I'm looking for a way to test, in my python script, if said script is running from Ansible so I can also run it through shell (for running unit tests etc). Calling AnsibleModule without calling from an ansible playbook will just endlessly wait for a response that will never come.
I'm expecting that there isn't a simple test and that I have to restructure in some way, but I'm open to any options.
def main():
# must test if running via ansible before next line
module = AnsibleModule(
argument_spec=dict(
server=dict(required=True, type='str'),
[...]
)
[... do things ...]
)
if __name__ == "__main__":
if running_via_ansible:
main()
else:
run_tests()
I believe there are a couple of answers, with various levels of trickery involved
since your module is written in python, ansible will use the AnsiballZ framework to run it, which means its sys.argv[0] will start with AnsiballZ_; it will also likely be written to $HOME/.ansible/tmp on the target machine, so one could sniff for .ansible/tmp showing up in argv[0] also
if the file contains the string WANT_JSON in it, then ansible will invoke it with the module's JSON payload as the first argument instead of feeding it JSON on sys.stdin (thus far the filename has been colocated with the AnsiballZ_ script, but I don't know that such a thing is guaranteed)
Similar, although apparently far more python specific: if it contains a triple-quoted sentinel """<<INCLUDE_ANSIBLE_MODULE_JSON_ARGS>>""" (or the ''' flavor works, too) then that magic string is replaced by the serialized JSON that, again, would have been otherwise provided via stdin
While this may not apply, or be helpful, I actually would expect that any local testing environment would have more "fingerprints" than trying to detect the opposite, and has the pleasing side-effect of "failing open" in that the module will assume it is running in production mode unless it can prove testing mode, which should make for less weird false positives. Then again, I guess the reasonable default depends on how problematic it would be for the module to attempt to carry out its payload when not really in use
I'm using pyinstaller to distribute my code as executable within my team as most of them are not coding/scripting people and do not have Python Interpreter installed.
For some advanced usage of my tool, I want to make it possible for the user to implement a small custom function to adjust functionality slightly (for the few experienced people). Hence I want to let them input a python file which defines a function with a fixed name and a string as return.
Is that possible?
I mean the py-file could be drag/dropped for example, and I'd tell them that their user-defined function needs to have a certain name, e.g. "analyze()" - is it now possible to import that from the drag/dropped pythonfile within my PyInstaller Script and use it as this?
I know, it certainly will not be safe/secure and they could do evil things, delete files and so one... But that are things which we don#t care at this point, please no discussions about it. Thanks!
To answer my own question: yes it does actually work to import a module/function from a given path/pythonfile at runtime (that I knew already) even in PyInstaller (that was new for me).
I used this for my Py2.7 program:
f = r'C:\path\to\userdefined\filewithfunction.py'
if os.path.exists(f):
import imp
userdefined = imp.load_source('', f) # Only Python 2.x, for 3.x see: https://stackoverflow.com/a/67692/701049
print userdefined # just a debugging print
userdefined.imported() # here you should use try/catch; or check whether the function with the desired name really exists in the object "userdefined". This is only a small demo as example how to import, so didnt do it here.
filewithfunction.py:
--------------------
def imported():
print 'yes it worked :-)'
As written in the comments of the example code, you'll need a slightly different approach in Python 3.x. See this link: https://stackoverflow.com/a/67692/701049
I can check the presence of a file or folder using OS library very easily.
The following two links have described that
directoryExistance fileExistance
I am attempting to use the subprocess library to do the same
and, I tried a couple of approaches already
1- status = subprocess.call(['test','-e',<path>]), which is always returning 1, no matter what I pass in path.
2- Using getstatusoutput,
/bin/sh: 1: : Permission denied
status, result = subprocess.getstatusoutput([<path>])
print(status)
print(result)
which is working fine because status variable returns 126 if the file/folder exist and 127 when the file/folder doesn't exist. Also the result variable contains message but the "result" variable contains the message : Permission denied
But the second solution looks like a hack to me. Is their a better way, of doing this ?
The test command is a shell builtin, and on many platforms doesn't exist as an independent command you can run.
If you use shell=True to use the shell to run this command, you should pass in a single string, not a list of tokens.
status = subprocess.call("test -e '{}'".format(path), shell=True)
This will produce a malformed command if path contains any single quotes; try path.replace("'", r"\'") if you want to be completely correct and robust, or use one of the existing quoting functions to properly escape any shell metacharacters in the command you pass in.
The subprocess library now offers a function run() which is slightly less unwieldy than the old legacy call() function; if backwards compatibility is not important, you should probably switch to that... or, as several commenters have already implored you, not use subprocess for this task when portable, lightweight native Python solutions are available.
As pointed in the comments section
status = subprocess.call(['test','-e',<path>])
can be made to work with a shell expansion if we use "shell=True"
Although using os.path might be much more efficient anyways.
