EDIT2：
A minimal demonstration is:
code = """\
a=1
def f1():
print(a)
print(f1.__closure__)
f1()
"""
def foo():
exec(code)
foo()
Which gives:
None
Traceback (most recent call last):
File "D:/workfiles/test_eval_rec.py", line 221, in <module>
foo()
File "D:/workfiles//test_eval_rec.py", line 219, in foo
exec(code)
File "<string>", line 5, in <module>
File "<string>", line 3, in f1
NameError: name 'a' is not defined
It can be seen that the __closure__ attribute of function defined inside code str passed to exec() is None, making calling the function fails.
Why does this happen and how can I define a function successfully?
I find several questions that may be related.
Closure lost during callback defined in exec()
Using exec() with recursive functions
Why exec() works differently when invoked inside of function and how to avoid it
Why are closures broken within exec?
NameError: name 'self' is not defined IN EXEC/EVAL
These questions are all related to "defining a function insdie exec()". I think the fourth question here is closest to the essence of these problems. The common cause of these problems is that when defining a function in exec(), the __closure__ attribute of the function object can not be set correctly and will always be None. However, many existing answers to this question didn't realize this point.
Why these questions are caused by wrong __closure__:
When defining a function, __closure__ attribute is set to a dict that contains all local symbols (at the place where the keyword def is used) that is used inside the newly defined funtion. When calling a function, local symbol tables will be retrived from the __closure__ attribute. Since the __closure__ is set to None, the local symbol tables can not be retrived as expected, making the function call fail.
These answers work by making None a correct __closure__ attribute:
Existing solutions to the questions listed above solve these problems by getting the function definition rid of the usage of local symbol, i.e, they make the local symbols used(variable, function definition) global by passing globals() as locals of exec or by using keyword global explicitly in the code string.
Why existing solution unsatisfying:
These solutions I think is just an escape of the core problem of setting __closure__ correctly when define a functioni inside exec(). And as symbols used in the function definition is made global, these solutions will produce redundant global symbol which I don't want.
Original Questions：
(You May ignore this session, I have figured something out, and what I currently want to ask is described as the session EDIT2. The original question can be viewed as a sepecial case of the question described in session EDIT2)
original title of this question is: Wrapping class function to new function with exec() raise NameError that ‘self’ is not defined
I want to wrap an existing member function to a new class function. However, exec() function failed with a NameError that ‘self’ is not defined.
I did some experiment with the following codes. I called globals() and locals() in the execed string, it seems that the locals() is different in the function definition scope when exec() is executed. "self" is in the locals() when in exec(), however, in the function definition scope inside the exec(), "self" is not in the locals().
class test_wrapper_function():
def __init__(self):
# first wrapper
def temp_func():
print("locals() inside the function definition without exec:")
print(locals())
return self.func()
print("locals() outside the function definition without exec:")
print(locals())
self.wrappered_func1 = temp_func
# third wrapper using eval
define_function_str = '''def temp_func():
print("locals() inside the function definition:")
print(locals())
print("globals() inside the function definition:")
print(globals())
return self.func()
print("locals() outside the function definition:")
print(locals())
print("globals() outside the function definition:")
print(globals())
self.wrappered_func2 = temp_func'''
exec(define_function_str)
# call locals() here, it will contains temp_func
def func(self):
print("hi!")
t = test_wrapper_function()
print("**********************************************")
t.wrappered_func1()
t.wrappered_func2()
I have read this link. In the exec(), memeber function, attribute of "self" can be accessed without problem, while in the function difinition in the exec(), "self" is not available any more. Why does this happen?
Why I want to do this:
I am building a PyQt program. I want to create several similar slots(). These slots can be generated by calling one member function with different arguments. I decided to generate these slots using exec() function of python. I also searched with the keyword "nested name scope in python exec", I found this question may be related, but there is no useful answer.
To be more specific. I want to define a family of slots like func_X (X can be 'a', 'b', 'c'...), each do something like self.do_something_on(X). Here, do_something is a member function of my QWidget. So I use a for loop to create these slots function. I used codes like this:
class MyWidget():
def __init__(self):
self.create_slots_family()
def do_something(self, character):
# in fact, this function is much more complex. Do some simplification.
print(character)
def create_slots_i(self, character):
# want to define a function like this:
# if character is 'C', define self.func_C such that self.func_C() works like self.do_something(C)
create_slot_command_str = "self.func_" + character + " = lambda:self.do_something('" + character + "')"
print(create_slot_command_str)
exec(create_slot_command_str)
def create_slots_family(self):
for c in ["A", "B", "C", "D"]:
self.create_slots_i(c)
my_widget = MyWidget()
my_widget.func_A()
Note that, as far as I know, the Qt slots should not accept any parameter, so I have to wrap self.do_something(character) to be a series function self.func_A, self.func_C and so on for all the possible characters.
