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.
Related
I recently started working in python with visual studio and I have 2 questions please:
Is there some kind of special configuration that you have to perform in order to be able to debug python code? Was I supposed to install something or did VS come this way?
Suppose im in a decoding session, inside a function that's declared in the scope of some class. Can I view the values of the class variables defined in the init? If so, how? I tried to write "self.someField" in the watch window but it didn't work.
Thanks you!
You could debug your python code like general debugging steps in VS, of course, it also has different settings or Environment options.
If you want to get much more detailed information, please see this document here:
Debugging your Python code
In addition, one thread for one issue, for the second issue:
2.Suppose im in a decoding session, inside a function that's declared in the scope of some class. Can I view the values of the class
variables defined in the init? If so, how? I tried to write
"self.someField" in the watch window but it didn't work.
If possible, I suggest you open a new case for this new issue, you could also share your main code, so other community members could really repro this issue in their side.
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')
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.
Say I'm working with the 'requests' Python library.
req = requests.get("http://google.com")
Now after this, if I type req., I'm supposed to get a list of all methods I can access. But for some reason I don't, even if I manually press Ctrl+Space.
If I try this in iPython, I get autocomplete recommendations. Even if I try it via the built in Python console in PyCharm, I get recommendations.
Why's this happening?
As Python is a dynamically typed language, you need to ensure it can work out what type things are, and inspect on the libraries on your system correctly. Try to make sure it's obvious what type the object is in your code.
One good way as of PyCharm 2.7 (back when versions were numbers) is to enable runtime type detection - PyCharm hooks into your program while it runs (while debugging), and checks the types of variables as they are used.
You can enable this by going to settings, going to the "Build, Execution, Deployment" section and then the "Python Debugger" subsection and enabling "Collect run-time types information for code insight".
Obviously it is worth noting that this isn't perfect - if you make changes, this won't be updated til the code is executed, and it can only tell you about values it has seen - other code paths you haven't tried could set other types.
You can also 'tell' PyCharm by using Epydoc or Sphinx style docstrings that contain information about parameter and return value types. PyCharm will use these to improve it's inspections.
Python also gained support for function annotations as of Python 3. These can be used for type hints as per PEP 484. See the typing module for more. This is more formal, so it can also be used for tools like mypy which a type checker that can programmatically check these types for consistency, giving Python a TypeScript-style optional static typing.
Python is a dynamically typed language, which means that the "get" function does not declare its return type. When you're entering code in IPython or in the PyCharm console, the code is actually being executed, and it's possible to inspect the object instance in the running interpreter and to get the list of its methods. When you're entering code in PyCharm or in any other Python IDE, it is not executed, and it's only possible to use static analysis to infer the return type of the method. This is not possible in all cases.
PyCharm has no idea what the dict contains if you fill it dynamically. So you have to hint PyCharm about the keys of dict beforehand. Prodict does exactly this to hint PyCharm, so you get code completion.
First, if you want to be able to access the response object, then you have to get a json response and convert it to dict. That's achieved with .json() method of requests like this:
response = requests.get("https://some.restservice.com/user/1").json()
OK, we loaded it to a dict object, now you can access keys with bracket syntax:
print(response['name'])
Since you ask for auto code completion, you certainly need to hint PyCharm about the keys of dict. If you already know the respone schema, you can use Prodict to hint PyCharm:
class Response(Prodict):
name: str
price: float
response_dict = requests.get("https://some.restservice.com/user/1").json()
response = Response.from_dict(response_dict)
print(response.name)
print(response.price)
In the above code, both name and price attributes are auto-complated.
If you don't know the schema of the response, then you can still use dot-notation to access dict attributes like this:
response_dict = requests.get("https://some.restservice.com/user/1").json()
response = Prodict.from_dict(response_dict)
print(response.name)
But code-completion will not be available since PyCharm can't know what the schema is.
What's more is, Prodict class is derived directly from dict, so you can use it as dict too.
This is the screenshot from Prodict repo that illustrates code completion:
Disclaimer: I am the author of Prodict.
if will just detect methods or variables and... with write some part of it:
File->Setting -> Editor -> General -> Code Completion
in top of opened window , unCheck [ Mach Case ]
It's an old question but probably all the provided answers missed the mark by a margin as wide as Sun's distance to Betelgeuse (none of the answers is accepted and #user1265125 is an active guy with 8 yrs here and more cred than me).
As it happens, I've just had exactly the same problem as OP and the solution was:
A NON-ASCII CHAR SOMEWHERE IN THE PROJECT'S FOLDER PATH
Seriously, PyCharm devs...[doubleFacepalm]
In my case the solution is to reset the settings, everething else wasn`t working for me.
"From the main menu, select File | Manage IDE Settings | Restore Default Settings.Alternatively, press Shift twice and type Restore default settings."
I had a similar problem. Only functions I had already used were suggested and only as plain text and not recognised as methods.
What fixed that for me was deleting the /.idea folder in the project directory. (Afterwards you will have to set your run configurations again)
With the latest version update to 2022.2, even auto-complete stopped working for me. After quite a bit of reading articles, I just found the https://youtrack.jetbrains.com/issue/PY-50489 issue which was the root problem. The old plugins were pending update, after that, the code completion issue was fixed.
So, try and check if you are facing the same problem, if the plugins are up to date in Settings —> Plugins.
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.