- Create 01-03-SUMMARY.md documenting NFL module and orchestrator refactor - Update STATE.md: Phase 1 complete, ready for Phase 2 - Update ROADMAP.md: Mark Phase 1 as complete (3/3 plans) - Phase 1 total duration: 23 min across 3 plans Phase 1: Script Architecture complete. All 4 core sports (MLB, NBA, NHL, NFL) now have dedicated modules with consistent patterns. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
122 lines
3.6 KiB
Markdown
122 lines
3.6 KiB
Markdown
---
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phase: 01-script-architecture
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plan: 03
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subsystem: data-pipeline
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tags: [python, scrapers, modular-architecture, nfl, orchestrator]
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# Dependency graph
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requires: [01-01, 01-02]
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provides:
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- nfl.py NFL-specific scrapers
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- Thin orchestrator scrape_schedules.py
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- Complete Phase 1 modular architecture
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affects: [02-01]
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# Tech tracking
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tech-stack:
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added: []
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patterns:
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- "Sport modules provide convenience functions (scrape_{sport}_games)"
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- "Orchestrator imports and calls module functions instead of inline code"
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- "Non-core sports marked with TODO for future extraction"
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key-files:
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created:
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- Scripts/nfl.py
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modified:
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- Scripts/scrape_schedules.py
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key-decisions:
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- "NFL uses cross-calendar-year season format (2025-26) like NBA/NHL"
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- "Non-core sports (WNBA, MLS, NWSL, CBB) remain inline with TODO markers"
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- "Orchestrator reduced from 3359 to 733 lines (78% reduction)"
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patterns-established:
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- "Each sport module exports: {SPORT}_TEAMS, scrape_{sport}_games, {SPORT}_GAME_SOURCES"
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- "Orchestrator calls module convenience functions for core sports"
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issues-created: []
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# Metrics
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duration: 8min
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completed: 2026-01-10
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---
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# Phase 1 Plan 03: NFL + Orchestrator Refactor Summary
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**Created NFL sport module and refactored scrape_schedules.py to thin orchestrator, completing Phase 1: Script Architecture**
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## Performance
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- **Duration:** 8 min
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- **Started:** 2026-01-10T06:10:46Z
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- **Completed:** 2026-01-10T06:18:23Z
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- **Tasks:** 2
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- **Files modified:** 2
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## Accomplishments
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- Created `Scripts/nfl.py` with NFL_TEAMS (32 teams), 3 game scrapers, 3 stadium scrapers
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- Refactored `Scripts/scrape_schedules.py` from 3359 to 733 lines (78% reduction)
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- All 4 core sports (MLB, NBA, NHL, NFL) now have dedicated modules
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- Phase 1: Script Architecture complete
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## Task Commits
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Each task was committed atomically:
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1. **Task 1: Create nfl.py sport module** - `a6c9230` (feat)
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2. **Task 2: Refactor scrape_schedules.py to orchestrator** - `b93205e` (feat)
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## Files Created/Modified
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- `Scripts/nfl.py` - NFL team mappings, ESPN/Pro-Football-Reference/CBS scrapers, stadium scrapers
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- `Scripts/scrape_schedules.py` - Thin orchestrator importing from sport modules
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## Decisions Made
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- NFL uses cross-calendar-year season format (2025-26) consistent with NBA/NHL
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- Non-core sports kept inline with TODO comments for future extraction phase
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- Orchestrator maintains backward-compatible CLI interface
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## Deviations from Plan
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None - plan executed exactly as written.
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## Issues Encountered
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None
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## Phase 1 Complete
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Phase 1: Script Architecture is now complete with all 3 plans executed:
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- 01-01: core.py + mlb.py (shared utilities and first sport module)
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- 01-02: nba.py + nhl.py (second and third sport modules)
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- 01-03: nfl.py + orchestrator refactor (fourth sport module and thin orchestrator)
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### Module Architecture
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```
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Scripts/
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core.py - Shared utilities (385 lines)
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mlb.py - MLB scrapers (412 lines)
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nba.py - NBA scrapers (412 lines)
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nhl.py - NHL scrapers (412 lines)
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nfl.py - NFL scrapers (573 lines)
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scrape_schedules.py - Orchestrator (733 lines)
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```
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**Total modular code:** 2,927 lines across 6 files
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**Original monolithic:** 3,359 lines in 1 file
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**Net change:** More organized, testable, maintainable code with clear separation of concerns
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## Next Phase Readiness
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- Phase 1 complete, ready for Phase 2: Stadium Foundation
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- All 4 core sports modularized with consistent patterns
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- Orchestrator provides clean entry point for all scraping operations
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---
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*Phase: 01-script-architecture*
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*Completed: 2026-01-10*
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