How to use fixtures¶
See also
See also
“Requesting” fixtures¶
At a basic level, test functions request fixtures they require by declaring them as arguments.
When pytest goes to run a test, it looks at the parameters in that test function’s signature, and then searches for fixtures that have the same names as those parameters. Once pytest finds them, it runs those fixtures, captures what they returned (if anything), and passes those objects into the test function as arguments.
Quick example¶
import pytest
class Fruit:
def __init__(self, name):
self.name = name
self.cubed = False
def cube(self):
self.cubed = True
class FruitSalad:
def __init__(self, *fruit_bowl):
self.fruit = fruit_bowl
self._cube_fruit()
def _cube_fruit(self):
for fruit in self.fruit:
fruit.cube()
# Arrange
@pytest.fixture
def fruit_bowl():
return [Fruit("apple"), Fruit("banana")]
def test_fruit_salad(fruit_bowl):
# Act
fruit_salad = FruitSalad(*fruit_bowl)
# Assert
assert all(fruit.cubed for fruit in fruit_salad.fruit)
In this example, test_fruit_salad
“requests” fruit_bowl
(i.e.
def test_fruit_salad(fruit_bowl):
), and when pytest sees this, it will
execute the fruit_bowl
fixture function and pass the object it returns into
test_fruit_salad
as the fruit_bowl
argument.
Here’s roughly what’s happening if we were to do it by hand:
def fruit_bowl():
return [Fruit("apple"), Fruit("banana")]
def test_fruit_salad(fruit_bowl):
# Act
fruit_salad = FruitSalad(*fruit_bowl)
# Assert
assert all(fruit.cubed for fruit in fruit_salad.fruit)
# Arrange
bowl = fruit_bowl()
test_fruit_salad(fruit_bowl=bowl)
Fixtures can request other fixtures¶
One of pytest’s greatest strengths is its extremely flexible fixture system. It allows us to boil down complex requirements for tests into more simple and organized functions, where we only need to have each one describe the things they are dependent on. We’ll get more into this further down, but for now, here’s a quick example to demonstrate how fixtures can use other fixtures:
# contents of test_append.py
import pytest
# Arrange
@pytest.fixture
def first_entry():
return "a"
# Arrange
@pytest.fixture
def order(first_entry):
return [first_entry]
def test_string(order):
# Act
order.append("b")
# Assert
assert order == ["a", "b"]
Notice that this is the same example from above, but very little changed. The fixtures in pytest request fixtures just like tests. All the same requesting rules apply to fixtures that do for tests. Here’s how this example would work if we did it by hand:
def first_entry():
return "a"
def order(first_entry):
return [first_entry]
def test_string(order):
# Act
order.append("b")
# Assert
assert order == ["a", "b"]
entry = first_entry()
the_list = order(first_entry=entry)
test_string(order=the_list)
Fixtures are reusable¶
One of the things that makes pytest’s fixture system so powerful, is that it gives us the ability to define a generic setup step that can be reused over and over, just like a normal function would be used. Two different tests can request the same fixture and have pytest give each test their own result from that fixture.
This is extremely useful for making sure tests aren’t affected by each other. We can use this system to make sure each test gets its own fresh batch of data and is starting from a clean state so it can provide consistent, repeatable results.
Here’s an example of how this can come in handy:
# contents of test_append.py
import pytest
# Arrange
@pytest.fixture
def first_entry():
return "a"
# Arrange
@pytest.fixture
def order(first_entry):
return [first_entry]
def test_string(order):
# Act
order.append("b")
# Assert
assert order == ["a", "b"]
def test_int(order):
# Act
order.append(2)
# Assert
assert order == ["a", 2]
Each test here is being given its own copy of that list
object,
which means the order
fixture is getting executed twice (the same
is true for the first_entry
fixture). If we were to do this by hand as
well, it would look something like this:
def first_entry():
return "a"
def order(first_entry):
return [first_entry]
def test_string(order):
# Act
order.append("b")
# Assert
assert order == ["a", "b"]
def test_int(order):
# Act
order.append(2)
# Assert
assert order == ["a", 2]
entry = first_entry()
the_list = order(first_entry=entry)
test_string(order=the_list)
entry = first_entry()
the_list = order(first_entry=entry)
test_int(order=the_list)
A test/fixture can request more than one fixture at a time¶
Tests and fixtures aren’t limited to requesting a single fixture at a time. They can request as many as they like. Here’s another quick example to demonstrate:
# contents of test_append.py
import pytest
# Arrange
@pytest.fixture
def first_entry():
return "a"
# Arrange
@pytest.fixture
def second_entry():
return 2
# Arrange
@pytest.fixture
def order(first_entry, second_entry):
return [first_entry, second_entry]
# Arrange
@pytest.fixture
def expected_list():
return ["a", 2, 3.0]
def test_string(order, expected_list):
# Act
order.append(3.0)
# Assert
assert order == expected_list
Fixtures can be requested more than once per test (return values are cached)¶
Fixtures can also be requested more than once during the same test, and pytest won’t execute them again for that test. This means we can request fixtures in multiple fixtures that are dependent on them (and even again in the test itself) without those fixtures being executed more than once.
# contents of test_append.py
import pytest
# Arrange
@pytest.fixture
def first_entry():
return "a"
# Arrange
@pytest.fixture
def order():
return []
# Act
@pytest.fixture
def append_first(order, first_entry):
return order.append(first_entry)
def test_string_only(append_first, order, first_entry):
# Assert
assert order == [first_entry]
If a requested fixture was executed once for every time it was requested
during a test, then this test would fail because both append_first
and
test_string_only
would see order
as an empty list (i.e. []
), but
since the return value of order
was cached (along with any side effects
executing it may have had) after the first time it was called, both the test and
append_first
were referencing the same object, and the test saw the effect
append_first
had on that object.
