I have something like that in my python code
class A:
__mess = "Yeap!"
def doSome(self):
self.FN()
def FN(self):
pass
def myFN(self):
print self.__mess
b = A()
b.FN = myFN
b.doSome()
But this doesn't work. Where am I wrong?
python 2.6.5
upd: I want to redefine method (FN) only for one exemplar (b).
upd2:
import new
class A:
__mess = "Yeap!"
def doSome(self):
self.FN()
def FN(self):
pass
def myFN(self):
print self.__mess
b = A()
b.FN = new.instancemethod(myFN, b, A)
b.doSome()
Doesn't work too.
Traceback (most recent call last):
File "", line 1, in
File "", line 4, in doSome
File "", line 2, in myFN
AttributeError: A instance has no
attribute '__mess'
myLoopFN is a function, not an instance method. Do
import new
b.loopFN = new.instancemethod( myLoopFN, b, A )
The problem is that Python treats instance methods very slightly differently to regular functions: they get the instance upon which they are run as the default first argument. If you define a method inside a class definition it automagically becomes an instance method, so that when you instantiate the class it gets passed the instance. However, when you define myLoopFN you do it outside the class definition, so that it is an ordinary function instead of an instance method. You fix this by explicitly declaring it as an instance method.
...
BUT
This is icky because it's not something you should do; changing instance methods at runtime will lead to problems. You'll never be sure whether your A is an original A or a modified one, and you won't be able to debug it because you can't tell whether you've changed loopFN or not. This will give you the kind of bugs that Nyarlathotep himself would be proud of.
The right way to do this is to subclass A and override the method, so that you can distinguish between the different classes.
class myA( A ):
def loopFN(self):
#put modified function here
This way, you can instantiate the modified class and be certain of its methods.
Edit
You are using a double-underscore variable name, __mess. You (almost certainly) don't want to do this. For some reason known only to our Benevolent Dictator for Life and a select few others, Python automatically mangles these __ names to _<class-name>__, to serve as a sort-of faux private variable. This is horrible, and besides there's no reason to call it __mess instead of (the much nicer) mess.
If you absolutely must call it __mess, you can refer to it as follows:
def myFN(self):
print( self._A__mess )
(mutatis mutandis when you change the name of A). This is nasty and unPythonic.
Regarding the second error (with __mess):
Change
print self.__mess
to
print self._mess
And change
class A:
__mess = "Yeap!"
to
class A:
_mess = "Yeap!"
Double underscores tell Python to use name-mangling.
An alternative is to change
def myFN(self):
print self.__mess
to
def myFN(self):
print self._A__mess
Related
I have an Object of the following class which inherates from the algorithm class.
class AP(Algorithm):
def evaluate(self, u):
return self.stuff *2 +u
The Algorithm class has a method called StoppingCritiria.
At some point in the project the object objAP = AP() gets created. Later on I can then actually access it.
And at that point in time I want to override the method StoppingCriteria by some function which calls the old StoppingCriteria.
I tried simply
def new_stopping(self):
return super().StoppingCriteria() and custom(self.u)
objAP.StoppingCriteria = newStoppingCriteria
But that did not work. What did work were two rather inconviniend solutions:
New AP class (not desirable since I possibly need to do that for lots of classes)
class AP_custom(AP):
def StoppingCriteria(self):
return super().StoppingCriteria() and custom(self)
Override the Method but not using super but rather copy pasting the code into the new function and adding my code to that. Not desirable since I want to changes in the original method to be applyed to my new function as well.
See Override a method at instance level for many possible solutions. None of them will really work with super though, since you're simply not defining the replacement function in a class. You can define it slightly differently though for it to work:
class Foo:
def bar(self):
print('bar')
f = Foo()
def _bar(self):
type(self).bar(self) # or Foo.bar(self)
print('baz')
from typing import MethodType
f.bar = MethodType(_bar, f)
f.bar() # outputs bar baz
Since you're replacing the method at the instance level, you don't really need to access the method of the super class, you just want to access the method of the class, which still exists in its original form.
Is there a way to circumvent the constructor __init__ of a class in python?