I am working on a python Command-Line-Interface program, and I find it boring when doing testings, for example, here is the help information of the program:
usage: pyconv [-h] [-f ENCODING] [-t ENCODING] [-o file_path] file_path
Convert text file from one encoding to another.
positional arguments:
file_path
optional arguments:
-h, --help show this help message and exit
-f ENCODING, --from ENCODING
Encoding of source file
-t ENCODING, --to ENCODING
Encoding you want
-o file_path, --output file_path
Output file path
When I made changes on the program and want to test something, I must open a terminal,
type the command(with options and arguments), type enter, and see if any error occurs
while running. If error really occurs, I must go back to the editor and check the code
from top to end, guessing where the bug positions, make small changes, write print lines,
return to the terminal, run command again...
Recursively.
So my question is, what is the best way to do testing with CLI program, can it be as easy
as unit testing with normal python scripts?
I think it's perfectly fine to test functionally on a whole-program level. It's still possible to test one aspect/option per test. This way you can be sure that the program really works as a whole. Writing unit-tests usually means that you get to execute your tests quicker and that failures are usually easier to interpret/understand. But unit-tests are typically more tied to the program structure, requiring more refactoring effort when you internally change things.
Anyway, using py.test, here is a little example for testing a latin1 to utf8 conversion for pyconv::
# content of test_pyconv.py
import pytest
# we reuse a bit of pytest's own testing machinery, this should eventually come
# from a separatedly installable pytest-cli plugin.
pytest_plugins = ["pytester"]
#pytest.fixture
def run(testdir):
def do_run(*args):
args = ["pyconv"] + list(args)
return testdir._run(*args)
return do_run
def test_pyconv_latin1_to_utf8(tmpdir, run):
input = tmpdir.join("example.txt")
content = unicode("\xc3\xa4\xc3\xb6", "latin1")
with input.open("wb") as f:
f.write(content.encode("latin1"))
output = tmpdir.join("example.txt.utf8")
result = run("-flatin1", "-tutf8", input, "-o", output)
assert result.ret == 0
with output.open("rb") as f:
newcontent = f.read()
assert content.encode("utf8") == newcontent
After installing pytest ("pip install pytest") you can run it like this::
$ py.test test_pyconv.py
=========================== test session starts ============================
platform linux2 -- Python 2.7.3 -- pytest-2.4.5dev1
collected 1 items
test_pyconv.py .
========================= 1 passed in 0.40 seconds =========================
The example reuses some internal machinery of pytest's own testing by leveraging pytest's fixture mechanism, see http://pytest.org/latest/fixture.html. If you forget about the details for a moment, you can just work from the fact that "run" and "tmpdir" are provided for helping you to prepare and run tests. If you want to play, you can try to insert a failing assert-statement or simply "assert 0" and then look at the traceback or issue "py.test --pdb" to enter a python prompt.
Start from the user interface with functional tests and work down towards unit tests. It can feel difficult, especially when you use the argparse module or the click package, which take control of the application entry point.
The cli-test-helpers Python package has examples and helper functions (context managers) for a holistic approach on writing tests for your CLI. It's a simple idea, and one that works perfectly with TDD:
Start with functional tests (to ensure your user interface definition) and
Work towards unit tests (to ensure your implementation contracts)
Functional tests
NOTE: I assume you develop code that is deployed with a setup.py file or is run as a module (-m).
Is the entrypoint script installed? (tests the configuration in your setup.py)
Can this package be run as a Python module? (i.e. without having to be installed)
Is command XYZ available? etc. Cover your entire CLI usage here!
Those tests are simplistic: They run the shell command you would enter in the terminal, e.g.
def test_entrypoint():
exit_status = os.system('foobar --help')
assert exit_status == 0
Note the trick to use a non-destructive operation (e.g. --help or --version) as we can't mock anything with this approach.
Towards unit tests
To test single aspects inside the application you will need to mimic things like command line arguments and maybe environment variables. You will also need to catch the exiting of your script to avoid the tests to fail for SystemExit exceptions.
Example with ArgvContext to mimic command line arguments:
#patch('foobar.command.baz')
def test_cli_command(mock_command):
"""Is the correct code called when invoked via the CLI?"""
with ArgvContext('foobar', 'baz'), pytest.raises(SystemExit):
foobar.cli.main()
assert mock_command.called
Note that we mock the function that we want our CLI framework (click in this example) to call, and that we catch SystemExit that the framework naturally raises. The context managers are provided by cli-test-helpers and pytest.
Unit tests
The rest is business as usual. With the above two strategies we've overcome the control a CLI framework may have taken away from us. The rest is usual unit testing. TDD-style hopefully.
Disclosure: I am the author of the cli-test-helpers Python package.
So my question is, what is the best way to do testing with CLI program, can it be as easy as unit testing with normal python scripts?
The only difference is that when you run Python module as a script, its __name__ attribute is set to '__main__'. So generally, if you intend to run your script from command line it should have following form:
import sys
# function and class definitions, etc.
# ...
def foo(arg):
pass
def main():
"""Entry point to the script"""
# Do parsing of command line arguments and other stuff here. And then
# make calls to whatever functions and classes that are defined in your
# module. For example:
foo(sys.argv[1])
if __name__ == '__main__':
main()
Now there is no difference, how you would use it: as a script or as a module. So inside your unit-testing code you can just import foo function, call it and make any assertions you want.
