AI 协作编写 Pytest 单元测试：覆盖率提升实战记录

核心模块测试用例生成实战

用户服务测试用例生成

首先，我向 AI 提供了用户服务的核心代码，以便理解上下文：

# app/services/user_service.py
class UserService:
    def __init__(self, db_session):
        self.db = db_session

    def create_user(self, user_data):
        """创建新用户"""
        if not self._validate_user_data(user_data):
            raise ValueError("Invalid user data")
        
        existing_user = self.db.query(User).filter_by(
            email=user_data['email']
        ).first()
        if existing_user:
            raise UserAlreadyExistsError("User already exists")
        
        hashed_password = self._hash_password(user_data['password'])
        user = User(
            email=user_data['email'],
            username=user_data['username'],
            password_hash=hashed_password,
            created_at=datetime.utcnow()
        )
        try:
            self.db.add(user)
            self.db.commit()
            return user
        except Exception as e:
            self.db.rollback()
            raise DatabaseError(f"Failed to create user: {str(e)}")

    def authenticate_user(self, email, password):
        """用户认证"""
        user = self.db.query(User).filter_by(email=email).first()
        if not user:
            raise UserNotFoundError("User not found")
        if not self._verify_password(password, user.password_hash):
            raise InvalidCredentialsError("Invalid credentials")
        
        user.last_login = datetime.utcnow()
        self.db.commit()
        return user

AI 生成的测试用例覆盖了多个维度，包括 Fixture 定义和参数化测试：

# tests/unit/test_user_service.py
import pytest
from unittest.mock import Mock, patch
from datetime import datetime
from app.services.user_service import UserService
from app.models.user import User
from app.exceptions import (
    UserAlreadyExistsError,
    UserNotFoundError,
    InvalidCredentialsError,
    DatabaseError
)

class TestUserService:
    @pytest.fixture
    def mock_db_session(self):
        """模拟数据库会话"""
        return Mock()

    @pytest.fixture
    def user_service(self, mock_db_session):
        """用户服务实例"""
        return UserService(mock_db_session)

    @pytest.fixture
    def valid_user_data(self):
        """有效用户数据"""
        return {
            'email': '[email protected]',
            'username': 'testuser',
            'password': 'SecurePass123!'
        }

    def test_create_user_success(self, user_service, valid_user_data):
        """测试正常创建用户流程"""
        with patch.object(user_service.db, 'query') as mock_query:
            mock_query.return_value.filter_by.return_value.first.return_value = None
            with patch.object(user_service, '_hash_password', return_value='hashed'):
                result = user_service.create_user(valid_user_data)
                assert result is not None
                assert result.email == valid_user_data['email']

测试结果分析与优化

最终结果令人振奋：测试覆盖率从 45% 提升到 85%，新增测试用例 312 个，发现并修复了 23 个潜在 bug。更重要的是，整个过程的效率提升了约 3 倍，让我有更多时间专注于复杂业务逻辑的测试设计。

这次协作不仅提升了代码质量，也让我重新审视了 AI 在软件开发中的价值。关键在于将 AI 作为辅助工具，而非完全依赖，保持对测试设计的把控权，确保生成的用例符合实际业务需求。