In Python's typing module, they have a really helpful constant that's True when type checking, but False otherwise. This means, for example, that you can import classes dynamically if TYPE_CHECKING evaluates to True.
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from module import Class
It would be super useful if unittest had something similar. I can see in the __init__.py file, there exists a variable defined as __unittest = True:
__all__ = ['TestResult', 'TestCase', 'TestSuite',
'TextTestRunner', 'TestLoader', 'FunctionTestCase', 'main',
'defaultTestLoader', 'SkipTest', 'skip', 'skipIf', 'skipUnless',
'expectedFailure', 'TextTestResult', 'installHandler',
__unittest = True
Is there any way to use __unittest in the same way as TYPE_CHECKING from typing?
Reason for this: I have some user examples in my code-base which can be run and plot graphs. I would like to run these examples as part of the unit tests to see when they break and need fixing. I need a dynamic way of stopping the examples trying to open a plotting window and blocking the unit tests, however.
Any help very much appreciated!
Reason for this: I have some user examples in my code-base which can be run and plot graphs. I would like to run these examples as part of the unit tests to see when they break and need fixing. I need a dynamic way of stopping the examples trying to open a plotting window and blocking the unit tests, however.
The best way to achieve that is by mocking. This will replace functionality with some "mocked" functionality. This is generally used for "plotting code" or code that makes "requests" and such like. Because you can disable certain functionality that you don't need/want while testing.
It also avoids cluttering the production code with unittest-related stuff. For type checking this is needed because that happens at runtime but unittests generally don't happen at runtime or should have any effect at runtime.
You haven't said what kind of plotting you used but in case it's matplotlib they do have some documentation to facilitate testing or see this QA.
To check what you are asking (that seems if unittest has been imported) you can check if the key "unittest" is in sys.modules
import sys
import unittest
if "unittest" in sys.modules:
print("I'm unittest-ing")
For situations like this, I'd suggest using command-line arguments to control whether code is run or not.
In this case, you could have a simple module that defines a value like is_unit_testing based on whether the -unittest argument has been passed to the python process.
To handle commandline arguments, please look here: How do I access command line arguments in Python?
import sys
# sys.argv is a list of all commandline arguments you can check through
command_line_arguments_list = sys.argv # e.g. ["arg1", "arg2", "-unittest"]
is_unit_testing = "-unittest" in command_line_arguments_list
You can then pass the arguments as you'd expect via command-line:
python myModule.py arg1 arg2 -unittest
This works well for anything like this where you want multiple 'builds' from the same code base. Such as having a 'no database'/'no gui' mode etc.
Related
Is there a way of unit testing what modules are imported in a Python file (a bit like ArchUnit in Java)? The context is in implementing a hexagonal architecture and wanting to ensure that the domain model does not import any code that resides in an adapter. I'd like unit tests to fail if there are forbidden imports.
For example, I might like to test that no modules within foo.bar.domain import anything from foo.bar.adapter. Imports of foo.bar.domain should be allowed from within foo.bar.adapter.
Is this possible in Python and what's the best way of achieving this?
You can use the -Ximporttime Python flag to trace imports. I'm not entirely sure what would be the logic for finding forbidden imports in your case, but here's a silly example script that might help:
import subprocess
import sys
process = subprocess.run(
('python3', '-Ximporttime', '-c', 'import ' + 'shlex'),
stdout=subprocess.DEVNULL,
stderr=subprocess.PIPE,
encoding='utf-8',
)
blacklisted_imports = {'enum', 're', 'zipfile'}
data = [
x.rpartition('|')[2].strip() for x in process.stderr.split('\n')
]
for import_ in data:
if import_ in blacklisted_imports:
print('found bad import:', import_)
Output:
found bad import: enum
found bad import: re
I am not aware that testing methods exist for this specific case, but someone might know more about it. One thing that comes to mind are try-catch with the methods from the other module being checked if you can call a method. Another hacky way, would be to add custom string constants in global context of the each module, and if they are exist you know that the submodule imported/used the other module.
Check more on this stack overflow post.