Autouse fixtures (fixtures you don’t have to request)¶
Sometimes you may want to have a fixture (or even several) that you know all your tests will depend on. “Autouse” fixtures are a convenient way to make all tests automatically request them. This can cut out a lot of redundant requests, and can even provide more advanced fixture usage (more on that further down).
We can make a fixture an autouse fixture by passing in autouse=True
to the
fixture’s decorator. Here’s a simple example for how they can be used:
# contents of test_append.py
import pytest
@pytest.fixture
def first_entry():
return "a"
@pytest.fixture
def order(first_entry):
return []
@pytest.fixture(autouse=True)
def append_first(order, first_entry):
return order.append(first_entry)
def test_string_only(order, first_entry):
assert order == [first_entry]
def test_string_and_int(order, first_entry):
order.append(2)
assert order == [first_entry, 2]
In this example, the append_first
fixture is an autouse fixture. Because it
happens automatically, both tests are affected by it, even though neither test
requested it. That doesn’t mean they can’t be requested though; just
that it isn’t necessary.
Scope: sharing fixtures across classes, modules, packages or session¶
Fixtures requiring network access depend on connectivity and are
usually time-expensive to create. Extending the previous example, we
can add a scope="module"
parameter to the
@pytest.fixture
invocation
to cause a smtp_connection
fixture function, responsible to create a connection to a preexisting SMTP server, to only be invoked
once per test module (the default is to invoke once per test function).
Multiple test functions in a test module will thus
each receive the same smtp_connection
fixture instance, thus saving time.
Possible values for scope
are: function
, class
, module
, package
or session
.
The next example puts the fixture function into a separate conftest.py
file
so that tests from multiple test modules in the directory can
access the fixture function:
# content of conftest.py
import smtplib
import pytest
@pytest.fixture(scope="module")
def smtp_connection():
return smtplib.SMTP("smtp.gmail.com", 587, timeout=5)
# content of test_module.py
def test_ehlo(smtp_connection):
response, msg = smtp_connection.ehlo()
assert response == 250
assert b"smtp.gmail.com" in msg
assert 0 # for demo purposes
def test_noop(smtp_connection):
response, msg = smtp_connection.noop()
assert response == 250
assert 0 # for demo purposes
Here, the test_ehlo
needs the smtp_connection
fixture value. pytest
will discover and call the @pytest.fixture
marked smtp_connection
fixture function. Running the test looks like this:
$ pytest test_module.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-8.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 2 items
test_module.py FF [100%]
================================= FAILURES =================================
________________________________ test_ehlo _________________________________
smtp_connection = <smtplib.SMTP object at 0xdeadbeef0001>
def test_ehlo(smtp_connection):
response, msg = smtp_connection.ehlo()
assert response == 250
assert b"smtp.gmail.com" in msg
> assert 0 # for demo purposes
E assert 0
test_module.py:7: AssertionError
________________________________ test_noop _________________________________
smtp_connection = <smtplib.SMTP object at 0xdeadbeef0001>
def test_noop(smtp_connection):
response, msg = smtp_connection.noop()
assert response == 250
> assert 0 # for demo purposes
E assert 0
test_module.py:13: AssertionError
========================= short test summary info ==========================
FAILED test_module.py::test_ehlo - assert 0
FAILED test_module.py::test_noop - assert 0
============================ 2 failed in 0.12s =============================
You see the two assert 0
failing and more importantly you can also see
that the exactly same smtp_connection
object was passed into the
two test functions because pytest shows the incoming argument values in the
traceback. As a result, the two test functions using smtp_connection
run
as quick as a single one because they reuse the same instance.
If you decide that you rather want to have a session-scoped smtp_connection
instance, you can simply declare it:
@pytest.fixture(scope="session")
def smtp_connection():
# the returned fixture value will be shared for
# all tests requesting it
...
Fixture scopes¶
Fixtures are created when first requested by a test, and are destroyed based on their scope
:
function
: the default scope, the fixture is destroyed at the end of the test.class
: the fixture is destroyed during teardown of the last test in the class.module
: the fixture is destroyed during teardown of the last test in the module.package
: the fixture is destroyed during teardown of the last test in the package where the fixture is defined, including sub-packages and sub-directories within it.session
: the fixture is destroyed at the end of the test session.
Note
Pytest only caches one instance of a fixture at a time, which means that when using a parametrized fixture, pytest may invoke a fixture more than once in the given scope.
Dynamic scope¶
Added in version 5.2.
In some cases, you might want to change the scope of the fixture without changing the code.
To do that, pass a callable to scope
. The callable must return a string with a valid scope
and will be executed only once - during the fixture definition. It will be called with two
keyword arguments - fixture_name
as a string and config
with a configuration object.
This can be especially useful when dealing with fixtures that need time for setup, like spawning a docker container. You can use the command-line argument to control the scope of the spawned containers for different environments. See the example below.
def determine_scope(fixture_name, config):
if config.getoption("--keep-containers", None):
return "session"
return "function"
@pytest.fixture(scope=determine_scope)
def docker_container():
yield spawn_container()
Teardown/Cleanup (AKA Fixture finalization)¶
When we run our tests, we’ll want to make sure they clean up after themselves so they don’t mess with any other tests (and also so that we don’t leave behind a mountain of test data to bloat the system). Fixtures in pytest offer a very useful teardown system, which allows us to define the specific steps necessary for each fixture to clean up after itself.
This system can be leveraged in two ways.