So the above is what I want to do orignially.
EDIT1：
(You May ignore this session, I have figured something out, and what I currently want to ask is described as the session EDIT2. This simplified version of original question can also be viewed as a sepecial case of the question described in session EDIT2)
As #Mad Physicist suggested. I provide a simplified version here, deleting some codes used for experiments.
class test_wrapper_function():
def __init__(self):
define_function_str = '''\
def temp_func():
return self.func()
self.wrappered_func2 = temp_func'''
exec(define_function_str)
def func(self):
print("hi!")
t = test_wrapper_function()
t.wrappered_func2()
I expected this to print a "hi". However, I got the following exception:
Traceback (most recent call last):
File "D:/workfiles/test_eval_class4.py", line 12, in <module>
t.wrappered_func2()
File "<string>", line 2, in temp_func
NameError: name 'self' is not defined
Using Exec
You've already covered most of the problems and workarounds with exec, but I feel that there is still value in adding a summary.
The key issue is that exec only knows about globals and locals, but not about free variables and the non-local namespace. That is why the docs say
If exec gets two separate objects as globals and locals, the code will be executed as if it were embedded in a class definition.
There is no way to make it run as though it were in a method body. However, as you've already noted, you can make exec create a closure and use that instead of the internal namespace by adding a method body to your snippet. However, there are still a couple of subtle restrictions there.
Your example of what you are trying to do showcases the issues perfectly, so I will use a modified version of that. The goal is to make a method that binds to self and has a variable argument in the exec string.
class Test:
def create_slots_i(self, c):
create_slot_command_str = f"self.func_{c} = lambda: self.do_something('{c}')"
exec(create_slot_command_str)
def do_something(self, c):
print(f'I did {c}!')
There are different ways of getting exec to "see" variables: literals, globals, and internal closures.
Literals. This works robustly, but only for simple types that can be easily instantiated from a string. The usage of c above is a perfect example. This will not help you with a complex object like self:
>>> t = Test()
>>> t.create_slots_i('a')
>>> t.func_a()
...
NameError: name 'self' is not defined
This happens exactly because exec has no concept of free variables. Since self is passed to it via the default locals(), it does not bind the reference to a closure.
globals. You can pass in a name self to exec via globals. There are a couple of ways of doing this, each with its own issues. Remember that globals are accessed by a function through its __globals__ (look at the table under "Callable types") attribute. Normally __globals__ refers to the __dict__ of the module in which a function is defined. In exec, this is the case by default as well, since that's what globals() returns.
Add to globals: You can create a global variable named self, which will make your problem go away, sort of:
>>> self = t
>>> t.func_a()
I did a!
But of course this is a house of cards that falls apart as soon as you delete, self, modify it, or try to run this on multiple instances:
>>> del self
>>> t.func_a()
...
NameError: name 'self' is not defined
Copy globals. A much more versatile solution, on the surface of it, is to copy globals() when you run exec in create_slots_i:
def create_slots_i(self, c):
create_slot_command_str = f"self.func_{c} = lambda: self.do_something('{c}')"
g = globals().copy()
g['self'] = self
exec(create_slot_command_str, g)
This appears to work normally, and for a very limited set of cases, it actually does:
>>> t = Test()
>>> t.create_slots_i('a')
>>> t.func_a()
I did a!
But now, your function's __globals__ attribute is no longer bound to the module you created it in. If it uses any other global values, especially ones that might change, you will not be able to see the changes. For limited functionality, this is OK, but in the general case, it can be a severe handicap.
Internal Closures. This is the solution you already hit upon, where you create a closure within the exec string to let it know that you have a free variable by artificial means. For example:
class Test:
def create_slots_i(self, c):
create_slot_command_str = f"""def make_func(self):
def func_{c}():
self.do_something('{c}')
return func_{c}
self.func_{c} = make_func(self)"""
g = globals().copy()
g['self'] = self
exec(create_slot_command_str, g)
def do_something(self, c):
print(f'I did {c}!')
This approach works completely:
>>> t = Test()
>>> t.create_slots_i('a')
>>> t.func_a()
I did a!
The only real drawbacks here are security, which is always a problem with exec, and the sheer awkwardness of this monstrosity.