I am writing functional tests using pytest for a software that can run locally and in the cloud. I want to create 2 modules, each with the same module/fixture names, and have pytest load one or the other depending if I'm running tests locally or in the cloud:
/fixtures
/fixtures/__init__.py
/fixtures/local_hybrids
/fixtures/local_hybrids/__init__.py
/fixtures/local_hybrids/foo.py
/fixtures/cloud_hybrids
/fixtures/cloud_hybrids/__init__.py
/fixtures/cloud_hybrids/foo.py
/test_hybrids/test_hybrids.py
foo.py (both of them):
import pytest
#pytest.fixture()
def my_fixture():
return True
/fixtures/__init__.py:
if True:
import local_hybrids as hybrids
else:
import cloud_hybrids as hybrids
/test_hybrids/test_hybrids.py:
from fixtures.hybrids.foo import my_fixture
def test_hybrid(my_fixture):
assert my_fixture
The last code block doesn't work of course, because import fixtures.hybrids is looking at the file system instead of __init__.py's "fake" namespace, which isn't like from fixtures import hybrids, which works (but then you cannot use the fixtures as the names would involve dot notation).
I realize that I could play with pytest_generate_test to alter the fixture dynamically (maybe?) but I'd really hate managing each fixture manually from within that function... I was hoping the dynamic import (if x, import this, else import that) was standard Python, unfortunately it clashes with the fixtures mechanism:
import fixtures
def test(fixtures.hybrids.my_fixture): # of course it doesn't work :)
...
I could also import each fixture function one after the other in init; more legwork, but still a viable option to fool pytest and get fixture names without dots.
Show me the black magic. :) Can it be done?
I think in your case it's better to define a fixture - environment or other nice name.
This fixture can be just a getter from os.environ['KEY'] or you can add custom command line argument like here
then use it like here
and the final use is here.
What im trying to tell is that you need to switch thinking into dependency injection: everything should be a fixture. In your case (and in my plugin as well), runtime environment should be a fixture, which is checked in all other fixtures which depend on the environment.
You might be missing something here: If you want to re-use those fixtures you need to say it explicitly:
from fixtures.hybrids.foo import my_fixture
#pytest.mark.usefixtures('my_fixture')
def test_hybrid(my_fixture):
assert my_fixture
In that case you could tweak pytest as following:
from local_hybrids import local_hybrids_fixture
from cloud_hybrids import cloud_hybrids_fixture
fixtures_to_test = {
"local":None,
"cloud":None
}
#pytest.mark.usefixtures("local_hybrids_fixture")
def test_add_local_fixture(local_hybrids_fixture):
fixtures_to_test["local"] = local_hybrids_fixture
#pytest.mark.usefixtures("cloud_hybrids_fixture")
def test_add_local_fixture(cloud_hybrids_fixture):
fixtures_to_test["cloud"] = cloud_hybrids_fixture
def test_on_fixtures():
if cloud_enabled:
fixture = fixtures_to_test["cloud"]
else:
fixture = fixtures_to_test["local"]
...
If there are better solutions around I am also interested ;)
I don't really think there is a "good way" of doing that in python, but still it is possible with a little amount of hacking. You can update sys.path for the subfolder with fixtures you would like to use and import fixtures directly. In dirty case it look's like that:
for your fixtures/__init__.py:
if True:
import local as hybrids
else:
import cloud as hybrids
def update_path(module):
from sys import path
from os.path import join, pardir, abspath
mod_dir = abspath(join(module.__file__, pardir))
path.insert(0, mod_dir)
update_path(hybrids)
and in the client code (test_hybrids/test_hybrids.py) :
import fixtures
from foo import spam
spam()
In other cases you can use much more complex actions to perform a fake-move of all modules/packages/functions etc from your cloud/local folder directly into the fixture's __init__.py. Still, I think - it does not worth a try.
One more thing - black magic is not the best thing to use, I would recommend you to use a dotted notation with "import X from Y" - this is much more stable solution.
Use the pytest plugins feature and put your fixtures in separate modules. Then at runtime select which plug-in you’ll be drawing from via a command line argument or an environment variable. It needs to be something global because you need to place different pytest_plugins list assignments based on the global value.
Take a look at the section Conditional Plugins from this repo https://github.com/jxramos/pytest_behavior/tree/main/conditional_plugins
I'd like to connect to a different database if my code is running under py.test. Is there a function to call or an environment variable that I can test that will tell me if I'm running under a py.test session? What's the best way to handle this?
A simpler solution I came to:
import sys
if "pytest" in sys.modules:
...
Pytest runner will always load the pytest module, making it available in sys.modules.