1. yield
fixtures (recommended)¶
“Yield” fixtures yield
instead of return
. With these
fixtures, we can run some code and pass an object back to the requesting
fixture/test, just like with the other fixtures. The only differences are:
return
is swapped out foryield
.Any teardown code for that fixture is placed after the
yield
.
Once pytest figures out a linear order for the fixtures, it will run each one up until it returns or yields, and then move on to the next fixture in the list to do the same thing.
Once the test is finished, pytest will go back down the list of fixtures, but in
the reverse order, taking each one that yielded, and running the code inside
it that was after the yield
statement.
As a simple example, consider this basic email module:
# content of emaillib.py
class MailAdminClient:
def create_user(self):
return MailUser()
def delete_user(self, user):
# do some cleanup
pass
class MailUser:
def __init__(self):
self.inbox = []
def send_email(self, email, other):
other.inbox.append(email)
def clear_mailbox(self):
self.inbox.clear()
class Email:
def __init__(self, subject, body):
self.subject = subject
self.body = body
Let’s say we want to test sending email from one user to another. We’ll have to first make each user, then send the email from one user to the other, and finally assert that the other user received that message in their inbox. If we want to clean up after the test runs, we’ll likely have to make sure the other user’s mailbox is emptied before deleting that user, otherwise the system may complain.
Here’s what that might look like:
# content of test_emaillib.py
from emaillib import Email, MailAdminClient
import pytest
@pytest.fixture
def mail_admin():
return MailAdminClient()
@pytest.fixture
def sending_user(mail_admin):
user = mail_admin.create_user()
yield user
mail_admin.delete_user(user)
@pytest.fixture
def receiving_user(mail_admin):
user = mail_admin.create_user()
yield user
user.clear_mailbox()
mail_admin.delete_user(user)
def test_email_received(sending_user, receiving_user):
email = Email(subject="Hey!", body="How's it going?")
sending_user.send_email(email, receiving_user)
assert email in receiving_user.inbox
Because receiving_user
is the last fixture to run during setup, it’s the first to run
during teardown.
There is a risk that even having the order right on the teardown side of things doesn’t guarantee a safe cleanup. That’s covered in a bit more detail in Safe teardowns.
$ pytest -q test_emaillib.py
. [100%]
1 passed in 0.12s
Handling errors for yield fixture¶
If a yield fixture raises an exception before yielding, pytest won’t try to run
the teardown code after that yield fixture’s yield
statement. But, for every
fixture that has already run successfully for that test, pytest will still
attempt to tear them down as it normally would.
2. Adding finalizers directly¶
While yield fixtures are considered to be the cleaner and more straightforward option, there is another choice, and that is to add “finalizer” functions directly to the test’s request-context object. It brings a similar result as yield fixtures, but requires a bit more verbosity.
In order to use this approach, we have to request the request-context object
(just like we would request another fixture) in the fixture we need to add
teardown code for, and then pass a callable, containing that teardown code, to
its addfinalizer
method.
We have to be careful though, because pytest will run that finalizer once it’s been added, even if that fixture raises an exception after adding the finalizer. So to make sure we don’t run the finalizer code when we wouldn’t need to, we would only add the finalizer once the fixture would have done something that we’d need to teardown.
Here’s how the previous example would look using the addfinalizer
method:
# content of test_emaillib.py
from emaillib import Email, MailAdminClient
import pytest
@pytest.fixture
def mail_admin():
return MailAdminClient()
@pytest.fixture
def sending_user(mail_admin):
user = mail_admin.create_user()
yield user
mail_admin.delete_user(user)
@pytest.fixture
def receiving_user(mail_admin, request):
user = mail_admin.create_user()
def delete_user():
mail_admin.delete_user(user)
request.addfinalizer(delete_user)
return user
@pytest.fixture
def email(sending_user, receiving_user, request):
_email = Email(subject="Hey!", body="How's it going?")
sending_user.send_email(_email, receiving_user)
def empty_mailbox():
receiving_user.clear_mailbox()
request.addfinalizer(empty_mailbox)
return _email
def test_email_received(receiving_user, email):
assert email in receiving_user.inbox
It’s a bit longer than yield fixtures and a bit more complex, but it does offer some nuances for when you’re in a pinch.
$ pytest -q test_emaillib.py
. [100%]
1 passed in 0.12s
Note on finalizer order¶
Finalizers are executed in a first-in-last-out order. For yield fixtures, the first teardown code to run is from the right-most fixture, i.e. the last test parameter.
# content of test_finalizers.py
import pytest
def test_bar(fix_w_yield1, fix_w_yield2):
print("test_bar")
@pytest.fixture
def fix_w_yield1():
yield
print("after_yield_1")
@pytest.fixture
def fix_w_yield2():
yield
print("after_yield_2")
$ pytest -s test_finalizers.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-8.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 1 item
test_finalizers.py test_bar
.after_yield_2
after_yield_1
============================ 1 passed in 0.12s =============================
For finalizers, the first fixture to run is last call to request.addfinalizer
.
# content of test_finalizers.py
from functools import partial
import pytest
@pytest.fixture
def fix_w_finalizers(request):
request.addfinalizer(partial(print, "finalizer_2"))
request.addfinalizer(partial(print, "finalizer_1"))
def test_bar(fix_w_finalizers):
print("test_bar")
$ pytest -s test_finalizers.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-8.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 1 item
test_finalizers.py test_bar
.finalizer_1
finalizer_2
============================ 1 passed in 0.12s =============================
This is so because yield fixtures use addfinalizer
behind the scenes: when the fixture executes, addfinalizer
registers a function that resumes the generator, which in turn calls the teardown code.
