Testing in Infra.git

The Bare Minimum

All operations on tests are performed using the test.py script. Here are some commands for the impatient:

./test.py testRun all tests in the repository and report results.
./test.py listList all tests in the repository, without running them.
./test.py test infraRun only tests found in the infra package.
./test.py trainRun all tests and write expectations.
./test.py test infra:*foo*Run tests from infra with ‘foo’ in their name.

By default, test.py collects coverage information, and not having 100% coverage is an error.

Writing Tests

test.py enforces some constraints so as to maintain a clear structure in the repository:

  • tests must be methods of subclasses of unittest.TestCase. test.py will not look for standalone functions. In addition, the method name must start with ‘test’.
  • tests classes must be contained in files named like *_test.py.
  • the coverage information for file foo.py is only collected from tests located in test/foo_test.py or tests/foo_test.py.

A test fails when an exception is raised, or if expectations don‘t match (read on). Test methods can return a value. When run in train mode, test.py stores these values on disk, in directories named like *.expected/ next to the file containing tests. When run in test mode, the return values are compared to the ones previously stored, and the test fails if they don’t match.


import unittest

class FooTest(unittest.TestCase):
  def test_sha1(self):
    ret = hashlib.sha1("Unimportant text").hexdigest()
    self.assertEqual(ret, '19c12dd68b216f1a7a26d5b0290355ceef8a35b2')

  def test_sha1_expectations(self):
    ret = hashlib.sha1("Unimportant text").hexdigest()
    return ret

test_sha1 and test_sha1_expectations performs the same task, in a different way. To have both tests pass, you have to run:

./test.py train   # record output of test_sha1_expectations
./test.py test

Testing App Engine with Endpoints

Writing unit tests for code that uses Google Cloud Endpoints can be difficult. More precisely, writing the unit tests is much like writing any unit test, but ensuring that one's unit tests will run can be painful.

Almost ubiquitously, one finds that testing App Engine involves testbed and webtest. The former facilitates stubbing of various backend services; the latter creates a mock application on which one can make API calls and inspect the results. Some interactions between Endpoints and webtest may prove turbid even to those used to testing App Engine applications; what follows is a series of prescriptions concerning the least obvious of these interactions.

For a more detailed description of the system, adapted to the novice and with pointers to enlightening reading, see Testing novice. For high-level documentation intended for the seasoned App Engine/Cloud Endpoints developer, read on.

A Worked Example

something.py contains the API:

class GoodRequest(messages.Message):
  data = messages.IntegerField(1)

class GreatReponse(messages.Message):
  data = messages.IntegerField(1)

@endpoints.api(name='someendpoint', version='v1')
class SomeEndpoint(remote.Service):

  @endpoints.method(GoodRequest, GreatResponse,
                    path='/exalt', http_method='POST',
  def glorify(self, request):
    glorious_number = request.data
    if glorious_number < 0:
      raise endpoints.BadRequestException(
          'Perhaps you wanted to make a PessimisticRequest?')
    response = GreatResponse(data=request.data ** 2)

test/something_test.py contains our test suite:

# other imports
from something import SomeEndpoint
from support import test_case

class MyNiceTestSuite(test_case.EndpointsTestCase):

  api_service_cls = SomeEndpoint

  def setUp(self):
    super(MyNiceTestSuite, self).setUp()
    # testbed setup, stub initialization, etc. should go here

  def testGlorifyPerformsWonderfulSquaring(self):
    request = {'data': 4}
    response = self.call_api('glorify', request).json_body
    self.assertEquals(response, {'data': 16})

  def testNegativeNumbersAreNotGloriousEnough(self):
    request = {'data': -4}
    with self.call_should_fail('400'):
      self.call_api('glorify', request)

test_case.EndpointsTestCase Is Balm to One Parched

test_case module (DEPSed as /luci/appengine/components/support/test_case.py) hides some of the complexity of writing test cases for Endpoints code. To explicate, EndpointsTestCase provides the following facilities:

  • explicit creation of endpoints.api_server and webtest.testApp with setUp
  • correct routing to endpoints methods (the user no longer needs to write '/_ah/spi/IncredibleEndpointName.someLongMethodName') with call_api
  • error management (which will become error handling pending a fix for bug in call_should_fail)

Much of the obscurity in Endpoints testing now evaporates. By using EndpointsTestCase, we avoid the pitfalls that inhere in setting up and posting to such an API in a test environment. A few final points:

  • api_service_cls, a class member of the test suite, must be set; otherwise, the test suite will not be able to create a test application and will not have any knowledge of the API's methods

  • EndpointsTestCase.call_api and EndpointsTestCase.call_should_fail are the recommended ways to make an API call and to handle errors, respectively. Note that the argument structure for call_api is (<method name>, <request body>); the method name is literally the name to which a method is bound in the API code, not the name specified in the decorator

Happy testing!