Of course, this solution only works if the code you're trying to test does not use pytest itself.
There's also another way documented in the manual:
https://docs.pytest.org/en/latest/example/simple.html#pytest-current-test-environment-variable
Pytest will set the following environment variable PYTEST_CURRENT_TEST.
Checking the existence of said variable should reliably allow one to detect if code is being executed from within the umbrella of pytest.
import os
if "PYTEST_CURRENT_TEST" in os.environ:
# We are running under pytest, act accordingly...
Note
This method works only when an actual test is being run.
This detection will not work when modules are imported during pytest collection.
A solution came from RTFM, although not in an obvious place. The manual also had an error in code, corrected below.
Detect if running from within a pytest run
Usually it is a bad idea to make application code behave differently
if called from a test. But if you absolutely must find out if your
application code is running from a test you can do something like
this:
# content of conftest.py
def pytest_configure(config):
import sys
sys._called_from_test = True
def pytest_unconfigure(config):
import sys # This was missing from the manual
del sys._called_from_test
and then check for the sys._called_from_test flag:
if hasattr(sys, '_called_from_test'):
# called from within a test run
else:
# called "normally"
accordingly in your application. It’s also a good idea to use your own
application module rather than sys for handling flag.
Working with pytest==4.3.1 the methods above failed, so I just went old school and checked with:
script_name = os.path.basename(sys.argv[0])
if script_name in ['pytest', 'py.test']:
print('Running with pytest!')
While the hack explained in the other answer (http://pytest.org/latest/example/simple.html#detect-if-running-from-within-a-pytest-run) does indeed work, you could probably design the code in such a way you would not need to do this.
If you design the code to take the database to connect to as an argument somehow, via a connection or something else, then you can simply inject a different argument when you're running the tests then when the application drives this. Your code will end up with less global state and more modulare and reusable. So to me it sounds like an example where testing drives you to design the code better.
This could be done by setting an environment variable inside the testing code. For example, given a project
conftest.py
mypkg/
__init__.py
app.py
tests/
test_app.py
In test_app.py you can add
import os
os.environ['PYTEST_RUNNING'] = 'true'
And then you can check inside app.py:
import os
if os.environ.get('PYTEST_RUNNING', '') == 'true':
print('pytest is running')
I have a module that defines a class which instantiates a class from one of two (or more) other modules. Below are a couple of code examples. In the first example, two modules are imported, but only one is used (one per instance of MyIo). In the second example, only the required module is imported. There may be one or more instances of MyIo in a higher level module.
I like that the second example only imports what is used, but I don't really like that the import is taking place in a 'code execution' section.
My questions are:
Which of the examples is a better architectural choice, and why?
Is there a penalty for importing modules that are not eventually
used?
Are imports in code execution sections in Python considered 'bad form?'
This example imports both modules, but only uses one...
''' MyIo.py '''
...
...
from DevSerial import Device as DeviceSerial
from DevUSB import Device as DeviceUSB
class MyIo:
def __init__(self, port)
if port.lower() == 'usb':
self.device=DeviceUSB()
else:
self.device=DeviceSerial(port)
...
...
The following imports only the module being used...
''' MyIo.py '''
...
...
class MyIo:
def __init__(self, port)
if port.lower() == 'usb':
from DevUSB import Device
self.device=Device()
else:
from DevSerial import Device
self.device=Device(port)
...
...
As per PEP 8, all imports should be together at the top of the file. Having them spread throughout the file leads to hard to maintain and debug software.
The only performance overhead I can think of is at program startup - it has to load more modules. Once the program is running there shouldn't be any extra overhead.
To answer your questions:
The former. It is clearly obvious what other files are used, whereas you have to dig through the second to find all the dependencies.
Yes, but only at startup.
Yes.
Actually, even tho you are importing the modules into a function, they will still exists into sys.modules once your function is done executing unless your are deleting them manually. So yeah, there's no point to don't import them directly at the top of your code (like example #1).
The most common use for imports that are not just jammed up at the top of the page is for situations where sibling modules represent different, mutually exclusive options: the best example is os.path, which is automatically swapped for the appropriate module. Even there its common to do the differential import up at the top and not down in the code.
Summary: when a certain python module is imported, I want to be able to intercept this action, and instead of loading the required class, I want to load another class of my choice.
