Every object in sympy is a subclass of the Basic class, and they all use __new__ without __init__, and mostly it's something like
def __new__(cls, some, parameter, **others):
obj = parentclass.__new__(cls, **others)
obj.some = some
obj.parameter = parameter
return obj
What's the difference to using __init__ like
def __init__(self, some, parameter, **others):
parentclass.__init__(self, **others) # or super().__init__(...)
self.some = some
self.parameter = parameter
?
Have a look at Number . They want the class of the object to be flexible. Number(...) => Int/Float/... which can not be achieved by __init__.
Furthermore the __init__ would get the arguments of __new__ but you do not need the original arguments, see matexpr.py or you need them to be adapted to what __new__ already did (for example for __reduce__).
Most object define their own __slots__ so there are fixed attributes that can be assigned to them. Assignment can be done in __new__ and __init__. I do not see the need to open a new __init__ for just setting them and doing no other operations - As Martijn Pieters and user4815162342 [source] pointed out the objects are immutable.
Sometimes __init__ is called not, once or twice if you change the class:
class X(object):
def __new__(self): # sorry but self is the class I apologize!
obj = object.__new__(Y)
return obj
def __init__(self):
print 1
>>> class Y(object):
def __init__(self):
print 2
>>> X() # no __init__ call, limiting you to stay in the class hierarchy
<__main__.Y object at 0x7f287e769350>
>>> class Y(X):
def __init__(self):
print 2
>>> X() # one __init__ call
2
<__main__.Y object at 0x7f287e7693d0>
>>> class X(object):
def __new__(self):
obj = Y()
return obj
def __init__(self):
print 1
>>> class Y(X):
def __new__(self):
return object.__new__(self)
def __init__(self):
print 2
>>> X() # __init__ called twice, structure copied from number.py
2
2
<__main__.Y object at 0x7f287e7692d0>
Correct me if I am wrong. I do not think this answer is complete but these are complications I found worth motivating to not use __init__ additionally to that the objects should be immutable as mentioned by Martijn Pieters and user4815162342 [source]
Waiting for 2 downvotes to delete the answer.
Related
I have two methods, one for the individual Instance, and one for every Instance in that class:
class MasterMatches(models.Model):
#classmethod
def update_url_if_any_matches_has_one(cls):
# apply to all instances, call instance method.
def update_url_if_any_matches_has_one(self):
# do something
Should I name these the same? Or, what is a good naming convention here?
The question of using the same names can be clarified by understanding how decorators work.
#dec
def foo(x):
print(x)
translates to
def foo(x):
print(x)
foo = dec(foo)
In your example the decorator syntax can be expanded to
class MasterMatches(models.Model):
def update_url_if_any_matches_has_one(cls):
# apply to all instances, call instance method.
update_url_if_any_matches_has_one = classmethod(update_url_if_any_matches_has_one)
def update_url_if_any_matches_has_one(self):
# do something
The former implementation of update_url_if_any_matches_has_one will be overwritten by the latter.
Usually use self declaration style. #classmethod use only if method not works with class instance fields.
Function decorated as #classmethod takes the first argument is the class type, while normal method takes instance of object.
class A:
#classmethod
def a(cls):
print(cls)
def b(self):
print(self)
a = A()
a.a()
a.b()
# Output:
# <class '__main__.A'>
# <__main__.A object at 0x03FC5DF0>
It can be useful if you have a static class fields. The to access therm you don't need explicitly specify the class name. But you don't get access to instance fields. Example:
class A:
field = 1
#classmethod
def a(cls):
print(cls.field)
def b(self):
self.field = 2
print(self.field, A.field)
a = A()
a.a()
a.b()
# Outputs:
# 1
# 2 1
Whenever I define a class whose instances create objects of other classes, I like defining the types of those other objects as class members:
class Foo(object):
DICT_TYPE = dict # just a trivial example
def __init__(self):
self.mydict = self.DICT_TYPE()
class Bar(Foo):
DICT_TYPE = OrderedDict # no need to override __init__ now
The idea is to allow potential subclasses to easily override it.
