So I have discovered the python extension for SPSS, and everything works fine, I have created some scripts now and included them in the extensions map and it works fine. However, now I have created a couple of scripts that require arguments, I thought I could just follow the same method but I guess not.
def Run(args):
import spss
def testing_p(variables):
all_variables = [spss.GetVariableName(i) for i in range(spss.GetVariableCount())]
variable_nr = [all_variables.index(i) for i in variables]
print all_variables
print variable_nr
With the following .xml-file:
<Command xmlns="http://xml.spss.com/extension" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" Name="testing_p" Language="Python">
</Command>
However, this keep throwing the error when calling testing_p(['my_var', 'my_var2']):
Warnings
This command should specify a valid subcommand at the beginning.
Execution of this command stops.
I cannot wrap my head around this because everything works fine when not put in the extensions map and only doing:
BEGIN PROGRAM.
import spss
def testing_p(variables):
all_variables = [spss.GetVariableName(i) for i in range(spss.GetVariableCount())]
variable_nr = [all_variables.index(i) for i in variables]
print all_variables
print variable_nr
END PROGRAM.
For an extension, which can be writen in Python, R, or Java, you need to create a syntax specification containing the command name, any subcommands, and the arguments and argument types you want. Here is a picture of the start of one (SPSSINC_TURF, which is installed with Statistics).
This will guide the Statistics parser in checking the user input. It also then calls the Run function with a complicated structure containing the user input. You can use the functions in the extensions module to map that to your Python variables and do further validation. Here is a picture of the start of the Run function for SPSSINC TURF.
Finally, if the syntax is valid, your Run function calls the worker function to do something useful, mapping all the parameters to the specified arguments by calling
processcmd(oobj, args, superturf, vardict=spssaux.VariableDict())
which was imported from extensions.py.
Look at the doc for extensions in the help system, and look at some of the extensions installed with Statistics for examples.
Finally, here is a slide from one of my presentations summarizing the flow from user input to results.
Related
Probably related to globals and locals in python exec(), Python 2 How to debug code injected by the exec block and How to get local variables updated, when using the `exec` call?
I am trying to develop a test framework for our desktop applications which uses click bot like functions.
My goal was to enable non-programmers to write small scripts which could work as a test script. So my idea is to structure the test scripts by files like:
tests-folder
| -> 01-first-test.py
| -> 02-second-test.py
| ... etc
| -> fixture.py
And then just execute these scripts in alphabetical order. However, I also wanted to have fixtures which would define functions, classes, variables and make them available to the different scripts without having the scripts to import that fixture explicitly. If that works, I could also have that approach for 2 or more directory levels.
I could get it working-ish with some hacking around, but I am not entirely convinced. I have a test_sequence.py which looks like this:
from pathlib import Path
from copy import deepcopy
from my_module.test import Failure
def run_test_sequence(test_dir: str):
error_occured = False
fixture = {
'some_pre_defined_variable': 'this is available in all scripts and fixtures',
'directory_name': test_dir,
}
# Check if fixture.py exists and load that first
fixture_file = Path(dir) / 'fixture.py'
if fixture_file.exists():
with open(fixture_file.absolute(), 'r') as code:
exec(code.read(), fixture, fixture)
# Go over all files in test sequence directory and execute them
for test_file in sorted(Path(test_dir).iterdir()):
if test_file.name == 'fixture.py':
continue
# Make a deepcopy, so scripts cannot influence one another
fixture_copy = deepcopy(fixture)
fixture_copy.update({
'some_other_variable': 'this is available in all scripts but not in fixture'
})
try:
with open(test_file.absolute(), 'r') as code:
exec(code.read(), fixture_locals, fixture_locals)
except Failure:
error_occured = True
return error_occured
This iterates over all files in the directory tests-folder and executes them in order (with fixture.py first). It also makes the local variables, functions and classes from fixture.py available to each test-script.
A test script could then just be arbitrary code that will be executed and if it raises my custom Failure exception, this will be noted as a failed test.
The whole sequence is started with a script that does
from my_module.test_sequence import run_test_sequence
if __name__ == '__main__':
exit(run_test_sequence('tests-folder')
This mostly works.
What it cannot do, and what leaves me unsatisfied with this approach:
I cannot debug the scripts itself. Since the code is loaded as string and then interpreted, breakpoints inside the test scripts are not recognized.
Calling fixture functions behaves weird. When I define a function in fixture.py like:
from my_hello_module import print_hello
def printer():
print_hello()
I will receive a message during execution that print_hello is undefined because the variables/modules/etc. in the scope surrounding printer are lost.
