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How to know the name of a classs loade like parameter on other class - Pyhton [duplicate]

This question already has answers here:
Getting the name of a variable as a string
(32 answers)
Closed 4 months ago.
Is it possible to get the original variable name of a variable passed to a function? E.g.
foobar = "foo"
def func(var):
print var.origname
So that:
func(foobar)
Returns:
>>foobar
EDIT:
All I was trying to do was make a function like:
def log(soup):
f = open(varname+'.html', 'w')
print >>f, soup.prettify()
f.close()
.. and have the function generate the filename from the name of the variable passed to it.
I suppose if it's not possible I'll just have to pass the variable and the variable's name as a string each time.

EDIT: To make it clear, I don't recommend using this AT ALL, it will break, it's a mess, it won't help you in any way, but it's doable for entertainment/education purposes.
You can hack around with the inspect module, I don't recommend that, but you can do it...
import inspect
def foo(a, f, b):
frame = inspect.currentframe()
frame = inspect.getouterframes(frame)[1]
string = inspect.getframeinfo(frame[0]).code_context[0].strip()
args = string[string.find('(') + 1:-1].split(',')
names = []
for i in args:
if i.find('=') != -1:
names.append(i.split('=')[1].strip())
else:
names.append(i)
print names
def main():
e = 1
c = 2
foo(e, 1000, b = c)
main()
Output:
['e', '1000', 'c']

To add to Michael Mrozek's answer, you can extract the exact parameters versus the full code by:
import re
import traceback
def func(var):
stack = traceback.extract_stack()
filename, lineno, function_name, code = stack[-2]
vars_name = re.compile(r'\((.*?)\).*$').search(code).groups()[0]
print vars_name
return
foobar = "foo"
func(foobar)
# PRINTS: foobar

Looks like Ivo beat me to inspect, but here's another implementation:
import inspect
def varName(var):
lcls = inspect.stack()[2][0].f_locals
for name in lcls:
if id(var) == id(lcls[name]):
return name
return None
def foo(x=None):
lcl='not me'
return varName(x)
def bar():
lcl = 'hi'
return foo(lcl)
bar()
# 'lcl'
Of course, it can be fooled:
def baz():
lcl = 'hi'
x='hi'
return foo(lcl)
baz()
# 'x'
Moral: don't do it.

Another way you can try if you know what the calling code will look like is to use traceback:
def func(var):
stack = traceback.extract_stack()
filename, lineno, function_name, code = stack[-2]
code will contain the line of code that was used to call func (in your example, it would be the string func(foobar)). You can parse that to pull out the argument

You can't. It's evaluated before being passed to the function. All you can do is pass it as a string.

#Ivo Wetzel's answer works in the case of function call are made in one line, like
e = 1 + 7
c = 3
foo(e, 100, b=c)
In case that function call is not in one line, like:
e = 1 + 7
c = 3
foo(e,
1000,
b = c)
below code works:
import inspect, ast
def foo(a, f, b):
frame = inspect.currentframe()
frame = inspect.getouterframes(frame)[1]
string = inspect.findsource(frame[0])[0]
nodes = ast.parse(''.join(string))
i_expr = -1
for (i, node) in enumerate(nodes.body):
if hasattr(node, 'value') and isinstance(node.value, ast.Call)
and hasattr(node.value.func, 'id') and node.value.func.id == 'foo' # Here goes name of the function:
i_expr = i
break
i_expr_next = min(i_expr + 1, len(nodes.body)-1)
lineno_start = nodes.body[i_expr].lineno
lineno_end = nodes.body[i_expr_next].lineno if i_expr_next != i_expr else len(string)
str_func_call = ''.join([i.strip() for i in string[lineno_start - 1: lineno_end]])
params = str_func_call[str_func_call.find('(') + 1:-1].split(',')
print(params)
You will get:
[u'e', u'1000', u'b = c']
But still, this might break.

You can use python-varname package
from varname import nameof
s = 'Hey!'
print (nameof(s))
Output:
s
Package below:
https://github.com/pwwang/python-varname

