"""Tests for high_level_api module"""
import pytest
import pandas as pd
from unittest.mock import Mock, MagicMock
from jvlink_mcp_server.database.high_level_api import (
get_favorite_performance,
get_jockey_stats,
get_frame_stats,
get_horse_history,
get_sire_stats,
VENUE_CODES,
GRADE_CODES
)
@pytest.fixture
def mock_db():
"""モックデータベース接続を作成"""
db = Mock()
return db
class TestGetFavoritePerformance:
"""get_favorite_performance関数のテスト"""
def test_basic_query(self, mock_db):
"""基本的なクエリのテスト"""
# モックデータを準備
mock_result = pd.DataFrame({
'total': [100],
'wins': [30],
'places_2': [60],
'places_3': [80]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
# 関数実行
result = get_favorite_performance(mock_db, ninki=1)
# 検証
assert result['total'] == 100
assert result['wins'] == 30
assert result['win_rate'] == 30.0
assert result['place_rate_2'] == 60.0
assert result['place_rate_3'] == 80.0
assert '1番人気' in result['conditions']
def test_with_venue(self, mock_db):
"""競馬場指定のテスト"""
mock_result = pd.DataFrame({
'total': [50],
'wins': [20],
'places_2': [30],
'places_3': [40]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_favorite_performance(mock_db, venue='東京', ninki=1)
# クエリに東京競馬場コード（05）が含まれているか確認
call_args = mock_db.execute_safe_query.call_args[0][0]
assert "JyoCD = '05'" in call_args
assert '東京競馬場' in result['conditions']
def test_with_grade(self, mock_db):
"""グレード指定のテスト"""
mock_result = pd.DataFrame({
'total': [20],
'wins': [10],
'places_2': [15],
'places_3': [18]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_favorite_performance(mock_db, ninki=1, grade='G1')
# クエリにG1コード（A）が含まれているか確認
call_args = mock_db.execute_safe_query.call_args[0][0]
assert "GradeCD = 'A'" in call_args
assert 'NL_RA' in call_args # グレード指定時はNL_RAと結合
def test_zero_results(self, mock_db):
"""結果が0件の場合のテスト"""
mock_result = pd.DataFrame({
'total': [0],
'wins': [0],
'places_2': [0],
'places_3': [0]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_favorite_performance(mock_db, ninki=1)
assert result['total'] == 0
assert result['win_rate'] == 0.0
def test_invalid_venue(self, mock_db):
"""不正な競馬場名のテスト"""
with pytest.raises(ValueError, match="不明な競馬場名"):
get_favorite_performance(mock_db, venue='無効な競馬場')
def test_ninki_zero_padding(self, mock_db):
"""人気番号のゼロパディングテスト"""
mock_result = pd.DataFrame({
'total': [10],
'wins': [1],
'places_2': [2],
'places_3': [3]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_favorite_performance(mock_db, ninki=5)
# クエリに05（ゼロパディング）が含まれているか確認
call_args = mock_db.execute_safe_query.call_args[0][0]
assert "Ninki = '05'" in call_args
class TestGetJockeyStats:
"""get_jockey_stats関数のテスト"""
def test_basic_query(self, mock_db):
"""基本的なクエリのテスト"""
mock_result = pd.DataFrame({
'jockey_name': ['ルメール'],
'total_rides': [200],
'wins': [50],
'places_2': [100],
'places_3': [140]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_jockey_stats(mock_db, jockey_name='ルメール')
assert result['jockey_name'] == 'ルメール'
assert result['total_rides'] == 200
assert result['wins'] == 50
assert result['win_rate'] == 25.0
def test_multiple_matches(self, mock_db):
"""複数の騎手がマッチした場合のテスト"""
mock_result = pd.DataFrame({
'jockey_name': ['武豊', '武幸四郎'],
'total_rides': [300, 100],
'wins': [60, 20],
'places_2': [150, 50],
'places_3': [210, 70]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_jockey_stats(mock_db, jockey_name='武')
# 合計を計算
assert result['total_rides'] == 400
assert result['wins'] == 80
assert result['jockey_name'] == '武豊' # 最も騎乗回数が多い
assert len(result['matched_jockeys']) == 2
def test_no_results(self, mock_db):
"""結果が0件の場合のテスト"""
mock_result = pd.DataFrame()
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_jockey_stats(mock_db, jockey_name='存在しない騎手')
