Following up on this question and it's answer, I am trying to create an SPSS custom function in Python, to use in SPSS syntax.
I have a program that works well in a syntax:
begin program.
import spss,spssaux, sys
def CustomFunction ():
#function code here
CustomFunction()
end program.
But I want the CustomFunction()to be available in "normal" SPSS syntax.
Standard syntax does not use Python code nor does it add Python functions to, say, the transformation system. If you have a Python module, its contents can be used directly by just importing that module. And don't worry about importing it multiple times as Python is smart about ignoring redundant imports.
If you want to use Python code as regular syntax, you need to create an extension command. These have standard-style syntax but are implemented in Python (or R or Java). There are many of these either installed with Statistics or installable from the Utilities menu (or the Extensions menu in V24). Information on how to write these is in the Python help doc and related topics in the Help system.
As an example, the SPSSINC TRANS extension command makes Python functions available as transformation code. If CustomFunction, say, creates or transforms a variable casewise and is stored in mymodule.py, it might be invoked like this.
SPSSINC TRANS RESULT=newvar
/FORMULA "mymodule.CustomFunction(x,y,z)".
Extension commands are automatically loaded when Statistics starts, so there is no need for a startup script.
Related
I am using vs code for python scripts. These scripts run on the server only.
The server however, passes certain variables to the script while executing the script.
e.g mbo is always passed in it. mbo is special keyword which corresponds to a some class.
Sample mbo.py
class Mbo:
def getString(column: str)-> str:
return 'ABC'
def setString(columnName: str)-> None:
# do something with columnName.
Goal:
In my project in any python file whenever the user types mbo followed by a . vs code should show autoscomplete for .getString() and .setString() without importing this class as it is passed to the script by server.
I can try to write an extension for vs code to add this feature.
Here, I am stuck that what kind of extension is needed here. A LSP? I don't want to loose the feature of the existing python LSP for python.
Can any one proficient with vs code extension API guide me in right direction.
Note: I cannot import this Mbo class just for autocompletion in vscode because I import it. Then I run the same script on server. The server throws errors about the file.
You could try making the imports conditional:
try:
mbo
except NameError:
import mbo
That might be enough to make one of the two IntelliSense engines in the Python extension work.
Otherwise you are looking at your own extension. LSP is obviously the best option but there's also the classic style of registering classes. The VS Code docs have the details. But you are still probably going to clash with the Python extension as both it and your extension will be registered to work with Python files.
I've got a kind of weird question--but would be immensely useful if it is possible--in Maya using Python, can I take in several points of user input and have Python create a separate script for me? In this instance, I want to take in controller and locator names and have Python spit out a complete IKFK match script also in Python (it's really just a lot of getAttr and setAttr commands, although with 6 if statements per limb for PV matching.) The only other wrinkle there is that it has to be able to prefix hierarchy names in the script if necessary if the rig is imported into a new scene rather than just opened. There's an expression component to my switches that it would be nice if Python could make for me, too.
Is this possible or am I crazy?
That's no problem. Just write a textfile with a .py extension into a path where maya can find it. Then you have to import it somewhere. Creating expressions is not a problem either.
Maybe it could make sense to think about the approach you choose. Imagine you have written a dozen of these new python files and you discover a problem in the script, you will have to redo it. I'd try to collect all data and only write the required informations into a textfile e.g. in json format. Then you can read the data and rebuild your skeletons.
I am aware that there are multiple libraries for both languages (R/Python) to call modules from the other one. I am looking for a way to have the backend of my code running in python mainly because of .pyc and speed, and also the front end running in R so I can have a Shiny app. I couldn't find a way to make python machine for the backend. If anyone knows how to do it in R/Rstudio please respond.
I don't have any good benchmarks on it's speed, but the reticulate package is the best way I know of to pass data to and from a python script without using a webserver. It lets you import python objects into R where they will act like R objects, accepting arguments and returning values.