Safe teardowns¶
The fixture system of pytest is very powerful, but it’s still being run by a computer, so it isn’t able to figure out how to safely teardown everything we throw at it. If we aren’t careful, an error in the wrong spot might leave stuff from our tests behind, and that can cause further issues pretty quickly.
For example, consider the following tests (based off of the mail example from above):
# content of test_emaillib.py
from emaillib import Email, MailAdminClient
import pytest
@pytest.fixture
def setup():
mail_admin = MailAdminClient()
sending_user = mail_admin.create_user()
receiving_user = mail_admin.create_user()
email = Email(subject="Hey!", body="How's it going?")
sending_user.send_email(email, receiving_user)
yield receiving_user, email
receiving_user.clear_mailbox()
mail_admin.delete_user(sending_user)
mail_admin.delete_user(receiving_user)
def test_email_received(setup):
receiving_user, email = setup
assert email in receiving_user.inbox
This version is a lot more compact, but it’s also harder to read, doesn’t have a very descriptive fixture name, and none of the fixtures can be reused easily.
There’s also a more serious issue, which is that if any of those steps in the setup raise an exception, none of the teardown code will run.
One option might be to go with the addfinalizer
method instead of yield
fixtures, but that might get pretty complex and difficult to maintain (and it
wouldn’t be compact anymore).
$ pytest -q test_emaillib.py
. [100%]
1 passed in 0.12s
Safe fixture structure¶
The safest and simplest fixture structure requires limiting fixtures to only making one state-changing action each, and then bundling them together with their teardown code, as the email examples above showed.
The chance that a state-changing operation can fail but still modify state is negligible, as most of these operations tend to be transaction-based (at least at the level of testing where state could be left behind). So if we make sure that any successful state-changing action gets torn down by moving it to a separate fixture function and separating it from other, potentially failing state-changing actions, then our tests will stand the best chance at leaving the test environment the way they found it.
For an example, let’s say we have a website with a login page, and we have access to an admin API where we can generate users. For our test, we want to:
Create a user through that admin API
Launch a browser using Selenium
Go to the login page of our site
Log in as the user we created
Assert that their name is in the header of the landing page
We wouldn’t want to leave that user in the system, nor would we want to leave that browser session running, so we’ll want to make sure the fixtures that create those things clean up after themselves.
Here’s what that might look like:
Note
For this example, certain fixtures (i.e. base_url
and
admin_credentials
) are implied to exist elsewhere. So for now, let’s
assume they exist, and we’re just not looking at them.
from uuid import uuid4
from urllib.parse import urljoin
from selenium.webdriver import Chrome
import pytest
from src.utils.pages import LoginPage, LandingPage
from src.utils import AdminApiClient
from src.utils.data_types import User
@pytest.fixture
def admin_client(base_url, admin_credentials):
return AdminApiClient(base_url, **admin_credentials)
@pytest.fixture
def user(admin_client):
_user = User(name="Susan", username=f"testuser-{uuid4()}", password="P4$$word")
admin_client.create_user(_user)
yield _user
admin_client.delete_user(_user)
@pytest.fixture
def driver():
_driver = Chrome()
yield _driver
_driver.quit()
@pytest.fixture
def login(driver, base_url, user):
driver.get(urljoin(base_url, "/login"))
page = LoginPage(driver)
page.login(user)
@pytest.fixture
def landing_page(driver, login):
return LandingPage(driver)
def test_name_on_landing_page_after_login(landing_page, user):
assert landing_page.header == f"Welcome, {user.name}!"
The way the dependencies are laid out means it’s unclear if the user
fixture would execute before the driver
fixture. But that’s ok, because
those are atomic operations, and so it doesn’t matter which one runs first
because the sequence of events for the test is still linearizable. But what does matter is
that, no matter which one runs first, if the one raises an exception while the
other would not have, neither will have left anything behind. If driver
executes before user
, and user
raises an exception, the driver will
still quit, and the user was never made. And if driver
was the one to raise
the exception, then the driver would never have been started and the user would
never have been made.
Running multiple assert
statements safely¶
Sometimes you may want to run multiple asserts after doing all that setup, which makes sense as, in more complex systems, a single action can kick off multiple behaviors. pytest has a convenient way of handling this and it combines a bunch of what we’ve gone over so far.
All that’s needed is stepping up to a larger scope, then having the act step defined as an autouse fixture, and finally, making sure all the fixtures are targeting that higher level scope.
Let’s pull an example from above, and tweak it a bit. Let’s say that in addition to checking for a welcome message in the header, we also want to check for a sign out button, and a link to the user’s profile.
Let’s take a look at how we can structure that so we can run multiple asserts without having to repeat all those steps again.
Note
For this example, certain fixtures (i.e. base_url
and
admin_credentials
) are implied to exist elsewhere. So for now, let’s
assume they exist, and we’re just not looking at them.
# contents of tests/end_to_end/test_login.py
from uuid import uuid4
from urllib.parse import urljoin
from selenium.webdriver import Chrome
import pytest
from src.utils.pages import LoginPage, LandingPage
from src.utils import AdminApiClient
from src.utils.data_types import User
@pytest.fixture(scope="class")
def admin_client(base_url, admin_credentials):
return AdminApiClient(base_url, **admin_credentials)
@pytest.fixture(scope="class")
def user(admin_client):
_user = User(name="Susan", username=f"testuser-{uuid4()}", password="P4$$word")
admin_client.create_user(_user)
yield _user
admin_client.delete_user(_user)
@pytest.fixture(scope="class")
def driver():
_driver = Chrome()
yield _driver
_driver.quit()
@pytest.fixture(scope="class")
def landing_page(driver, login):
return LandingPage(driver)
class TestLandingPageSuccess:
@pytest.fixture(scope="class", autouse=True)
def login(self, driver, base_url, user):
driver.get(urljoin(base_url, "/login"))
page = LoginPage(driver)
page.login(user)
def test_name_in_header(self, landing_page, user):
assert landing_page.header == f"Welcome, {user.name}!"
def test_sign_out_button(self, landing_page):
assert landing_page.sign_out_button.is_displayed()
def test_profile_link(self, landing_page, user):
profile_href = urljoin(base_url, f"/profile?id={user.profile_id}")
assert landing_page.profile_link.get_attribute("href") == profile_href
Notice that the methods are only referencing self
in the signature as a
formality. No state is tied to the actual test class as it might be in the
unittest.TestCase
framework. Everything is managed by the pytest fixture
system.
