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How to overwrite self after reading yaml? [duplicate]

I would like to replace an object instance by another instance inside a method like this:
class A:
def method1(self):
self = func(self)
The object is retrieved from a database.

It is unlikely that replacing the 'self' variable will accomplish whatever you're trying to do, that couldn't just be accomplished by storing the result of func(self) in a different variable. 'self' is effectively a local variable only defined for the duration of the method call, used to pass in the instance of the class which is being operated upon. Replacing self will not actually replace references to the original instance of the class held by other objects, nor will it create a lasting reference to the new instance which was assigned to it.

As far as I understand, If you are trying to replace the current object with another object of same type (assuming func won't change the object type) from an member function. I think this will achieve that:
class A:
def method1(self):
newObj = func(self)
self.__dict__.update(newObj.__dict__)

It is not a direct answer to the question, but in the posts below there's a solution for what amirouche tried to do:
Python object conversion
Can I dynamically convert an instance of one class to another?
And here's working code sample (Python 3.2.5).
class Men:
def __init__(self, name):
self.name = name
def who_are_you(self):
print("I'm a men! My name is " + self.name)
def cast_to(self, sex, name):
self.__class__ = sex
self.name = name
def method_unique_to_men(self):
print('I made The Matrix')
class Women:
def __init__(self, name):
self.name = name
def who_are_you(self):
print("I'm a women! My name is " + self.name)
def cast_to(self, sex, name):
self.__class__ = sex
self.name = name
def method_unique_to_women(self):
print('I made Cloud Atlas')
men = Men('Larry')
men.who_are_you()
#>>> I'm a men! My name is Larry
men.method_unique_to_men()
#>>> I made The Matrix
men.cast_to(Women, 'Lana')
men.who_are_you()
#>>> I'm a women! My name is Lana
men.method_unique_to_women()
#>>> I made Cloud Atlas
Note the self.__class__ and not self.__class__.__name__. I.e. this technique not only replaces class name, but actually converts an instance of a class (at least both of them have same id()). Also, 1) I don't know whether it is "safe to replace a self object by another object of the same type in [an object own] method"; 2) it works with different types of objects, not only with ones that are of the same type; 3) it works not exactly like amirouche wanted: you can't init class like Class(args), only Class() (I'm not a pro and can't answer why it's like this).

Yes, all that will happen is that you won't be able to reference the current instance of your class A (unless you set another variable to self before you change it.) I wouldn't recommend it though, it makes for less readable code.
Note that you're only changing a variable, just like any other. Doing self = 123 is the same as doing abc = 123. self is only a reference to the current instance within the method. You can't change your instance by setting self.
What func(self) should do is to change the variables of your instance:
def func(obj):
obj.var_a = 123
obj.var_b = 'abc'
Then do this:
class A:
def method1(self):
func(self) # No need to assign self here

In many cases, a good way to achieve what you want is to call __init__ again. For example:
class MyList(list):
def trim(self,n):
self.__init__(self[:-n])
x = MyList([1,2,3,4])
x.trim(2)
assert type(x) == MyList
assert x == [1,2]
Note that this comes with a few assumptions such as the all that you want to change about the object being set in __init__. Also beware that this could cause problems with inheriting classes that redefine __init__ in an incompatible manner.

Yes, there is nothing wrong with this. Haters gonna hate. (Looking at you Pycharm with your in most cases imaginable, there's no point in such reassignment and it indicates an error).
A situation where you could do this is:
some_method(self, ...):
...
if(some_condition):
self = self.some_other_method()
...
return ...
Sure, you could start the method body by reassigning self to some other variable, but if you wouldn't normally do that with other parametres, why do it with self?

One can use the self assignment in a method, to change the class of instance to a derived class.
Of course one could assign it to a new object, but then the use of the new object ripples through the rest of code in the method. Reassiging it to self, leaves the rest of the method untouched.
class aclass:
def methodA(self):
...
if condition:
self = replace_by_derived(self)
# self is now referencing to an instance of a derived class
# with probably the same values for its data attributes
# all code here remains untouched
...
self.methodB() # calls the methodB of derivedclass is condition is True
...
def methodB(self):
# methodB of class aclass
...
class derivedclass(aclass):
def methodB(self):
#methodB of class derivedclass
...
But apart from such a special use case, I don't see any advantages to replace self.