A Better Way
Since you are already creating closures, there is really no need to use exec at all. In fact, the only thing you are really doing is creating methods so that self.func_... will bind the method for you, since you need a function with the signature of your slot and access to self. You can write a simple method that will generate functions that you can assign to your slots directly. The advantage of doing it this way is that (a) you avoid calling exec entirely, and (b) you don't need to have a bunch of similarly named auto-generated methods polluting your class namespace. The slot generator would look something like this:
def create_slots_i(self, c):
def slot_func():
self.do_something(c) # This is a real closure now
slot_func.__name__ = f'func_{c}'
return slot_func
Since you will not be referring to these function objects anywhere except your slots, __name__ is the only way to get the "name" under which they were stored. That is the same thing that def does for you under the hood.
You can now assign slots directly:
some_widget.some_signal.connect(self.create_slots_i('a'))
Note
I originally had a more complex approach in mind for you, since I thought you cared about generating bound methods, instead of just setting __name__. In case you have a sufficiently complex scenario where it still applies, here is my original blurb:
A quick recap of the descriptor protocol: when you bind a function with the dot operator, e.g., t.func_a, python looks at the class for descriptors with that name. If your class has a data descriptor (like property, but not functions), then that descriptor will shadow anything you may have placed in the instance __dict__. However, if you have a non-data descriptor (one a __get__ method but without a __set__ method, like a function object), then it will only be bound if an instance attribute does not shadow it. Once this decision has been made, actually invoking the descriptor protocol involves calling type(t).func_a.__get__(t). That's how a bound method knows about self.
Now you can return a bound method from within your generator:
def create_slots_i(self, c):
def slot_func(self):
self.do_something(c) # This is a closure on `c`, but not on `self` until you bind it
slot_func.__name__ = f'func_{c}'
return slot_func.__get__(self)
Why this phenomena happen:
Actually the answer of the question 4 listed above can answer this question.
When call exec() on one code string, the code string is first compiled. I suppose that during compiling, the provided globals and locals is not considered. The symbol in the exec()ed code str is compiled to be in the globals. So the function defined in the code str will be considered using global variables, and thus __closure__ is set to None.
Refer to this answer for more information about what the func exec does.
How to deal with this phenomena:
Imitating the solutions provided in the previous questions, for the minimal demostration the question, it can also be modified this way to work:
a=1 # moving out of the variable 'code'
code = """\
def f1():
print(a)
print(f1.__closure__)
f1()
"""
def foo():
exec(code)
foo()
Although the __closure__ is still None, the exception can be avoided because now only the global symbol is needed and __closure__ should also be None if correctly set. You can read the part The reason why the solutions work in the question body for more information.
This was originally added in Revision 4 of the question.
TL;DR
To set correct __closure__ attribute of function defined in the code string passed to exec() function. Just wrap the total code string with a function definition.
I provide an example here to demonstrate all possible situations. Suppose you want to define a function named foo inside a code string used by exec(). The foo use function, variables that defined inside and outside the code string:
def f1():
outside_local_variable = "this is local variable defined outside code str"
def outside_local_function():
print("this is function defined outside code str")
code = """\
local_variable = "this is local variable defined inside code str"
def local_function():
print("this is function defined inside code str")
def foo():
print(local_variable)
local_function()
print(outside_local_variable)
outside_local_function()
foo()
"""
exec(code)
f1()
It can be wrapper like this:
def f1():
outside_local_variable = "this is local variable defined outside code str"
def outside_local_function():
print("this is function defined outside code str")
code = """\
def closure_helper_func(outside_local_variable, outside_local_function):
local_variable = "this is local variable defined inside code str"
def local_function():
print("this is function defined inside code str")
def foo():
print(local_variable)
local_function()
print(outside_local_variable)
outside_local_function()
foo()
closure_helper_func(outside_local_variable, outside_local_function)
"""
exec(code)
f1()
Detailed explanation:
Why the __closure__ attribute is not corretly set:
please refer to The community wiki answer.
How to set the __closure__ attribute to what's expected:
Just wrap the whole code str with a helper function definition and call the helper function once, then during compiling, the variables are considered to be local, and will be stored in the __closure__ attribute.
For the minimal demonstration in the question, it can be modified to following:
code = """\
def closure_helper_func():
a=1
def f1():
print(a)
print(f1.__closure__)
f1()
closure_helper_func()
"""
def foo():
exec(code)
foo()
This output as expected
(<cell at 0x0000019CE6239A98: int object at 0x00007FFF42BFA1A0>,)
1
The example above provide a way to add symbols that defined in the code str to the __closure__ For example, in the minimal demo, a=1 is a defined inside the code str. But what if one want to add the local symbols defined outside the code str? For example, in the code snippet in EDIT1 session, the self symbol needs to be added to the __closure__, and the symbol is provided in the locals() when exec() is called. Just add the name of these symbols to the arguments of helper function and you can handle this situation.
