In Python, how do I get a reference to the current class object within a class statement? Example:
def setup_class_members(cls, prefix):
setattr(cls, prefix+"_var1", "hello")
setattr(cls, prefix+"_var2", "goodbye")
class myclass(object):
setup_class_members(cls, "coffee") # How to get "cls"?
def mytest(self):
print(self.coffee_var1)
print(self.coffee_var2)
x = myclass()
x.mytest()
>>> hello
>>> goodbye
Alternatives that I've written off are:
Use locals(): This gives a dict in a class statement that can be written to. This seems to work for classes, however the documentation tells you not to do this. (I might be tempted to go with this alternative if someone can assure me that this will continue to work for some time.)
Add members to the class object after the class statement: My actual application is to derive a PyQt4 QWidget class with dynamically created pyqtProperty class attributes. QWidget is unusual in that it has a custom metaclass. Very roughly, the metaclass compiles a list of pyqtProperties and stores it as additional member. For this reason, properties that are added to the class after creation have no effect. An example to clear this up:
from PyQt4 import QtCore, QtGui
# works
class MyWidget1(QtGui.QWidget):
myproperty = QtCore.pyqtProperty(int)
# doesn't work because QWidget's metaclass doesn't get to "compile" myproperty
class MyWidget2(QtGui.QWidget):
pass
MyWidget2.myproperty = QtCore.pyqtProperty(int)
Please note that the above will work for most programming cases; my case just happens to be one of those unusual corner cases.
For Python 3, the class must be declared as
class myclass(object, metaclass = Meta):
prefix = "coffee"
...
A few other points:
The metaclass may be a callable, not just a class (Python 2&3)
If the base class of your class already has a non-standard metaclass, you have to make sure you call it's __init__() and __new__() methods instead of type's.
The class statement accepts keyword parameters that are passed on to the metaclass (Python 3 only)
A rewrite of mouad's solution in Python 3 using all of the above is...
def MetaFun(name, bases, attr, prefix=None):
if prefix:
attr[prefix+"_var1"] = "hello"
attr[prefix+"_var2"] = "goodbye"
return object.__class__(name, bases, attr)
class myclass(object, metaclass = MetaFun, prefix="coffee"):
def mytest(self):
print(self.coffee_var1)
print(self.coffee_var2)
AFAIK there is two way to do what you want:
Using metaclass, this will create your two variables in class creation time (which i think is what you want):
class Meta(type):
def __new__(mcs, name, bases, attr):
prefix = attr.get("prefix")
if prefix:
attr[prefix+"_var1"] = "hello"
attr[prefix+"_var2"] = "goodbye"
return type.__new__(mcs, name, bases, attr)
class myclass(object):
__metaclass__ = Meta
prefix = "coffee"
def mytest(self):
print(self.coffee_var1)
print(self.coffee_var2)
Create your two class variable in instantiation time:
class myclass(object):
prefix = "coffee"
def __init__(self):
setattr(self.__class__, self.prefix+"_var1", "hello")
setattr(self.__class__, self.prefix+"_var2", "goodbye")
def mytest(self):
print(self.coffee_var1)
print(self.coffee_var2)
N.B: I'm not sure what you want to achieve because if you want to create dynamic variables depending on the prefix variable why are you accessing like you do in your mytest method ?! i hope it was just an example.
Two more approaches you might use:
A class decorator.
def setup_class_members(prefix):
def decorator(cls):
setattr(cls, prefix+"_var1", "hello")
setattr(cls, prefix+"_var2", "goodbye")
return cls
return decorator
#setup_class_members("coffee")
class myclass(object):
# ... etc
Especially if you need to add attributes in various combinations, the decorator approach is nice because it does not have any effect on inheritance.
If you are dealing with a small set of of attributes that you wish to combine in various ways, you can use mixin classes. A mixin class is a regular class, it's just intended to "mix in" various attributes to some other class.
class coffee_mixin(object):
coffee_var1 = "hello"
coffee_var2 = "goodbye"
class tea_mixin(object):
tea_var1 = "good morning old bean"
tea_var2 = "pip pip cheerio"
class myclass(coffee_mixin, tea_mixin):
# ... etc
See zope.interface.declarations._implements for an example of doing this kind of magic. Just be warned that it's a serious maintainability and portability risk.
Related
I've got some code where I need to refer to a superclass when defining stuff in a derived class:
class Base:
def foo(self):
print('foo')
def bar(self):
print('bar')
class Derived_A(Base):
meth = Base.foo
class Derived_B(Base):
meth = Base.bar
Derived_A().meth()
Derived_B().meth()
This works, but I don't like verbatim references to Base in derived classes. Is there a way to use super or alike for this?
