capacity, year_opened, and coordinates for canonicalization pipeline - Phase 2.1 complete** - -## Performance - -- **Duration:** 7 min -- **Started:** 2026-01-10T07:02:05Z -- **Completed:** 2026-01-10T07:09:00Z -- **Tasks:** 2 -- **Files modified:** 2 - -## Accomplishments -- Created NWSL sport module following established pattern from MLS/WNBA -- All 13 NWSL stadiums with complete data (capacity, year_opened, coordinates) -- Cross-referenced shared stadium coordinates from mls.py (10 stadiums shared with MLS) -- Integrated with scrape_schedules.py pipeline for stadium updates -- **Phase 2.1 complete:** MLS (30), WNBA (13), NWSL (13) modules all created - -## NWSL Stadiums Summary - -| Stadium | Team | City | Capacity | Year | Shared With | -|---------|------|------|----------|------|-------------| -| BMO Stadium | LA | Los Angeles, CA | 22,000 | 2018 | LAFC | -| PayPal Park | SJ | San Jose, CA | 18,000 | 2015 | SJ Earthquakes | -| SeatGeek Stadium | CHI | Bridgeview, IL | 20,000 | 2006 | NWSL-specific | -| Shell Energy Stadium | HOU | Houston, TX | 22,039 | 2012 | Houston Dynamo | -| CPKC Stadium | KC | Kansas City, MO | 11,500 | 2024 | NWSL-specific | -| Red Bull Arena | NJ | Harrison, NJ | 25,000 | 2010 | NY Red Bulls | -| WakeMed Soccer Park | NC | Cary, NC | 10,000 | 2002 | NWSL-specific | -| Inter&Co Stadium | ORL | Orlando, FL | 25,500 | 2017 | Orlando City SC | -| Providence Park | POR | Portland, OR | 25,218 | 1926 | Portland Timbers | -| Lumen Field | SEA | Seattle, WA | 37,722 | 2002 | Sounders/Seahawks | -| Snapdragon Stadium | SD | San Diego, CA | 35,000 | 2022 | San Diego FC | -| America First Field | UTA | Sandy, UT | 20,213 | 2008 | Real Salt Lake | -| Audi Field | WAS | Washington, DC | 20,000 | 2018 | DC United | - -## Task Commits - -Each task was committed atomically: - -1. **Task 1: Create nwsl.py module with complete stadium data** - `75e2498` (feat) -2. **Task 2: Integrate NWSL module with scrape_schedules.py** - `5307fdf` (feat) - -## Files Created/Modified -- `Scripts/nwsl.py` - New NWSL sport module with 13 teams, 13 stadiums, complete data -- `Scripts/scrape_schedules.py` - Import NWSL module, remove inline NWSL_TEAMS dict and stadium stub - -## Decisions Made -- Cross-referenced shared stadium coordinates from mls.py for 10 stadiums (all MLS-NWSL shared venues) -- Identified 3 NWSL-specific stadiums: SeatGeek Stadium, CPKC Stadium, WakeMed Soccer Park -- CPKC Stadium is the first purpose-built stadium for an NWSL team (opened 2024) -- CBB deferred - 350+ D1 teams requires dedicated scoped phase with different approach - -## Deviations from Plan - -None - plan executed exactly as written - -## Issues Encountered - -None - -## Phase 2.1 Complete - -**Summary of all plans in Phase 2.1:** - -| Plan | Sport | Stadiums | Commits | -|------|-------|----------|---------| -| 02.1-01 | MLS | 30 | addc9b3, 8f1803b | -| 02.1-02 | WNBA | 13 | 5a51dab, f141136 | -| 02.1-03 | NWSL | 13 | 75e2498, 5307fdf | - -**Total:** 56 new stadiums added to canonicalization pipeline - -**Deferred:** -- CBB (College Basketball) - 350+ D1 teams requires separate scoped phase with tier-based approach - -## Next Phase Readiness -- All secondary sport stadium data flowing through canonicalization pipeline -- Stadium update verified: MLS 30, WNBA 13, NWSL 13 stadiums returned -- Total stadium count now 178 (MLB 30, NBA 30, NHL 32, NFL 30, MLS 30, WNBA 13, NWSL 13, CBB 0) -- Ready for Phase 2.2 or next roadmap phase - ---- -*Phase: 2.1-additional-sports-stadiums* -*Plan: 03* -*Completed: 2026-01-10* diff --git a/.planning/phases/9.1-fix-flaky-test-when-ran-in-parallel/9.1-01-PLAN.md b/.planning/phases/9.1-fix-flaky-test-when-ran-in-parallel/9.1-01-PLAN.md deleted file mode 100644 index 57aa27a..0000000 --- a/.planning/phases/9.1-fix-flaky-test-when-ran-in-parallel/9.1-01-PLAN.md +++ /dev/null @@ -1,232 +0,0 @@ ---- -phase: 9.1-fix-flaky-test-when-ran-in-parallel -plan: 01 -type: execute ---- - - -Fix test suite flakiness where 5 tests fail in parallel execution but pass individually. - -Purpose: Ensure reliable CI/CD testing by resolving Swift Testing parallel execution state pollution discovered in Phase 9. -Output: All 5 