python中的单元测试-如果不测试代码则在python中进行单元测试没有人会

python中的单元测试_如果不测试代码，则在python中进⾏单元测试没有⼈会python中的单元测试Catchbugsbeforeyouevenwritethem甚⾄在编写错误之前就将其捕获Pythonisamulti-purposelanguagethatisusedforeverythingbackend.Inthisarticle,IwillteachyoutoperformbasicunittestinginPython,howtomockmodules,andmakesureyourcodeisclean.Python是⼀种⽤于所有后端的多⽤途语⾔。在本⽂中，我将教您使⽤Python执⾏基本的单元测试，如何模拟模块并确保代码⼲净。什么是单元测试？(WhatisUnit-testing?)Unit-testingisoneofthewaystotestyourcode.Otherwaysincludefunctionaltesting,integrationtesting,regressiontestingandsoon.Testingisvitaltoanylargercodebase,asitletsyouiterateandperformchangesquickly,withoutworryingtomuchaboutwhatisgoingtobreak.单元测试是测试代码的⽅法之⼀。其他⽅式包括功能测试，集成测试，回归测试等等。测试对于任何更⼤的代码库都是⾄关重要的，因为它使您可以快速迭代并执⾏更改，⽽不必担⼼会发⽣什么。Unit-testingisthelowesttestingmethodontheabstractionlevel.Unit-testingisconcernedwithtestingindividualmodulesandfunctionsinisolation.Thatis,bymakingsureallthepartsofyoursystemworkcorrectly,youcanmaketheassumptionthatthewholesystemisworkingok.单元测试是抽象级别上最低的测试⽅法。单元测试是关于隔离测试单独的模块和功能。也就是说，通过确保系统的所有部分正常⼯作，您可以假设整个系统都可以正常⼯作。Thatis,inidealworld,ofcourse.Whileunit-testingisveryvaluable,thewholesystemisnotmerelyasumofitsparts:evenifeveryfunctionisworkingasintended,youwillstillneedtotesthowwelldotheyfittogether(whichisoutofscopeofthisarticle).就是说，在理想世界中。尽管单元测试⾮常有价值，但是整个系统不仅仅是其各个部分的总和：即使每个功能都按预期⼯作，您仍然需要测试它们之间的配合程度(这超出了本⽂的范围))。单元测试与TDD有何关系？(HowdoesUnit-testingrelatetoTDD?)Unit-testingisoneofthefoundationsofTDD.TDDstandsforTestDrivenDevelopment,andisamethodologyforproducingqualitysoftware.Inessence,itallboilsdowntothese:单元测试是TDD的基础之⼀。TDD代表“测试驱动开发”，是⼀种⽣产⾼质量软件的⽅法。从本质上讲，这全都归结为以下⼏点：1.Writetestsfirst.Thinkabouthowdifferentpartsofyoursystemworkinisolationandwriteteststhatvalidatetheirintendedbehaviour.Yourtestsmustfail,becauseyouhavenotwrittenanyactualcodeyet.⾸先编写测试。考虑⼀下系统的不同部分如何隔离⼯作，并编写验证其预期⾏为的测试。测试必须失败，因为您尚未编写任何实际代码。2.Writejustenoughcodetomakethetestspass.编写⾜够的代码以使测试通过。3.Refactorwhatyoujustwrote.重构您刚刚写的内容。4.Gotostep1.转到步骤1。Thatisit!Thewholecycletakesacoupleofminutes,butthissimpletechniquewillmakesureyoursystemis(1)workingaccordingtothespecsand(2)istestable.ButtogetstartedwithTDD,youneedtomasterbasicunit-testingfirst.这就对了！整个周期需要花费⼏分钟，但是这种简单的技术将确保您的系统(1)根据规范⼯作，并且(2)是可测试的。但是要开始使⽤TDD，您需要⾸先掌握基本的单元测试。unittest模块(unittestmodule)Unit-testinginPythonisavailableoutoftheboxwiththeunittestmodule.Wewilllearnunit-testingbydevelopingourownfactorialfunction.Togetstarted,openanewPythonfileaddwritethiscodeitit:Python中的单元测试可与unittest模块⼀起使⽤。我们将通过开发我们⾃⼰的阶乘函数来学习单元测试。⾸先，打开⼀个新的Python⽂件，添加以下代码：importunittestclassMyTestCase(unittest.TestCase):deftest_something(self):self.assertEqual(True,False)if__name__=='__main__':unittest.main()Online1youcannoticetheimportedunittestmodule.Onlines4-6wedefineatestcasebyextendingtheTestCaseclass.Init,weonlyhave1testatthemoment,thetest_something.Itisimportantthattestsareprefixedwithtest_,sothatthetestrunnercanfindthem.Finally,onlines9-10weexecutethetests.Ifyoutryrunningthisfilenow,thetestwillfail:在第1⾏上，您可以注意到导⼊的unittest模块。在第4-6⾏，我们通过扩展TestCase类来定义测试⽤例。