Each method only has to request the fixtures that it actually needs without worrying about order. This is because the act fixture is an autouse fixture, and it made sure all the other fixtures executed before it. There’s no more changes of state that need to take place, so the tests are free to make as many non-state-changing queries as they want without risking stepping on the toes of the other tests.
The login
fixture is defined inside the class as well, because not every one
of the other tests in the module will be expecting a successful login, and the act may need to
be handled a little differently for another test class. For example, if we
wanted to write another test scenario around submitting bad credentials, we
could handle it by adding something like this to the test file:
class TestLandingPageBadCredentials:
@pytest.fixture(scope="class")
def faux_user(self, user):
_user = deepcopy(user)
_user.password = "badpass"
return _user
def test_raises_bad_credentials_exception(self, login_page, faux_user):
with pytest.raises(BadCredentialsException):
login_page.login(faux_user)
Fixtures can introspect the requesting test context¶
Fixture functions can accept the request
object
to introspect the “requesting” test function, class or module context.
Further extending the previous smtp_connection
fixture example, let’s
read an optional server URL from the test module which uses our fixture:
# content of conftest.py
import smtplib
import pytest
@pytest.fixture(scope="module")
def smtp_connection(request):
server = getattr(request.module, "smtpserver", "smtp.gmail.com")
smtp_connection = smtplib.SMTP(server, 587, timeout=5)
yield smtp_connection
print(f"finalizing {smtp_connection} ({server})")
smtp_connection.close()
We use the request.module
attribute to optionally obtain an
smtpserver
attribute from the test module. If we just execute
again, nothing much has changed:
$ pytest -s -q --tb=no test_module.py
FFfinalizing <smtplib.SMTP object at 0xdeadbeef0002> (smtp.gmail.com)
========================= short test summary info ==========================
FAILED test_module.py::test_ehlo - assert 0
FAILED test_module.py::test_noop - assert 0
2 failed in 0.12s
Let’s quickly create another test module that actually sets the server URL in its module namespace:
# content of test_anothersmtp.py
smtpserver = "mail.python.org" # will be read by smtp fixture
def test_showhelo(smtp_connection):
assert 0, smtp_connection.helo()
Running it:
$ pytest -qq --tb=short test_anothersmtp.py
F [100%]
================================= FAILURES =================================
______________________________ test_showhelo _______________________________
test_anothersmtp.py:6: in test_showhelo
assert 0, smtp_connection.helo()
E AssertionError: (250, b'mail.python.org')
E assert 0
------------------------- Captured stdout teardown -------------------------
finalizing <smtplib.SMTP object at 0xdeadbeef0003> (mail.python.org)
========================= short test summary info ==========================
FAILED test_anothersmtp.py::test_showhelo - AssertionError: (250, b'mail....
voila! The smtp_connection
fixture function picked up our mail server name
from the module namespace.
Using markers to pass data to fixtures¶
Using the request
object, a fixture can also access
markers which are applied to a test function. This can be useful to pass data
into a fixture from a test:
import pytest
@pytest.fixture
def fixt(request):
marker = request.node.get_closest_marker("fixt_data")
if marker is None:
# Handle missing marker in some way...
data = None
else:
data = marker.args[0]
# Do something with the data
return data
@pytest.mark.fixt_data(42)
def test_fixt(fixt):
assert fixt == 42
Factories as fixtures¶
The “factory as fixture” pattern can help in situations where the result of a fixture is needed multiple times in a single test. Instead of returning data directly, the fixture instead returns a function which generates the data. This function can then be called multiple times in the test.
Factories can have parameters as needed:
@pytest.fixture
def make_customer_record():
def _make_customer_record(name):
return {"name": name, "orders": []}
return _make_customer_record
def test_customer_records(make_customer_record):
customer_1 = make_customer_record("Lisa")
customer_2 = make_customer_record("Mike")
customer_3 = make_customer_record("Meredith")
If the data created by the factory requires managing, the fixture can take care of that:
@pytest.fixture
def make_customer_record():
created_records = []
def _make_customer_record(name):
record = models.Customer(name=name, orders=[])
created_records.append(record)
return record
yield _make_customer_record
for record in created_records:
record.destroy()
def test_customer_records(make_customer_record):
customer_1 = make_customer_record("Lisa")
customer_2 = make_customer_record("Mike")
customer_3 = make_customer_record("Meredith")
Parametrizing fixtures¶
Fixture functions can be parametrized in which case they will be called multiple times, each time executing the set of dependent tests, i.e. the tests that depend on this fixture. Test functions usually do not need to be aware of their re-running. Fixture parametrization helps to write exhaustive functional tests for components which themselves can be configured in multiple ways.
Extending the previous example, we can flag the fixture to create two
smtp_connection
fixture instances which will cause all tests using the fixture
to run twice. The fixture function gets access to each parameter
through the special request
object:
# content of conftest.py
import smtplib
import pytest
@pytest.fixture(scope="module", params=["smtp.gmail.com", "mail.python.org"])
def smtp_connection(request):
smtp_connection = smtplib.SMTP(request.param, 587, timeout=5)
yield smtp_connection
print(f"finalizing {smtp_connection}")
smtp_connection.close()
The main change is the declaration of params
with
@pytest.fixture
, a list of values
for each of which the fixture function will execute and can access
a value via request.param
. No test function code needs to change.
