---
phase: 01-script-architecture
plan: 02
type: execute
---

<objective>
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.
</objective>

<execution_context>
@~/.claude/get-shit-done/workflows/execute-phase.md
@~/.claude/get-shit-done/templates/summary.md
</execution_context>

<context>
@.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
</context>

<tasks>

<task type="auto">
  <name>Task 1: Create nba.py sport module</name>
  <files>Scripts/nba.py</files>
  <action>
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.
  </action>
  <verify>python3 -c "from Scripts.nba import scrape_nba_games, NBA_GAME_SOURCES; print('OK')"</verify>
  <done>nba.py exists, imports from core.py, exports NBA scrapers</done>
</task>

<task type="auto">
  <name>Task 2: Create nhl.py sport module</name>
  <files>Scripts/nhl.py</files>
  <action>
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.
  </action>
  <verify>python3 -c "from Scripts.nhl import scrape_nhl_games, NHL_GAME_SOURCES; print('OK')"</verify>
  <done>nhl.py exists, imports from core.py, exports NHL scrapers</done>
</task>

</tasks>

<verification>
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)
</verification>

<success_criteria>
- 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
</success_criteria>

<output>
After completion, create `.planning/phases/01-script-architecture/01-02-SUMMARY.md`
</output>