You can make the instance a singleton element of the class
and mark the methods with #classmethod.
from enum import IntEnum
from collections import namedtuple
class kind(IntEnum):
circle = 1
square = 2
def attr(y): return [getattr(y, x) for x in 'k l b u r'.split()]
class Shape(namedtuple('Shape', 'k,l,b,u,r')):
self = None
#classmethod
def __repr__(cls):
return "<Shape({},{},{},{},{}) object at {}>".format(
*(attr(cls.self)+[id(cls.self)]))
#classmethod
def transform(cls, func):
cls.self = cls.self._replace(**func(cls.self))
Shape.self = Shape(k=1, l=2, b=3, u=4, r=5)
s = Shape.self
def nextkind(self):
return {'k': self.k+1}
print(repr(s)) # <Shape(1,2,3,4,5) object at 139766656561792>
s.transform(nextkind)
print(repr(s)) # <Shape(2,2,3,4,5) object at 139766656561888>

Prevent access to an instance variable from subclass, without affecting base class

Say I have a simple class Foo, which comes from an external library, thus I cannot change it directly:
class Foo(object):
def __init__(self, x):
self.x = x
I want to create a subclass Bar and prevent x from being change from an instance of Bar, but still use the x in Bar's methods.
Here's what I tried, and it will probably enlighten the basic idea, but unfortunately it doesn't work:
class Bar(Foo):
#property
def x(self):
return super().x
#x.setter
def x(self, value):
raise NotImplementedError('Do not change x directly, use "do_stuff()" instead')
def do_stuff(self, value):
if <something>:
super().x = value
So basically I've created some wrapper functions (do_stuff()) around an attribute, and now I want to prevent the attribute from being changed directly, as it might mess up some functionality of the wrapper functions. Is this possible in a reasonable way?
Edited with a better example of what I want. I'm not trying to prevent them from seeing the variable x, but instead changing it from outside of do_stuff()

This should be much simpler to accomplish if you are willing to avoid inheritance altogether:
def main():
bar = Bar(123)
bar.fizz()
bar.buzz()
bar.fizz()
bar.set_x(456)
print('bar.x =', bar.x)
try:
bar.x = 123
except AttributeError:
print('bar.x cannot be set directly')
else:
raise AssertionError('an AttributeError should have been raised')
bar.mutate_x(789)
bar.fizz()
bar.set_x(0)
bar.fizz()
bar.mutate_x(1)
bar.fizz()
bar.set_x('Hello World')
bar.fizz()
class Foo:
def __init__(self, x):
self.x = x
def fizz(self):
print(self.x)
def buzz(self):
self.x = None
class Bar:
def __init__(self, x):
self.__foo = foo = Foo(x)
self.__copy_methods(foo)
def __copy_methods(self, obj):
for name in dir(obj):
if name.startswith('__') or name.endswith('__'):
continue
attr = getattr(obj, name)
if callable(attr):
setattr(self, name, attr)
#property
def x(self):
return self.__foo.x
def set_x(self, value):
if isinstance(value, int) and value > 0:
self.__foo.x = value
mutate_x = set_x
if __name__ == '__main__':
main()

The short answer is: No, this is not possible in a reasonable way.
Python's guiding principle here, to use the phrasing from the style guide is that we are all responsible users. Meaning that code is trusted not to do silly things, and people should generally avoid messing with members of other people's classes without a good reason.
The first and best way to prevent people from accidentally changing a value is to mark it using the single underscore (_variable). This however may not offer you the protection you want against accidental modification of your variables.
The next step up in protection is to use a double underscore. Quoting from PEP-8:
To avoid name clashes with subclasses, use two leading underscores to invoke Python's name mangling rules.
Python mangles these names with the class name: if class Foo has an attribute named __a , it cannot be accessed by Foo.__a . (An insistent user could still gain access by calling Foo._Foo__a .) Generally, double leading underscores should be used only to avoid name conflicts with attributes in classes designed to be subclassed.
The mangling makes it more difficult to accidentally overwrite a value.
I added emphasis to that last sentence because it is important. Using this mechanism for preventing accidental access to a member is not really the something that should be done for a lot of members.
In your specific case, the way that I'd solve the problem would be to not subclass at all. Consider:
class Foo(object):
def __init__(self, x):
self.x = x
class Bar():
def __init__(self, x):
self._foo = Foo(x)
#property
def x(self):
return self._foo.x
def do_stuff(self, value):
# Validate the value, and the wrapped object's state
if valid:
self._foo.x = value
Of course this means that Bar has to wrap all of Foo's methods that you want to wrap. Yes, someone could still,
b = Bar(100)
b._foo.x = 127 # shame on them :)
or
b = Bar(100)
b._foo = EvilFoo(127)
but it's harder to unintentionally do.