I've just found a problem with this habbit, when the "type" I use is not really a type, but a factory function. For example, RLock is confusingly not a class:
def RLock(*args, **kwargs):
return _RLock(*args, **kwargs)
Thus using it the same way is no good:
class Foo(object):
LOCK_TYPE = threading.RLock # alas, RLock() is a function...
def __init__(self):
self.lock = self.LOCK_TYPE()
The problem here is that since RLock is a function, self.LOCK_TYPE gets bound to self, resulting with a bound-method, consequently leading to an error.
Here's a quick demonstration of how things go wrong when a function is used instead of a class (for a case simpler than RLock above):
def dict_factory():
return {}
class Foo(object):
DICT_TYPE1 = dict
DICT_TYPE2 = dict_factory
f = Foo()
f.DICT_TYPE1()
=> {}
f.DICT_TYPE2()
=> TypeError: dict_factory() takes no arguments (1 given)
Does anybody have a good solution for this problem? Is my habbit of defining those class members fundamentally wrong?
I guess I could replace it with a factory method. Would that be a better approach?
class Foo(object);
def __init__(self):
self.lock = self._make_lock()
def _make_lock(self):
return threading.RLock()
you could use the staticmethod decorator to ensure your class does not get passed in
>>> class Foo(object):
... DICT_TYPE = staticmethod(my_dict)
...
>>> f = Foo()
>>> f.DICT_TYPE()
{}
The problem can be bypassed by using a classproperty (e.g. as defined in this answer):
class Foo(object):
#classproperty
def DICT_TYPE(cls):
return dict_factory
When should the following code be used in Python
(Assume that Baseclass inherits from Parent class and Parent class has some variables initiated in __init__() method)
class Baseclass(Parent):
def __init__(self, some_arg):
self.some_arg = some_arg
super(Baseclass, self).__init__()
Does this code makes all the local variables defined in __init__ method of Parent class accessible in Baseclass? What significance does it make?
super keeps your code from being repetitive; a complex __init__ needn't be c/p'ed into your inheriting classes. It also makes MRO work as it should, such that if you use multiple inheritance it will work correctly.
One reason to do this would be to ensure that all of your inheriting objects have certain attributes which they don't have from the parent. If you simply write a new __init__, they won't have them unless you repeat your code. For example:
>>> class A(object):
... def __init__(self, x):
... self.x = x
...
>>> class B(A):
... def __init__(self, y):
... self.y = y
...
>>> Stick = B(15)
>>> Stick.x
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'B' object has no attribute 'x'
>>>
Without calling super during the __init__ the entire method is simply overridden. A call to super here ensures that both variables exist in the inherited class.
>>> class C(A):
... def __init__(self, x, y):
... super(C, self).__init__(x)
... self.y = y
...
>>> Dave = C(15, 22)
>>> Dave.x
15
>>> Dave.y
22
>>>
Note that in the super call, x is passed to the __init__() call, but self is taken care of in the super(C, self) part of the code.
EDIT: TyrantWave also rightly points out that super is also quite useful outside of __init__. Take an object with a simple foo method for example.
class Parent(object):
def foo(self):
return "I say foo!"
The inherited class may want to just alter the output of this function instead of totally rewriting it. So instead of repeating ourselves and writing the same code over again, we just call super to get the parent's return value, then work with the data and return the child class's modified results.
class Child(Parent):
def foo(self):
parent_result = super(Child, self).foo()
return "I'm a child!! %s" % parent_result
In the above, the call to super returns the Parents value for foo() and then the Child goes on to work with the data further before returning it themselves.
>>> Alan = Parent()
>>> Stan = Child()
>>> Alan.foo()
'I say foo!'
>>> Stan.foo()
"I'm a child!! I say foo!"
>>>
Toward the end of a program I'm looking to load a specific variable from all the instances of a class into a dictionary.
For example:
class Foo():
def __init__(self):
self.x = {}
foo1 = Foo()
foo2 = Foo()
...
Let's say the number of instances will vary and I want the x dict from each instance of Foo() loaded into a new dict. How would I do that?
The examples I've seen in SO assume one already has the list of instances.
One way to keep track of instances is with a class variable:
class A(object):
instances = []
def __init__(self, foo):
self.foo = foo
A.instances.append(self)
At the end of the program, you can create your dict like this:
foo_vars = {id(instance): instance.foo for instance in A.instances}
There is only one list:
>>> a = A(1)
>>> b = A(2)
>>> A.instances
[<__main__.A object at 0x1004d44d0>, <__main__.A object at 0x1004d4510>]
>>> id(A.instances)
4299683456
>>> id(a.instances)
4299683456
>>> id(b.instances)
4299683456
#JoelCornett's answer covers the basics perfectly. This is a slightly more complicated version, which might help with a few subtle issues.