Example:
class A(object):
def __init__(self):
print "FAILURE"
def Print(self):
print "YEHAA"
Now I would like to create an instance of A. It could look like this, however this syntax is not correct.
a = A
a.Print()
EDIT:
An even more complex example:
Suppose I have an object C, which purpose it is to store one single parameter and do some computations with it. The parameter, however, is not passed as such but it is embedded in a huge parameter file. It could look something like this:
class C(object):
def __init__(self, ParameterFile):
self._Parameter = self._ExtractParamterFile(ParameterFile)
def _ExtractParamterFile(self, ParameterFile):
#does some complex magic to extract the right parameter
return the_extracted_parameter
Now I would like to dump and load an instance of that object C. However, when I load this object, I only have the single variable self._Parameter and I cannot call the constructor, because it is expecting the parameter file.
#staticmethod
def Load(file):
f = open(file, "rb")
oldObject = pickle.load(f)
f.close()
#somehow create newObject without calling __init__
newObject._Parameter = oldObject._Parameter
return newObject
In other words, it is not possible to create an instance without passing the parameter file. In my "real" case, however, it is not a parameter file but some huge junk of data I certainly not want to carry around in memory or even store it to disc.
And since I want to return an instance of C from the method Load I do somehow have to call the constructor.
OLD EDIT:
A more complex example, which explains why I am asking the question:
class B(object):
def __init__(self, name, data):
self._Name = name
#do something with data, but do NOT save data in a variable
#staticmethod
def Load(self, file, newName):
f = open(file, "rb")
s = pickle.load(f)
f.close()
newS = B(???)
newS._Name = newName
return newS
As you can see, since data is not stored in a class variable I cannot pass it to __init__. Of course I could simply store it, but what if the data is a huge object, which I do not want to carry around in memory all the time or even save it to disc?
You can circumvent __init__ by calling __new__ directly. Then you can create a object of the given type and call an alternative method for __init__. This is something that pickle would do.
However, first I'd like to stress very much that it is something that you shouldn't do and whatever you're trying to achieve, there are better ways to do it, some of which have been mentioned in the other answers. In particular, it's a bad idea to skip calling __init__.
When objects are created, more or less this happens:
a = A.__new__(A, *args, **kwargs)
a.__init__(*args, **kwargs)
You could skip the second step.
Here's why you shouldn't do this: The purpose of __init__ is to initialize the object, fill in all the fields and ensure that the __init__ methods of the parent classes are also called. With pickle it is an exception because it tries to store all the data associated with the object (including any fields/instance variables that are set for the object), and so anything that was set by __init__ the previous time would be restored by pickle, there's no need to call it again.
If you skip __init__ and use an alternative initializer, you'd have a sort of a code duplication - there would be two places where the instance variables are filled in, and it's easy to miss one of them in one of the initializers or accidentally make the two fill the fields act differently. This gives the possibility of subtle bugs that aren't that trivial to trace (you'd have to know which initializer was called), and the code will be more difficult to maintain. Not to mention that you'd be in an even bigger mess if you're using inheritance - the problems will go up the inheritance chain, because you'd have to use this alternative initializer everywhere up the chain.
Also by doing so you'd be more or less overriding Python's instance creation and making your own. Python already does that for you pretty well, no need to go reinventing it and it will confuse people using your code.
Here's what to best do instead: Use a single __init__ method that is to be called for all possible instantiations of the class that initializes all instance variables properly. For different modes of initialization use either of the two approaches:
Support different signatures for __init__ that handle your cases by using optional arguments.
Create several class methods that serve as alternative constructors. Make sure they all create instances of the class in the normal way (i.e. calling __init__), as shown by Roman Bodnarchuk, while performing additional work or whatever. It's best if they pass all the data to the class (and __init__ handles it), but if that's impossible or inconvenient, you can set some instance variables after the instance was created and __init__ is done initializing.
If __init__ has an optional step (e.g. like processing that data argument, although you'd have to be more specific), you can either make it an optional argument or make a normal method that does the processing... or both.