You're on the right track, you want to make x a property instead of having it be an attribute in the subclass. Where you went wrong was trying to store the raw data for x on super. What you want to do is exploit the fact that the parent class can use the new property of the subclass transparently and does not need to know that it is now a property and not a attribute. Something like this should work for you:
class Foo(object):
def __init__(self, x):
self.x = x
class Bar(Foo):
_protected_x = None
#property
def x(self):
return self._protected_x
#x.setter
def x(self, value):
if self._protected_x is None:
self._protected_x = value
else:
raise ValueError("Use set_x to change x.")
def set_x(self, value):
self._protected_x = value
b = Bar(12)
print b.x
b.set_x(5)
print b.x

Dynamically generate method from string?

I have a dict of different types for which I want to add a simple getter based on the name of the actual parameter.
For example, for three storage parameters, let's say:
self.storage = {'total':100,'used':88,'free':1}
I am looking now for a way (if possible?) to generate a function on the fly with some meta-programming magic.
Instead of
class spaceObj(object):
def getSize(what='total'):
return storage[what]
or hard coding
#property
def getSizeTotal():
return storage['total']
but
class spaceObj(object):
# manipulting the object's index and magic
#property
def getSize:
return ???
so that calling mySpaceObj.getSizeFree would be derived - with getSize only defined once in the object and related functions derived from it by manipulating the objects function list.
Is something like that possible?

While certainly possible to get an unknown attribute from a class as a property, this is not a pythonic approach (__getattr__ magic methods are rather rubyist)
class spaceObj(object):
storage = None
def __init__(self): # this is for testing only
self.storage = {'total':100,'used':88,'free':1}
def __getattr__(self, item):
if item[:7] == 'getSize': # check if an undefined attribute starts with this
return self.getSize(item[7:])
def getSize(self, what='total'):
return self.storage[what.lower()]
print (spaceObj().getSizeTotal) # 100

You can put the values into the object as properties:
class SpaceObj(object):
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
storage = {'total':100,'used':88,'free':1}
o = SpaceObj(**storage)
print o.total
or
o = SpaceObj(total=100, used=88, free=1)
print o.total
or using __getattr__:
class SpaceObj(object):
def __init__(self, **kwargs):
self.storage = kwargs
def __getattr__(self,name):
return self.storage[name]
o = SpaceObj(total=100, used=88, free=1)
print o.total
The latter approach takes a bit more code but it's more safe; if you have a method foo and someone create the instance with SpaceObj(foo=1), then the method will be overwritten with the first approach.

>>> import new
>>> funcstr = "def wat(): print \"wat\";return;"
>>> funcbin = compile(funcstr,'','exec')
>>> ns = {}
>>> exec funcbin in ns
>>> watfunction = new.function(ns["wat"].func_code,globals(),"wat")
>>> globals()["wat"]=watfunction
>>> wat()
wat

Python Classes: turn all inherited methods private

Class Bar inherits from Foo:
class Foo(object):
def foo_meth_1(self):
return 'foometh1'
def foo_meth_2(self):
return 'foometh2'
class Bar(Foo):
def bar_meth(self):
return 'bar_meth'
Is there a way of turning all methods inherited from Foo private?
class Bar(Foo):
def bar_meth(self):
return 'bar_meth'
def __foo_meth_1(self):
return 'foometh1'
def __foo_meth_2(self):
return 'foometh2'

