I have some py.test tests that have multiple dependent and parameterized fixtures and I want to measure the time taken by each fixture. However, in the logs with --durations it only shows time for setup for actual tests, but doesn't give me a breakdown of how long each individual fixture took.
Here is a concrete example of how to do this:
import logging
import time
import pytest
logger = logging.getLogger(__name__)
#pytest.hookimpl(hookwrapper=True)
def pytest_fixture_setup(fixturedef, request):
start = time.time()
yield
end = time.time()
logger.info(
'pytest_fixture_setup'
f', request={request}'
f', time={end - start}'
)
With output similar to:
2018-10-29 20:43:18,783 - INFO pytest_fixture_setup, request=<SubRequest 'some_data_source' for <Function 'test_ruleset_customer_to_campaign'>>, time=3.4723987579345703
The magic is hookwrapper:
pytest plugins can implement hook wrappers which wrap the execution of other hook implementations. A hook wrapper is a generator function which yields exactly once. When pytest invokes hooks it first executes hook wrappers and passes the same arguments as to the regular hooks.
One fairly important gotcha that I ran into is that the conftest.py has to be in your project's root folder in order to pick up the pytest_fixture_setup hook.
There isn't anything builtin for that, but you can easily implement yourself by using the new pytest_fixture_setup hook in a conftest.py file.
Related
I would like to create a Python package which contains a fixture for pytest. That fixture should mock the behavior of an identification web service. The service contains some parameters for the clients, e.g. a username and a password and other non-credentials. I want the plugin users to set those globally once so that they can test all behavior they want.
I've seen that I can parametrize fixtures and use pytest.mark.parametrize to pass the values.
How can I add a global setting for all tests for my fixture?
If I understand your requirement, you have a couple of issues: having a global fixture value shared between tests and having the fixture as a plugin.
First, you can develop your plugin as usual inside your code, along with your tests. A basic version of a shared value can be achieved using a global variable.
Consider this sample code in conftest.py:
class MyClientClass:
def __init__(self, auth):
self.auth = auth
default_client = None
#pytest.fixture(scope="session")
def web_client(request):
global default_client
param = getattr(request, "param", None)
if param:
default_client = MyClientClass(request.param)
return default_client
Then your tests can look like this (only the first test does the initialization, the others can benefit the auth):
import pytest
#pytest.mark.parametrize("web_client", [{"user": "user", "pass": "pass"}],
indirect=True)
def test_with_init_creds(web_client):
print(web_client.auth)
def test_some(web_client):
print(web_client.auth)
def test_another(web_client):
print(web_client.auth)
Now, once you are happy with the local fixture, you can put its code to an installable library. Check out these two links from the official documentation: https://docs.pytest.org/en/7.1.x/how-to/writing_plugins.html#writing-your-own-plugin and https://docs.pytest.org/en/7.1.x/how-to/writing_plugins.html#making-your-plugin-installable-by-others. The important thing is to have the entry point pytest11 so the plugin is discoverable.
I created a very small plugin using poetry, which you can also reference: https://github.com/pksol/pytest-fastapi-deps
I'm a starter with pytest. Just learned about fixture and tried to do this:
My tests call functions I wrote, and get test data from a code practicing website.
Each test is from a particular page and has several sets of test data.
So, I want to use #pytest.mark.parametrize to parametrize my single test func.
Also, as the operations of the tests are samelike, I want to made the pageObject instantiation and the steps to get test data from page as a fixture.
# content of conftest.py
#pytest.fixture
def get_testdata_from_problem_page():
def _get_testdata_from_problem_page(problem_name):
page = problem_page.ProblemPage(problem_name)
return page.get_sample_data()
return _get_testdata_from_problem_page
# content of test_problem_a.py
import pytest
from page_objects import problem_page
from problem_func import problem_a
#pytest.mark.parametrize('input,expected', test_data)
def test_problem_a(get_testdata_from_problem_page):
input, expected = get_testdata_from_problem_page("problem_a")
assert problem_a.problem_a(input) == expected
Then I realized, as above, I can't parametrize the test using pytest.mark as the test_data should be given outside the test function....