For posterity, here's some code I wrote for this task, in general I think there is a missing module in Python to give everyone nice and robust inspection of the caller environment. Similar to what rlang eval framework provides for R.
import re, inspect, ast
#Convoluted frame stack walk and source scrape to get what the calling statement to a function looked like.
#Specifically return the name of the variable passed as parameter found at position pos in the parameter list.
def _caller_param_name(pos):
#The parameter name to return
param = None
#Get the frame object for this function call
thisframe = inspect.currentframe()
try:
#Get the parent calling frames details
frames = inspect.getouterframes(thisframe)
#Function this function was just called from that we wish to find the calling parameter name for
function = frames[1][3]
#Get all the details of where the calling statement was
frame,filename,line_number,function_name,source,source_index = frames[2]
#Read in the source file in the parent calling frame upto where the call was made
with open(filename) as source_file:
head=[source_file.next() for x in xrange(line_number)]
source_file.close()
#Build all lines of the calling statement, this deals with when a function is called with parameters listed on each line
lines = []
#Compile a regex for matching the start of the function being called
regex = re.compile(r'\.?\s*%s\s*\(' % (function))
#Work backwards from the parent calling frame line number until we see the start of the calling statement (usually the same line!!!)
for line in reversed(head):
lines.append(line.strip())
if re.search(regex, line):
break
#Put the lines we have groked back into sourcefile order rather than reverse order
lines.reverse()
#Join all the lines that were part of the calling statement
call = "".join(lines)
#Grab the parameter list from the calling statement for the function we were called from
match = re.search('\.?\s*%s\s*\((.*)\)' % (function), call)
paramlist = match.group(1)
#If the function was called with no parameters raise an exception
if paramlist == "":
raise LookupError("Function called with no parameters.")
#Use the Python abstract syntax tree parser to create a parsed form of the function parameter list 'Name' nodes are variable names
parameter = ast.parse(paramlist).body[0].value
#If there were multiple parameters get the positional requested
if type(parameter).__name__ == 'Tuple':
#If we asked for a parameter outside of what was passed complain
if pos >= len(parameter.elts):
raise LookupError("The function call did not have a parameter at postion %s" % pos)
parameter = parameter.elts[pos]
#If there was only a single parameter and another was requested raise an exception
elif pos != 0:
raise LookupError("There was only a single calling parameter found. Parameter indices start at 0.")
#If the parameter was the name of a variable we can use it otherwise pass back None
if type(parameter).__name__ == 'Name':
param = parameter.id
finally:
#Remove the frame reference to prevent cyclic references screwing the garbage collector
del thisframe
#Return the parameter name we found
return param

If you want a Key Value Pair relationship, maybe using a Dictionary would be better?
...or if you're trying to create some auto-documentation from your code, perhaps something like Doxygen (http://www.doxygen.nl/) could do the job for you?

I wondered how IceCream solves this problem. So I looked into the source code and came up with the following (slightly simplified) solution. It might not be 100% bullet-proof (e.g. I dropped get_text_with_indentation and I assume exactly one function argument), but it works well for different test cases. It does not need to parse source code itself, so it should be more robust and simpler than previous solutions.
#!/usr/bin/env python3
import inspect
from executing import Source
def func(var):
callFrame = inspect.currentframe().f_back
callNode = Source.executing(callFrame).node
source = Source.for_frame(callFrame)
expression = source.asttokens().get_text(callNode.args[0])
print(expression, '=', var)
i = 1
f = 2.0
dct = {'key': 'value'}
obj = type('', (), {'value': 42})
func(i)
func(f)
func(s)
func(dct['key'])
func(obj.value)
Output:
i = 1
f = 2.0
s = string
dct['key'] = value
obj.value = 42
Update: If you want to move the "magic" into a separate function, you simply have to go one frame further back with an additional f_back.
def get_name_of_argument():
callFrame = inspect.currentframe().f_back.f_back
callNode = Source.executing(callFrame).node
source = Source.for_frame(callFrame)
return source.asttokens().get_text(callNode.args[0])
def func(var):
print(get_name_of_argument(), '=', var)

If you want to get the caller params as in #Matt Oates answer answer without using the source file (ie from Jupyter Notebook), this code (combined from #Aeon answer) will do the trick (at least in some simple cases):
def get_caller_params():
# get the frame object for this function call
thisframe = inspect.currentframe()
# get the parent calling frames details
frames = inspect.getouterframes(thisframe)
# frame 0 is the frame of this function
# frame 1 is the frame of the caller function (the one we want to inspect)
# frame 2 is the frame of the code that calls the caller
caller_function_name = frames[1][3]
code_that_calls_caller = inspect.findsource(frames[2][0])[0]
# parse code to get nodes of abstract syntact tree of the call
nodes = ast.parse(''.join(code_that_calls_caller))
# find the node that calls the function
i_expr = -1
for (i, node) in enumerate(nodes.body):
if _node_is_our_function_call(node, caller_function_name):
i_expr = i
break
# line with the call start
idx_start = nodes.body[i_expr].lineno - 1
# line with the end of the call
if i_expr < len(nodes.body) - 1:
# next expression marks the end of the call
idx_end = nodes.body[i_expr + 1].lineno - 1
else:
# end of the source marks the end of the call
idx_end = len(code_that_calls_caller)
call_lines = code_that_calls_caller[idx_start:idx_end]
str_func_call = ''.join([line.strip() for line in call_lines])
str_call_params = str_func_call[str_func_call.find('(') + 1:-1]
params = [p.strip() for p in str_call_params.split(',')]
return params
def _node_is_our_function_call(node, our_function_name):
node_is_call = hasattr(node, 'value') and isinstance(node.value, ast.Call)
if not node_is_call:
return False
function_name_correct = hasattr(node.value.func, 'id') and node.value.func.id == our_function_name
return function_name_correct
You can then run it as this:
def test(*par_values):
par_names = get_caller_params()
for name, val in zip(par_names, par_values):
print(name, val)
a = 1
b = 2
string = 'text'
test(a, b,
string
)
to get the desired output:
a 1
b 2
string text

