<自动化测试>之<使用unittest Python测试框架进行参数化测试>

时间:2022-01-21 16:32:59

最近在看视频时,虫师简单提到了简化自动化测试脚本用例中的代码量,而python中本身的参数化方法用来测试很糟糕,他在实际操作中使用了parameterized参数化...

有兴趣就查了下使用的方法,来分享给大家,使用Python测试框架进行参数化测试 下载安装https://github.com/wolever/parameterized或PIP install: $ pip install parameterized

parameterized了修正对于一切nose参数化测试,py.test参数化测试,单元测试参数化测试。

# test_math.py
from nose.tools import assert_equal
from parameterized import parameterized import unittest
import math @parameterized([
(2, 2, 4),
(2, 3, 8),
(1, 9, 1),
(0, 9, 0),
])
def test_pow(base, exponent, expected):
assert_equal(math.pow(base, exponent), expected) class TestMathUnitTest(unittest.TestCase):
@parameterized.expand([
("negative", -1.5, -2.0),
("integer", 1, 1.0),
("large fraction", 1.6, 1),
])
def test_floor(self, name, input, expected):
assert_equal(math.floor(input), expected)
在 nose (and nose2)下运行: $ nosetests -v test_math.py
test_math.test_pow(2, 2, 4) ... ok
test_math.test_pow(2, 3, 8) ... ok
test_math.test_pow(1, 9, 1) ... ok
test_math.test_pow(0, 9, 0) ... ok
test_floor_0_negative (test_math.TestMathUnitTest) ... ok
test_floor_1_integer (test_math.TestMathUnitTest) ... ok
test_floor_2_large_fraction (test_math.TestMathUnitTest) ... ok ----------------------------------------------------------------------
Ran 7 tests in 0.002s OK
As the package name suggests, nose is best supported and will be used for all further examples. With py.test (version 2.0 and above): $ py.test -v test_math.py
============================== test session starts ==============================
platform darwin -- Python 2.7.2 -- py-1.4.30 -- pytest-2.7.1
collected 7 items test_math.py::test_pow::[0] PASSED
test_math.py::test_pow::[1] PASSED
test_math.py::test_pow::[2] PASSED
test_math.py::test_pow::[3] PASSED
test_math.py::TestMathUnitTest::test_floor_0_negative
test_math.py::TestMathUnitTest::test_floor_1_integer
test_math.py::TestMathUnitTest::test_floor_2_large_fraction =========================== 7 passed in 0.10 seconds ============================
With unittest (and unittest2): $ python -m unittest -v test_math
test_floor_0_negative (test_math.TestMathUnitTest) ... ok
test_floor_1_integer (test_math.TestMathUnitTest) ... ok
test_floor_2_large_fraction (test_math.TestMathUnitTest) ... ok ----------------------------------------------------------------------
Ran 3 tests in 0.000s OK
(note: because unittest does not support test decorators, only tests created with @parameterized.expand will be executed)

在@parameterized与@parameterized.expand装饰接受列表或可迭代的元组或param(...),或调用它返回一个列表或可迭代, 下面是比较全的使用方法示例:

from parameterized import parameterized, param

# A list of tuples
@parameterized([
(2, 3, 5),
(3, 5, 8),
])
def test_add(a, b, expected):
assert_equal(a + b, expected) # A list of params
@parameterized([
param("", 10),
param("", 16, base=16),
])
def test_int(str_val, expected, base=10):
assert_equal(int(str_val, base=base), expected) # An iterable of params
@parameterized(
param.explicit(*json.loads(line))
for line in open("testcases.jsons")
)
def test_from_json_file(...):
... # A callable which returns a list of tuples
def load_test_cases():
return [
("test1", ),
("test2", ),
]
@parameterized(load_test_cases)
def test_from_function(name):
...

请注意,在使用迭代器或生成器时,在开始测试运行之前,所有项目都将被加载到内存中(我们明确地做到这一点,以确保生成器在多进程或多线程测试环境中精确地耗尽一次) 。

@parameterized装饰可用于测试类的方法,和独立的功能:

from parameterized import parameterized

class AddTest(object):
@parameterized([
(2, 3, 5),
])
def test_add(self, a, b, expected):
assert_equal(a + b, expected) @parameterized([
(2, 3, 5),
])
def test_add(a, b, expected):
assert_equal(a + b, expected)

并且@parameterized.expand可以用于在不能使用测试生成器的情况下生成测试方法(例如,当测试类是子类时unittest.TestCase):

import unittest
from parameterized import parameterized class AddTestCase(unittest.TestCase):
@parameterized.expand([
("2 and 3", 2, 3, 5),
("3 and 5", 2, 3, 5),
])
def test_add(self, _, a, b, expected):
assert_equal(a + b, expected)

会创建测试用例:

$ nosetests example.py
test_add_0_2_and_3 (example.AddTestCase) ... ok
test_add_1_3_and_5 (example.AddTestCase) ... ok ----------------------------------------------------------------------
Ran 2 tests in 0.001s OK

请注意,@parameterized.expand通过在测试类上创建新方法。如果第一个参数是一个字符串,该字符串将被添加到方法名称的末尾。例如,上面的测试用例会生成方法 test_add_0_2_and_3test_add_1_3_and_5

生成的测试用例的名称@parameterized.expand可以使用testcase_func_namekeyword参数自定义。该值应该是这三个参数的函数:testcase_funcparam_num,和params,应该返回测试用例的名字。 testcase_func将被测试的功能,param_num将参数列表中的测试用例参数的索引,和param (一个实例param)将被使用的参数。

import unittest
from parameterized import parameterized def custom_name_func(testcase_func, param_num, param):
return "%s_%s" %(
testcase_func.__name__,
parameterized.to_safe_name("_".join(str(x) for x in param.args)),
) class AddTestCase(unittest.TestCase):
@parameterized.expand([
(2, 3, 5),
(2, 3, 5),
], testcase_func_name=custom_name_func)
def test_add(self, a, b, expected):
assert_equal(a + b, expected)

创建测试用例:

$ nosetests example.py
test_add_1_2_3 (example.AddTestCase) ... ok
test_add_2_3_5 (example.AddTestCase) ... ok ----------------------------------------------------------------------
Ran 2 tests in 0.001s OK

param(...)助手类存储一个特定的测试情况的参数。它可以用于将关键字参数传递给测试用例:

from parameterized import parameterized, param

@parameterized([
param("", 10),
param("", 16, base=16),
])
def test_int(str_val, expected, base=10):
assert_equal(int(str_val, base=base), expected)

如果测试用例有一个docstring,则该测试用例的参数将追加到docstring的第一行。这个行为可以用doc_func参数控制:

from parameterized import parameterized

@parameterized([
(1, 2, 3),
(4, 5, 9),
])
def test_add(a, b, expected):
""" Test addition. """
assert_equal(a + b, expected) def my_doc_func(func, num, param):
return "%s: %s with %s" %(num, func.__name__, param) @parameterized([
(5, 4, 1),
(9, 6, 3),
], doc_func=my_doc_func)
def test_subtraction(a, b, expected):
assert_equal(a - b, expected)
$ nosetests example.py
Test addition. [with a=1, b=2, expected=3] ... ok
Test addition. [with a=4, b=5, expected=9] ... ok
0: test_subtraction with param(*(5, 4, 1)) ... ok
1: test_subtraction with param(*(9, 6, 3)) ... ok ----------------------------------------------------------------------
Ran 4 tests in 0.001s OK

仔细学习可以查看在github上有详尽的使用方法

from <自动化测试>之<使用unittest Python测试框架进行参数化测试> wolever & thanks!!!