Are there solutions for this? Thanks very much~~
If I understand you correctly, you want to write one parameterized test per page. In this case you just have to write a function instead of a fixture and use that for parametrization:
import pytest
from page_objects import problem_page
from problem_func import problem_a
def get_testdata_from_problem_page(problem_name):
page = problem_page.ProblemPage(problem_name)
# returns a list of (input, expected) tuples
return page.get_sample_data()
#pytest.mark.parametrize('input,expected',
get_testdata_from_problem_page("problem_a"))
def test_problem_a(input, expected):
assert problem_a.problem_a(input) == expected
As you wrote, a fixture can only be used as a parameter to a test function or to another fixture, not in a decorator.
If you want to use the function to get test data elsewhere, just move it to a common module and import it. This can be just some custom utility module, or you could put it into contest.py, though you still have to import it.
Note also that the fixture you wrote does not do anything - it defines a local function that is not called and returns.
I am using pytest and would like to invoke a test function for a number of objects returned by a server, and for a number of servers.
The servers are defined in a YAML file and those definitions are provided as parametrization to a fixture "server_connection" that returns a Connection object for a single server. Due to the parametrization, it causes the test function to be invoked once for each server.
I am able to do this with a loop in the test function: There is a second fixture "server_objects" that takes a "server_connection" fixture as input and returns a list of server objects. The pytest test function then takes that second fixture and executes the actual test in a loop through the server objects.
Here is that code:
import pytest
SD_LIST = ... # read list of server definitions from YAML file
#pytest.fixture(
params=SD_LIST,
scope='module'
)
def server_connection(request):
server_definition = request.param
return Connection(server_definition.url, ...)
#pytest.fixture(
scope='module'
)
def server_objects(request, server_connection):
return server_connection.get_objects()
def test_object_foo(server_objects):
for server_object in server_objects:
# Perform test for a single server object:
assert server_object == 'foo'
However, the disadvantage is of course that a test failure causes the entire test function to end.
What I want to happen instead is that the test function is invoked for each single server object, so that a test failure for one object does not prevent the tests on the other objects. Ideally, I'd like to have a fixture that provides a single server object, that I can pass to the test function:
...
#pytest.fixture(
scope='module'
)
def server_object(request, server_connection):
server_objects = server_connection.get_objects()
# TBD: Some magic to parametrize this fixture with server_objects
def test_object_foo(server_object):
# Perform test for a single server object:
assert server_object == 'foo'
I have read through all pytest docs regarding fixtures but did not find a way to do this.
I know about pytest hooks and have used e.g. pytest_generate_tests() before, but I did not find a way how pytest_generate_tests() can access the values of other fixtures.
Any ideas?
Update: Let me add that I also did search SO for this, but did not find an answer. I specifically looked at:
pytest fixture of fixtures
How to parametrize a Pytest fixture
py.test: Pass a parameter to a fixture function
initing a pytest fixture with a parameter
I am new to pytest. When is #pytest.hookimpl executes? And what is the complete usage of it? I have tried with logs. For (hookwrapper=true), it is printing, 3 sets of after and before yield for a single test.
pytest uses #pytest.hookimpl just to label hook methods. (So #pytest.hookimpl is executed when pytest collects the hook method.)
If you read the source code of pytest, you can find these codes:
def normalize_hookimpl_opts(opts):
opts.setdefault("tryfirst", False)
opts.setdefault("trylast", False)
opts.setdefault("hookwrapper", False)
opts.setdefault("optionalhook", False)
It means pytest will label the hook method with #pytest.hookimpl(tryfirst=False, trylast=False, hookwrapper=False, optionalhook=False) by default. Pytest will treat these hook methods in different ways according to this label(decorator) when executing them.
Take the hookwrapper parameter for example. If the hook method is labeled as hookwrapper=True, pytest will execute the part before yield first and then execute other same type hook methods. After these methods executed, the part after yield will be executed. (This feature is just like pytest fixtures.)
One usage of #pytest.hookimpl(hookwrapper=True) is that you can calculate the total cost time of some hook methods.
(Here, the example code will calculate the tests collect time.)
#pytest.hookimpl(hookwrapper=True)
def pytest_collection(session):
collect_timeout = 5
collect_begin_time = time.time()
yield
collect_end_time = time.time()
c_time = collect_end_time - collect_begin_time
if c_time > collect_timeout:
raise Exception('Collection timeout.')
I am building some tests for python3 code using py.test. The code accesses a Postgresql Database using aiopg (Asyncio based interface to postgres).
My main expectations:
Every test case should have access to a new asyncio event loop.
A test that runs too long will stop with a timeout exception.