Reason: I am working on some legacy code. I need to write some unit test code before I start some enhancement/refactoring. The code imports a certain module which will fail in a unit test setting, however. (Because of database server dependency)
Pseduo Code:
from LegacyDataLoader import load_me_data
...
def do_something():
data = load_me_data()
So, ideally, when python excutes the import line above in a unit test, an alternative class, says MockDataLoader, is loaded instead.
I am still using 2.4.3. I suppose there is an import hook I can manipulate
Edit
Thanks a lot for the answers so far. They are all very helpful.
One particular type of suggestion is about manipulation of PYTHONPATH. It does not work in my case. So I will elaborate my particular situation here.
The original codebase is organised in this way
./dir1/myapp/database/LegacyDataLoader.py
./dir1/myapp/database/Other.py
./dir1/myapp/database/__init__.py
./dir1/myapp/__init__.py
My goal is to enhance the Other class in the Other module. But since it is legacy code, I do not feel comfortable working on it without strapping a test suite around it first.
Now I introduce this unit test code
./unit_test/test.py
The content is simply:
from myapp.database.Other import Other
def test1():
o = Other()
o.do_something()
if __name__ == "__main__":
test1()
When the CI server runs the above test, the test fails. It is because class Other uses LegacyDataLoader, and LegacydataLoader cannot establish database connection to the db server from the CI box.
Now let's add a fake class as suggested:
./unit_test_fake/myapp/database/LegacyDataLoader.py
./unit_test_fake/myapp/database/__init__.py
./unit_test_fake/myapp/__init__.py
Modify the PYTHONPATH to
export PYTHONPATH=unit_test_fake:dir1:unit_test
Now the test fails for another reason
File "unit_test/test.py", line 1, in <module>
from myapp.database.Other import Other
ImportError: No module named Other
It has something to do with the way python resolves classes/attributes in a module
You can intercept import and from ... import statements by defining your own __import__ function and assigning it to __builtin__.__import__ (make sure to save the previous value, since your override will no doubt want to delegate to it; and you'll need to import __builtin__ to get the builtin-objects module).
For example (Py2.4 specific, since that's what you're asking about), save in aim.py the following:
import __builtin__
realimp = __builtin__.__import__
def my_import(name, globals={}, locals={}, fromlist=[]):
print 'importing', name, fromlist
return realimp(name, globals, locals, fromlist)
__builtin__.__import__ = my_import
from os import path
and now:
$ python2.4 aim.py
importing os ('path',)
So this lets you intercept any specific import request you want, and alter the imported module[s] as you wish before you return them -- see the specs here. This is the kind of "hook" you're looking for, right?
There are cleaner ways to do this, but I'll assume that you can't modify the file containing from LegacyDataLoader import load_me_data.
The simplest thing to do is probably to create a new directory called testing_shims, and create LegacyDataLoader.py file in it. In that file, define whatever fake load_me_data you like. When running the unit tests, put testing_shims into your PYTHONPATH environment variable as the first directory. Alternately, you can modify your test runner to insert testing_shims as the first value in sys.path.
This way, your file will be found when importing LegacyDataLoader, and your code will be loaded instead of the real code.
The import statement just grabs stuff from sys.modules if a matching name is found there, so the simplest thing is to make sure you insert your own module into sys.modules under the target name before anything else tries to import the real thing.
# in test code
import sys
import MockDataLoader
sys.modules['LegacyDataLoader'] = MockDataLoader
import module_under_test
There are a handful of variations on the theme, but that basic approach should work fine to do what you describe in the question. A slightly simpler approach would be this, using just a mock function to replace the one in question:
# in test code
import module_under_test
def mock_load_me_data():
# do mock stuff here
module_under_test.load_me_data = mock_load_me_data
That simply replaces the appropriate name right in the module itself, so when you invoke the code under test, presumably do_something() in your question, it calls your mock routine.
Well, if the import fails by raising an exception, you could put it in a try...except loop:
try:
from LegacyDataLoader import load_me_data
except: # put error that occurs here, so as not to mask actual problems
from MockDataLoader import load_me_data
Is that what you're looking for? If it fails, but doesn't raise an exception, you could have it run the unit test with a special command line tag, like --unittest, like this:
import sys
if "--unittest" in sys.argv:
from MockDataLoader import load_me_data
else:
from LegacyDataLoader import load_me_data