Use classmethod decorator for your Load method:
class B(object):
def __init__(self, name, data):
self._Name = name
#store data
#classmethod
def Load(cls, file, newName):
f = open(file, "rb")
s = pickle.load(f)
f.close()
return cls(newName, s)
So you can do:
loaded_obj = B.Load('filename.txt', 'foo')
Edit:
Anyway, if you still want to omit __init__ method, try __new__:
>>> class A(object):
... def __init__(self):
... print '__init__'
...
>>> A()
__init__
<__main__.A object at 0x800f1f710>
>>> a = A.__new__(A)
>>> a
<__main__.A object at 0x800f1fd50>
Taking your question literally I would use meta classes :
class MetaSkipInit(type):
def __call__(cls):
return cls.__new__(cls)
class B(object):
__metaclass__ = MetaSkipInit
def __init__(self):
print "FAILURE"
def Print(self):
print "YEHAA"
b = B()
b.Print()
This can be useful e.g. for copying constructors without polluting the parameter list.
But to do this properly would be more work and care than my proposed hack.
Not really. The purpose of __init__ is to instantiate an object, and by default it really doesn't do anything. If the __init__ method is not doing what you want, and it's not your own code to change, you can choose to switch it out though. For example, taking your class A, we could do the following to avoid calling that __init__ method:
def emptyinit(self):
pass
A.__init__ = emptyinit
a = A()
a.Print()
This will dynamically switch out which __init__ method from the class, replacing it with an empty call. Note that this is probably NOT a good thing to do, as it does not call the super class's __init__ method.
You could also subclass it to create your own class that does everything the same, except overriding the __init__ method to do what you want it to (perhaps nothing).
Perhaps, however, you simply wish to call the method from the class without instantiating an object. If that is the case, you should look into the #classmethod and #staticmethod decorators. They allow for just that type of behavior.
In your code you have put the #staticmethod decorator, which does not take a self argument. Perhaps what may be better for the purpose would a #classmethod, which might look more like this:
#classmethod
def Load(cls, file, newName):
# Get the data
data = getdata()
# Create an instance of B with the data
return cls.B(newName, data)
UPDATE: Rosh's Excellent answer pointed out that you CAN avoid calling __init__ by implementing __new__, which I was actually unaware of (although it makes perfect sense). Thanks Rosh!
I was reading the Python cookbook and there's a section talking about this: the example is given using __new__ to bypass __init__()
>>> class A:
def __init__(self,a):
self.a = a
>>> test = A('a')
>>> test.a
'a'
>>> test_noinit = A.__new__(A)
>>> test_noinit.a
Traceback (most recent call last):
File "", line 1, in
test_noinit.a
AttributeError: 'A' object has no attribute 'a'
>>>
However I think this only works in Python3. Below is running under 2.7
>>> class A:
def __init__(self,a):
self.a = a
>>> test = A.__new__(A)
Traceback (most recent call last):
File "", line 1, in
test = A.__new__(A)
AttributeError: class A has no attribute '__new__'
>>>
As I said in my comment you could change your __init__ method so that it allows creation without giving any values to its parameters:
def __init__(self, p0, p1, p2):
# some logic
would become:
def __init__(self, p0=None, p1=None, p2=None):
if p0 and p1 and p2:
# some logic
or:
def __init__(self, p0=None, p1=None, p2=None, init=True):
if init:
# some logic
I'm making a program in python in which specific instances of an object must be decorated with new functions built at runtime.
I've seen very simple examples of adding functions to objects through MethodType:
import types
def foo():
print("foo")
class A:
bar = "bar"
a = A()
a.foo = types.MethodType(foo, a)
But none of the examples I've seen show how a function added in this manner can reference to the new owner's attributes. As far as I know, even though this binds the foo() function to the instance a, foo() must still be a pure function, and cannot contain references to anything local.
In my case, I need functions to change attributes of the object they are added to. Here are two examples of the kind of thing I need to be able to do:
class A:
foo = "foo"
def printme():
print(foo)
def nofoo():
foo = "bar"
def printBar():
if foo != "foo"
self.printme()
I would then need a way to add a copy of a nofoo() or printBar() to an A object in such a way that they can access the object attributes named foo and the function named printme() correctly.
So, is this possible? Is there a way to do this kind of programming in vanilla Python? or at least Is there a programming pattern that achieves this kind of behavior?