If you want to be able to access all the "live" instances of a given class, subclass the following (or include equivalent code in your own base class):
from weakref import WeakSet
class base(object):
def __new__(cls, *args, **kwargs):
instance = object.__new__(cls, *args, **kwargs)
if "instances" not in cls.__dict__:
cls.instances = WeakSet()
cls.instances.add(instance)
return instance
This addresses two possible issues with the simpler implementation that #JoelCornett presented:
Each subclass of base will keep track of its own instances separately. You won't get subclass instances in a parent class's instance list, and one subclass will never stumble over instances of a sibling subclass. This might be undesirable, depending on your use case, but it's probably easier to merge the sets back together than it is to split them apart.
The instances set uses weak references to the class's instances, so if you del or reassign all the other references to an instance elsewhere in your code, the bookkeeping code will not prevent it from being garbage collected. Again, this might not be desirable for some use cases, but it is easy enough to use regular sets (or lists) instead of a weakset if you really want every instance to last forever.
Some handy-dandy test output (with the instances sets always being passed to list only because they don't print out nicely):
>>> b = base()
>>> list(base.instances)
[<__main__.base object at 0x00000000026067F0>]
>>> class foo(base):
... pass
...
>>> f = foo()
>>> list(foo.instances)
[<__main__.foo object at 0x0000000002606898>]
>>> list(base.instances)
[<__main__.base object at 0x00000000026067F0>]
>>> del f
>>> list(foo.instances)
[]
You would probably want to use weak references to your instances. Otherwise the class could likely end up keeping track of instances that were meant to have been deleted. A weakref.WeakSet will automatically remove any dead instances from its set.
One way to keep track of instances is with a class variable:
import weakref
class A(object):
instances = weakref.WeakSet()
def __init__(self, foo):
self.foo = foo
A.instances.add(self)
#classmethod
def get_instances(cls):
return list(A.instances) #Returns list of all current instances
At the end of the program, you can create your dict like this:
foo_vars = {id(instance): instance.foo for instance in A.instances}
There is only one list:
>>> a = A(1)
>>> b = A(2)
>>> A.get_instances()
[<inst.A object at 0x100587290>, <inst.A object at 0x100587250>]
>>> id(A.instances)
4299861712
>>> id(a.instances)
4299861712
>>> id(b.instances)
4299861712
>>> a = A(3) #original a will be dereferenced and replaced with new instance
>>> A.get_instances()
[<inst.A object at 0x100587290>, <inst.A object at 0x1005872d0>]
You can also solve this problem using a metaclass:
When a class is created (__init__ method of metaclass), add a new instance registry
When a new instance of this class is created (__call__ method of metaclass), add it to the instance registry.
The advantage of this approach is that each class has a registry - even if no instance exists. In contrast, when overriding __new__ (as in Blckknght's answer), the registry is added when the first instance is created.
class MetaInstanceRegistry(type):
"""Metaclass providing an instance registry"""
def __init__(cls, name, bases, attrs):
# Create class
super(MetaInstanceRegistry, cls).__init__(name, bases, attrs)
# Initialize fresh instance storage
cls._instances = weakref.WeakSet()
def __call__(cls, *args, **kwargs):
# Create instance (calls __init__ and __new__ methods)
inst = super(MetaInstanceRegistry, cls).__call__(*args, **kwargs)
# Store weak reference to instance. WeakSet will automatically remove
# references to objects that have been garbage collected
cls._instances.add(inst)
return inst
def _get_instances(cls, recursive=False):
"""Get all instances of this class in the registry. If recursive=True
search subclasses recursively"""
instances = list(cls._instances)
if recursive:
for Child in cls.__subclasses__():
instances += Child._get_instances(recursive=recursive)
# Remove duplicates from multiple inheritance.
return list(set(instances))
Usage: Create a registry and subclass it.