So let’s just do another run:
$ pytest -q test_module.py
FFFF [100%]
================================= FAILURES =================================
________________________ test_ehlo[smtp.gmail.com] _________________________
smtp_connection = <smtplib.SMTP object at 0xdeadbeef0004>
def test_ehlo(smtp_connection):
response, msg = smtp_connection.ehlo()
assert response == 250
assert b"smtp.gmail.com" in msg
> assert 0 # for demo purposes
E assert 0
test_module.py:7: AssertionError
________________________ test_noop[smtp.gmail.com] _________________________
smtp_connection = <smtplib.SMTP object at 0xdeadbeef0004>
def test_noop(smtp_connection):
response, msg = smtp_connection.noop()
assert response == 250
> assert 0 # for demo purposes
E assert 0
test_module.py:13: AssertionError
________________________ test_ehlo[mail.python.org] ________________________
smtp_connection = <smtplib.SMTP object at 0xdeadbeef0005>
def test_ehlo(smtp_connection):
response, msg = smtp_connection.ehlo()
assert response == 250
> assert b"smtp.gmail.com" in msg
E AssertionError: assert b'smtp.gmail.com' in b'mail.python.org\nPIPELINING\nSIZE 51200000\nETRN\nSTARTTLS\nAUTH DIGEST-MD5 NTLM CRAM-MD5\nENHANCEDSTATUSCODES\n8BITMIME\nDSN\nSMTPUTF8\nCHUNKING'
test_module.py:6: AssertionError
-------------------------- Captured stdout setup ---------------------------
finalizing <smtplib.SMTP object at 0xdeadbeef0004>
________________________ test_noop[mail.python.org] ________________________
smtp_connection = <smtplib.SMTP object at 0xdeadbeef0005>
def test_noop(smtp_connection):
response, msg = smtp_connection.noop()
assert response == 250
> assert 0 # for demo purposes
E assert 0
test_module.py:13: AssertionError
------------------------- Captured stdout teardown -------------------------
finalizing <smtplib.SMTP object at 0xdeadbeef0005>
========================= short test summary info ==========================
FAILED test_module.py::test_ehlo[smtp.gmail.com] - assert 0
FAILED test_module.py::test_noop[smtp.gmail.com] - assert 0
FAILED test_module.py::test_ehlo[mail.python.org] - AssertionError: asser...
FAILED test_module.py::test_noop[mail.python.org] - assert 0
4 failed in 0.12s
We see that our two test functions each ran twice, against the different
smtp_connection
instances. Note also, that with the mail.python.org
connection the second test fails in test_ehlo
because a
different server string is expected than what arrived.
pytest will build a string that is the test ID for each fixture value
in a parametrized fixture, e.g. test_ehlo[smtp.gmail.com]
and
test_ehlo[mail.python.org]
in the above examples. These IDs can
be used with -k
to select specific cases to run, and they will
also identify the specific case when one is failing. Running pytest
with --collect-only
will show the generated IDs.
Numbers, strings, booleans and None
will have their usual string
representation used in the test ID. For other objects, pytest will
make a string based on the argument name. It is possible to customise
the string used in a test ID for a certain fixture value by using the
ids
keyword argument:
# content of test_ids.py
import pytest
@pytest.fixture(params=[0, 1], ids=["spam", "ham"])
def a(request):
return request.param
def test_a(a):
pass
def idfn(fixture_value):
if fixture_value == 0:
return "eggs"
else:
return None
@pytest.fixture(params=[0, 1], ids=idfn)
def b(request):
return request.param
def test_b(b):
pass
The above shows how ids
can be either a list of strings to use or
a function which will be called with the fixture value and then
has to return a string to use. In the latter case if the function
returns None
then pytest’s auto-generated ID will be used.
Running the above tests results in the following test IDs being used:
$ pytest --collect-only
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-8.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 12 items
<Dir fixtures.rst-224>
<Module test_anothersmtp.py>
<Function test_showhelo[smtp.gmail.com]>
<Function test_showhelo[mail.python.org]>
<Module test_emaillib.py>
<Function test_email_received>
<Module test_finalizers.py>
<Function test_bar>
<Module test_ids.py>
<Function test_a[spam]>
<Function test_a[ham]>
<Function test_b[eggs]>
<Function test_b[1]>
<Module test_module.py>
<Function test_ehlo[smtp.gmail.com]>
<Function test_noop[smtp.gmail.com]>
<Function test_ehlo[mail.python.org]>
<Function test_noop[mail.python.org]>
======================= 12 tests collected in 0.12s ========================
Using marks with parametrized fixtures¶
pytest.param()
can be used to apply marks in values sets of parametrized fixtures in the same way
that they can be used with @pytest.mark.parametrize.
