76e24ab22b
## Refactoring - Changed `ManualOutcomeSubmission.outcome` from `str` to `PlayOutcome` enum type - Removed custom validator (Pydantic handles enum validation automatically) - Added direct import of PlayOutcome (no circular dependency due to TYPE_CHECKING guard) - Updated tests to use enum values while maintaining backward compatibility Benefits: - Better type safety with IDE autocomplete - Cleaner code (removed 15 lines of validator boilerplate) - Backward compatible (Pydantic auto-converts strings to enum) - Access to helper methods (is_hit(), is_out(), etc.) Files modified: - app/models/game_models.py: Enum type + import - tests/unit/config/test_result_charts.py: Updated 7 tests + added compatibility test ## Documentation Created comprehensive CLAUDE.md files for all backend/app/ subdirectories to help future AI agents quickly understand and work with the code. Added 8,799 lines of documentation covering: - api/ (906 lines): FastAPI routes, health checks, auth patterns - config/ (906 lines): League configs, PlayOutcome enum, result charts - core/ (1,288 lines): GameEngine, StateManager, PlayResolver, dice system - data/ (937 lines): API clients (planned), caching layer - database/ (945 lines): Async sessions, operations, recovery - models/ (1,270 lines): Pydantic/SQLAlchemy models, polymorphic patterns - utils/ (959 lines): Logging, JWT auth, security - websocket/ (1,588 lines): Socket.io handlers, real-time events - tests/ (475 lines): Testing patterns and structure Each CLAUDE.md includes: - Purpose & architecture overview - Key components with detailed explanations - Patterns & conventions - Integration points - Common tasks (step-by-step guides) - Troubleshooting with solutions - Working code examples - Testing guidance Total changes: +9,294 lines / -24 lines Tests: All passing (62/62 model tests, 7/7 ManualOutcomeSubmission tests)
482 lines
16 KiB
Python
482 lines
16 KiB
Python
"""
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Unit Tests for Result Charts
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Tests result chart abstraction, hit location calculation, and PD auto mode.
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"""
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import pytest
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from unittest.mock import Mock
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from pydantic import ValidationError
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from app.config.result_charts import (
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PlayOutcome,
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calculate_hit_location,
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ResultChart,
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ManualResultChart,
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PdAutoResultChart,
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)
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from app.models.game_models import ManualOutcomeSubmission
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# ============================================================================
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# HELPER FUNCTION TESTS
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# ============================================================================
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class TestCalculateHitLocation:
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"""Test calculate_hit_location() helper function"""
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def test_groundball_returns_infield_position(self):
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"""Test groundballs return infield positions"""
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outcome = PlayOutcome.GROUNDBALL_C
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# Run 100 times to test distribution
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locations = set()
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for _ in range(100):
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location = calculate_hit_location(outcome, 'R')
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locations.add(location)
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# Should only get infield positions
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valid_infield = {'1B', '2B', 'SS', '3B', 'P', 'C'}
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assert locations.issubset(valid_infield)
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def test_flyout_returns_outfield_position(self):
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"""Test flyouts return outfield positions"""
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outcome = PlayOutcome.FLYOUT_B
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# Run 100 times to test distribution
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locations = set()
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for _ in range(100):
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location = calculate_hit_location(outcome, 'R')
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locations.add(location)
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# Should only get outfield positions
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valid_outfield = {'LF', 'CF', 'RF'}
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assert locations.issubset(valid_outfield)
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def test_returns_none_for_outcomes_not_requiring_location(self):
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"""Test returns None for strikeouts, walks, etc."""