Since you can have multiple variables with the same content, instead of passing the variable (content), it might be safer (and will be simpler) to pass it's name in a string and get the variable content from the locals dictionary in the callers stack frame. :
def displayvar(name):
import sys
return name+" = "+repr(sys._getframe(1).f_locals[name])

If it just so happens that the variable is a callable (function), it will have a __name__ property.
E.g. a wrapper to log the execution time of a function:
def time_it(func, *args, **kwargs):
start = perf_counter()
result = func(*args, **kwargs)
duration = perf_counter() - start
print(f'{func.__name__} ran in {duration * 1000}ms')
return result

How to check that print was called in a function?

Suppose f conditionally calls print; I'd like to know whether this happens within test_*(). How can this be accomplished?
Example:
def f(integer): # defined in and imported from separate module
if isinstance(integer, str):
print("WARNING: integer is str")
def test_f():
f("5")
assert print.called
Attempted approach:
def tracked_call(self, *args, **kwargs):
self.called = True
self.__call__(*args, **kwargs)
print.__call__ = tracked_call
>>> AttributeError: 'builtin_function_or_method' object attribute '__call__' is read-only

Solution 1 (best): check that print was called, and that it prints specific text; doesn't use a fixture:
import builtins
import contextlib, io
from unittest.mock import Mock
def test_f():
mock = Mock()
mock.side_effect = print # ensure actual print is called to capture its txt
print_original = print
builtins.print = mock
try:
str_io = io.StringIO()
with contextlib.redirect_stdout(str_io):
f("5")
output = str_io.getvalue()
assert print.called # `called` is a Mock attribute
assert output.startswith("WARNING:")
finally:
builtins.print = print_original # ensure print is "unmocked"
(If print in f writes to sys.stderr instead of the default sys.stdout, use contextlib.redirect_stderr.)
Solution 2: check that print prints specific text within call; from docs:
def test_f(capsys):
f("5")
out, err = capsys.readouterr()
assert out.startswith("WARNING:")
This assuming the default print(file=sys.stdout), else the string of interest is in err. If specific text is of no interest, can do assert out or err to verify that something was printed. This doesn't necessarily test whether print was called, as we can do print(end='').

Threading problem with threadpool and objects

I have a problem when using objects and treads.
Below follows a simplified example of the code.
I am using a threadpool to loop over a list of jobs.
class File(object):
def __init__(self, name, streams = [])
self.name = name
self.streams = streams
def appendStream(stream):
self.streams.append(stream)
class Job(object):
def __init__(self, file):
self.file = file
def main():
...
jobs = []
for f in input_files:
f_obj = File(f)
jobs.append(Job(f_obj))
with ThreadPool(processes = 2, initializer = init, initargs = (log, p_lock)) as pool:
pool.map(func = process_job, iterable = jobs, chunksize = 1)
...
The function (process_job) used by the thread pool resides in the same .py file.
def process_job(job):
...
get_info(job.file)
...
This function in turn uses a function (get_info) from a self defined package.
This function creates an argument list and then calls subprocess.check_output().
The subprocess returns a json struct which is looped over to update the contents of the input object.
def get_info(file):
...
args = ["ffprobe", ..., "-i", file.name]
try:
output = subprocess.check_output(args)
except Exception as e:
print(e)
data = info_json.decode('utf8')
json_data = json.loads(data)
for item in info_json:
file.appendStream(item["stream"])
...
The problem is that when running this code the threads spawned by the pool is updating each others file objects.
For example when running this with 5 input files the 5th job.file.streams will contain 5 streams i.e the 4 previous streams that belongs to the other files.
Why is this happening and how can I solve it.
Best regards!