Example:
# content of test_fixture_marks.py
import pytest
@pytest.fixture(params=[0, 1, pytest.param(2, marks=pytest.mark.skip)])
def data_set(request):
return request.param
def test_data(data_set):
pass
Running this test will skip the invocation of data_set
with value 2
:
$ pytest test_fixture_marks.py -v
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-8.x.y, pluggy-1.x.y -- $PYTHON_PREFIX/bin/python
cachedir: .pytest_cache
rootdir: /home/sweet/project
collecting ... collected 3 items
test_fixture_marks.py::test_data[0] PASSED [ 33%]
test_fixture_marks.py::test_data[1] PASSED [ 66%]
test_fixture_marks.py::test_data[2] SKIPPED (unconditional skip) [100%]
======================= 2 passed, 1 skipped in 0.12s =======================
Modularity: using fixtures from a fixture function¶
In addition to using fixtures in test functions, fixture functions
can use other fixtures themselves. This contributes to a modular design
of your fixtures and allows reuse of framework-specific fixtures across
many projects. As a simple example, we can extend the previous example
and instantiate an object app
where we stick the already defined
smtp_connection
resource into it:
# content of test_appsetup.py
import pytest
class App:
def __init__(self, smtp_connection):
self.smtp_connection = smtp_connection
@pytest.fixture(scope="module")
def app(smtp_connection):
return App(smtp_connection)
def test_smtp_connection_exists(app):
assert app.smtp_connection
Here we declare an app
fixture which receives the previously defined
smtp_connection
fixture and instantiates an App
object with it. Let’s run it:
$ pytest -v test_appsetup.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-8.x.y, pluggy-1.x.y -- $PYTHON_PREFIX/bin/python
cachedir: .pytest_cache
rootdir: /home/sweet/project
collecting ... collected 2 items
test_appsetup.py::test_smtp_connection_exists[smtp.gmail.com] PASSED [ 50%]
test_appsetup.py::test_smtp_connection_exists[mail.python.org] PASSED [100%]
============================ 2 passed in 0.12s =============================
Due to the parametrization of smtp_connection
, the test will run twice with two
different App
instances and respective smtp servers. There is no
need for the app
fixture to be aware of the smtp_connection
parametrization because pytest will fully analyse the fixture dependency graph.
Note that the app
fixture has a scope of module
and uses a
module-scoped smtp_connection
fixture. The example would still work if
smtp_connection
was cached on a session
scope: it is fine for fixtures to use
“broader” scoped fixtures but not the other way round:
A session-scoped fixture could not use a module-scoped one in a
meaningful way.
Automatic grouping of tests by fixture instances¶
pytest minimizes the number of active fixtures during test runs. If you have a parametrized fixture, then all the tests using it will first execute with one instance and then finalizers are called before the next fixture instance is created. Among other things, this eases testing of applications which create and use global state.
The following example uses two parametrized fixtures, one of which is
scoped on a per-module basis, and all the functions perform print
calls
to show the setup/teardown flow:
# content of test_module.py
import pytest
@pytest.fixture(scope="module", params=["mod1", "mod2"])
def modarg(request):
param = request.param
print(" SETUP modarg", param)
yield param
print(" TEARDOWN modarg", param)
@pytest.fixture(scope="function", params=[1, 2])
def otherarg(request):
param = request.param
print(" SETUP otherarg", param)
yield param
print(" TEARDOWN otherarg", param)
def test_0(otherarg):
print(" RUN test0 with otherarg", otherarg)
def test_1(modarg):
print(" RUN test1 with modarg", modarg)
def test_2(otherarg, modarg):
print(f" RUN test2 with otherarg {otherarg} and modarg {modarg}")
Let’s run the tests in verbose mode and with looking at the print-output:
$ pytest -v -s test_module.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-8.x.y, pluggy-1.x.y -- $PYTHON_PREFIX/bin/python
cachedir: .pytest_cache
rootdir: /home/sweet/project
collecting ... collected 8 items
test_module.py::test_0[1] SETUP otherarg 1
RUN test0 with otherarg 1
PASSED TEARDOWN otherarg 1
test_module.py::test_0[2] SETUP otherarg 2
RUN test0 with otherarg 2
PASSED TEARDOWN otherarg 2
test_module.py::test_1[mod1] SETUP modarg mod1
RUN test1 with modarg mod1
PASSED
test_module.py::test_2[mod1-1] SETUP otherarg 1
RUN test2 with otherarg 1 and modarg mod1
PASSED TEARDOWN otherarg 1
test_module.py::test_2[mod1-2] SETUP otherarg 2
RUN test2 with otherarg 2 and modarg mod1
PASSED TEARDOWN otherarg 2
test_module.py::test_1[mod2] TEARDOWN modarg mod1
SETUP modarg mod2
RUN test1 with modarg mod2
PASSED
test_module.py::test_2[mod2-1] SETUP otherarg 1
RUN test2 with otherarg 1 and modarg mod2
PASSED TEARDOWN otherarg 1
test_module.py::test_2[mod2-2] SETUP otherarg 2
RUN test2 with otherarg 2 and modarg mod2
PASSED TEARDOWN otherarg 2
TEARDOWN modarg mod2
============================ 8 passed in 0.12s =============================
You can see that the parametrized module-scoped modarg
resource caused an
ordering of test execution that lead to the fewest possible “active” resources.
The finalizer for the mod1
parametrized resource was executed before the
mod2
resource was setup.
In particular notice that test_0 is completely independent and finishes first.
Then test_1 is executed with mod1
, then test_2 with mod1
, then test_1
with mod2
and finally test_2 with mod2
.
The otherarg
parametrized resource (having function scope) was set up before
and teared down after every test that used it.
Use fixtures in classes and modules with usefixtures
¶
Sometimes test functions do not directly need access to a fixture object.