flaky tests pass consistently in full parallel test suite execution. - - - -~/.claude/get-shit-done/workflows/execute-phase.md -~/.claude/get-shit-done/templates/summary.md - - - -@.planning/PROJECT.md -@.planning/ROADMAP.md -@.planning/STATE.md -@.planning/codebase/TESTING.md - -# Prior phase context -@.planning/phases/09-trip-planner-modes-tdd/09-01-SUMMARY.md -@.planning/phases/09-trip-planner-modes-tdd/09-02-SUMMARY.md -@.planning/phases/09-trip-planner-modes-tdd/09-03-SUMMARY.md - -# Test files with flaky tests -@SportsTimeTests/ScenarioAPlannerSwiftTests.swift -@SportsTimeTests/ScenarioBPlannerTests.swift -@SportsTimeTests/ScenarioCPlannerTests.swift - -**Flaky tests identified (5 total):** - -From ScenarioAPlannerSwiftTests.swift (3 tests): -- `plan_StopDepartureDate_IsLastGameDate()` (line ~300) -- `plan_ManyGames_HandledEfficiently()` (line ~493) -- `plan_ThreeSameDayGames_PicksFeasibleCombinations()` (line ~944) - -From ScenarioBPlannerTests.swift (2 tests): -- `plan_FillerSameDayAsAnchor_Excluded()` -- `plan_MustSeeGamesTooFarApart_Fails()` - -From ScenarioCPlannerTests.swift (1 test): -- `corridor_MultipleGamesMixed_FiltersCorrectly()` - -**Root cause:** Swift Testing runs tests in parallel by default. Tests likely share mutable state (actor instances, simulator state) causing interference. - -**Tech stack available:** -- Swift Testing framework (iOS 26+) -- `#expect()` assertions -- `@Suite` and `@Test` attributes -- `.serialized` trait for controlling parallelization -- `confirmation()` for actor synchronization - -**Key observation:** ScenarioAPlannerSwiftTests is missing `@Suite` attribute (other test files have it). - - - - - - Task 1: Add Swift Testing isolation to flaky tests - SportsTimeTests/ScenarioAPlannerSwiftTests.swift, SportsTimeTests/ScenarioBPlannerTests.swift, SportsTimeTests/ScenarioCPlannerTests.swift - -Apply Swift Testing isolation patterns to prevent state pollution: - -1. **Add @Suite attribute to ScenarioAPlannerSwiftTests** (currently missing): - - Add `@Suite("ScenarioA Tests")` before `struct ScenarioAPlannerSwiftTests` - - Matches pattern used in ScenarioBPlannerTests and ScenarioCPlannerTests - -2. **Apply .serialized trait to flaky tests:** - - Modify the 5 flaky test functions to use `.serialized` trait - - Swift Testing syntax: `@Test(.serialized, "test description")` - - This prevents parallel execution of these specific tests - - Example: Change `@Test("handles many games")` to `@Test(.serialized, "handles many games")` - -3. **Verify actor synchronization patterns:** - - Review if tests use `confirmation()` for actor operations (Swift Testing pattern for async/actor testing) - - Add `confirmation()` if tests modify shared actor state and don't already use it - - Only needed if actors are shared across tests (check planner initialization in `plan()` helper) - -**Why .serialized:** These tests likely interfere due to parallel execution timing. Running them serially eliminates race conditions while maintaining all other tests' parallel execution benefits. - -**What to avoid and WHY:** -- Don't add `.serialized` to ALL tests - only the 5 flaky ones. Other tests benefit from parallel execution speed. -- Don't use XCTest patterns (like `setUp()`/`tearDown()`) - this is Swift Testing, use Swift Testing patterns only. -- Don't modify test assertions - tests validate correct behavior individually, issue is isolation not correctness. - - -Run full test suite in parallel: -```bash -xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' test -``` - -All 5 previously flaky tests must pass: -- `plan_StopDepartureDate_IsLastGameDate()` -- `plan_ManyGames_HandledEfficiently()` -- `plan_ThreeSameDayGames_PicksFeasibleCombinations()` -- `plan_FillerSameDayAsAnchor_Excluded()` -- `plan_MustSeeGamesTooFarApart_Fails()` -- `corridor_MultipleGamesMixed_FiltersCorrectly()` - -Run suite 3 times to confirm consistency (flaky tests would fail at least once in 3 runs). - - -- @Suite attribute added to ScenarioAPlannerSwiftTests -- .serialized trait applied to all 5 flaky tests -- Full test suite passes 3 consecutive times -- Test output shows serialized tests running (no parallel interference) - - - - - Task 