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assert calculate_hit_location(PlayOutcome.STRIKEOUT, 'R') is None
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assert calculate_hit_location(PlayOutcome.WALK, 'R') is None
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assert calculate_hit_location(PlayOutcome.HOMERUN, 'R') is None
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assert calculate_hit_location(PlayOutcome.SINGLE_1, 'R') is None
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# ============================================================================
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# PLAYOUTCOME HELPER TESTS
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# ============================================================================
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class TestPlayOutcomeRequiresHitLocation:
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"""Test PlayOutcome.requires_hit_location() method"""
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def test_groundballs_require_location(self):
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"""Test all groundball variants require location"""
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assert PlayOutcome.GROUNDBALL_A.requires_hit_location() is True
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assert PlayOutcome.GROUNDBALL_B.requires_hit_location() is True
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assert PlayOutcome.GROUNDBALL_C.requires_hit_location() is True
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def test_flyouts_require_location(self):
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"""Test all flyout variants require location"""
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assert PlayOutcome.FLYOUT_A.requires_hit_location() is True
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assert PlayOutcome.FLYOUT_B.requires_hit_location() is True
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assert PlayOutcome.FLYOUT_C.requires_hit_location() is True
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def test_other_outcomes_do_not_require_location(self):
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"""Test strikes, walks, hits don't require location"""
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assert PlayOutcome.STRIKEOUT.requires_hit_location() is False
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assert PlayOutcome.WALK.requires_hit_location() is False
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assert PlayOutcome.HOMERUN.requires_hit_location() is False
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assert PlayOutcome.SINGLE_1.requires_hit_location() is False
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assert PlayOutcome.DOUBLE_2.requires_hit_location() is False
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# ============================================================================
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# MANUAL RESULT CHART TESTS
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# ============================================================================
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class TestManualResultChart:
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"""Test ManualResultChart (should not be used)"""
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def test_raises_not_implemented_error(self):
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"""Test ManualResultChart.get_outcome() raises NotImplementedError"""
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chart = ManualResultChart()
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with pytest.raises(NotImplementedError) as exc_info:
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chart.get_outcome(
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roll=Mock(),
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state=Mock(),
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batter=Mock(),
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pitcher=Mock()
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)
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assert "manual mode" in str(exc_info.value).lower()
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assert "websocket" in str(exc_info.value).lower()
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# ============================================================================
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# PD AUTO RESULT CHART TESTS
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# ============================================================================
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class TestPdAutoResultChart:
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"""Test PdAutoResultChart auto mode implementation"""
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def create_mock_player(self, name, card_type, ratings_data):
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"""Helper to create mock player with card data"""
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player = Mock()
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player.name = name
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if card_type == 'batting':
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card = Mock()
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card.hand = 'R'
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card.ratings = {
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'R': Mock(**ratings_data),
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'L': Mock(**ratings_data)
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}
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player.batting_card = card
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player.pitching_card = None
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else: # pitching
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card = Mock()
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card.hand = 'R'
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card.ratings = {
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'R': Mock(**ratings_data),
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'L': Mock(**ratings_data)
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}
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player.pitching_card = card
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player.batting_card = Mock(hand='R')
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return player
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def test_select_card_coin_flip_distribution(self):
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"""Test _select_card() has ~50/50 distribution"""
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chart = PdAutoResultChart()
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# Create mock players with valid cards
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batter = self.create_mock_player('Batter', 'batting', {'homerun': 10.0})
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pitcher = self.create_mock_player('Pitcher', 'pitching', {'homerun': 5.0})
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# Run 1000 trials
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batting_count = 0
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for _ in range(1000):
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_, is_batting = chart._select_card(batter, pitcher)
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if is_batting:
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batting_count += 1
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# Should be approximately 50% (allow 10% variance)
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assert 400 <= batting_count <= 600
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def test_select_card_uses_correct_handedness(self):
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"""Test _select_card() selects rating for correct handedness"""
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chart = PdAutoResultChart()
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# Create batter with batting card
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batter = self.create_mock_player('Batter', 'batting', {'homerun': 10.0})
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# Create pitcher with specific hand
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pitcher = Mock()
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pitcher.name = 'Pitcher'
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pitcher.pitching_card = Mock(hand='L') # LHP
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pitcher.batting_card = None
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# Force batting card selection
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rating, is_batting = chart._select_card(batter, pitcher)
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# Should have selected rating vs LHP
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assert rating is not None
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def test_build_distribution_creates_cumulative_values(self):
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"""Test _build_distribution() builds cumulative thresholds"""
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chart = PdAutoResultChart()
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# Create mock rating
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rating = Mock(
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homerun=5.0,
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triple=2.0,
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double_two=8.0,
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single_one=15.0,
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walk=10.0,
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strikeout=20.0,
