Btukfyl

There is no reason given that you can't build on what was done in a previous test or should rebuild it all from scratch for the next test. At least no reason is usually offered but instead people just confidently say "you shouldn't". That isn't helpful.

In general I am tired of reading too many answers here that say basically "you shouldn't do that" instead of giving any information on how to best do it if in the questioners judgment there is good reason to do so. If I wanted someone's opinion on whether I should do something then I would have asked for opinions on whether doing it is a good idea.

That out of the way, if you read say loadTestsFromTestCase and what it calls it ultimately scans for methods with some name pattern in whatever order they are encountered in the classes method dictionary, so basically in key order. It take this information and makes a testsuite of mapping it to the TestCase class. Giving it instead a list ordered as you would like is one way to do this. I am not so sure of the most efficient/cleanest way to do it but this does work.

Why do you need specific test order? The tests should be isolated and therefore it should be possible to run them in any order, or even in parallel.

If you need to test something like user unsubscribing, the test could create a fresh database with a test subscription and then try to unsubscribe. This scenario has its own problems, but in the end it’s better than having tests depend on each other. (Note that you can factor out common test code, so that you don’t have to repeat the DB setup code or create testing data ad nauseam.)

If you use 'nose' and you write your test cases as functions (and not as methods of some TestCase derived class) 'nose' doesn't fiddle with the order, but uses the order of the functions as defined in the file. In order to have the assert_* methods handy without needing to subclass TestCase I usually use the testing module from numpy. Example:

from numpy.testing import *



def test_aaa():

    assert_equal(1, 1)



def test_zzz():

    assert_equal(1, 1)



def test_bbb():

    assert_equal(1, 1)

Running that with ''nosetest -vv'' gives:

test_it.test_aaa ... ok

test_it.test_zzz ... ok

test_it.test_bbb ... ok

----------------------------------------------------------------------

Ran 3 tests in 0.050s

OK

Note to all those who contend that unit tests shouldn't be ordered: while it is true that unit tests should be isolated and can run independently, your functions and classes are usually not independent. They rather build up on another from simpler/low-level functions to more complex/high-level functions. When you start optimising your low-level functions and mess up (for my part, I do that frequently; if you don't, you probably don't need unit test anyway;-) then it's a lot better for diagnosing the cause, when the tests for simple functions come first, and tests for functions that depend on those functions later. If the tests are sorted alphabetically the real cause usually gets drowned among one hundred failed assertions, which are not there because the function under test has a bug, but because the low-level function it relies on has.

That's why I want to have my unit tests sorted the way I specified them: not to use state that was built up in early tests in later tests, but as a very helpful tool in diagnosing problems.

Don't rely on the order. If they use some common state like the filesystem or database, then you should create setUp and tearDown methods that get your environment into a testable state, then clean up after the tests have run. Each test should assume that the environment is as defined in setUp, and should make no further assumptions.

I half agree with the idea that tests souldn't be ordered. In some cases it helps (it's easier damn it!) to have them in order... after all that's the reason for the 'unit' in UnitTest.

That said one alternative is to use mock objects to mockout and patch the items that should run before that specific code under test. You can also put a dummy function in there to monkey patch your code. For more info check out Mock, which is part of the standard library now.
Mock

Here are some YouTube videos if you haven't used Mock before.

Video 1

Video 2

Video 3

More to the point, try using class methods to structure your code, then place all the class methods in one main test method.

import unittest

import sqlite3



class MyOrderedTest(unittest.TestCase):



    @classmethod

    def setUpClass(cls):

        cls.create_db()

        cls.setup_draft()

        cls.draft_one()

        cls.draft_two()

        cls.draft_three()



    @classmethod

    def create_db(cls):

        cls.conn = sqlite3.connect(":memory:")



    @classmethod

    def setup_draft(cls):

        cls.conn.execute("CREATE TABLE players ('draftid' INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL, 'first', 'last')")



    @classmethod

    def draft_one(cls):

        player = ("Hakeem", "Olajuwon")

        cls.conn.execute("INSERT INTO players (first, last) VALUES (?, ?)", player)



    @classmethod

    def draft_two(cls):

        player = ("Sam", "Bowie")

        cls.conn.execute("INSERT INTO players (first, last) VALUES (?, ?)", player)



    @classmethod

    def draft_three(cls):

        player = ("Michael", "Jordan")

        cls.conn.execute("INSERT INTO players (first, last) VALUES (?, ?)", player)



    def test_unordered_one(self):

        cur = self.conn.execute("SELECT * from players")

        draft = [(1, u'Hakeem', u'Olajuwon'), (2, u'Sam', u'Bowie'), (3, u'Michael', u'Jordan')]

        query = cur.fetchall()

        print query

        self.assertListEqual(query, draft)



    def test_unordered_two(self):

        cur = self.conn.execute("SELECT first, last FROM players WHERE draftid=3")

        result = cur.fetchone()

        third = " ".join(result)

        print third

        self.assertEqual(third, "Michael Jordan")

There are a number of reasons for prioritizing tests, not the least of which is productivity, which is what JUnit Max is geared for. It's sometimes helpful to keep very slow tests in their own module so that you can get quick feedback from the those tests that that don't suffer from the same heavy dependencies. Ordering is also helpful in tracking down failures from tests that are not completely self-contained.

Ok, may be a bit later, but anyway...

You should try proboscis library. It will allow you to make tests order as well as set up any test dependencies. I use it and this library is awesome truly.

