I would like to place a function at the end of a script which is used in the script. This, of course, does not work as the function is not known yet.
Can I therefore import this funtion in the same script?
If I do it like the following, I get the error " ImportError: cannot import name:'subfunction' "
from the_script_in_use import subfuction
a=subfunction(b)
def subfunction(value)
do something
return a
One way to do this in Python is writing:
def main():
b = 5
a = subfunction(b)
print a
def subfunction(value):
a = value + 10
return a
if __name__ == '__main__':
main()
This way you can write your code in the order you like, as long as you keep calling the function main at the end.
You may use the statement :
if __name__ == '__main__':
Which will be executed if you run this file as a script. In your case:
def main_function()
a=subfunction(b)
def subfunction(value)
do something
return a
if __name__ == '__main__':
main_function()
Note there is no need to import your function.
Doing so you can order your fonction the way you want.
you can try to use pass :
def func1():
pass
func1()
def func1():
print "yes"
But this does not actually help you run the function.
#conf.py
def init():
global mylist
mylist=[]
#change.py
import conf
def change():
if __name__ == "__main__":
print('Direct')
conf.mylist.append('Directly executed')
print(conf.mylist)
else:
conf.mylist.append('It was imported')
#exec.py
import conf
import change
conf.init()
change.change()
print (conf.mylist)
When running exec.py the result is what I expected, but when running change.py directly I didn't get any output (no Direct , no conf.mylist)
Yes, that's the normal behavior. You need to call the change function for this code to execute.
You can add the following to the end of change.py
if __name__=="__main__":
change()
This is because change is never invoked. Invoke it at the end of the file with change()
I am trying to understand the usage of #main annotation in python.
With the below python program,
def cube(x):
return x * x * x
def run_tests():
printf("Should be 1:", cube(1))
printf("Should be 8:", cube(2))
printf("Should be 27:", cube(3))
#main
def main():
print("Starting")
run_tests()
print("Ending.")
I get the following error:
PS C:\Users\MOHET01\Desktop> python.exe -i .\cube.py
Traceback (most recent call last):
File ".\cube.py", line 9, in <module>
#main
NameError: name 'main' is not defined
>>>
Function that is imported from ucb is as shown below:
def main(fn):
"""Call fn with command line arguments. Used as a decorator.
The main decorator marks the function that starts a program. For example,
interact()
#main
def my_run_function():
# function body
Use this instead of the typical __name__ == "__main__" predicate.
"""
if inspect.stack()[1][0].f_locals['__name__'] == '__main__':
args = sys.argv[1:] # Discard the script name from command line
print(args)
print(*args)
print(fn)
fn(*args) # Call the main function
return fn
My question:
Despite i define function with intrinsic name main, Why do i see this error?
I should use this:
def main():
#Do something
if __name__ == "__main__":
#Here use the method that will be the main
main()
I hope this helps
The #main decorator is implemented in a file your course provides, but you have not imported it. The page you linked says to use
from ucb import main, interact
to import the ucb.py features in your program.
As for why the error says name 'main' is not defined, that's because the function definition doesn't actually finish defining anything until the decorators execute. The reuse of the name main for both the decorator and the decorated function is confusing; the main in #main is a different function from the main you're defining in def main(): .... The main in #main is defined to run the decorated function if the file is run as a script, while the main in def main(): ... is the function to be run.
I would strongly recommend not using anything like this decorator when you don't have to. The standard way to perform the task the decorator performs is to write
if __name__ == '__main__':
whatever_function_you_would_have_put_the_decorator_on()
or if you want to handle command line arguments like the decorator would,
if __name__ == '__main__':
import sys
whatever_function_you_would_have_put_the_decorator_on(*sys.argv[1:])
The decorator is an attempt to hide the issues of sys.argv and __name__ so you don't have to know about them, but it has a problem. If you try to write something like this:
#main
def hello():
print(hello_string)
hello_string = 'Hi there.'
you'll get a NameError, because hello_string won't be assigned until after the decorator runs. If you continue to write Python beyond this course, you'll find that using if __name__ == '__main__' is less bug-prone and more understandable to other programmers than using a decorator for this.
You are using the function before it is defined. In other words, you need to define the main function higher up (in the document) than where you use it as a decorator:
def main():
pass
#main
def somefunction():
pass
The #main notation means the main function is being used to "decorate", or modify, another function. There are various articles on python decorators:
http://simeonfranklin.com/blog/2012/jul/1/python-decorators-in-12-steps/
http://www.artima.com/weblogs/viewpost.jsp?thread=240808
http://www.jeffknupp.com/blog/2013/11/29/improve-your-python-decorators-explained/
You can only use a decorator on a different function. Example:
def foo(f):
def inner():
print("before")
f()
print("after")
return inner
#foo
def bar():
print("bar")
if __name__ == "__main__":
bar()
Output:
before
bar
after
I want to do the following:
I have a class which should provide several functions, which need different inputs. And I would like to use these functions from within other scripts, or solely from commandline.
e.g. I have the class "test". It has a function "quicktest" (which basically justs prints something). (From commandline) I want to be able to
$ python test.py quicktest "foo" "bar"
Whereas quicktest is the name of the function, and "foo" and "bar" are the variables.