P.S.: In my system, I also add attributes dynamically to objects. Your first thought then might be "How can I ever be sure that the object I'm adding the nofoo() function to actually has an attribute named foo?", but I also have a fairly robust tag system that makes sure that I never try to add a nofoo() function to an object that hasn't a foo variable. The reason I mention this is that solutions that look at the class definition aren't very useful to me.
As said in the comments, your function actually must take at least one parameter: self, the instance the method is being called on. The self parameter can be used as it would be used in a normal instance method. Here is an example:
>>> from types import MethodType
>>>
>>> class Class:
def method(self):
print('method run')
>>> cls = Class()
>>>
>>> def func(self): # must accept one argument, `self`
self.method()
>>> cls.func = MethodType(func, cls)
>>> cls.func()
method run
>>>
Without your function accepting self, an exception would be raised:
>>> def func():
self.method()
>>> cls.func = MethodType(func, cls)
>>> cls.func()
Traceback (most recent call last):
File "<pyshell#21>", line 1, in <module>
cls.func()
TypeError: func() takes 0 positional arguments but 1 was given
>>>
class A:
def __init__(self):
self.foo = "foo"
def printme(self):
print(self.foo)
def nofoo(self):
self.foo = "bar"
a.nofoo = types.MethodType(nofoo, a)
a.nofoo()
a.printme()
prints
bar
It's not entirely clear what you're trying to do, and I'm worried that whatever it is may be a bad idea. However, I can explain how to do what you're asking, even if it isn't what you want, or should want. I'll point out that it's very uncommon to want to do the second version below, and even rarer to want to do the third version, but Python does allow them both, because "even rarer than very uncommon" still isn't "never". And, in the same spirit…
The short answer is "yes". A dynamically-added method can access the owner object exactly the same way a normal method can.
First, here's a normal, non-dynamic method:
class C:
def meth(self):
return self.x
c = C()
c.x = 3
c.meth()
Obviously, with a normal method like this, when you call c.meth(), the c ends up as the value of the self parameter, so self.x is c.x, which is 3.
Now, here's how you dynamically add a method to a class:
class C:
pass
c = C()
c.x = 3
def meth(self):
print(self.x)
C.meth = meth
c.meth()
This is actually doing exactly the same thing. (Well, we've left another name for the same function object sitting around in globals, but that's the only difference) If C.meth is the same function it was in the first version, then obviously whatever magic made c.meth() work in the first version will do the exact same thing here.
(This used to be slightly more complicated in Python 2, because of unbound methods, and classic classes too… but fortunately you don't have to worry about that.)
Finally, here's how you dynamically add a method to an instance:
class C:
pass
c = C()
c.x = 3
def meth(self):
print(self.x)
c.meth = types.MethodType(meth, c)
c.meth()
Here, you actually have to know the magic that makes c.meth() work in the first two cases. So read the Descriptor HOWTO. After that, it should be obvious.
But if you just want to pretend that Guido is a wizard (Raymond definitely is a wizard) and it's magic… Well, in the first two versions, Guido's magic wand creates a special bound method object whenever you ask for c.meth, but even he isn't magical enough to do that when C.meth doesn't exist. But we can painstakingly create that same bound method object and store it as c.meth. After that, we're going to get the same thing we stored whenever we ask for c.meth, which we explicitly built as the same thing we got in the first two examples, so it'll obviously do the same thing.
But what if we did this:
class C:
pass
c = C()
c.x = 3
def meth(self):
print(self.x)
c.meth = meth
c.meth(c)
Here, you're not letting Guido do his descriptor magic to create c.meth, and you're not doing it manually, you're just sticking a regular function there. Which means if you want anything to show up as the self parameter, you have to explicitly pass it as an argument, as in that silly c.meth(c) line at the end. But if you're willing to do that, then even this one works. No matter how self ends up as c, self.x is going to be c.x.
I would like to know if there is a way to create a list that will execute some actions each time I use the method append(or an other similar method).
I know that I could create a class that inherits from list and overwrite append, remove and all other methods that change content of list but I would like to know if there is an other way.