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groundout_a=10.0,
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groundout_b=15.0,
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groundout_c=15.0,
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# Zero out others
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bp_homerun=0.0,
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double_three=0.0,
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single_two=0.0,
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bp_single=0.0,
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hbp=0.0,
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lineout=0.0,
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popout=0.0,
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flyout_a=0.0,
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flyout_bq=0.0,
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flyout_lf_b=0.0,
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flyout_rf_b=0.0,
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double_pull=0.0,
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single_center=0.0,
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)
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distribution = chart._build_distribution(rating, is_batting_card=True)
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# Should have entries
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assert len(distribution) > 0
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# Cumulative values should be increasing
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prev_threshold = 0
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for threshold, outcome in distribution:
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assert threshold > prev_threshold
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prev_threshold = threshold
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# Total should be ~100% (within rounding)
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assert distribution[-1][0] >= 95.0 # Allow some missing outcomes
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def test_select_outcome_uses_distribution(self):
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"""Test _select_outcome() selects based on cumulative distribution"""
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chart = PdAutoResultChart()
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# Simple distribution: 0-50 = STRIKEOUT, 50-100 = WALK
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distribution = [
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(50.0, PlayOutcome.STRIKEOUT),
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(100.0, PlayOutcome.WALK),
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]
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# Run 1000 trials
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results = {'strikeout': 0, 'walk': 0}
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for _ in range(1000):
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outcome = chart._select_outcome(distribution)
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if outcome == PlayOutcome.STRIKEOUT:
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results['strikeout'] += 1
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elif outcome == PlayOutcome.WALK:
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results['walk'] += 1
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# Should be approximately 50/50 (allow 10% variance)
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assert 400 <= results['strikeout'] <= 600
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assert 400 <= results['walk'] <= 600
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def test_get_outcome_returns_tuple(self):
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"""Test get_outcome() returns (outcome, location) tuple"""
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chart = PdAutoResultChart()
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batter = self.create_mock_player('Batter', 'batting', {
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'homerun': 100.0, # Always HR
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'triple': 0.0,
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'double_two': 0.0,
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'single_one': 0.0,
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'walk': 0.0,
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'strikeout': 0.0,
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'groundout_a': 0.0,
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'groundout_b': 0.0,
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'groundout_c': 0.0,
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'bp_homerun': 0.0,
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'double_three': 0.0,
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'single_two': 0.0,
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'bp_single': 0.0,
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'hbp': 0.0,
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'lineout': 0.0,
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'popout': 0.0,
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'flyout_a': 0.0,
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'flyout_bq': 0.0,
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'flyout_lf_b': 0.0,
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'flyout_rf_b': 0.0,
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'double_pull': 0.0,
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'single_center': 0.0,
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})
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pitcher = self.create_mock_player('Pitcher', 'pitching', {'homerun': 0.0})
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outcome, location = chart.get_outcome(
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roll=Mock(),
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state=Mock(),
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batter=batter,
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pitcher=pitcher
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)
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assert isinstance(outcome, PlayOutcome)
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assert outcome == PlayOutcome.HOMERUN
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assert location is None # HRs don't need location
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def test_get_outcome_calculates_location_for_groundballs(self):
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"""Test get_outcome() calculates location for groundballs"""
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chart = PdAutoResultChart()
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batter = self.create_mock_player('Batter', 'batting', {
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'groundout_c': 100.0, # Always groundball
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'homerun': 0.0,
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'triple': 0.0,
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'double_two': 0.0,
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'single_one': 0.0,
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'walk': 0.0,
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'strikeout': 0.0,
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'groundout_a': 0.0,
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'groundout_b': 0.0,
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'bp_homerun': 0.0,
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'double_three': 0.0,
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'single_two': 0.0,
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'bp_single': 0.0,
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'hbp': 0.0,
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'lineout': 0.0,
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'popout': 0.0,
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'flyout_a': 0.0,
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'flyout_bq': 0.0,
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'flyout_lf_b': 0.0,
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'flyout_rf_b': 0.0,
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'double_pull': 0.0,
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'single_center': 0.0,
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})
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pitcher = self.create_mock_player('Pitcher', 'pitching', {'homerun': 0.0})
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outcome, location = chart.get_outcome(
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roll=Mock(),
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state=Mock(),
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batter=batter,
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pitcher=pitcher
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)
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assert outcome == PlayOutcome.GROUNDBALL_C
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assert location is not None
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assert location in ['1B', '2B', 'SS', '3B', 'P', 'C']
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def test_get_outcome_raises_error_with_no_cards(self):
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"""Test get_outcome() raises error if both players missing cards"""
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chart = PdAutoResultChart()
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batter = Mock(name='Batter', batting_card=None, pitching_card=None)
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pitcher = Mock(name='Pitcher', batting_card=None, pitching_card=None)