There were a few wonky problems that I had when I just wanted to run functions from a single file. It ran into problems with import statements and multiple functions that called on each other. What worked well was to run the import statements separately (see the sapply() statement below) and to merge all the code in my python script into a single object. This worked nicely and seemed about as fast as running it in python normally (though I haven't done any real benchmarking)
library(reticulate)
use_python(python = '/usr/bin/python') # optionally specify python location
# Import statements are here, not in the file
sapply(c("import mysql.connector", "import re"), py_run_string)
# File contains only the definition of class MismatchFinder
source_python("python_script.py")
# Now we can call on that python object from R
result <- MismatchFinder()$find_mismatch(arg1, arg2)
My impression is that it might be simpler if you make your python code into a module and load it with: py_module <- import_from_path('my_python_module', path = 'PATH') but I didn't try that.
Hope this helps!
I believe what you are looking for is the code below. It will run a python script in R.
system('python3 file_name.py')
My script depends on loading lots of variables in a minute and uses them globally in many functions. Every time I call that script in iPython, it loads them again, taking time.
I tried to take these calls to load and populate functions out of that script, but then these global variables are not available to the functions in the script.
It gives NameError: name 'clf' is not defined error message.
Is there a best way to refactor this code to keep these globals in memory and make the script use them? The script loads many variables like these, and uses them in other functions as globals.
vectorizer_title, vectorizer_desc, clf,
df_instance, vocab, all_tokens, df_dist_all,
df_soc2class_proba, dict_p2s,
dict_f2m, token_pattern, cleanup_pattern,
excluded_words = load_data_and_model(lang)
dict_token2idx_all, dict_token2idx_instance,
dist_array, token_dist_to_instance_min,
dict_bigram_by_instance, denominate,
similar_threshold = populate_data(1)
I had asked this question after trying
from depended_library import *
it had not worked in iPython.
But used with python and used in a Flask Web API it works.
Importing library using the "from" statement executes also the codes out of functions in the depended_library in addition to defining functions.
(If someone explains the problem with iPython and suggest a solution, I shall select it as answer.)
I have Sage 4.7.1 installed and have run into an odd problem. Many of my older scripts that use functions like deepcopy() and uniq() no longer recognize them as global names. I have been able to fix this by importing the python modules one by one, but this is quite tedious. But when I start the command-line Sage interface, I can type "list2=deepcopy(list1)" without importing the copy module, and this works fine. How is it possible that the command line Sage can recognize global name 'deepcopy' but if I load my script that uses the same name it doesn't recognize it?
oops, sorry, not familiar with stackoverflow yet. I type: 'sage_4.7.1/sage" to start the command line interface; then, I type "load jbom.py" to load up all the functions I defined in a python script. When I use one of the functions from the script, it runs for a few seconds (complex function) then hits a spot where I use some function that Sage normally has as a global name (deepcopy, uniq, etc) but for some reason the script I loaded does not know what the function is. And to reiterate, my script jbom.py used to work the last time I was working on this particular research, just as I described.
It also makes no difference if I use 'load jbom.py' or 'import jbom'. Both methods get the functions I defined in my script (but I have to use jbom. in the second case) and both get the same error about 'deepcopy' not being a global name.
REPLY TO DSM: I have been sloppy about describing the problem, for which I am sorry. I have created a new script 'experiment.py' that has "import jbom" as its first line. Executing the function in experiment.py recognizes the functions in jbom.py but deepcopy is not recognized. I tried loading jbom.py as "load jbom.py" and I can use the functions just like I did months ago. So, is this all just a problem of layering scripts without proper usage of import/load etc?
SOLVED: I added "from sage.all import *" to the beginning of jbom.py and now I can load experiment.py and execute the functions calling jbom.py functions without any problems. From the Sage doc on import/load I can't really tell what I was doing wrong exactly.
Okay, here's what's going on:
You can only import files ending with .py (ignoring .py[co]) These are standard Python files and aren't preparsed, so 1/3 == int(0), not QQ(1)/QQ(3), and you don't have the equivalent of a from sage.all import * to play with.
You can load and attach both .py and .sage files (as well as .pyx and .spyx and .m). Both have access to Sage definitions but the .py files aren't preparsed (so y=17 makes y a Python int) while the .sage files are (so y=17 makes y a Sage Integer).
So import jbom here works just like it would in Python, and you don't get the access to what Sage has put in scope. load etc. are handy but they don't scale up to larger programs so well. I've proposed improving this in the past and making .sage scripts less second-class citizens, but there hasn't yet been the mix of agreement on what to do and energy to do it. In the meantime your best bet is to import from sage.all.