Python doesn't have privates, only obfuscated method names. But I suppose you could iterate over the methods of the superclass when creating the instance, removing them from yourself and creating new obfuscatingly named method names for those functions. setattr and getattr could be useful if you use a function to create obfuscated names.
With that said, it's a pretty cthuhlu-oid thing to do. You mention the intent is to keep the namespace cleaner, but this is more like mixing ammonia and chlorine. If the method needs to be hidden, hide it in the superclass. The don't create instances of the superclass -- instead create a specific class that wraps the hidden methods in public ones, which you could name the same thing but strip the leading whitespace.
Assuming I understand your intent correctly, I would suggest doing something like this:
class BaseFoo(object):
def __init__(self):
raise NotImplementedError('No instances of BaseFoo please.')
def _foo(self):
return 'Foo.'
def _bar(self):
return 'Bar.'
class HiddenFoo(BaseFoo):
def __init__(self): pass
class PublicFoo(BaseFoo):
def __init__(self): pass
foo = BaseFoo._foo
bar = BaseFoo._bar
def try_foobar(instance):
print 'Trying ' + instance.__class__.__name__
try:
print 'foo: ' + instance.foo
print 'bar: ' + instance.bar
except AttributeError, e:
print e
foo_1 = HiddenFoo()
foo_2 = PublicFoo()
try_foobar(foo_1)
try_foobar(foo_2)
And if PublicFoo.foo would do something more than BaseFoo.foo, you would write a wrapper that does whatever is needed, and then calls foo from the superclass.

This is only possible with Pyhtons's metaclasses. But this is quite sophisticated and I am not sure if it is worth the effort. For details have a look here
Why would you like to do so?

Since foo() and __foo() are completely different methods with no link between them, Python is unable to understand what you want to do. So you have to explain to it step by step, meaning (like sapth said) to remove the old methods and add new ones.
This is an Object Oriented Design flaw and a better approach would be through delegation:
class Basic:
def meth_1(self):
return 'meth1'
def meth_2(self):
return 'meth2'
class Foo(Basic):
# Nothing to do here
pass
class Bar:
def __init__(self):
self.dg = Basic()
def bar_meth(self):
return 'bar_meth ' + self.__meth_1()
def __meth_1(self):
return self.dg.meth_1()
def __meth_2(self):
return self.dg.meth_2()
While Foo inherits the Basic class because he wants the public methods from him, Bar will only delegate the job to Basic because he doesn't want to integrate Basic's interface into its own interface.

You can use metaclasses, but Boo will no longer be an actual subclass of Foo, unless you want Foo's methods to be both 'private' and 'public' in instances of Bar (you cannot selectively inherit names or delattr members inherited from parent classes). Here is a very contrived example:
from inspect import getmembers, isfunction
class TurnPrivateMetaclass(type):
def __new__(cls, name, bases, d):
private = {'__%s' % i:j for i,j in getmembers(bases[0]) if isfunction(j)}
d.update(private)
return type.__new__(cls, name, (), d)
class Foo:
def foo_meth_1(self): return 'foometh1'
def foo_meth_2(self): return 'foometh2'
class Bar(Foo, metaclass=TurnPrivateMetaclass):
def bar_meth(self): return 'bar_meth'
b = Bar()
assert b.__foo_meth_1() == 'foometh1'
assert b.__foo_meth_2() == 'foometh2'
assert b.bar_meth() == 'bar_meth
If you wanted to get attribute access working, you could create a new Foo base class in __new__ with all renamed methods removed.

How to implement property() with dynamic name (in python)

I am programming a simulations for single neurons. Therefore I have to handle a lot of Parameters. Now the Idea is that I have two classes, one for a SingleParameter and a Collection of parameters. I use property() to access the parameter value easy and to make the code more readable. This works perfect for a sinlge parameter but I don't know how to implement it for the collection as I want to name the property in Collection after the SingleParameter. Here an example:
class SingleParameter(object):
def __init__(self, name, default_value=0, unit='not specified'):
self.name = name
self.default_value = default_value
self.unit = unit
self.set(default_value)
def get(self):
return self._v
def set(self, value):
self._v = value
v = property(fget=get, fset=set, doc='value of parameter')
par1 = SingleParameter(name='par1', default_value=10, unit='mV')
par2 = SingleParameter(name='par2', default_value=20, unit='mA')
# par1 and par2 I can access perfectly via 'p1.v = ...'
# or get its value with 'p1.v'
class Collection(object):
def __init__(self):
self.dict = {}
def __getitem__(self, name):
return self.dict[name] # get the whole object
# to get the value instead:
# return self.dict[name].v
def add(self, parameter):
self.dict[parameter.name] = parameter
# now comes the part that I don't know how to implement with property():
# It shoule be something like
# self.__dict__[parameter.name] = property(...) ?
col = Collection()
col.add(par1)
col.add(par2)
col['par1'] # gives the whole object
# Now here is what I would like to get:
# col.par1 -> should result like col['par1'].v
# col.par1 = 5 -> should result like col['par1'].v = 5
Other questions that I put to understand property():
Why do managed attributes just work for class attributes and not for instance attributes in python?
How can I assign a new class attribute via __dict__ in python?