As #torek spotted it seems to be a case of the "Mutable Default Argument".
“Least Astonishment” and the Mutable Default Argument

Python function call within a property of a class

I am trying to use the "setx" function of a Property in a Class to do some processing of date information that I get from excel. I have a few of my own functions that do the data processing which I tested outside the class, and they worked just fine. But when I move them into the class they suddenly become invisible unless I use the self. instance first. When I use the self.My_xldate_as_tuple() method I get an error:
My_xldate_as_tuple() takes 1 positional argument but 2 were given
Even though the code is EXACTLY what i used outside the class before and it worked.
Before moving into the Property Set block, I was doing the processing of date data outside of the class and setting the variables from outside of the class. That gets clunky when I have about 15 different operations that are all based on when the NumDates Property change. I'm showing shortened versions of both the working set of code and the non-working set of code. What is going on with the self. call that changes how the function takes inputs?
Broken Code:
class XLDataClass(object):
_NumDates = []
TupDates = []
def getNumDates(self): return self._NumDates
def setNumDates(self, value):
self._NumDates = value
self.TupDates = list(map(self.My_xldate_as_tuple,value)) #Error here
#This version doesn't work either, since it can't find My_xldate_as_tuple anymore
self.TupDates = list(map(My_xldate_as_tuple,value))
def delNumDates(self):del self._NumDates
NumDates = property(getNumDates,setNumDates,delNumDates,"Ordinal Dates")
#exact copy of the My_xldate_as_tuple function that works outside the class
def My_xldate_as_tuple(Date):
return xlrd.xldate_as_tuple(Date,1)
#Other code and functions here
#end XlDataClass
def GetExcelData(filename,rowNum,titleCol):
csv = np.genfromtxt(filename, delimiter= ",")
NumDates = deque(csv[rowNum,:])
if titleCol == True:
NumDates.popleft()
return NumDates
#Setup
filedir = "C:/Users/blahblahblah"
filename = filedir + "/SamplePandL.csv"
xlData = XLDataClass()
#Put csv data into xlData object
xlData.NumDates= GetExcelData(filename,0,1)
Working Code:
class XLDataClass(object):
NumDates = []
TupDates = []
#Other code and functions here
#end XlDataClass
#exact copy of the same function outside of the class, which works here
def My_xldate_as_tuple(Date):
return xlrd.xldate_as_tuple(Date,1)
def GetExcelData(filename,rowNum,titleCol):
csv = np.genfromtxt(filename, delimiter= ",")
NumDates = deque(csv[rowNum,:])
if titleCol == True:
NumDates.popleft()
return NumDates
#Setup
filedir = "C:/Users/blahblahblah"
filename = filedir + "/SamplePandL.csv"
xlData = XLDataClass()
#Put csv data into xlData object
xlData.NumDates = GetExcelData(filename,0,1)
#same call to the function that was inside the Setx Property of the class, but it works here.
xlData.TupDates = list(map(self.My_xldate_as_tuple,value))

Instance methods in Python require an explicit self in the argument list. Inside the class, you need to write your method definition like:
def My_xldate_as_tuple(self, Date):

How to watch for a variable change in python without dunder setattr or pdb

There is large python project where one attribute of one class just have wrong value in some place.
It should be sqlalchemy.orm.attributes.InstrumentedAttribute, but when I run tests it is constant value, let's say string.
There is some way to run python program in debug mode, and run some check (if variable changed type) after each step throught line of code automatically?
P.S. I know how to log changes of attribute of class instance with help of inspect and property decorator. Possibly here I can use this method with metaclasses...
But sometimes I need more general and powerfull solution...
Thank you.
P.P.S. I need something like there: https://stackoverflow.com/a/7669165/816449, but may be with more explanation of what is going on in that code.

