Python批量测试案例怎么编写？

本文目录导读：

1. 使用unittest框架
2. 使用参数化测试（第三方库）
3. 使用pytest框架（推荐）
4. 完整的批量测试示例
5. 使用建议
6. 运行方式

我来介绍几种Python批量测试案例的编写方法：

使用unittest框架

import unittest
import math
# 批量测试数学函数
class TestMathFunctions(unittest.TestCase):
    def test_power(self):
        """批量测试乘方运算"""
        test_cases = [
            (2, 3, 8),
            (3, 2, 9),
            (10, 0, 1),
            (2, -1, 0.5),
            (5, 2, 25)
        ]
        for base, exp, expected in test_cases:
            with self.subTest(f"测试 {base}^{exp}"):
                result = pow(base, exp)
                self.assertEqual(result, expected)
    def test_sqrt(self):
        """批量测试平方根"""
        test_cases = [
            (4, 2),
            (9, 3),
            (16, 4),
            (25, 5),
            (100, 10)
        ]
        for number, expected in test_cases:
            with self.subTest(f"sqrt({number})"):
                result = math.sqrt(number)
                self.assertAlmostEqual(result, expected)
# 批量测试字符串处理
class TestStringMethods(unittest.TestCase):
    def test_string_operations(self):
        """批量测试字符串操作"""
        test_data = [
            # (input_string, expected_length, expected_upper)
            ("hello", 5, "HELLO"),
            ("Python", 6, "PYTHON"),
            ("test123", 7, "TEST123"),
            ("", 0, ""),
            ("ABC", 3, "ABC")
        ]
        for input_str, exp_len, exp_upper in test_data:
            with self.subTest(f"测试: '{input_str}'"):
                self.assertEqual(len(input_str), exp_len)
                self.assertEqual(input_str.upper(), exp_upper)
# 批量测试数据处理
class TestDataProcessing(unittest.TestCase):
    def test_calculate_average(self):
        """批量测试平均值计算"""
        test_cases = [
            ([1, 2, 3, 4, 5], 3),
            ([10, 20, 30], 20),
            ([0, 0, 0], 0),
            ([5], 5),
            ([1, 2, 3, 4], 2.5)
        ]
        for numbers, expected_avg in test_cases:
            with self.subTest(f"平均值: {numbers}"):
                avg = sum(numbers) / len(numbers) if numbers else 0
                self.assertAlmostEqual(avg, expected_avg)
if __name__ == '__main__':
    unittest.main()

使用参数化测试（第三方库）

pip install parameterized

from parameterized import parameterized
import unittest
class TestParameterized(unittest.TestCase):
    @parameterized.expand([
        ("case1", 2, 3, 6),
        ("case2", 0, 5, 0),
        ("case3", -2, 3, -6),
        ("case4", 2.5, 2, 5.0),
        ("case5", 10, 0, 0),
    ])
    def test_multiply(self, name, a, b, expected):
        """参数化乘法测试"""
        result = a * b
        self.assertEqual(result, expected)
    @parameterized.expand([
        ("valid", "user@example.com", True),
        ("invalid_no_at", "userexample.com", False),
        ("invalid_dot", "user@com", False),
        ("empty", "", False),
        ("valid_complex", "user.name+tag@example.co.uk", True),
    ])
    def test_email_validation(self, name, email, expected_valid):
        """参数化邮箱验证测试"""
        import re
        pattern = r'^[\w\.-]+@[\w\.-]+\.\w+$'
        result = bool(re.match(pattern, email))
        self.assertEqual(result, expected_valid)
if __name__ == '__main__':
    unittest.main()

使用pytest框架（推荐）

import pytest
import json
# 测试数据
test_data = [
    (1, 2, 3),
    (5, 5, 10),
    (-1, 1, 0),
    (0, 0, 0),
    (100, 200, 300)
]
# 简单的参数化测试
@pytest.mark.parametrize("a,b,expected", test_data)
def test_addition(a, b, expected):
    """批量测试加法"""
    result = a + b
    assert result == expected
# 测试用户数据处理
class TestUserData:
    @pytest.mark.parametrize("user_data,expected_valid", [
        ({"name": "张三", "age": 25, "email": "zhang@test.com"}, True),
        ({"name": "", "age": 25, "email": "test@test.com"}, False),
        ({"name": "李四", "age": -1, "email": "li@test.com"}, False),
        ({"name": "王五", "age": 150, "email": "wang@test.com"}, False),
        ({"name": "赵六", "age": 30, "email": ""}, False),
    ])
    def test_user_validation(self, user_data, expected_valid):
        """批量测试用户数据验证"""
        def validate_user(data):
            if not data.get("name"):
                return False
            if not (0 < data.get("age", 0) < 120):
                return False
            if not data.get("email"):
                return False
            return True
        result = validate_user(user_data)
        assert result == expected_valid
# 从文件读取测试数据
def load_test_data():
    """从JSON文件加载测试数据"""
    data = [
        {"input": "hello", "expected": "HELLO"},
        {"input": "world", "expected": "WORLD"},
        {"input": "python", "expected": "PYTHON"},
        {"input": "test", "expected": "TEST"},
    ]
    return [(d["input"], d["expected"]) for d in data]
@pytest.mark.parametrize("input_str,expected", load_test_data())
def test_uppercase_from_data(input_str, expected):
    """从数据源加载测试数据"""
    result = input_str.upper()
    assert result == expected
# 组合参数化测试
@pytest.mark.parametrize("operation", ["add", "subtract", "multiply"])
@pytest.mark.parametrize("a,b", [(2, 3), (5, 5), (10, 0)])
def test_operations(operation, a, b):
    """组合参数化测试"""
    if operation == "add":
        result = a + b
    elif operation == "subtract":
        result = a - b
    elif operation == "multiply":
        result = a * b
    # 验证基本运算
    assert isinstance(result, (int, float))

