测试数据驱动
Here is an example pytest_generate_tests
function implementing a parametrization scheme similar to Michael Foord’s unittest parametrizer but in a lot less code:,unittest也有这样的设计:https://github.com/testing-cabal/unittest-ext/blob/master/params.py
# content of ./test_parametrize.py
import pytest
def pytest_generate_tests(metafunc):
# called once per each test function
funcarglist = metafunc.cls.params[metafunc.function.__name__]
argnames = sorted(funcarglist[0])
metafunc.parametrize(argnames, [[funcargs[name] for name in argnames]
for funcargs in funcarglist])
class TestClass(object):
# a map specifying multiple argument sets for a test method
params = {
'test_equals': [dict(a=1, b=2), dict(a=3, b=3), ],
'test_zerodivision': [dict(a=1, b=0), ],
}
def test_equals(self, a, b):
assert a == b
def test_zerodivision(self, a, b):
with pytest.raises(ZeroDivisionError):
a / b
Our test generator looks up a class-level definition which specifies which argument sets to use for each test function. Let’s run it:
$ pytest -q
F.. [100%]
================================= FAILURES =================================
________________________ TestClass.test_equals[1-2] ________________________
self = <test_parametrize.TestClass object at 0xdeadbeef>, a = 1, b = 2
def test_equals(self, a, b):
> assert a == b
E assert 1 == 2
E -1
E +2
test_parametrize.py:18: AssertionError
1 failed, 2 passed in 0.12 seconds
这不就是数据驱动嘛,脚本只要写一条,有多条数据就有多条用例
原文地址:https://blog.csdn.net/u012897401/article/details/86598614
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