Also (from within another script) I want to
from test import test
# this
t = test()
t.quicktest(["foo1", "bar1"])
# or this
test().quicktest(["foo2", "bar2"])
I just can't bring that to work. I managed to write a class for the first request and one for the second, but not for both of them. The problem is that I sometimes have to call the functions via (self), sometimes not, and also I have to provide the given parameters at any time, which is also kinda complicated.
So, does anybody have an idea for that?
This is what I already have:
Works only from commandline:
class test:
def quicktest(params):
pprint(params)
if (__name__ == '__main__'):
if (sys.argv[1] == "quicktest"):
quicktest(sys.argv)
else:
print "Wrong call."
Works only from within other scripts:
class test:
_params = sys.argv
def quicktest(self, params):
pprint(params)
pprint(self._params)
if (__name__ == '__main__'):
if (sys.argv[1] == "quicktest"):
quicktest()
else:
print "Wrong call"
try the following (note that the different indentation, the if __name__ part is not part of class test anymore):
class test:
def quicktest(params):
pprint(params)
if __name__ == '__main__':
if sys.argv[1] == "quicktest":
testObj = test()
testObj.quicktest(sys.argv)
else:
print "Wrong call."
from other scripts:
from test import test
testObj = test()
testObj.quicktest(...)
The if __name__ == '__main__': block needs to be at the top level:
class Test(object): # Python class names are capitalized and should inherit from object
def __init__(self, *args):
# parse args here so you can import and call with options too
self.args = args
def quicktest(self):
return 'ret_value'
if __name__ == '__main__':
test = Test(sys.argv[1:])
You can parse the command line with the help of argparse to parse the value from the command line.
Your class which has the method and associate methods to arguments.
Say I have a module with the following:
def main():
pass
if __name__ == "__main__":
main()
I want to write a unit test for the bottom half (I'd like to achieve 100% coverage). I discovered the runpy builtin module that performs the import/__name__-setting mechanism, but I can't figure out how to mock or otherwise check that the main() function is called.
This is what I've tried so far:
import runpy
import mock
#mock.patch('foobar.main')
def test_main(self, main):
runpy.run_module('foobar', run_name='__main__')
main.assert_called_once_with()
I will choose another alternative which is to exclude the if __name__ == '__main__' from the coverage report , of course you can do that only if you already have a test case for your main() function in your tests.
As for why I choose to exclude rather than writing a new test case for the whole script is because if as I stated you already have a test case for your main() function the fact that you add an other test case for the script (just for having a 100 % coverage) will be just a duplicated one.
For how to exclude the if __name__ == '__main__' you can write a coverage configuration file and add in the section report:
[report]
exclude_lines =
if __name__ == .__main__.:
More info about the coverage configuration file can be found here.
Hope this can help.
You can do this using the imp module rather than the import statement. The problem with the import statement is that the test for '__main__' runs as part of the import statement before you get a chance to assign to runpy.__name__.
For example, you could use imp.load_source() like so:
import imp
runpy = imp.load_source('__main__', '/path/to/runpy.py')
The first parameter is assigned to __name__ of the imported module.
Whoa, I'm a little late to the party, but I recently ran into this issue and I think I came up with a better solution, so here it is...
I was working on a module that contained a dozen or so scripts all ending with this exact copypasta:
if __name__ == '__main__':
if '--help' in sys.argv or '-h' in sys.argv:
print(__doc__)
else:
sys.exit(main())
Not horrible, sure, but not testable either. My solution was to write a new function in one of my modules:
def run_script(name, doc, main):
"""Act like a script if we were invoked like a script."""
if name == '__main__':
if '--help' in sys.argv or '-h' in sys.argv:
sys.stdout.write(doc)
else:
sys.exit(main())
and then place this gem at the end of each script file:
run_script(__name__, __doc__, main)
Technically, this function will be run unconditionally whether your script was imported as a module or ran as a script. This is ok however because the function doesn't actually do anything unless the script is being ran as a script. So code coverage sees the function runs and says "yes, 100% code coverage!" Meanwhile, I wrote three tests to cover the function itself:
#patch('mymodule.utils.sys')
def test_run_script_as_import(self, sysMock):
"""The run_script() func is a NOP when name != __main__."""
mainMock = Mock()
sysMock.argv = []
run_script('some_module', 'docdocdoc', mainMock)
self.assertEqual(mainMock.mock_calls, [])
self.assertEqual(sysMock.exit.mock_calls, [])
self.assertEqual(sysMock.stdout.write.mock_calls, [])
#patch('mymodule.utils.sys')
def test_run_script_as_script(self, sysMock):
"""Invoke main() when run as a script."""