Well, here is a sort of slow approach. It can be modified for watching for local variable change (just by name). Here is how it works: we do sys.settrace and analyse the value of obj.attr each step. The tricky part is that we receive 'line' events (that some line was executed) before line is executed. So, when we notice that obj.attr has changed, we are already on the next line and we can't get the previous line frame (because frames aren't copied for each line, they are modified ). So on each line event I save traceback.format_stack to watcher.prev_st and if on the next call of trace_command value has changed, we print the saved stack trace to file. Saving traceback on each line is quite an expensive operation, so you'd have to set include keyword to a list of your projects directories (or just the root of your project) in order not to watch how other libraries are doing their stuff and waste cpu.
watcher.py
import traceback
class Watcher(object):
def __init__(self, obj=None, attr=None, log_file='log.txt', include=[], enabled=False):
"""
Debugger that watches for changes in object attributes
obj - object to be watched
attr - string, name of attribute
log_file - string, where to write output
include - list of strings, debug files only in these directories.
Set it to path of your project otherwise it will take long time
to run on big libraries import and usage.
"""
self.log_file=log_file
with open(self.log_file, 'wb'): pass
self.prev_st = None
self.include = [incl.replace('\\','/') for incl in include]
if obj:
self.value = getattr(obj, attr)
self.obj = obj
self.attr = attr
self.enabled = enabled # Important, must be last line on __init__.
def __call__(self, *args, **kwargs):
kwargs['enabled'] = True
self.__init__(*args, **kwargs)
def check_condition(self):
tmp = getattr(self.obj, self.attr)
result = tmp != self.value
self.value = tmp
return result
def trace_command(self, frame, event, arg):
if event!='line' or not self.enabled:
return self.trace_command
if self.check_condition():
if self.prev_st:
with open(self.log_file, 'ab') as f:
print >>f, "Value of",self.obj,".",self.attr,"changed!"
print >>f,"###### Line:"
print >>f,''.join(self.prev_st)
if self.include:
fname = frame.f_code.co_filename.replace('\\','/')
to_include = False
for incl in self.include:
if fname.startswith(incl):
to_include = True
break
if not to_include:
return self.trace_command
self.prev_st = traceback.format_stack(frame)
return self.trace_command
import sys
watcher = Watcher()
sys.settrace(watcher.trace_command)
testwatcher.py
from watcher import watcher
import numpy as np
import urllib2
class X(object):
def __init__(self, foo):
self.foo = foo
class Y(object):
def __init__(self, x):
self.xoo = x
def boom(self):
self.xoo.foo = "xoo foo!"
def main():
x = X(50)
watcher(x, 'foo', log_file='log.txt', include =['C:/Users/j/PycharmProjects/hello'])
x.foo = 500
x.goo = 300
y = Y(x)
y.boom()
arr = np.arange(0,100,0.1)
arr = arr**2
for i in xrange(3):
print 'a'
x.foo = i
for i in xrange(1):
i = i+1
main()

There's a very simple way to do this: use watchpoints.
Basically you only need to do
from watchpoints import watch
watch(your_object.attr)
That's it. Whenever the attribute is changed, it will print out the line that changed it and how it's changed. Super easy to use.
It also has more advanced features, for example, you can call pdb when the variable is changed, or use your own callback functions instead of print it to stdout.

A simpler way to watch for an object's attribute change (which can also be a module-level variable or anything accessible with getattr) would be to leverage hunter library, a flexible code tracing toolkit. To detect state changes we need a predicate which can look like the following:
import traceback
class MutationWatcher:
def __init__(self, target, attrs):
self.target = target
self.state = {k: getattr(target, k) for k in attrs}
def __call__(self, event):
result = False
for k, v in self.state.items():
current_value = getattr(self.target, k)
if v != current_value:
result = True
self.state[k] = current_value
print('Value of attribute {} has chaned from {!r} to {!r}'.format(
k, v, current_value))
if result:
traceback.print_stack(event.frame)
return result
Then given a sample code:
class TargetThatChangesWeirdly:
attr_name = 1
def some_nested_function_that_does_the_nasty_mutation(obj):
obj.attr_name = 2
def some_public_api(obj):
some_nested_function_that_does_the_nasty_mutation(obj)
We can instrument it with hunter like:
# or any other entry point that calls the public API of interest
if __name__ == '__main__':
obj = TargetThatChangesWeirdly()
import hunter
watcher = MutationWatcher(obj, ['attr_name'])
hunter.trace(watcher, stdlib=False, action=hunter.CodePrinter)
some_public_api(obj)
Running the module produces:
Value of attribute attr_name has chaned from 1 to 2
File "test.py", line 44, in <module>
some_public_api(obj)
File "test.py", line 10, in some_public_api
some_nested_function_that_does_the_nasty_mutation(obj)
File "test.py", line 6, in some_nested_function_that_does_the_nasty_mutation
obj.attr_name = 2
test.py:6 return obj.attr_name = 2
... return value: None
You can also use other actions that hunter supports. For instance, Debugger which breaks into pdb (debugger on an attribute change).

Try using __setattr__ to override the function that is called when an attribute assignment is attempted. Documentation for __setattr__

You can use the python debugger module (part of the standard library)
To use, just import pdb at the top of your source file:
import pdb
and then set a trace wherever you want to start inspecting the code:
pdb.set_trace()
You can then step through the code with n, and investigate the current state by running python commands.

def __setattr__(self, name, value):
if name=="xxx":
util.output_stack('xxxxx')
super(XXX, self).__setattr__(name, value)
This sample code helped me.