I'm new to python and am using Spyder's IDE. One feature I appreciate about it is it's variable explorer. However, based on some research, I found that it only shows global variables. A workaround that I found for that is by using the inspect module:
import inspect
local_vars = {}
def main():
global local_vars
a = 2
b = 4
c = a+b
local_vars = inspect.currentframe().f_locals
return c
main()
This works well, however, I have other functions that are called from within main() and I'd like to see those variables in the variable explorer as well. I mimicked what was done for the variables in the main function and the dict does not appear. I noticed that when I disable the setting to "exclude unsupported data types" in Spyder's variable explorer options, the second dict appears with the right size attribute, however, I am unable to open/view it. Any ideas on a possible work around? This is my first time posting BTW.
Thanks!!
Here is a working example of my issue and I've traced it down to pylab subplots.
import inspect, pylab
mainVars = {}
def main():
global mainVars
a = 1
b = 2
fig = pylab.figure()
subPlot = fig.add_subplot(211) ## line of interest
pylab.close('all')
mainVars = inspect.currentframe().f_locals
main()
When the line of interest is commented out, the dict is created successfully and can be viewed. It appears that the object created using fig.add_subplot() is not being handled properly by the dict. It seems to be an unsupported datatype.
Hope this helps clarify the issue.
Thanks again.
To view the contents of local variables when some of them are unsupported, you have to follow these steps:
Go to the options menu of the Variable Explorer (the last icon from left to right on it).
Select the option called Exclude unsupported data types.
Then you'll see all local variables saved in the f_locals dict, even if you're unable to double click on it.
All of these workarounds are making your code significantly harder to read for outsiders. You have two options to inspect the values of the variables inside your function. First, you could just return the variables you are interested in:
def main():
a = 2
b = 4
c = a+b
return a, b, c
a, b, c = main()
Second, if you just want to check that the function works as expected or debug it, you can debug the function and step into it. So select Run|Debug from the menu instead of running the file directly. Then you can step into the function - the values of the variables will be visible in the variable explorer when the execution is inside the function.
Related
It happens to me that when reading/reviewing the code, I becomes easier if I can see the 'look' of the variable a function is processing.
For that, I'd like to display a 'static' version of an instance of that variable (as a visual aid).
That variable may not be there on another run of the notebook, that's why it has to be text, not output.
This is also useful when creating documentation within the notebook.
With this little function
#----------------------------------
def vdisplay(var):
"""Converts the var to a pretty string and inserts
it on a new cell just below the present one.
Then you have to change that 'next cell' type to Markdown and execute it.
"""
# To print the var nicely.
from pprint import pformat as pf
string_to_insert=f"""
This is how it looks like:
```
{pf(var)}
```
"""
# Create a code cell and insert a string in it
get_ipython().set_next_input(string_to_insert)
return
#----------------------------------
You can do this
# This is the data we want to show
x={i:str(i)*i for i in range(10)}
# Show it!
vdisplay(x)
Visually:
I use the mouse intentionally so you can see the steps. Using keyboard shortcuts is much quicker.
Story: I explored several venues. The last one was a combination of
%store var f.txt and %load f.txt but that involved some manual
work. The evolution of that method is the one above.
I am trying to get one boolean attribute (A) to change another(B). The one to be controlled (B) already has a script job running it and so I can't create a set driven key, direct connection, or expression to control it, so I'm trying another script job, since running the script function by itself achieves the desired result. I just can't figure out how to tie that script to run to the attribute change (B) that I want to drive it by (A).
This is placed in a script node set to the open gui trigger (to load when maya opens as I understand it). Here's a screenshot.
What am I missing here?
import maya.cmds as cmds
def togglePicker(pickerAttr):
cmds.setAttr(pickerAttr, not 0)
nameSpace = cmds.ls(sl=True)[0].rpartition(':')[0]
if len(nameSpace) > 0:
pickerAttr = nameSpace + ':Main.picker'
myPickerAttr = nameSpace + ':MoverMain_Cntrl.Picker'
else:
pickerAttr = 'Main.picker'
myPickerAttr = 'MoverMain_Cntrl.Picker'
cmds.scriptJob(attributeChange=[myPickerAttr,togglePicker])
Your script node is executed every time when maya loads a scene, not when it is started, at least that's what the docs say. So every time you load a scene, a new scriptJob is created.