The following shows how to fix the problem in EDIT1 session.
class test_wrapper_function():
def __init__(self):
define_function_str = '''\
def closure_helper_func(self):
def temp_func():
return self.func()
self.wrappered_func2 = temp_func
closure_helper_func(self)
'''
exec(define_function_str)
def func(self):
print("hi!")
t = test_wrapper_function()
t.wrappered_func2()
The following shows how to fix the codes in the session "Why I want to do this"
class MyWidget():
def __init__(self):
self.create_slots_family()
def do_something(self, character):
# in fact, this function is much more complex. Do some simplification.
print(character)
def create_slots_i(self, character):
# want to define a function like this:
# if character is 'C', define self.func_C such that self.func_C() works like self.do_something(C)
# create_slot_command_str = "self.func_" + character + " = lambda:self.do_something('" + character + "')"
create_slot_command_str = """
def closure_helper_func(self):
self.func_""" + character + " = lambda:self.do_something('" + character + """')
closure_helper_func(self)
"""
# print(create_slot_command_str)
exec(create_slot_command_str)
def create_slots_family(self):
for c in ["A", "B", "C", "D"]:
self.create_slots_i(c)
my_widget = MyWidget()
my_widget.func_A()
This solution seems to be too tricky. However, I can not find a more elegant way to declare that some variables should be local symbol during compiling.
This question already has answers here:
Defining private module functions in python
(11 answers)
Closed last year.
for example i have myClassFile.py file with code as follow:
class myClass:
def first(self):
return 'tea'
def second(self):
print(f'drink {self.first()}')
then i have run.py file with code as follow:
from myClassFile import myClass
class_ = myClass()
class_.second()
which when i run will output
>>> 'drink tea'
how to prevent someone to write below code on run.py file or outside myClass ?
class_.first()
so that if they used that method outside myClass class it will be an error or some sort
You can add a level of protection around methods and attributes by prefixing them with __.
But you can't make them totally private (as far as I know), there's always a way around, as shown in example below.
class MyClass:
def __init__(self):
self.__a = 1
def __method(self):
return 2
obj = MyClass()
# obj.__a # raise an exception
# obj.__method() # raise an exception
print(dir(obj)) # you can see the method and attributes have been renamed !
print(obj._MyClass__a) # 1
print(obj._MyClass__method()) # 2
Python does not have support for these. You can mark them private by prefixing them with _, or make it harder to call them by prefixing them with __.
These are called private methods. To make a private variable or a method in python, just prefix it with a __, so def second(self) turns into def __second(self).
This also works for variables and functional programming variables!
class Test:
def test(self):
self.__test()
def __test(self):
print('_test')
x = Test()
x.__test()
gives an error, but x.test() prints _test out successfully!
Note, this can still be run by using x.__Test__test()
I thought that the following code would result in an error because as far as I have read, a method in a Python class must either have "self" (or any other label, but "self" by convention) as its first argument, or "cls" or similar if the #classmethod decorator is used, or none if the #staticmethod decorator is used.
How come I get no error running this with Python 3.5 in the Terminal, even though test_method does not meet these requirements? It seems to work fine as a static method, but without the decorator.
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sys
class MyClass:
def test_method(args):
print(args[1])
#staticmethod
def static_method():
print("static_method")
#classmethod
def class_method(cls):
print("class_method")
def main(args):
MyClass.test_method(args)
if __name__ == '__main__':
sys.exit(main(sys.argv))
Output:
$ python3 testscript.py "testing"
$ testing
EDIT:
My question could also be phrased differently, drawing attention away from self and to #staticmethod: "How come I'm getting a seemingly working static method without the #staticmethod decorator?"
In Python 2, functions defined in a class body are automatically converted to "unbound methods", and cannot be called directly without a staticmethod decorator. In Python 3, this concept was removed; MyClass.text_method is a simple function that lives inside the MyClass namespace, and can be called directly.
The main reason to still use staticmethod in Python 3 is if you also want to call the method on an instance. If you don't use the decorator, the method will always be passed the instance as the first parameter, causing a TypeError.
There is nothing special about this. In python 3 there is no difference between a function defined inside a class or a function defined outside a class. Both of them are normal functions.