mainMock = Mock()
sysMock.argv = []
run_script('__main__', 'docdocdoc', mainMock)
mainMock.assert_called_once_with()
sysMock.exit.assert_called_once_with(mainMock())
self.assertEqual(sysMock.stdout.write.mock_calls, [])
#patch('mymodule.utils.sys')
def test_run_script_with_help(self, sysMock):
"""Print help when the user asks for help."""
mainMock = Mock()
for h in ('-h', '--help'):
sysMock.argv = [h]
run_script('__main__', h*5, mainMock)
self.assertEqual(mainMock.mock_calls, [])
self.assertEqual(sysMock.exit.mock_calls, [])
sysMock.stdout.write.assert_called_with(h*5)
Blam! Now you can write a testable main(), invoke it as a script, have 100% test coverage, and not need to ignore any code in your coverage report.
Python 3 solution:
import os
from importlib.machinery import SourceFileLoader
from importlib.util import spec_from_loader, module_from_spec
from importlib import reload
from unittest import TestCase
from unittest.mock import MagicMock, patch
class TestIfNameEqMain(TestCase):
def test_name_eq_main(self):
loader = SourceFileLoader('__main__',
os.path.join(os.path.dirname(os.path.dirname(__file__)),
'__main__.py'))
with self.assertRaises(SystemExit) as e:
loader.exec_module(module_from_spec(spec_from_loader(loader.name, loader)))
Using the alternative solution of defining your own little function:
# module.py
def main():
if __name__ == '__main__':
return 'sweet'
return 'child of mine'
You can test with:
# Override the `__name__` value in your module to '__main__'
with patch('module_name.__name__', '__main__'):
import module_name
self.assertEqual(module_name.main(), 'sweet')
with patch('module_name.__name__', 'anything else'):
reload(module_name)
del module_name
import module_name
self.assertEqual(module_name.main(), 'child of mine')
I did not want to exclude the lines in question, so based on this explanation of a solution, I implemented a simplified version of the alternate answer given here...
I wrapped if __name__ == "__main__": in a function to make it easily testable, and then called that function to retain logic:
# myapp.module.py
def main():
pass
def init():
if __name__ == "__main__":
main()
init()
I mocked the __name__ using unittest.mock to get at the lines in question:
from unittest.mock import patch, MagicMock
from myapp import module
def test_name_equals_main():
# Arrange
with patch.object(module, "main", MagicMock()) as mock_main:
with patch.object(module, "__name__", "__main__"):
# Act
module.init()
# Assert
mock_main.assert_called_once()
If you are sending arguments into the mocked function, like so,
if __name__ == "__main__":
main(main_args)
then you can use assert_called_once_with() for an even better test:
expected_args = ["expected_arg_1", "expected_arg_2"]
mock_main.assert_called_once_with(expected_args)
If desired, you can also add a return_value to the MagicMock() like so:
with patch.object(module, "main", MagicMock(return_value='foo')) as mock_main:
One approach is to run the modules as scripts (e.g. os.system(...)) and compare their stdout and stderr output to expected values.
I found this solution helpful. Works well if you use a function to keep all your script code.
The code will be handled as one code line. It doesn't matter if the entire line was executed for coverage counter (though this is not what you would actually actually expect by 100% coverage)
The trick is also accepted pylint. ;-)
if __name__ == '__main__': \
main()
If it's just to get the 100% and there is nothing "real" to test there, it is easier to ignore that line.
If you are using the regular coverage lib, you can just add a simple comment, and the line will be ignored in the coverage report.
if __name__ == '__main__':
main() # pragma: no cover
https://coverage.readthedocs.io/en/coverage-4.3.3/excluding.html
Another comment by # Taylor Edmiston also mentions it
My solution is to use imp.load_source() and force an exception to be raised early in main() by not providing a required CLI argument, providing a malformed argument, setting paths in such a way that a required file is not found, etc.
import imp
import os
import sys
def mainCond(testObj, srcFilePath, expectedExcType=SystemExit, cliArgsStr=''):
sys.argv = [os.path.basename(srcFilePath)] + (
[] if len(cliArgsStr) == 0 else cliArgsStr.split(' '))
testObj.assertRaises(expectedExcType, imp.load_source, '__main__', srcFilePath)
Then in your test class you can use this function like this:
def testMain(self):
mainCond(self, 'path/to/main.py', cliArgsStr='-d FailingArg')
To import your "main" code in pytest in order to test it you can import main module like other functions thanks to native importlib package :
def test_main():
import importlib
loader = importlib.machinery.SourceFileLoader("__main__", "src/glue_jobs/move_data_with_resource_partitionning.py")
runpy_main = loader.load_module()
assert runpy_main()