Pytest和Nose的多维参数化测试
项目描述
在Python中编写参数化测试有多种方法。Unittest最近提供了一些支持，Nose允许产生测试用例，Pytest有内置的参数化支持，而优秀的nose_parameterized包增强了大多数测试框架的这些功能。
testdimensions提供了一种方便的方法，在简单场景中编写多维测试矩阵。如果您的函数接受多个参数，并且想要测试参数组合的笛卡尔积，那么testdimensions就是为您准备的。
指定您的测试为一个表格，其中
Y轴标签是倒数第三个参数的值
X轴标签是倒数第二个参数的值
单元格值是预期值（最后一个参数）
列之间由两个空格分隔（确保所有行都如此）
# test_math.py
@pytest_mark_dimensions('base,exponent,expected', '''
# y: base
# x: exponent
# cell: expected
2 3 9
0 0 0 0
1 1 1 1
2 4 8 512
''')
def test_pow(base, exponent, expected):
assert math.pow(base, exponent) == expected
@pytest_mark_dimensions('input,function,expected', '''
round math.floor math.ceil
-1.5 -2.0 -2.0 -1.0
1.0 1.0 1.0 1.0
1.6 2.0 1.0 2.0
''')
def test_round_floor_ceil(input, function, expected):
assert function(input) == expected输出
$ pytest -v =========================== test session starts =============================== platform linux -- Python 3.5.2, pytest-3.0.3, py-1.4.31, pluggy-0.4.0 collected 18 items test_math.py::test_pow[0-2-0] PASSED test_math.py::test_pow[0-3-0] PASSED test_math.py::test_pow[0-9-0] PASSED test_math.py::test_pow[1-2-1] PASSED test_math.py::test_pow[1-3-1] PASSED test_math.py::test_pow[1-9-1] PASSED test_math.py::test_pow[2-2-4] PASSED test_math.py::test_pow[2-3-8] PASSED test_math.py::test_pow[2-9-512] PASSED test_math.py::test_round_floor_ceil[-1.5-function0--2.0] PASSED test_math.py::test_round_floor_ceil[-1.5-function1--2.0] PASSED test_math.py::test_round_floor_ceil[-1.5-function2--1.0] PASSED test_math.py::test_round_floor_ceil[1.0-function3-1.0] PASSED test_math.py::test_round_floor_ceil[1.0-function4-1.0] PASSED test_math.py::test_round_floor_ceil[1.0-function5-1.0] PASSED test_math.py::test_round_floor_ceil[1.6-function6-2.0] PASSED test_math.py::test_round_floor_ceil[1.6-function7-1.0] PASSED test_math.py::test_round_floor_ceil[1.6-function8-2.0] PASSED ============================ 18 passed in 0.03 seconds ========================
安装
$ pip install testdimensions
兼容性
Py2.6 |
Py2.7 |
Py3.3 |
Py3.4 |
Py3.5 |
PyPy |
|
|---|---|---|---|---|---|---|
nose |
no |
yes |
no |
no |
yes |
no |
nose2 |
no |
no |
no |
no |
no |
no |
py.test |
未测试 |
yes |
未测试 |
未测试 |
yes |
未测试 |
unittest |
no |
no |
no |
no |
no |
no |
unittest2 |
no |
no |
no |
no |
no |
no |
依赖关系
nose_parameterized 用于Nose支持
详尽的用法示例
@pytest_mark_dimensions 装饰器是@pytest.mark.parametrize的扩展，其第一个参数是一个逗号分隔的测试参数列表。第二个参数是一个定义实际测试的多行字符串。您还可以使用关键字参数将值注入测试的全局命名空间。
要创建超过二维的测试，只需定义多个表，并在其中穿插额外参数的值。
@pytest_mark_dimensions('a,b,expected', '''
-10 0 9 million
-9 -19 -9 0 999991
0 -10 0 9 million
10 0 10 19 1000010
''',
million=1000000)
def test_add(a, b, expected):
assert a + b == expected
@pytest_mark_dimensions('operation,a,b,expected', '''
operation = operator.sub
-10 0 9 million
-9 1 -9 -18 -1000009
0 10 0 -9 -million
10 20 10 1 -999990
operation = operator.add
-10 0 9 million
-9 -19 -9 0 999991
0 -10 0 9 million
10 0 10 19 1000010
operation = operator.mul
-10 0 9 million
-9 90 0 -81 -9000000
0 0 0 0 0
10 -100 0 90 10000000
''',
million=1000000)
def test_arithmetic_operations(operation, a, b, expected):
assert operation(a, b) == expected对于Nose支持，您需要安装nose_parameterized并使用@nosedimensions装饰器
@nosedimensions('a,b,expected', '''
-10 0 9 million
-9 -19 -9 0 999991
0 -10 0 9 million
10 0 10 19 1000010
''',
million=1000000)
def test_add(a, b, expected):
assert a + b == expected
@nosedimensions('operation,a,b,expected', '''
operation = operator.sub
-10 0 9 million
-9 1 -9 -18 -1000009
0 10 0 -9 -million
10 20 10 1 -999990
operation = operator.add
-10 0 9 million
-9 -19 -9 0 999991
0 -10 0 9 million
10 0 10 19 1000010
operation = operator.mul
-10 0 9 million
-9 90 0 -81 -9000000
0 0 0 0 0
10 -100 0 90 10000000
''',
million=1000000)
def test_arithmetic_operations(operation, a, b, expected):
assert operation(a, b) == expected请注意，您仍然需要像使用Pytest一样枚举测试参数。
关闭
testdimensions-0.0.1.tar.gz的哈希值
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|---|---|---|
| SHA256 | 1f110d2150609c2cb7feda5b03fedec4f70b8eb58fc7684e6d3559f3d36982cb |
|
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