assert result['total_rides'] == 0
assert result['win_rate'] == 0.0
class TestGetFrameStats:
"""get_frame_stats関数のテスト"""
def test_basic_query(self, mock_db):
"""基本的なクエリのテスト"""
mock_result = pd.DataFrame({
'wakuban': ['1', '2', '3', '4', '5', '6', '7', '8'],
'total': [100, 100, 100, 100, 100, 100, 100, 100],
'wins': [10, 12, 15, 13, 14, 11, 9, 16],
'places_2': [25, 28, 30, 27, 29, 26, 24, 31],
'places_3': [40, 42, 45, 43, 44, 41, 39, 46]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
df = get_frame_stats(mock_db)
assert len(df) == 8
assert 'wakuban' in df.columns
assert 'win_rate' in df.columns
assert df['win_rate'].iloc[0] == 10.0 # 10/100 * 100
def test_with_conditions(self, mock_db):
"""条件付きクエリのテスト"""
mock_result = pd.DataFrame({
'wakuban': ['1'],
'total': [50],
'wins': [5],
'places_2': [15],
'places_3': [25]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
df = get_frame_stats(mock_db, venue='東京', distance=1600)
call_args = mock_db.execute_safe_query.call_args[0][0]
assert "JyoCD = '05'" in call_args
assert "Kyori = '1600'" in call_args
def test_empty_result(self, mock_db):
"""結果が空の場合のテスト"""
mock_result = pd.DataFrame()
mock_db.execute_safe_query = Mock(return_value=mock_result)
df = get_frame_stats(mock_db)
assert df.empty
assert list(df.columns) == ['wakuban', 'total', 'wins', 'places_2', 'places_3',
'win_rate', 'place_rate_2', 'place_rate_3']
class TestGetHorseHistory:
"""get_horse_history関数のテスト"""
def test_basic_query(self, mock_db):
"""基本的なクエリのテスト"""
mock_result = pd.DataFrame({
'race_date': ['2023-0521', '2023-0430'],
'venue_code': ['05', '06'],
'race_name': ['日本ダービー', '皐月賞'],
'distance': ['2400', '2000'],
'finish': ['01', '02'],
'popularity': ['03', '02'],
'jockey': ['ルメール', '武豊'],
'time': ['022434', '020112'],
'horse_name': ['テスト馬', 'テスト馬']
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
df = get_horse_history(mock_db, horse_name='テスト馬')
assert len(df) == 2
assert df['venue'].iloc[0] == '東京'
assert df['venue'].iloc[1] == '中山'
assert df['finish'].iloc[0] == 1 # ゼロパディング除去
assert df['popularity'].iloc[0] == 3
def test_no_results(self, mock_db):
"""結果が0件の場合のテスト"""
mock_result = pd.DataFrame()
mock_db.execute_safe_query = Mock(return_value=mock_result)
df = get_horse_history(mock_db, horse_name='存在しない馬')
assert df.empty
class TestGetSireStats:
"""get_sire_stats関数のテスト"""
def test_basic_query(self, mock_db):
"""基本的なクエリのテスト"""
mock_result = pd.DataFrame({
'sire_name': ['ディープインパクト'],
'total_runs': [1000],
'wins': [200],
'places_2': [400],
'places_3': [600]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_sire_stats(mock_db, sire_name='ディープインパクト')
assert result['sire_name'] == 'ディープインパクト'
assert result['total_runs'] == 1000
assert result['wins'] == 200
assert result['win_rate'] == 20.0
def test_with_conditions(self, mock_db):
"""条件付きクエリのテスト"""
mock_result = pd.DataFrame({
'sire_name': ['ディープインパクト'],
'total_runs': [500],
'wins': [100],
'places_2': [200],
'places_3': [300]
})
mock_db.execute_safe_query = Mock(return_value=mock_result)
result = get_sire_stats(
mock_db,
sire_name='ディープインパクト',
venue='東京',
distance=1600
)
call_args = mock_db.execute_safe_query.call_args[0][0]
assert "Bamei1 LIKE '%ディープインパクト%'" in call_args
assert "JyoCD = '05'" in call_args
assert "Kyori = '1600'" in call_args
class TestConstants:
"""定数のテスト"""
def test_venue_codes(self):
"""競馬場コードのテスト"""
assert VENUE_CODES['東京'] == '05'
assert VENUE_CODES['中山'] == '06'
assert len(VENUE_CODES) == 10
def test_grade_codes(self):
"""グレードコードのテスト"""
assert GRADE_CODES['G1'] == 'A'
assert GRADE_CODES['G2'] == 'B'
assert GRADE_CODES['G3'] == 'C'
assert GRADE_CODES['A'] == 'A' # 直接指定も可能