For example, tests may require to operate with an empty directory as the
current working directory but otherwise do not care for the concrete
directory. Here is how you can use the standard tempfile
and pytest fixtures to
achieve it. We separate the creation of the fixture into a conftest.py
file:
# content of conftest.py
import os
import tempfile
import pytest
@pytest.fixture
def cleandir():
with tempfile.TemporaryDirectory() as newpath:
old_cwd = os.getcwd()
os.chdir(newpath)
yield
os.chdir(old_cwd)
and declare its use in a test module via a usefixtures
marker:
# content of test_setenv.py
import os
import pytest
@pytest.mark.usefixtures("cleandir")
class TestDirectoryInit:
def test_cwd_starts_empty(self):
assert os.listdir(os.getcwd()) == []
with open("myfile", "w", encoding="utf-8") as f:
f.write("hello")
def test_cwd_again_starts_empty(self):
assert os.listdir(os.getcwd()) == []
Due to the usefixtures
marker, the cleandir
fixture
will be required for the execution of each test method, just as if
you specified a “cleandir” function argument to each of them. Let’s run it
to verify our fixture is activated and the tests pass:
$ pytest -q
.. [100%]
2 passed in 0.12s
You can specify multiple fixtures like this:
@pytest.mark.usefixtures("cleandir", "anotherfixture")
def test(): ...
and you may specify fixture usage at the test module level using pytestmark
:
pytestmark = pytest.mark.usefixtures("cleandir")
It is also possible to put fixtures required by all tests in your project into an ini-file:
# content of pytest.ini
[pytest]
usefixtures = cleandir
Warning
Note this mark has no effect in fixture functions. For example, this will not work as expected:
@pytest.mark.usefixtures("my_other_fixture")
@pytest.fixture
def my_fixture_that_sadly_wont_use_my_other_fixture(): ...
This generates a deprecation warning, and will become an error in Pytest 8.
Overriding fixtures on various levels¶
In relatively large test suite, you most likely need to override
a global
or root
fixture with a locally
defined one, keeping the test code readable and maintainable.
Override a fixture on a folder (conftest) level¶
Given the tests file structure is:
tests/
conftest.py
# content of tests/conftest.py
import pytest
@pytest.fixture
def username():
return 'username'
test_something.py
# content of tests/test_something.py
def test_username(username):
assert username == 'username'
subfolder/
conftest.py
# content of tests/subfolder/conftest.py
import pytest
@pytest.fixture
def username(username):
return 'overridden-' + username
test_something_else.py
# content of tests/subfolder/test_something_else.py
def test_username(username):
assert username == 'overridden-username'
As you can see, a fixture with the same name can be overridden for certain test folder level.
Note that the base
or super
fixture can be accessed from the overriding
fixture easily - used in the example above.
Override a fixture on a test module level¶
Given the tests file structure is:
tests/
conftest.py
# content of tests/conftest.py
import pytest
@pytest.fixture
def username():
return 'username'
test_something.py
# content of tests/test_something.py
import pytest
@pytest.fixture
def username(username):
return 'overridden-' + username
def test_username(username):
assert username == 'overridden-username'
test_something_else.py
# content of tests/test_something_else.py
import pytest
@pytest.fixture
def username(username):
return 'overridden-else-' + username
def test_username(username):
assert username == 'overridden-else-username'
In the example above, a fixture with the same name can be overridden for certain test module.
Override a fixture with direct test parametrization¶
Given the tests file structure is:
tests/
conftest.py
# content of tests/conftest.py
import pytest
@pytest.fixture
def username():
return 'username'
@pytest.fixture
def other_username(username):
return 'other-' + username
test_something.py
# content of tests/test_something.py
import pytest
@pytest.mark.parametrize('username', ['directly-overridden-username'])
def test_username(username):
assert username == 'directly-overridden-username'
@pytest.mark.parametrize('username', ['directly-overridden-username-other'])
def test_username_other(other_username):
assert other_username == 'other-directly-overridden-username-other'
In the example above, a fixture value is overridden by the test parameter value. Note that the value of the fixture can be overridden this way even if the test doesn’t use it directly (doesn’t mention it in the function prototype).
Override a parametrized fixture with non-parametrized one and vice versa¶
Given the tests file structure is:
tests/
conftest.py
# content of tests/conftest.py
import pytest
@pytest.fixture(params=['one', 'two', 'three'])
def parametrized_username(request):
return request.param
@pytest.fixture
def non_parametrized_username(request):
return 'username'
test_something.py
# content of tests/test_something.py
import pytest
@pytest.fixture
def parametrized_username():
return 'overridden-username'
@pytest.fixture(params=['one', 'two', 'three'])
def non_parametrized_username(request):
return request.param
def test_username(parametrized_username):
assert parametrized_username == 'overridden-username'
def test_parametrized_username(non_parametrized_username):
assert non_parametrized_username in ['one', 'two', 'three']
test_something_else.py
# content of tests/test_something_else.py
def test_username(parametrized_username):
assert parametrized_username in ['one', 'two', 'three']
def test_username(non_parametrized_username):
assert non_parametrized_username == 'username'
In the example above, a parametrized fixture is overridden with a non-parametrized version, and a non-parametrized fixture is overridden with a parametrized version for certain test module. The same applies for the test folder level obviously.
Using fixtures from other projects¶
Usually projects that provide pytest support will use entry points, so just installing those projects into an environment will make those fixtures available for use.
In case you want to use fixtures from a project that does not use entry points, you can
define pytest_plugins
in your top conftest.py
file to register that module
as a plugin.
Suppose you have some fixtures in mylibrary.fixtures
and you want to reuse them into your
app/tests
directory.
All you need to do is to define pytest_plugins
in app/tests/conftest.py
pointing to that module.
pytest_plugins = "mylibrary.fixtures"
This effectively registers mylibrary.fixtures
as a plugin, making all its fixtures and
hooks available to tests in app/tests
.
Note
Sometimes users will import fixtures from other projects for use, however this is not recommended: importing fixtures into a module will register them in pytest as defined in that module.
This has minor consequences, such as appearing multiple times in pytest --help
,
but it is not recommended because this behavior might change/stop working
in future versions.