其中，我们⽬前只有1个测试，即test_something。重要的是，测试必须以test_作为前缀，以便测试运⾏器可以找到它们。最后，在9-10⾏，我们执⾏测试。如果尝试⽴即运⾏此⽂件，则测试将失败：======================================================================FAIL:test_something(__main__.MyTestCase)----------------------------------------------------------------------Traceback(mostrecentcalllast):File"main.py",line6,intest_somethingself.assertEqual(True,False)AssertionError:True!=False----------------------------------------------------------------------Ran1testin0.001sFAILED(failures=1)Thatishappeningbecauseonline6weareassertingthatTrueandFalseareequal,whichisobviouslyfalse.Let'schangethattotestour(unwritten!)function:之所以会这样，是因为在第6⾏中，我们断⾔True和False相等，这显然是错误的。让我们更改它以测试我们的(未编写！)功能：classFactorialTestCase(unittest.TestCase):deftest_factorial(self):result=factorial(3)self.assertEqual(result,6)Ifyourunthisnow,itwillstillfail,becausewedidnotwritethefactorialfunctionyet.Let'smakethistestpass:如果您现在运⾏此命令，它将仍然会失败，因为我们尚未编写factorial函数。让我们通过这个测试：deffactorial(num):return6Whilethisisnotmathematicallysound,thismakesourtestpass.Let’swritesomemoretests:尽管这在数学上并不合理，但这使我们的测试通过了。让我们再写⼀些测试：deftest_factorial(self):self.assertEqual(factorial(1),1)self.assertEqual(factorial(2),2)self.assertEqual(factorial(3),6)self.assertEqual(factorial(10),3628800)Checkthatthetestsnowfail(sincefactorialreturns6allthetime)andmakethechangestothefactorialfunction:检查测试现在是否失败(因为factorial始终返回6)，并对阶乘函数进⾏更改：deffactorial(num):ifnum==1:return1returnnum*factorial(num-1)And,ifyourunthis,thetestspass:⽽且，如果运⾏此命令，则测试通过：Ran1testin0.002sOKNow,let’stakeastepbackandunderstandwhatwejustdid.现在，让我们退后⼀步，了解我们刚才所做的事情。断⾔(Assertions)Whenwewritetests,wewanttotestforsomething.Ifsomethingisequal,ornotequal,ifafunctionthrowsanexception,ifamethodwascalledwithcertainparameters,etc.Suchchecksarecalledassertions.Assertionsarethingsthatarealwayssupposedtobetrueforthecodetoworkproperly.编写测试时，我们想测试⼀些东西。如果相等或不相等，则函数抛出异常，使⽤特定参数调⽤⽅法等。此类检查称为断⾔。断⾔是为了使代码正常⼯作⽽总是应该做的事情。OneassertionyoujustsawiftheassertEqual.Itchecksthat2variablespassedinareequaltoeachother.assertEqualisavailablethroughself,andisprovidedbytheTestCaseparentclass.Herearesomeofthecommonassertionsyouwillfinduseful:您刚刚看到了⼀个断⾔是否为assertEqual。它检查传⼊的2个变量是否相等。assertEqual通过self可⽤，由TestCase⽗类提供。以下是⼀些有⽤的常见断⾔：assertEqual(x,y)/assertNotEqual(x,y)assertEqual(x,y)/assertNotEqual(x,y)assertTrue(x)/assertFalse(x)assertTrue(x)/assertFalse(x)assertIs(x,y)assertIs(x,y)assertIsNone(x)assertIsNone(x)assertIn(x,y)assertIn(x,y)assertIsInstance(x,y)/assertNotIsInstance(x,y)assertIsInstance(x,y)/assertNotIsInstance(x,y)assertRaises(exc,fun,*args,**kwargs)assertRaises(exc,fun,*args,**kwargs)assertGreater(x,y)/assertLess(x,y)/assertGreaterEqual(x,y)/assertLessEqual(x,y)assertGreater(x,y)/assertLess(x,y)/assertGreaterEqual(x,y)/assertLessEqual(x,y)Someoftheseareavailableusingacontextmanager,likeassertRaises.Itmakesthecodeabiteasiertoread:其中⼀些可以使⽤上下⽂管理器来使⽤，例如assertRaises。它使代码更易于阅读：withself.assertRaises(Exception):do_something_that_throws("please")Usingtheseassertionsyoucantestprettymuchanything!