Every test case should have access to a database connection.
I don't want to repeat myself when writing the test cases.
Using py.test fixtures I can get pretty close to what I want, but I still have to repeat myself a bit in every asynchronous test case.
This is how my code looks like:
#pytest.fixture(scope='function')
def tloop(request):
# This fixture is responsible for getting a new event loop
# for every test, and close it when the test ends.
...
def run_timeout(cor,loop,timeout=ASYNC_TEST_TIMEOUT):
"""
Run a given coroutine with timeout.
"""
task_with_timeout = asyncio.wait_for(cor,timeout)
try:
loop.run_until_complete(task_with_timeout)
except futures.TimeoutError:
# Timeout:
raise ExceptAsyncTestTimeout()
#pytest.fixture(scope='module')
def clean_test_db(request):
# Empty the test database.
...
#pytest.fixture(scope='function')
def udb(request,clean_test_db,tloop):
# Obtain a connection to the database using aiopg
# (That's why we need tloop here).
...
# An example for a test:
def test_insert_user(tloop,udb):
#asyncio.coroutine
def insert_user():
# Do user insertion here ...
yield from udb.insert_new_user(...
...
run_timeout(insert_user(),tloop)
I can live with the solution that I have so far, but it can get cumbersome to define an inner coroutine and add the run_timeout line for every asynchronous test that I write.
I want my tests to look somewhat like this:
#some_magic_decorator
def test_insert_user(udb):
# Do user insertion here ...
yield from udb.insert_new_user(...
...
I attempted to create such a decorator in some elegant way, but failed. More generally, if my test looks like:
#some_magic_decorator
def my_test(arg1,arg2,...,arg_n):
...
Then the produced function (After the decorator is applied) should be:
def my_test_wrapper(tloop,arg1,arg2,...,arg_n):
run_timeout(my_test(),tloop)
Note that some of my tests use other fixtures (besides udb for example), and those fixtures must show up as arguments to the produced function, or else py.test will not invoke them.
I tried using both wrapt and decorator python modules to create such a magic decorator, however it seems like both of those modules help me create a function with a signature identical to my_test, which is not a good solution in this case.
This can probably solved using eval or a similar hack, but I was wondering if there is something elegant that I'm missing here.
I’m currently trying to solve a similar problem. Here’s what I’ve come up with so far. It seems to work but needs some clean-up:
# tests/test_foo.py
import asyncio
#asyncio.coroutine
def test_coro(loop):
yield from asyncio.sleep(0.1)
assert 0
# tests/conftest.py
import asyncio
#pytest.yield_fixture
def loop():
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
yield loop
loop.close()
def pytest_pycollect_makeitem(collector, name, obj):
"""Collect asyncio coroutines as normal functions, not as generators."""
if asyncio.iscoroutinefunction(obj):
return list(collector._genfunctions(name, obj))
def pytest_pyfunc_call(pyfuncitem):
"""If ``pyfuncitem.obj`` is an asyncio coroutinefunction, execute it via
the event loop instead of calling it directly."""
testfunction = pyfuncitem.obj
if not asyncio.iscoroutinefunction(testfunction):
return
# Copied from _pytest/python.py:pytest_pyfunc_call()
funcargs = pyfuncitem.funcargs
testargs = {}
for arg in pyfuncitem._fixtureinfo.argnames:
testargs[arg] = funcargs[arg]
coro = testfunction(**testargs) # Will no execute the test yet!
# Run the coro in the event loop
loop = testargs.get('loop', asyncio.get_event_loop())
loop.run_until_complete(coro)
return True # TODO: What to return here?
So I basically let pytest collect asyncio coroutines like normal functions. I also intercept text exectuion for functions. If the to-be-tested function is a coroutine, I execute it in the event loop. It works with or without a fixture creating a new event loop instance per test.
Edit: According to Ronny Pfannschmidt, something like this will be added to pytest after the 2.7 release. :-)
Every test case should have access to a new asyncio event loop.
The test suite of asyncio uses unittest.TestCase. It uses setUp() method to create a new event loop. addCleanup(loop.close) is close automatically the event loop, even on error.
Sorry, I don't know how to write this with py.test if you don't want to use TestCase. But if I remember correctly, py.test supports unittest.TestCase.
A test that runs too long will stop with a timeout exception.
You can use loop.call_later() with a function which raises a BaseException as a watch dog.