Stacktraces are useless. On failure it shows the stacktrace but of course only shows my line which says `exec(...)' and the insides of that function, but none of the code that has been loaded.
I am sure there are other drawbacks, that I have not found yet, but these are the most annoying ones.
I also tried to find a solution through __import__ but I couldn't get it to inject my custom locals or globals into the imported script.
Is there a solution, that I am too inexperienced to find or another builtin Python function that actually does, what I am trying to do? Or is there no way to achieve this and I should rather have each test-script import the fixture and file/directory names from the test-scripts itself. I want those scripts to have as few dependencies and pythony code as possible. Ideally they are just:
from my_module.test import *
click(x, y, LEFT)
write('admin')
press('tab')
write('password')
press('enter')
if text_on_screen('Login successful'):
succeed('Test successful')
else:
fail('Could not login')
Additional note: I think I had the debugger working when I still used execfile, but it is not available in python3 environments.
I'm trying to learn how to use variables from Jenkins in Python scripts. I've already learned that I need to call the variables, but I'm not sure how to implement them in the case of using os.path.join().
I'm not a developer; I'm a technical writer. This code was written by somebody else. I'm just trying to adapt the Jenkins scripts so they are parameterized so we don't have to modify the Python scripts for every release.
I'm using inline Jenkins python scripts inside a Jenkins job. The Jenkins string parameters are "BranchID" and "BranchIDShort". I've looked through many questions that talk about how you have to establish the variables in the Python script, but with the case of os.path.join(),I'm not sure what to do.
Here is the original code. I added the part where we establish the variables from the Jenkins parameters, but I don't know how to use them in the os.path.join() function.
# Delete previous builds.
import os
import shutil
BranchID = os.getenv("BranchID")
BranchIDshort = os.getenv("BranchIDshort")
print "Delete any output from a previous build."
if os.path.exists(os.path.join("C:\\Doc192CS", "Output")):
shutil.rmtree(os.path.join("C:\\Doc192CS", "Output"))
I expect output like: c:\Doc192CS\Output
I am afraid that if I do the following code:
if os.path.exists(os.path.join("C:\\Doc",BranchIDshort,"CS", "Output")):
shutil.rmtree(os.path.join("C:\\Doc",BranchIDshort,"CS", "Output"))
I'll get: c:\Doc\192\CS\Output.
Is there a way to use the BranchIDshort variable in this context to get the output c:\Doc192CS\Output?
User #Adonis gave the correct solution as a comment. Here is what he said:
Indeed you're right. What you would want to do is rather:
os.path.exists(os.path.join("C:\\","Doc{}CS".format(BranchIDshort),"Output"))
(in short use a format string for the 2nd argument)
So the complete corrected code is:
import os
import shutil
BranchID = os.getenv("BranchID")
BranchIDshort = os.getenv("BranchIDshort")
print "Delete any output from a previous build."
if os.path.exists(os.path.join("C:\\Doc{}CS".format(BranchIDshort), "Output")):
shutil.rmtree(os.path.join("C:\\Doc{}CS".format(BranchIDshort), "Output"))
Thank you, #Adonis!
I am invoking Robot Framework on a folder with a command like following:
robot --name MyTestSuite --variablefile lib/global_variables.py --variable TARGET_TYPE:FOO --variable IMAGE_TYPE:BAR --prerunmodifier MyCustomModifier.py ./tests
MyCustomModifier.py contains a simple SuiteVisitor class, which includes/excludes tags and does a few other things based on some of the variable values set.
How do I access TARGET_TYPE and IMAGE_TYPE in that class? The method shown here does not work, because I want access to the variables before tests start executing, and therefore I get a RobotNotRunningError with message Cannot access execution context.
After finding this issue report, I tried to downgrade to version 2.9.1 but nothing changed.
None of public API's seem to provide this information but debugging the main code does provide an alternative way of obtaining it. It has to be said that this example code will work with version 3.0.2, but may not work in the future as these are internal functions subject to change. That said, I do think that the approach will remain.
As Robot Framework is an application, it obtains the command line arguments through it's main function: run_cli (when running from command line). This function is filled with the arguments from the system itself and can be obtained throughout every python script via:
import sys
cli_args = sys.argv[1:]
Robot Framework has a function that interprets the commandline argument list and make it into a more readable object:
from robot.run import RobotFramework
import sys
options, arguments = RobotFramework().parse_arguments(sys.argv[1:])
The argument variable is a list where all the variables from the command line are added. An example:
arguments[0] = IMAGE_TYPE:BAR
This should allow you to access the information you need.
I am trying write a simple user defined function in Python that I pass a value to from Excel via Xlwings. I ran across some examples with an Add-in that you need to import user defined functions, but that seems overly complex.