使⽤这些断⾔，您⼏乎可以测试任何东西！模拟(Mocking)Recallthatunittestingistestingindividualpartsofsysteminisolation.But,thisisneverthecasewiththesystemswedesign.Differentpartsdependonotherparts,andtomaketestingpossibleyousometimesneedtomockthemout.Forexample,ifyouaretestingthebehaviourofanHTTPresponseparser,thereisnoneedtoperformanactualHTTPresponse:allyouneedtodoitmockit.回想⼀下，单元测试在隔离测试系统的各个部分。但是，我们设计的系统从来没有这种情况。不同的部分取决于其他部分，为了使测试成为可能，您有时需要将它们模拟出来。例如，如果您正在测试HTTP响应解析器的⾏为，则⽆需执⾏实际的HTTP响应：只需对其进⾏模拟即可。Mocking,then,isamethodofabstractingimplementationofsoftwaremodulesthatarenotrelevanttothebehaviouryouaretesting.Moreover,youcanassertifamockwascalled,howmanytimeswasitcalled,andwhatargumentsweresuppliedtoit.Theseadditionalassertionswill,nodoubt,makeyourtestsmorerobust.那么，模拟是⼀种抽象化与所测试⾏为⽆关的软件模块实现的⽅法。此外，您可以断⾔是否调⽤了模拟程序，调⽤了多少次以及向其提供了哪些参数。毫⽆疑问，这些额外的断⾔将使您的测试更加强⼤。MockinginPythonisalsoavailableviatheunittestmodule.Let'sstartwithasimpleexample.Supposeyouwroteafunctionthatcallsthesuppliedcallback:也可以通过unittest模块使⽤Python进⾏模拟。让我们从⼀个简单的例⼦开始。假设您编写了⼀个调⽤提供的回调的函数：defcall_this_function(func):func()Totestit,youjustneedtopassaMagicMock(availablethroughunittest.mock):要对其进⾏测试，您只需传递⼀个MagicMock(可通过unittest.mock)：importunittestfromunittest.mockimportMagicMockdefcall_this_function(func):func()classCallbackTestCase(unittest.TestCase):deftest_callback(self):mock=MagicMock()call_this_function(mock)mock.assert_called_once()if__name__=='__main__':unittest.main()MagicMockisaspecialtypeofobject.Youcancallititself,callanymethodyoucancomeupwithanditwillneverthrow.Instead,itwillmemorizeallcallsandmakethemavailabletoyouthroughassertions.Notethatinthiscase,assertionsarecalledonthemockobject,insteadofself.Herearesomeoftheassertionsavailableformockobjects:MagicMock是⼀种特殊的对象。您可以调⽤它本⾝，调⽤可以使⽤的任何⽅法，并且它永远不会抛出。相反，它将记住所有调⽤，并通过断⾔使您可以使⽤它们。请注意，在这种情况下，断⾔是在mock对象上调⽤的，⽽不是self。以下是⼀些可⽤于模拟对象的断⾔：assert_calledassert_calledassert_called_onceassert_called_onceassert_called_withassert_called_withassert_called_once_withassert_called_once_withassert_not_calledassert_not_called模拟进⼝(Mockingimports)Sometimes,whenyouaretestingaclass,youneedtomockoutacertainfunctionorclassthatisimportedinit.Considerthisexample:有时，当您测试⼀个类时，您需要模拟其中导⼊的某个函数或类。考虑以下⽰例：fromsome_libraryimportapi_actiondefdo_stuff():result=api_action('/stuff')returnresultNow,totestthiscode,youwanttomocktheapi_actionfunction.Thisisactuallyveryeasytodowiththepatchdecorator(availablefromunittest.mock):现在，要测试此代码，您想模拟api_action函数。使⽤patch装饰器实际上很容易做到(可从unittest.mock)：importunittestfromunittest.mockimportpatchfrommainimportdo_stuffclassApiTestCase(unittest.TestCase):@patch('main.api_action',side_effect='abacaba')deftest_stuff(self,api_action_mock):result=do_stuff()self.assertEqual(result,'abacaba')api_action_mock.assert_called_once_with('/stuff')if__name__=='__main__':unittest.main()Thepatchdecoratorisappliedtothetestfunctionthatweareworkingwith.Itacceptsasanargumentthepathtothemockedmodule.Thereisaveryimportantnotehere:youspecifythepathrelativetothetestingcode.Forexample,themain.pyfileimportedthe