class Registry(object):
__metaclass__ = MetaInstanceRegistry
class Base(Registry):
def __init__(self, x):
self.x = x
class A(Base):
pass
class B(Base):
pass
class C(B):
pass
a = A(x=1)
a2 = A(2)
b = B(x=3)
c = C(4)
for cls in [Base, A, B, C]:
print cls.__name__
print cls._get_instances()
print cls._get_instances(recursive=True)
print
del c
print C._get_instances()
If using abstract base classes from the abc module, just subclass abc.ABCMeta to avoid metaclass conflicts:
from abc import ABCMeta, abstractmethod
class ABCMetaInstanceRegistry(MetaInstanceRegistry, ABCMeta):
pass
class ABCRegistry(object):
__metaclass__ = ABCMetaInstanceRegistry
class ABCBase(ABCRegistry):
__metaclass__ = ABCMeta
#abstractmethod
def f(self):
pass
class E(ABCBase):
def __init__(self, x):
self.x = x
def f(self):
return self.x
e = E(x=5)
print E._get_instances()
Another option for quick low-level hacks and debugging is to filter the list of objects returned by gc.get_objects() and generate the dictionary on the fly that way. In CPython that function will return you a (generally huge) list of everything the garbage collector knows about, so it will definitely contain all of the instances of any particular user-defined class.
Note that this is digging a bit into the internals of the interpreter, so it may or may not work (or work well) with the likes of Jython, PyPy, IronPython, etc. I haven't checked. It's also likely to be really slow regardless. Use with caution/YMMV/etc.
However, I imagine that some people running into this question might eventually want to do this sort of thing as a one-off to figure out what's going on with the runtime state of some slice of code that's behaving strangely. This method has the benefit of not affecting the instances or their construction at all, which might be useful if the code in question is coming out of a third-party library or something.
Here's a similar approach to Blckknght's, which works with subclasses as well. Thought this might be of interest, if someone ends up here. One difference, if B is a subclass of A, and b is an instance of B, b will appear in both A.instances and B.instances. As stated by Blckknght, this depends on the use case.
from weakref import WeakSet
class RegisterInstancesMixin:
instances = WeakSet()
def __new__(cls, *args, **kargs):
o = object.__new__(cls, *args, **kargs)
cls._register_instance(o)
return o
#classmethod
def print_instances(cls):
for instance in cls.instances:
print(instance)
#classmethod
def _register_instance(cls, instance):
cls.instances.add(instance)
for b in cls.__bases__:
if issubclass(b, RegisterInstancesMixin):
b._register_instance(instance)
def __init_subclass__(cls):
cls.instances = WeakSet()
class Animal(RegisterInstancesMixin):
pass
class Mammal(Animal):
pass
class Human(Mammal):
pass
class Dog(Mammal):
pass
alice = Human()
bob = Human()
cannelle = Dog()
Animal.print_instances()
Mammal.print_instances()
Human.print_instances()
Animal.print_instances() will print three objects, whereas Human.print_instances() will print two.
Using the answer from #Joel Cornett I've come up with the following, which seems to work. i.e. i'm able to total up object variables.
import os
os.system("clear")
class Foo():
instances = []
def __init__(self):
Foo.instances.append(self)
self.x = 5
class Bar():
def __init__(self):
pass
def testy(self):
self.foo1 = Foo()
self.foo2 = Foo()
self.foo3 = Foo()
foo = Foo()
print Foo.instances
bar = Bar()
bar.testy()
print Foo.instances
x_tot = 0
for inst in Foo.instances:
x_tot += inst.x
print x_tot
output:
[<__main__.Foo instance at 0x108e334d0>]
[<__main__.Foo instance at 0x108e334d0>, <__main__.Foo instance at 0x108e33560>, <__main__.Foo instance at 0x108e335a8>, <__main__.Foo instance at 0x108e335f0>]
5
10
15
20
(For Python)
I have found a way to record the class instances via the "dataclass" decorator while defining a class. Define a class attribute 'instances' (or any other name) as a list of the instances you want to record. Append that list with the 'dict' form of created objects via the dunder method __dict__. Thus, the class attribute 'instances' will record instances in the dict form, which you want.
For example,
from dataclasses import dataclass
#dataclass
class player:
instances=[]
def __init__(self,name,rank):
self.name=name
self.rank=rank
self.instances.append(self.__dict__)
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>