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with pytest.raises(ValueError) as exc_info:
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chart.get_outcome(
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roll=Mock(),
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state=Mock(),
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batter=batter,
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pitcher=pitcher
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)
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assert "cannot auto-resolve" in str(exc_info.value).lower()
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assert "missing card data" in str(exc_info.value).lower()
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def test_outcome_distribution_matches_ratings(self):
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"""Test outcome distribution roughly matches rating percentages"""
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chart = PdAutoResultChart()
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# Create player with known distribution
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batter = self.create_mock_player('Batter', 'batting', {
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'strikeout': 50.0,
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'walk': 50.0,
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'homerun': 0.0,
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'triple': 0.0,
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'double_two': 0.0,
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'single_one': 0.0,
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'groundout_a': 0.0,
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'groundout_b': 0.0,
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'groundout_c': 0.0,
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'bp_homerun': 0.0,
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'double_three': 0.0,
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'single_two': 0.0,
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'bp_single': 0.0,
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'hbp': 0.0,
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'lineout': 0.0,
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'popout': 0.0,
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'flyout_a': 0.0,
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'flyout_bq': 0.0,
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'flyout_lf_b': 0.0,
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'flyout_rf_b': 0.0,
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'double_pull': 0.0,
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'single_center': 0.0,
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})
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pitcher = self.create_mock_player('Pitcher', 'pitching', {'homerun': 0.0})
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# Force batting card every time for consistent test
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original_select = chart._select_card
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chart._select_card = lambda b, p: (batter.batting_card.ratings['R'], True)
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try:
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# Run 1000 trials
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outcomes = {'strikeout': 0, 'walk': 0}
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for _ in range(1000):
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outcome, _ = chart.get_outcome(
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roll=Mock(),
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state=Mock(),
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batter=batter,
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pitcher=pitcher
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)
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if outcome == PlayOutcome.STRIKEOUT:
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outcomes['strikeout'] += 1
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elif outcome == PlayOutcome.WALK:
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outcomes['walk'] += 1
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# Should be approximately 50/50 (allow 10% variance)
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assert 400 <= outcomes['strikeout'] <= 600
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assert 400 <= outcomes['walk'] <= 600
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finally:
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chart._select_card = original_select
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# ============================================================================
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# MANUAL OUTCOME SUBMISSION TESTS
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# ============================================================================
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class TestManualOutcomeSubmission:
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"""Test ManualOutcomeSubmission model validation"""
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def test_valid_outcome_with_location(self):
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"""Test valid submission with outcome and location"""
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submission = ManualOutcomeSubmission(
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outcome=PlayOutcome.GROUNDBALL_C,
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hit_location='SS'
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)
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assert submission.outcome == PlayOutcome.GROUNDBALL_C
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assert submission.hit_location == 'SS'
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def test_valid_outcome_without_location(self):
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"""Test valid submission without location"""
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submission = ManualOutcomeSubmission(
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outcome=PlayOutcome.STRIKEOUT
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)
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assert submission.outcome == PlayOutcome.STRIKEOUT
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assert submission.hit_location is None
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def test_valid_outcome_from_string(self):
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"""Test Pydantic converts string to enum automatically"""
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submission = ManualOutcomeSubmission(
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outcome='groundball_c',
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hit_location='SS'
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)
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# Pydantic converts string to enum
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assert submission.outcome == PlayOutcome.GROUNDBALL_C
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assert submission.hit_location == 'SS'
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def test_invalid_outcome_raises_error(self):
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"""Test invalid outcome value raises ValidationError"""
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with pytest.raises(ValidationError) as exc_info:
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ManualOutcomeSubmission(outcome='invalid_outcome')
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assert 'outcome' in str(exc_info.value).lower()
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def test_invalid_hit_location_raises_error(self):
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"""Test invalid hit location raises ValidationError"""
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with pytest.raises(ValidationError) as exc_info:
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ManualOutcomeSubmission(
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outcome=PlayOutcome.GROUNDBALL_C,
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hit_location='INVALID'
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)
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assert 'hit_location' in str(exc_info.value).lower()
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def test_all_valid_hit_locations_accepted(self):
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"""Test all valid hit locations are accepted"""
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valid_locations = ['1B', '2B', 'SS', '3B', 'LF', 'CF', 'RF', 'P', 'C']
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for location in valid_locations:
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submission = ManualOutcomeSubmission(
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outcome=PlayOutcome.GROUNDBALL_C,
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hit_location=location
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)
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assert submission.hit_location == location
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def test_none_hit_location_is_valid(self):
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"""Test None for hit_location is valid"""
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submission = ManualOutcomeSubmission(
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outcome=PlayOutcome.STRIKEOUT,
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hit_location=None
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)
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assert submission.hit_location is None
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