207 lines
7.1 KiB
Python
207 lines
7.1 KiB
Python
"""
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测试接口模块
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"""
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import os
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import sys
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import unittest
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from unittest import mock
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from io import StringIO
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# 添加项目根目录到Python路径
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sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
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from src.interface.api import TFTStrategistAPI
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from src.interface.cli import TFTCommandLine
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from src.recommendation.recommendation_engine import TeamComposition
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from src.data_provider import DataLoader, DataQueryAPI
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class TestTFTStrategistAPI(unittest.TestCase):
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"""测试TFTStrategistAPI类"""
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def setUp(self):
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"""测试前准备"""
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# 模拟DataLoader
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self.mock_loader = mock.Mock()
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self.mock_loader.load_all_data.return_value = True
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# 模拟加载的数据
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self.job_data = {
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"version": "15.7",
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"data": [
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{
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"jobId": "10157",
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"name": "重装战士",
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"level": {
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"2": "16%最大生命值",
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"4": "32%最大生命值",
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}
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}
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]
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}
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self.race_data = {
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"version": "15.7",
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"data": [
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{
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"raceId": "10154",
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"name": "街头恶魔",
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"level": {
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"3": "+6% 生命值",
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"5": "+10% 生命值",
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}
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}
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]
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}
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self.chess_data = {
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"version": "15.7",
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"data": [
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{
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"chessId": "10275",
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"displayName": "布兰德",
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"raceIds": "10154",
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"jobIds": "10172",
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"price": "4"
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},
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{
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"chessId": "10276",
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"displayName": "阿利斯塔",
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"raceIds": "",
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"jobIds": "10157",
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"price": "3"
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}
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]
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}
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# 设置模拟数据返回
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self.mock_loader.get_data.side_effect = lambda data_type: {
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'job': self.job_data,
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'race': self.race_data,
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'chess': self.chess_data
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}.get(data_type)
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# 模拟DataQueryAPI
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self.mock_api = mock.Mock()
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self.mock_api.get_version.return_value = "15.7"
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self.mock_api.get_all_jobs.return_value = self.job_data["data"]
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self.mock_api.get_all_races.return_value = self.race_data["data"]
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self.mock_api.get_all_chess.return_value = self.chess_data["data"]
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self.mock_api.load_all_data.return_value = True
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# 模拟RecommendationEngine
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self.mock_recommendation_engine = mock.Mock()
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# 创建API实例，并注入模拟对象
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with mock.patch('src.interface.api.DataQueryAPI', return_value=self.mock_api):
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with mock.patch('src.interface.api.RecommendationEngine', return_value=self.mock_recommendation_engine):
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self.api = TFTStrategistAPI(use_local_data=True)
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def test_get_version(self):
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"""测试获取版本号"""
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version = self.api.get_version()
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self.assertEqual(version, "15.7")
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# 由于在初始化和测试中都会调用get_version，所以不再断言调用次数
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def test_customize_scoring(self):
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"""测试自定义评分系统"""
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# 捕获调用customize_scoring时的参数
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with mock.patch.object(self.api.scorer, 'customize_scoring') as mock_customize:
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self.api.customize_scoring(synergy_level_weight=2.0)
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mock_customize.assert_called_once_with(synergy_level_weight=2.0)
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def test_get_scoring_config(self):
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"""测试获取评分配置"""
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config = self.api.get_scoring_config()
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self.assertIn('synergy_level_weight', config)
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self.assertIn('synergy_count_weight', config)
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self.assertIn('chess_cost_weight', config)
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def test_recommend_team(self):
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"""测试推荐阵容"""
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# 创建模拟的TeamComposition
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team = TeamComposition()
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team.chess_list = [{"displayName": "布兰德", "price": "4"}]
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team.score = 10.5
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# 设置recommend_team的返回值
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self.mock_recommendation_engine.recommend_team.return_value = [team]
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# 调用API
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teams = self.api.recommend_team(population=8)
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# 验证结果
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self.assertEqual(len(teams), 1)
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self.assertEqual(teams[0]['score'], 10.5)
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self.assertEqual(len(teams[0]['chess_list']), 1)
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self.assertEqual(teams[0]['chess_list'][0]['displayName'], "布兰德")
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# 验证调用参数
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self.mock_recommendation_engine.recommend_team.assert_called_once_with(
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population=8,
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required_synergies=[],
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required_chess=[],
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max_results=5
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)
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def test_score_team(self):
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"""测试计算阵容评分"""
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# 设置score_team的返回值
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self.api.scorer.score_team = mock.Mock(return_value=15.5)
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# 创建阵容数据
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team_dict = {
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'chess_list': [{"displayName": "布兰德", "price": "4"}]
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}
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# 调用API
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score = self.api.score_team(team_dict)
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# 验证结果
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self.assertEqual(score, 15.5)
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class TestTFTCommandLine(unittest.TestCase):
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"""测试TFTCommandLine类"""
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@mock.patch('src.interface.cli.input', side_effect=['', ''])
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@mock.patch('sys.stdout', new_callable=StringIO)
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def test_run_without_input(self, mock_stdout, mock_input):
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"""测试不输入羁绊和棋子时的运行"""
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# 模拟RecommendationEngine返回空阵容列表
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mock_engine = mock.Mock()
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mock_engine.recommend_team.return_value = []
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# 模拟API
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mock_api = mock.Mock()
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mock_api.get_version.return_value = "15.7"
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# 使用模拟对象创建CLI实例
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with mock.patch('src.interface.cli.DataQueryAPI', return_value=mock_api):
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with mock.patch('src.interface.cli.RecommendationEngine', return_value=mock_engine):
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cli = TFTCommandLine()
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# 捕获参数解析错误
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with mock.patch('argparse.ArgumentParser.parse_args',
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return_value=mock.MagicMock(
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population=9, results=3,
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level_weight=1.0, count_weight=0.5, cost_weight=0.1)):
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cli.run()
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# 验证输出包含版本信息
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output = mock_stdout.getvalue()
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self.assertIn("云顶之弈阵容推荐器", output)
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self.assertIn("15.7", output) # 版本号
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self.assertIn("阵容人口: 9", output)
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# 验证推荐调用
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mock_engine.recommend_team.assert_called_once_with(
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population=9,
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required_synergies=[],
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required_chess=[],
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max_results=3
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)
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if __name__ == '__main__':
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unittest.main() |