完整的批量测试示例

import unittest
import pytest
from typing import List, Tuple
# 要测试的业务函数
def calculate_discount(price: float, quantity: int) -> float:
    """计算折扣价格"""
    if price < 0 or quantity < 0:
        raise ValueError("价格和数量不能为负数")
    total = price * quantity
    # 批量折扣
    if quantity >= 100:
        total *= 0.8  # 20% off
    elif quantity >= 50:
        total *= 0.9  # 10% off
    elif quantity >= 10:
        total *= 0.95  # 5% off
    return round(total, 2)
class TestDiscountCalculation:
    # 测试数据： (价格, 数量, 期望折扣价)
    test_cases = [
        (100, 1, 100.0),      # 无折扣
        (100, 10, 950.0),     # 5%折扣
        (100, 50, 4500.0),    # 10%折扣
        (100, 100, 8000.0),   # 20%折扣
        (50, 5, 250.0),       # 无折扣
        (20, 200, 3200.0),    # 20%折扣
        (1000, 1, 1000.0),    # 高价单品
        (0.99, 100, 79.2),    # 低价批量
    ]
    @pytest.mark.parametrize("price,quantity,expected", test_cases)
    def test_discount_cases(self, price, quantity, expected):
        """批量测试折扣计算"""
        result = calculate_discount(price, quantity)
        assert result == expected, f"价格{price}*数量{quantity}应得{expected}，实际{result}"
    @pytest.mark.parametrize("price,quantity", [
        (-100, 10),
        (100, -5),
        (-1, -1)
    ])
    def test_invalid_input(self, price, quantity):
        """测试无效输入"""
        with pytest.raises(ValueError):
            calculate_discount(price, quantity)
# 批量测试报告生成
def generate_test_report(results: List[Tuple[str, bool, str]]):
    """生成测试报告"""
    print("\n" + "="*50)
    print("测试报告")
    print("="*50)
    passed = 0
    failed = 0
    for test_name, result, error_msg in results:
        status = "✓" if result else "✗"
        print(f"{status} {test_name}: {'通过' if result else f'失败 - {error_msg}'}")
        if result:
            passed += 1
        else:
            failed += 1
    print("="*50)
    print(f"总计: {len(results)} | 通过: {passed} | 失败: {failed}")
    print("="*50)
# 主函数
if __name__ == "__main__":
    # 使用unittest运行
    print("使用unittest运行:")
    unittest.main(argv=[''], exit=False)
    # 使用pytest运行
    print("\n\n使用pytest运行:")
    pytest.main(['-v', __file__])
    # 自定义测试运行
    print("\n\n自定义测试批量运行:")
    test_runner = TestDiscountCalculation()
    test_results = []
    for price, quantity, expected in TestDiscountCalculation.test_cases:
        try:
            test_runner.test_discount_cases(price, quantity, expected)
            test_results.append((f"折扣测试({price},{quantity})", True, ""))
        except AssertionError as e:
            test_results.append((f"折扣测试({price},{quantity})", False, str(e)))
    generate_test_report(test_results)

使用建议

1. 对于小型项目：使用unittest即可
2. 对于中型项目：推荐pytest，更简洁灵活
3. 需要大量重复测试：使用parameterized或@pytest.mark.parametrize
4. 测试数据复杂：从外部文件（JSON/CSV/Excel）读取测试数据
5. 测试组织：按功能模块分组，每个测试类的测试用例保持相关

运行方式

# 运行unittest
python -m unittest test_file.py
# 运行pytest（更详细输出）
pytest -v test_file.py
# 运行特定测试类
pytest -v test_file.py::TestDiscountCalculation

这些方法可以让你高效地编写和管理批量测试案例,提高测试覆盖率和代码质量。

标签： Pytest