assert

目录 1. @pytest.mark.parametrize 标记 1.1. empty_parameter_set_mark 选项 1.2. 多个标记组合 1.3. 标记测试模块 2. pytest_generate_tests 钩子方法 往期索引： https://www.cnblogs.com/luizyao/p/11771740.html 在实际工作中，测试用例可能需要支持多种场景，我们可以把和场景强相关的部分抽象成参数，通过对参数的赋值来驱动用例的执行； 参数化的行为表现在不同的层级上： fixture 的参数化：参考 4、fixtures：明确的、模块化的和可扩展的 -- fixture 的参数化 ； 测试用例的参数化：使用 @pytest.mark.parametrize 可以在测试用例、测试类甚至测试模块中标记多个参数或 fixture 的组合； 另外，我们也可以通过 pytest_generate_tests 这个钩子方法自定义参数化的方案； 1. @pytest.mark.parametrize 标记 @pytest.mark.parametrize 的根本作用是在 收集 测试用例的过程中，通过对 指定参数 的赋值来新增被标记对象的 调用（执行） ； 首先，我们来看一下它在源码中的定义： # _pytest/python.py def parametrize

I found this in a multi-threaded c application. The authors commented that it's used to make a thread crash in a custom assert function. GCC is fine with it, but clang issues the following warning: note: consider using __builtin_trap() or qualifying pointer with 'volatile' and also issues one of those, for each usage of the assert function: warning: indirection of non-volatile null pointer will be deleted, not trap What is going on here? Is __builtin_trap specific to clang? Should I use it? Writing to NULL address is not guaranteed to crash your program reliably, so GCC introduced __builtin

I'm evaluating "test frameworks" for automated system tests; so far I'm looking for a python framework. In py.test or nose I can't see something like the EXPECT macros I know from google testing framework. I'd like to make several assertions in one test while not aborting the test at the first failure. Am I missing something in these frameworks or does this not work? Does anybody have suggestions for python test framworks usable for automated system tests? I was wanting something similar for functional testing that I'm doing using nose. I eventually came up with this: def raw_print(str, *args)

what is the difference between java assert and if () {} else exit; ? can i just use if () {} else exit instead of assert ? A bit of google maybe ? " The main thing you should keep in mind is that the if-else statement should be used for program flow control and the assert keyword should only be used for testing purposes. You should never use asserts to actually perform any operation required for your application to work properly. According to Sun's official Java documentation: "Each assertion contains a boolean expression that you believe will be true when the assertion executes." " Read more:

so, here is my problem: I code in python, but I need to improve performance in some part of my code that are too slow. A good(and easy) solution seems to be using cython; I tried it and got good results. The issue is that I use assert statement in my python code. Before using cython, I could compile my python code with the -OO option, so that I can deliver a version not executing any assertion test, and still have the assert for debug. But the files that are compiled in cython seems to always execute the asserts. Is there some options that can be passed to cython compilation to remove(or not

I have a function that returns a tuple that, among others, contains a float value. Usually I use assertAlmostEquals to compare those, but this does not work with tuples. Also, the tuple contains other data-types as well. Currently I am asserting every element of the tuple individually, but that gets too much for a list of such tuples. Is there any good way to write assertions for such cases? Consider this function: def f(a): return [(1.0/x, x * 2) for x in a] Now I want to write a test for it: def testF(self): self.assertEqual(f(range(1,3)), [(1.0, 2), (0.5, 4)]) This will fail because the

#####了解异常##### # IndexError 索引超出序列的范围 # KeyError 字典中查找一个不存在的关键字 # NameError 尝试访问一个不存在的变量 # IndentationError 缩进错误 # AttributeError 尝试访问未知的对象属性 # StopIteration 迭代器没有更多的值 # AssertionError 断言语句（assert）失败, assert 5>3 #对,不报错;assert 5<2 #错,报错 # ### 异常处理 try: 　　code1 except: 　　code2 把可能存在问题的代码放到try这个代码块之后, 如果出现异常直接执行except这个代码块里面内容 如果没有异常,就不走except # 2.带有分支的异常处理 try: 　　dic = {"a":1} 　　print(dic["b"]) #except后可以跟系统错误类型名,若是这种错误类型,则执行这条语句 except IndexError: 　　print("我是IndexError错误类") except KeyError: 　　print("我是KeyError错误类") except: 　　print("有异常错误") # 4.关于异常处理的扩展写法 # try ... finally 如果有报错,报错让你报