Maybe too little too late,
but you can always use
import os.system
result = os.system(<'Insert your command with options here'>
assert(0 == result)
In that way, you can run your program as if it was from command line, and evaluate the exit code.
(Update after I studied pytest)
You can also use capsys.
(from running pytest --fixtures)
capsys
Enable text capturing of writes to sys.stdout and sys.stderr.
The captured output is made available via ``capsys.readouterr()`` method
calls, which return a ``(out, err)`` namedtuple.
``out`` and ``err`` will be ``text`` objects.
This isn't for Python specifically, but what I do to test command-line scripts is to run them with various predetermined inputs and options and store the correct output in a file. Then, to test them when I make changes, I simply run the new script and pipe the output into diff correct_output -. If the files are the same, it outputs nothing. If they're different, it shows you where. This will only work if you are on Linux or OS X; on Windows, you will have to get MSYS.
Example:
python mycliprogram --someoption "some input" | diff correct_output -
To make it even easier, you can add all these test runs to your 'make test' Makefile target, which I assume you already have. ;)
If you are running many of these at once, you could make it a little more obvious where each one ends by adding a fail tag:
python mycliprogram --someoption "some input" | diff correct_output - || tput setaf 1 && echo "FAILED"
The short answer is yes, you can use unit tests, and should. If your code is well structured, it should be quite easy to test each component separately, and if you need to to can always mock sys.argv to simulate running it with different arguments.
pytest-console-scripts is a Pytest plugin for testing python scripts installed via console_scripts entry point of setup.py.
For Python 3.5+, you can use the simpler subprocess.run to call your CLI command from your test.
Using pytest:
import subprocess
def test_command__works_properly():
try:
result = subprocess.run(['command', '--argument', 'value'], check=True, capture_output=True, text=True)
except subprocess.CalledProcessError as error:
print(error.stdout)
print(error.stderr)
raise error
The output can be accessed via result.stdout, result.stderr, and result.returncode if needed.
The check parameter causes an exception to be raised if an error occurs. Note Python 3.7+ is required for the capture_output and text parameters, which simplify capturing and reading stdout/stderr.
Given that you are explicitly asking about testing for a command line application, I believe that you are aware of unit-testing tools in python and that you are actually looking for a tool to automate end-to-end tests of a command line tool. There are a couple of tools out there that are specifically designed for that. If you are looking for something that's pip-installable, I would recommend cram. It integrates well with the rest of the python environment (e.g. through a pytest extension) and it's quite easy to use:
Simply write the commands you want to run prepended with $ and the expected output prepended with . For example, the following would be a valid cram test:
$ echo Hello
Hello
By having four spaces in front of expected output and two in front of the test, you can actually use these tests to also write documentation. More on that on the website.
You can use standard unittest module:
# python -m unittest <test module>
or use nose as a testing framework. Just write classic unittest files in separate directory and run:
# nosetests <test modules directory>
Writing unittests is easy. Just follow online manual for unittesting
I would not test the program as a whole this is not a good test strategy and may not actually catch the actual spot of the error. The CLI interface is just front end to an API. You test the API via your unit tests and then when you make a change to a specific part you have a test case to exercise that change.
So, restructure your application so that you test the API and not the application it self. But, you can have a functional test that actually does run the full application and checks that the output is correct.
In short, yes testing the code is the same as testing any other code, but you must test the individual parts rather than their combination as a whole to ensure that your changes do not break everything.
I'm writing a Python class in C and I want to put assertions in my debug code. assert.h suits me fine. This only gets put in debug compiles so there's no chance of an assert failure impacting a user of the Python code*.
I'm trying to divide my 'library' code (which should be separate to the code linked against Python) so I can use it from other C code. My Python methods are therefore thinnish wrappers around my pure-C code.
So I can't do this in my 'library' code:
if (black == white)
{
PyErr_SetString(PyExc_RuntimeError, "Remap failed");
}
because this pollutes my pure-C code with Python. It's also far uglier than a simple
assert(black != white);
I believe that the Distutils compiler always sets NDEBUG, which means I can't use assert.h even in debug builds.
Mac OS and Linux.
Help!
*one argument I've heard against asserting in C code called from Python.
Just use assert.h. It's a myth that distutils always defines NDEBUG; it only does so for Microsoft's msvc on Windows, and then only when invoked from a Python release build (not from a Python debug build).
To then define NDEBUG in your own release builds, pass a -D command line option to setup.py build_ext.
Edit: It seems that NDEBUG is defined by default through Python's Makefile's OPT setting. To reset this, run
OPT="-g -O3" python setup.py build
Create your own macro, such as myassert() for different situations. Or create a macro, which checks a global variable to see if the macro is used from Python code or "normal" C. The Python module entry point would have to set this variable to true, or you could use function pointers, one for Python code, another default one for C code.
Undefine the NDEBUG macro in your setup.py:
ext_modules = [Extension(
...
undef_macros=['NDEBUG'],
)]
This will result in a command line like
gcc ... -DNDEBUG ... -UNDEBUG ...
Which (while ugly) does the correct thing, i.e. it keeps assertions enabled.