Why isn't my example working?
VBA:
Function Hello(name As String) As String
RunPython ("import Test; Test.sayhi(name)")
End Function
Python (Test.py):
from xlwings import Workbook, Range
def sayhi(name):
wb = Workbook.caller()
return 'Hello {}'.format(name)
Error:
NameError: name 'name' is not defined
Make sure you're supplying the argument correctly:
RunPython ("import Test; Test.sayhi('" & name & "')")
The text inside RunPython() should be a valid python script. So the comment from "Tim Williams" is a quick solution. You just need to be careful to avoid ' character inside the name variable to break the python script.
If you need to write UDF (User Defined Function) a lot, or need to pass in value to get the output and then handle the result via VBA, try use ExcelPython instead of Xlwings.
Note, ExcelPython and Xlwings can work together, you can have both without conflict.
I think it's better you play the example to understand the difference. My understanding is limited to my knowledge, which might not be correct.
To summarize the difference:
ExcelPython needs a installer to be installed, it is good in UDF, which helps if you want to pass arguments in and out, and the function is cached in memory, so later call will be very quick.
Xlwings is simpler by just add the VBA module, no installer needed. It trigger Python in the background each time to run the script (each call starts a new process), in the script you can manipulate (read/write) Excel via COM.
I have the same question in the beginning, but later I find out using VBA in Excel side (intellisense) plus ExcelPython on UDF (simply process and return the data back) is a nice combination, so I think ExcelPython is only what I need.
As mentioned earlier, the 2 components have no conflict, you can have both. If the 2 author agree too, it is a good idea to combine them.
Please excuse what I know is an incredibly basic question that I have nevertheless been unable to resolve on my own.
I'm trying to switch over my data analysis from Matlab to Python, and I'm struggling with something very basic: in Matlab, I write a function in the editor, and to use that function I simply call it from the command line, or within other functions. The function that I compose in the matlab editor is given a name at the function definition line, and it's generally best for the function name to match the .m file name to avoid confusion.
I don't understand how functions differ in Python, because I have not been successful translating the same approach there.
For instance, if I write a function in the Python editor (I'm using Python 2.7 and Spyder), simply saving the .py file and calling it by its name from the Python terminal does not work. I get a "function not defined" error. However, if I execute the function within Spyder's editor (using the "run file" button), not only does the code execute properly, from that point on the function is also call-able directly from the terminal.
So...what am I doing wrong? I fully appreciate that using Python isn't going to be identical to Matlab in every way, but it seems that what I'm trying to do isn't unreasonable. I simply want to be able to write functions and call them from the python command line, without having to run each and every one through the editor first. I'm sure my mistake here must be very simple, yet doing quite a lot of reading online hasn't led me to an answer.
Thanks for any information!
If you want to use functions defined in a particular file in Python you need to "import" that file first. This is similar to running the code in that file. Matlab doesn't require you to do this because it searches for files with a matching name and automagically reads in the code for you.
For example,
myFunction.py is a file containing
def myAdd(a, b):
return a + b
In order to access this function from the Python command line or another file I would type
from myFunction import myAdd
And then during this session I can type
myAdd(1, 2)
There are a couple of ways of using import, see here.
You need to a check for __main__ to your python script
def myFunction():
pass
if __name__ == "__main__":
myFunction()
then you can run your script from terminal like this
python myscript.py
Also if your function is in another file you need to import it
from myFunctions import myFunction
myFunction()
Python doesn't have MATLAB's "one function per file" limitation. You can have as many functions as you want in a given file, and all of them can be accessed from the command line or from other functions.
Python also doesn't follow MATLAB's practice of always automatically making every function it can find usable all the time, which tends to lead to function name collisions (two functions with the same name).
Instead, Python uses the concept of a "module". A module is just a file (your .py file). That file can have zero or more functions, zero or more variables, and zero or more classes. When you want to use something from that file, you just import it.
So say you have a file 'mystuff.py':
X = 1
Y = 2
def myfunc1(a, b):
do_something
def myfunc2(c, d):
do_something
And you want to use it, you can just type import mystuff. You can then access any of the variables or functions in mystuff. To call myfunc2, you can just do mystuff.myfunc2(z, w).
What basically happens is that when you type import mystuff, it just executes the code in the file, and makes all the variables that result available from mystuff.<varname>, where <varname> is the name of the variable. Unlike in MATLAB, Python functions are treated like any other variable, so they can be accessed just like any other variable. The same is true with classes.
There are other ways to import, too, such as from mystuff import myfunc.
You run python programs by running them with
python program.py