Look at built-in functions getattr and setattr. You'll probably be a lot happier.

Using the same get/set functions for both classes forces you into an ugly hack with the argument list. Very sketchy, this is how I would do it:
In class SingleParameter, define get and set as usual:
def get(self):
return self._s
def set(self, value):
self._s = value
In class Collection, you cannot know the information until you create the property, so you define the metaset/metaget function and particularize them only later with a lambda function:
def metaget(self, par):
return par.s
def metaset(self, value, par):
par.s = value
def add(self, par):
self[par.name] = par
setattr(Collection, par.name,
property(
fget=lambda x : Collection.metaget(x, par),
fset=lambda x, y : Collection.metaset(x,y, par))

Properties are meant to dynamically evaluate attributes or to make them read-only. What you need is customizing attribute access. __getattr__ and __setattr__ do that really fine, and there's also __getattribute__ if __getattr__ is not enough.
See Python docs on customizing attribute access for details.

Have you looked at the traits package? It seems that you are reinventing the wheel here with your parameter classes. Traits also have additional features that might be useful for your type of application (incidently I know a person that happily uses traits in neural simulations).

Now I implemented a solution with set-/getattr:
class Collection(object):
...
def __setattr__(self, name, value):
if 'dict' in self.__dict__:
if name in self.dict:
self[name].v = value
else:
self.__dict__[name] = value
def __getattr__(self, name):
return self[name].v
There is one thing I quite don't like that much: The attributes are not in the __dict__. And if I have them there as well I would have a copy of the value - which can be dangerous...

Finally I succeded to implement the classes with property(). Thanks a lot for the advice. It took me quite a bit to work it out - but I can promise you that this exercise helps you to understand better pythons OOP.
I implemented it also with __getattr__ and __setattr__ but still don't know the advantages and disadvantages to the property-solution. But this seems to be worth another question. The property-solutions seems to be quit clean.
So here is the code:
class SingleParameter(object):
def __init__(self, name, default_value=0, unit='not specified'):
self.name = name
self.default_value = default_value
self.unit = unit
self.set(default_value)
def get(*args):
self = args[0]
print "get(): "
print args
return self._v
def set(*args):
print "set(): "
print args
self = args[0]
value = args[-1]
self._v = value
v = property(fget=get, fset=set, doc='value of parameter')
class Collection(dict):
# inheriting from dict saves the methods: __getitem__ and __init__
def add(self, par):
self[par.name] = par
# Now here comes the tricky part.
# (Note: this property call the get() and set() methods with one
# more argument than the property of SingleParameter)
setattr(Collection, par.name,
property(fget=par.get, fset=par.set))
# Applying the classes:
par1 = SingleParameter(name='par1', default_value=10, unit='mV')
par2 = SingleParameter(name='par2', default_value=20, unit='mA')
col = Collection()
col.add(par1)
col.add(par2)
# Setting parameter values:
par1.v = 13
col.par1 = 14
# Getting parameter values:
par1.v
col.par1
# checking identity:
par1.v is col.par1
# to access the whole object:
col['par1']
As I am new I am not sure how to move on:
how to treat follow up questions (like this itself):
get() is seems to be called twice - why?
oop-design: property vs. "__getattr__ & __setattr__" - when should I use what?
is it rude to check the own answer to the own question as accepted?
is it recommended to rename the title in order to put correlated questions or questions elaborated with the same example into the same context?
Other questions that I put to understand property():
Why do managed attributes just work for class attributes and not for instance attributes in python?
How can I assign a new class attribute via __dict__ in python?

I have a class that does something similar, but I did the following in the collection object:
setattr(self, par.name, par.v)