For example, if test case #1 from module A should depend on test case #3 from module B you CAN set this behaviour using the library.

http://docs.python.org/library/unittest.html

Note that the order in which the various test cases will be run is determined by sorting the test function names with respect to the built-in ordering for strings.

If you need set order explicitly, use a monolithic test.

class Monolithic(TestCase):

  def step1(self):

      ...



  def step2(self):

      ...



  def steps(self):

    for name in sorted(dir(self)):

      if name.startswith("step"):

        yield name, getattr(self, name) 



  def test_steps(self):

    for name, step in self.steps():

      try:

        step()

      except Exception as e:

        self.fail("{} failed ({}: {})".format(step, type(e), e)

Check out post for details.

There are scenarios where the order can be important and where setUp and Teardown come in as to limited. There's only one setUp and tearDown method, which is logical but you can only put so much information in them until it get's unclear what setUp or tearDown might actually be doing.

Take this integration test as an example:

You are writing tests to see if the registration form and the login form are working correctly. In such a case the order is important, as you can't login without an existing account.
More importantly the order of your tests represents some kind of user interaction. Where each test might represent a step in the whole process or flow you're testing.

Dividing your code in those logical pieces has several advantages.

Might not be the best solution but, I often use one method that kicks off the actual tests.

def test_registration_login_flow(self):

    _test_registration_flow()

    _test_login_flow()

A simple method for ordering "unittest" tests is to follow the init.d mechanism of giving them numeric names:

def test_00_createEmptyObject(self):

    obj = MyObject()

    self.assertIsEqual(obj.property1, 0)

    self.assertIsEqual(obj.dict1, {})



def test_01_createObject(self):

    obj = MyObject(property1="hello", dict1={"pizza":"pepperoni"})

    self.assertIsEqual(obj.property1, "hello")

    self.assertIsDictEqual(obj.dict1, {"pizza":"pepperoni"})



def test_10_reverseProperty(self):

    obj = MyObject(property1="world")

    obj.reverseProperty1()

    self.assertIsEqual(obj.property1, "dlrow")

However, in such cases, you might want to consider structuring your tests differently so that you can build on previous construction cases. For instance, in the above, it might make sense to have a "construct and veirfy" function that constructs the object and validates it's assignment of parameters.

def make_myobject(self, property1, dict1):  # Must be specified by caller

    obj = MyObject(property1=property1, dict1=dict1)

    if property1:

        self.assertEqual(obj.property1, property1)

    else:

        self.assertEqual(obj.property1, 0)

    if dict1:

        self.assertDictEqual(obj.dict1, dict1)

    else:

        self.assertEqual(obj.dict1, {})

    return obj



def test_00_createEmptyObject(self):

    obj = self.make_object(None, None)



def test_01_createObject(self):

    obj = self.make_object("hello", {"pizza":"pepperoni"})



def test_10_reverseProperty(self):

    obj = self.make_object("world", None)

    obj.reverseProperty()

    self.assertEqual(obj.property1, "dlrow")

I agree with the statement that a blanket "don't do that" answer is a bad response.

I have a similar situation where I have a single data source and one test will wipe the data set causing other tests to fail.

My solution was to use the operating system environment variables in my Bamboo server...

(1) The test for the "data purge" functionality starts with a while loop that checks the state of an environment variable "BLOCK_DATA_PURGE." If the "BLOCK_DATA_PURGE" variable is greater than zero, the loop will write a log entry to the effect that it is sleeping 1 second. Once the "BLOCK_DATA_PURGE" has a zero value, execution proceeds to test the purge functionality.

(2) Any unit test which needs the data in the table simply increments "BLOCK_DATA_PURGE" at the beginning (in setup()) and decrements the same variable in teardown().

The effect of this is to allow various data consumers to block the purge functionality so long as they need without fear that the purge could execute in between tests. Effectively the purge operation is pushed to the last step...or at least the last step that requires the original data set.

Today I am going to extend this to add more functionality to allow some tests to REQUIRE_DATA_PURGE. These will effectively invert the above process to ensure that those tests only execute after the data purge to test data restoration.

See the example of WidgetTestCase on http://docs.python.org/library/unittest.html#organizing-test-code , it says that

Class instances will now each run one of the test_*() methods, with self.widget created and destroyed separately for each instance.

So it might be of no use to specify the order of test cases, if you do not access global variables.

I have implemented a plugin nosedep for Nose which adds support for test dependencies and test prioritization.

As mentioned in the other answers/comments this is often a bad idea, however there can be exceptions where you would want to do this (in my case it was performance for integration tests - with a huge overhead for getting into a testable state, minutes vs hours).

A minimal example is:

def test_a:

  pass



@depends(before=test_a)

def test_b:

  pass

To ensure that test_b is always run before test_a.

The philosophy behind unit tests is to make them independent of each other. This means that the first step of each test will always be to try to rethink how you are testing each piece to match that philosophy. This can involve changing how you approach testing and being creative by narrowing your tests to smaller scopes.

However, if you still find that you need tests in a specific order (as that is viable), you could try checking out the answer to Python unittest.TestCase execution order .

Contrary to what was said here:
- tests have to run in isolation (order must not matters for that)
AND
- ordering them is important because they describe what the system do and how the developper implements it.

IOW, each test brings you informations of the system and the developper logic.

So if these informations are not ordered that can make your code difficult to understand.