By comparison, if I want to print 'edited' each time I edit an attribute of an object I will not execute print("edited") in all methods of the class of that object. Instead, I will only overwrite __setattribute__.
I tried to create my own type which inherits of list and overwrite __setattribute__ but that doesn't work. When I use myList.append __setattribute__ isn't called. I would like to know what's realy occured when I use myList.append ? Is there some magic methods called that I could overwrite ?
I know that the question have already been asked there : What happens when you call `append` on a list?. The answer given is just, there is no answer... I hope it's a mistake.
I don't know if there is an answer to my request so I will also explain you why I'm confronted to that problem. Maybe I can search in an other direction to do what I want. I have got a class with several attributes. When an attribute is edited, I want to execute some actions. Like I explain before, to do this I am use to overwrite __setattribute__. That works fine for most of attributes. The problem is lists. If the attribute is used like this : myClass.myListAttr.append(something), __setattribute__ isn't called while the value of the attribute have changed.
The problem would be the same with dictionaries. Methods like pop doesn't call __setattribute__.
If I understand correctly, you would want something like Notify_list that would call some method (argument to the constructor in my implementation) every time a mutating method is called, so you could do something like this:
class Test:
def __init__(self):
self.list = Notify_list(self.list_changed)
def list_changed(self,method):
print("self.list.{} was called!".format(method))
>>> x = Test()
>>> x.list.append(5)
self.list.append was called!
>>> x.list.extend([1,2,3,4])
self.list.extend was called!
>>> x.list[1] = 6
self.list.__setitem__ was called!
>>> x.list
[5, 6, 2, 3, 4]
The most simple implementation of this would be to create a subclass and override every mutating method:
class Notifying_list(list):
__slots__ = ("notify",)
def __init__(self,notifying_method, *args,**kw):
self.notify = notifying_method
list.__init__(self,*args,**kw)
def append(self,*args,**kw):
self.notify("append")
return list.append(self,*args,**kw)
#etc.
This is obviously not very practical, writing the entire definition would be very tedious and very repetitive, so we can create the new subclass dynamically for any given class with functions like the following:
import functools
import types
def notify_wrapper(name,method):
"""wraps a method to call self.notify(name) when called
used by notifying_type"""
#functools.wraps(method)
def wrapper(*args,**kw):
self = args[0]
# use object.__getattribute__ instead of self.notify in
# case __getattribute__ is one of the notifying methods
# in which case self.notify will raise a RecursionError
notify = object.__getattribute__(self, "_Notify__notify")
# I'd think knowing which method was called would be useful
# you may want to change the arguments to the notify method
notify(name)
return method(*args,**kw)
return wrapper
def notifying_type(cls, notifying_methods="all"):
"""creates a subclass of cls that adds an extra function call when calling certain methods
The constructor of the subclass will take a callable as the first argument
and arguments for the original class constructor after that.
The callable will be called every time any of the methods specified in notifying_methods
is called on the object, it is passed the name of the method as the only argument
if notifying_methods is left to the special value 'all' then this uses the function
get_all_possible_method_names to create wrappers for nearly all methods."""
if notifying_methods == "all":
notifying_methods = get_all_possible_method_names(cls)
def init_for_new_cls(self,notify_method,*args,**kw):
self._Notify__notify = notify_method
namespace = {"__init__":init_for_new_cls,
"__slots__":("_Notify__notify",)}
for name in notifying_methods:
method = getattr(cls,name) #if this raises an error then you are trying to wrap a method that doesn't exist
namespace[name] = notify_wrapper(name, method)
# I figured using the type() constructor was easier then using a meta class.
return type("Notify_"+cls.__name__, (cls,), namespace)
unbound_method_or_descriptor = ( types.FunctionType,
type(list.append), #method_descriptor, not in types
type(list.__add__),#method_wrapper, also not in types
)
def get_all_possible_method_names(cls):
"""generates the names of nearly all methods the given class defines
three methods are blacklisted: __init__, __new__, and __getattribute__ for these reasons:
__init__ conflicts with the one defined in notifying_type
__new__ will not be called with a initialized instance, so there will not be a notify method to use
__getattribute__ is fine to override, just really annoying in most cases.
Note that this function may not work correctly in all cases
it was only tested with very simple classes and the builtin list."""