2: Verify test isolation doesn't reduce coverage - SportsTimeTests/ScenarioAPlannerSwiftTests.swift, SportsTimeTests/ScenarioBPlannerTests.swift, SportsTimeTests/ScenarioCPlannerTests.swift - -Confirm serialization fixes flakiness without compromising test quality: - -1. **Run tests individually to confirm behavior unchanged:** - ```bash - # Run each flaky test individually - xcodebuild -only-testing:SportsTimeTests/ScenarioAPlannerSwiftTests/plan_StopDepartureDate_IsLastGameDate test - xcodebuild -only-testing:SportsTimeTests/ScenarioAPlannerSwiftTests/plan_ManyGames_HandledEfficiently test - # ... repeat for all 5 - ``` - All must still pass individually (sanity check). - -2. **Measure performance impact:** - - Note full suite execution time before changes (from Task 1 baseline) - - Note full suite execution time after .serialized changes - - Document in SUMMARY.md (expected: minimal impact since only 5/180+ tests serialized) - -3. **Verify no new flaky tests introduced:** - - Check test output for any other tests now showing intermittent failures - - Run suite 5 times total (2 more runs after Task 1's 3 runs) - - All 180+ tests must pass consistently - -**What to avoid and WHY:** -- Don't skip individual test verification - ensures serialization didn't break test logic -- Don't accept new flaky tests - if any appear, investigate whether .serialized needs to be applied more broadly or if there's a different issue - - -```bash -# Verify all tests pass consistently -for i in {1..5}; do - echo "Run $i/5" - xcodebuild -project SportsTime.xcodeproj -scheme SportsTime -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' test | grep "Test Suite 'All tests'" -done -``` - -Expected output (all 5 runs): -- "Test Suite 'All tests' passed" -- No failures in any of the 5 runs - - -- All 5 previously flaky tests pass individually -- Full test suite passes 5 consecutive times (100% success rate) -- No new flaky tests detected -- Performance impact documented (serializing 5/180+ tests should add ~1-2 seconds max) - - - - - - -Before declaring phase complete: -- [ ] Full test suite passes consistently (5/5 runs successful) -- [ ] All 5 previously flaky tests now pass in parallel execution -- [ ] No new flaky tests introduced -- [ ] Individual test execution still passes for all 5 tests -- [ ] Test isolation change documented in SUMMARY.md - - - - -- All tasks completed -- All verification checks pass -- 5 flaky tests now pass reliably in parallel test suite -- No degradation in test coverage or execution -- CI/CD testing is now reliable - - - -After completion, create `.planning/phases/9.1-fix-flaky-test-when-ran-in-parallel/9.1-01-SUMMARY.md`: - -# Phase 9.1 Plan 01: Fix Flaky Test Parallel Execution Summary - -**[Substantive one-liner describing solution - e.g., "Applied .serialized trait to 5 flaky tests for reliable CI/CD execution"]** - -## Performance - -- **Duration:** [time] -- **Started:** [timestamp] -- **Completed:** [timestamp] -- **Tests:** 5 flaky tests fixed - -## Accomplishments - -- Fixed test suite flakiness affecting 5 tests -- Added @Suite attribute to ScenarioAPlannerSwiftTests -- Applied .serialized trait to prevent parallel execution interference -- Verified consistent test suite execution (5/5 runs pass) - -## Files Created/Modified - -- `SportsTimeTests/ScenarioAPlannerSwiftTests.swift` - Added @Suite, .serialized to 3 tests -- `SportsTimeTests/ScenarioBPlannerTests.swift` - Added .serialized to 2 tests -- `SportsTimeTests/ScenarioCPlannerTests.swift` - Added .serialized to 1 test - -## Decisions Made - -| Decision | Rationale | -|----------|-----------| -| Use .serialized trait instead of global serialization | Only 5/180+ tests affected, maintains parallel execution benefits for other tests | -| Add @Suite to ScenarioAPlannerSwiftTests | Matches pattern in other test files, provides better test organization | - -## Deviations from Plan - -[Auto-fixed issues or deferred enhancements] - -## Issues Encountered - -[Problems and resolutions, or "None"] - -## Next Phase Readiness - -- Test suite reliability: 100% (5/5 parallel runs pass) -- Ready for Phase 10: Trip Builder Options TDD -- No blockers -