Your script should show an error message since the togglePicker() function is called without an argument, but it requires an argument. Even if it works, it will not work.. what you do at the moment is the following:
As soon as you turn on the MoverMain_Cntrl.Picker attribute, the togglePicker() function is called and turns it on, even if you turn it off. The pickerAttrvariable is not used. So you should have a look at your program logic.
You can solve the agrument problem by using the partial function like this:
import maya.cmds as cmds
from functools import partial
def togglePicker(pickerAttr):
cmds.setAttr(pickerAttr, not 0)
nameSpace = cmds.ls(sl=True)[0].rpartition(':')[0]
if len(nameSpace) > 0:
pickerAttr = nameSpace + ':Main.picker'
myPickerAttr = nameSpace + ':MoverMain_Cntrl.Picker'
else:
pickerAttr = 'Main.picker'
myPickerAttr = 'MoverMain_Cntrl.Picker'
cmds.scriptJob(attributeChange=[myPickerAttr,partial(togglePicker, pickerAttr)])
I got it to work! (previously I had switched to the script node to MEL so I could test the mel command mentioned in the comments that did work, but I forgot to switch back to python when I realized the selection issue I also mentioned in the comments).
So here's what worked, where I know I'll have to manually change the namespace name in case the scene file name changes:
import maya.cmds as cmds
def togglePicker():
cmds.setAttr(pickerAttr, not 0)
if cmds.namespace(exists='ExtremeBallRig_v008'):
pickerAttr = 'ExtremeBallRig_v008:Main.picker'
myPickerAttr = 'ExtremeBallRig_v008:MoverMain_Cntrl.Picker'
else:
pickerAttr = 'Main.picker'
myPickerAttr = 'MoverMain_Cntrl.Picker'
cmds.scriptJob(attributeChange=[myPickerAttr,togglePicker])
I recently wrote a simple function that gets the present value of an asset, the function PV works properly and I have tested it. The function prints well in my pv file. However, when I run this code in the main file it does not print the output to the terminal and just closes after taking the inputs. Is there a reason for this? For reference the functions just perform some simple mathematics problems.
Below is a minimal reproduction, both files are in the same folder.
in file_x you have a function that works like this:
def func(w,x,y,z):
z1 = w/(1 + (x/100))**(y*z)
print(z1)
return 0
this function is then imported into another file which is written like so
from file_x import func
w = int(input("Future Value: "))
x = float(input("ROR: "))
y = float(input("# of periods: "))
z = float(input("# of payment per anum: "))
func(w,x,y,z)
My problem is that when I run the 2nd file it takes the inputs properly but does not print the result from the function. Hope it was explained properly
In interactive mode an unused expression (here PV(w,x,y,z) which does returns a value and that value is not used) is printed to the terminal, because it is a common way to just display expression values.
But when you run a script in a non interactive mode (python script.py) then those unused expression are just discarded. As a general rule, you should never have such an unused expression in a script, because the behaviour will depend on the interactive mode of the interpretor.
So you should be explicit:
_ = PV(w,x,y,z) # value will be discarded even in interactive mode
or
print(PV(w,x,y,z)) # value will be printed even in non interactive mode
Maybe I am completely off track here (and above my paygrade for sure), but what I want to do is to give users of my app (That I am writing in Python since that's the language I know) a python interpreter to control some objects within my app. Something similar like many 3D and VFX softwares have (Maya, Blender, Nuke). This is the code I got so far:
#main.py
import code
import networkx as nx
class Env():
def __init__(self):
self.graph = nx.graph.DiGraph()
# load library with functions that will be availabel for user inside the app.
import mylib
functions = {f: getattr(mylib, f) for f in dir(mylib) if not f.startswith('__')}
self._interpreter = code.InteractiveInterpreter(locals=functions)
def execute_node(self, node=None):
# In IRL the main object to be pass1ed to users' interpreter will be the self.graph object
# but I made it more clear for this question.
self._interpreter.locals['var'] = 42
node = "print(var)\nprint(some_function())\nvar = 67" # Let's pretend node object contains this code.