The self that you are talking about here or maybe cls comes into picture only when you access the function through an instance. Hence here you didn't get any error.
However if you modify your code just a little bit to look like the following, then you'd get an error that you expected.
def main(args):
MyClass().test_method(args)
# Should throw an error
EDIT:
#staticmethod will work on both class instances like MyClass().test_method(args)and just a regular direct call like MyClass.test_method(args)
However a regular method(without self in it) can't be called on a class instance. So you will always have to call it as MyClass.test_method(args)
self isn't necessarily required. However, if you want to reference any variable or value that is associated with the object(instantiation of the class) (E.g. for a class about cars, it's speed, self.speed) you'll need to have self as a parameter in the function. For this reason, it's common practice to always have self as an argument, otherwise you aren't really using the class for the right reason.
EDIT:
This will actually throw an error if you do the following:
class a():
def __init__(self, x):
self.asd = x
def hello(x):
print(x)
>>> g = a(4)
>>> g.hello(5)
as when calling "hello", both "self" and "4" will be passed as parameters. It would work in the following instance, which is what I was saying above:
>>> g = a
>>> g.hello(4)
or
>>> a.hello(4)
To add on to the existing answers here and provide a code example:
class MyClass:
def __init__(self):
pass
def myStaticMethod():
print("a static method")
#staticmethod
def myStaticMethodWithArg(my_arg):
print(my_arg)
print("a static method")
MyClass.myStaticMethod()
MyClass.myStaticMethodWithArg("skhsdkj")
abc = MyClass()
abc.myStaticMethodWithArg("avc")
Try removing the #staticmethod decorator and rerunning the code and see what happens! (The very last call will fail since the method is passed in both self and the string input. By adding the decorator, we can guide the interpreter to perform our desired action)
I'm trying to use this code in python:
class A:
func = lambda: "go away"
#classmethod
def apply(cls):
cls.func()
A.apply()
And I receive this error:
unbound method <lambda>() must be called with A instance as first argument (got nothing instead)
How can I make it work?
Doing apply(A) works. However you will need to fix the issues with func as well.
So here you have a bunch of problems. I am not really sure what you are trying to achieve, but you definitely have to take another look on documentation.
First, take a look on your class.
Inside you want to specify a function, and Python uses a def func(args) method to it. If you want to use it inside a class, you should use self as a parameter.
From the documentation:
class MyClass:
"""A simple example class"""
i = 12345
def f(self):
return 'hello world'
Also, lambda, in words is an anonymous function. When you define it, you should do something like:
s = lambda x: x**2
s(2)
and x would be your function parameter, and x**2 something you want to return, so the function will return 4.
Hope it will reduce some mess and you will write your code in a better way. Good luck!
This question already has answers here:
How can I call a function within a class?
(2 answers)
Closed 6 months ago.
How can i call a private function from some other function within the same class?
class Foo:
def __bar(arg):
#do something
def baz(self, arg):
#want to call __bar
Right now, when i do this:
__bar(val)
from baz(), i get this:
NameError: global name '_Foo__createCodeBehind' is not defined
Can someone tell me what the reason of the error is?
Also, how can i call a private function from another private function?
There is no implicit this-> in Python like you have in C/C++ etc. You have to call it on self.
class Foo:
def __bar(self, arg):
#do something
def baz(self, arg):
self.__bar(arg)
These methods are not really private though. When you start a method name with two underscores Python does some name mangling to make it "private" and that's all it does, it does not enforce anything like other languages do. If you define __bar on Foo, it is still accesible from outside of the object through Foo._Foo__bar. E.g., one can do this:
f = Foo()
f._Foo__bar('a')
This explains the "odd" identifier in the error message you got as well.
You can find it here in the docs.
__bar is "private" (in the sense that its name has been mangled), but it's still a method of Foo, so you have to reference it via self and pass self to it. Just calling it with a bare __bar() won't work; you have to call it like so: self.__bar(). So...
>>> class Foo(object):
... def __bar(self, arg):
... print '__bar called with arg ' + arg
... def baz(self, arg):
... self.__bar(arg)
...
>>> f = Foo()
>>> f.baz('a')
__bar called with arg a
You can access self.__bar anywhere within your Foo definition, but once you're outside the definition, you have to use foo_object._Foo__bar(). This helps avoid namespace collisions in the context of class inheritance.
If that's not why you're using this feature, you might reconsider using it. The convention for creating "private" variables and methods in Python is to prepend an underscore to the name. This has no syntactic significance, but it conveys to users of your code that the variable or method is part of implementation details that may change.