blacklist = ("__init__","__new__","__getattribute__")
for name,attr in vars(cls).items():
if (name not in blacklist and
isinstance(attr, unbound_method_or_descriptor)):
yield name
Once we can use notifying_type creating Notify_list or Notify_dict would be as simple as:
import collections
mutating_list_methods = set(dir(collections.MutableSequence)) - set(dir(collections.Sequence))
Notify_list = notifying_type(list, mutating_list_methods)
mutating_dict_methods = set(dir(collections.MutableMapping)) - set(dir(collections.Mapping))
Notify_dict = notifying_type(dict, mutating_dict_methods)
I have not tested this extensively and it quite possibly contains bugs / unhandled corner cases but I do know it worked correctly with list!
Alright, so I was taking a look at some source when I came across this:
>>> def __parse(self, filename):
... "parse ID3v1.0 tags from MP3 file"
... self.clear()
... try:
... fsock = open(filename, "rb", 0)
... try:
... fsock.seek(-128, 2)
... tagdata = fsock.read(128)
... finally:
... fsock.close()
... if tagdata[:3] == 'TAG':
... for tag, (start, end, parseFunc) in self.tagDataMap.items():
... self[tag] = parseFunc(tagdata[start:end])
... except IOError:
... pass
...
So, I decided to test it out.
>>> __parse("blah.mp3")
And, I received this error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: __parse() takes exactly 2 arguments (1 given)
This wouldn't be the first time I've encountered this, I keep thinking I'm meant to include self in the argument parameter list, but I know that that's not right. Could someone explain to me why this happens a lot with code I try to play around with, I suppose its due to my level of understanding about the terms, I barely even understand what init or self does, or why it's relevant. def x(b): print b is the same as def x(self, b): self.b = b print self.b isn't it? Why does it matter so much!
I just want a basic explanation, so I can get this out of my mind,thanks.
The def __parse was inside some class definition.
You can't pull the method defs out of the class definitions. The method function definition is part of the class.
Look at these two examples:
def add( a, b ):
return a + b
And
class Adder( object ):
def __init__( self ):
self.grand_total = 0
def add( self, a, b ):
self.grand_total += a+b
return a+b
Notes.
The function does not use self.
The class method does use self. Generally, all instance methods will use self, unless they have specific decorators like #classmethod that say otherwise.
The function doesn't depend on anything else else.
The class method depends on being called by an instance of the class Adder; further, it depends on that instance of the class Adder having been initialized correctly. In this case, the initialization function (__init__) has assured that each instance of Adder always has an instance variable named grand_total and that instance variable has an initial value of 0.
You can't pull the add method function out of the Adder class and use it separately. It is not a stand-alone function. It was defined inside the class and has certain expectations because of that location inside the class.
Functions/methods can be written outside of a class and then used for a technique in Python called monkeypatching:
class C(object):
def __init__(self):
self.foo = 'bar'
def __output(self):
print self.foo
C.output = __output
c = C()
c.output()
Looks like you're a bit confused about classes and object-oriented programming. The 'self' thing is one of the gotchas in python for people coming from other programming languages. IMO the official tutorial doesn't handle it too well. This tutorial seems quite good.
If you've ever learnt java, self in python is very similar to this in java. The difference is that python requires you to list self as the first argument to every function in a class definition.
If python is your first programming language (or your first object-oriented language), you could remember this as a simple rule-of-thumb: if you're defining a function that's part of a class, you need to include self as the first argument. If you're defining a function that's not part of a class, you shouldn't include self in the arguments. You can't take a class function and make it stand-alone without doing some (or possibly a lot of) extra coding. Finally, never include self as an argument when calling a function.
There are exceptions to those rules, but they're not worth worrying about now.
self is passed in automatically by the instancemethod wrapper on classes. This function isn't wrapped; it's not a method, it's just a function. It doesn't even make sense without being attached to a class, since it needs the self parameter.
As an aside, it is possible to create static methods of a class in Python. The simplest way to do this is via decorators (e.g. #staticmethod). I suspect this kind of thing is usually not the Pythonic solution though.