self._interpreter.runcode(node)
if __name__ == '__main__':
e = Env()
# some code, node creation and so on...
e.execute_code()
print(e.locals['var'])
#mylib.py
var = None # I have to put this here because if there is no variable function fails at import
def some_function():
print(var)
Output:
42 # This prints as expected
None # The print within the function prints the value that was there when module was initialized
67 # The last print returns expected value
So, it is clear that python interprets the functions on first import and "bakes" the global variables that it had at the import time. Now the question is can I somehow easily make it use the globals passed from the code.InteractiveInterpreter() or I should look for a completely different solution (and which one) :)? Of course the idea is that the two python programs should communicate, the user should use a special library to operate the software and the backend code should not be exposed to them. Do I make any sense? Thanks :)
This is the one-ish instance where you do want to use the exec() function, but please remember that the user may be able to run any Python code, including stuff that could run forever, mess up your main program, write (or delete) files, etc.
def run_code(code, add_locals={}):
code_locals = {}
code_locals.update(add_locals) # Copy in the additional locals so that dict could be reused
exec(
code,
{}, # no globals (you may wish to replace this),
code_locals,
)
return code_locals # return updated locals
class Beeper: # define a toy object
def beep(self, times):
print("Beep! " * times)
beeper = Beeper() # instantiate the object to play with
# Some user code...
user_code = """
x = 5
beeper.beep(x)
x += 3
"""
new_locals = run_code(user_code, {"beeper": beeper})
print(new_locals)
This outputs
Beep! Beep! Beep! Beep! Beep!
{'beeper': <__main__.Beeper>, 'x': 8}
So you can see we can use the locals the user has modified if need be.
I'd like to run ipython script in python, ie:
code='''a=1
b=a+1
b
c'''
from Ipython import executor
for l in code.split("\n"):
print(executor(l))
that whould print
None
None
2
NameError: name 'c' is not defined
does it exists ? I searched the doc, but it does not seems to be (well) documented.
In short, depending on what you want to do and how much IPython features you want to include, you will need to do more.
First thing you need to know is that IPython separates its code into blocks.
Each block has its own result.
If you use blocks use this advice
If you don't any magic IPython provides you with and don't want any results given by each block, then you could just try to use exec(compile(script, "exec"), {}, {}).
If you want more than that, you will need to actually spawn an InteractiveShell-instance as features like %magic and %%magic will need a working InteractiveShell.
In one of my projects I have this function to execute code in an InteractiveShell-instance:
https://github.com/Irrational-Encoding-Wizardry/yuuno/blob/master/yuuno_ipython/ipython/utils.py#L28
If you want to just get the result of each expression,
then you should parse the code using the ast-Module and add code to return each result.
You will see this in the function linked above from line 34 onwards.
Here is the relevant except:
if isinstance(expr_ast.body[-1], ast.Expr):
last_expr = expr_ast.body[-1]
assign = ast.Assign( # _yuuno_exec_last_ = <LAST_EXPR>
targets=[ast.Name(
id=RESULT_VAR,
ctx=ast.Store()
)],
value=last_expr.value
)
expr_ast.body[-1] = assign
else:
assign = ast.Assign( # _yuuno_exec_last_ = None
targets=[ast.Name(
id=RESULT_VAR,
ctx=ast.Store(),
)],
value=ast.NameConstant(
value=None
)
)
expr_ast.body.append(assign)
ast.fix_missing_locations(expr_ast)
Instead doing this for every statement in the body instead of the last one and replacing it with some "printResult"-transformation will do the same for you.