You can't do that.
class keyword in Python is used to create classes which are instances of type type. In it's simplified version, it does the following:
Python creates a namespace and executes the body of the class in that namespace so that it will be populated with all methods and attributes and so on...
Then calls the three-arguments form of type(). The result of this call is your class which is then assign to a symbol which is the name of your class.
The point is when the body of the class is being executed. It doesn't know about the "bases". Those bases are passed to the type() after that.
I also explained the reasons why you can't use super() here.
Does this work for you?
class Base:
def foo(self):
print('foo')
def bar(self):
print('bar')
class Derived_A(Base):
def __init__(self):
self.meth = super().foo
class Derived_B(Base):
def __init__(self):
self.meth = super().bar
a = Derived_A().meth()
b = Derived_B().meth()
You'll need to lookup the method on the base class after the new type is created. In the body of the class definition, the type and base classes are not accessible.
Something like:
class Derived_A(Base):
def meth(self):
return super().foo()
Now, it is possible to do some magic behind the scenes to expose Base to the scope of the class definition as its being executed, but that's much dirtier, and would mean that you'd need to supply a metaclass in your class definition.
Since you want "magic", there is still one sane option we can take before diving into metaclasses. Requires Python 3.9+
def alias(name):
def inner(cls):
return getattr(cls, name).__get__(cls)
return classmethod(property(inner))
class Base:
def foo(self):
...
class Derived_A(Base):
meth = alias("foo")
Derived_A().meth() # works
Derived_A.meth() # also works
Yes, this does require passing the method name as a string, which destroys your IDE and typechecker's ability to reason about it. But there isn't a good way to get what you are wanting without some compromises like that.
Really, a bit of redundancy for readability is probably worth it here.
I have a class Step, which I want to derive by many sub-classes. I want every class deriving from Step to be "registered" by a name I choose for it (not the class's name), so I can later call Step.getStepTypeByName().
Something like this, only working :):
class Step(object):
_STEPS_BY_NAME = {}
#staticmethod
def REGISTER(cls, name):
_STEPS_BY_NAME[name] = cls
class Derive1(Step):
REGISTER(Derive1, "CustomDerive1Name")
...
class Derive2(Step):
REGISTER(Derive2, "CustomDerive2Name")
...
Your solution do not work for three reasons.
The first one is that _STEPS_BY_NAME only exists as an attribute of the Step class, so Step.REGISTER cannot access _STEPS_BY_NAME without a reference to the Step class. IOW you have to make it a classmethod (cf below)
The second one is that you need to explicitely use Step.REGISTER(cls) - the name REGISTER does not exist outside the Step class.
The third reason is that within a class statement's body, the class object has not yet been created not bound to it's name, so you cannot not reference the class itself at this point.
IOW, you'd want this instead:
class Step(object):
_STEPS_BY_NAME = {}
# NB : by convention, "ALL_UPPER" names denote pseudo-constants
#classmethod
def register(cls, name):
# here `cls` is the current class
cls._STEPS_BY_NAME[name] = stepclass
class Derive1(Step):
...
Step.register(Derive1, "CustomDerive1Name")
class Derive2(Step):
...
Step.register(Derive2, "CustomDerive2Name")
Now with a minor modification to Step.register you could use it as a class decorator, making things much clearer:
class Step(object):
_STEPS_BY_NAME = {}
#classmethod
def register(cls, name):
def _register(stepclass):
cls._STEPS_BY_NAME[name] = stepclass
return stepclass
return _register
#Step.register("CustomDerive1Name")
class Derive1(Step):
...
#Step.register("CustomDerive2Name")
class Derive2(Step):
...
As a last note: unless you have a compelling reason to register your subclasses in the base class itself, it might be better to use module-level variables and functions (a Python module is actually a kind of singleton):
# steps.py
class Step(object):
#....
_STEPS_BY_NAME = {}
def register(name):
def _register(cls):
_STEPS_BY_NAME[name] = cls
return cls
return _register
def get_step_class(name):
return _STEPS_BY_NAME[name]
And in your other modules
import steps
#steps.register("CustomDerive1Name")
class Derive1(steps.Step):
# ...
The point here is to avoid giving too many responsabilies to your Step class. I don't know your concrete use case so I can't tell which design best fits your need, but I've been using this last one on quite a few projects and it always worked fine so far.
You are close. Use this
class Step(object):
pass
class Derive1(Step):
pass
class Derive2(Step):
pass
_STEPS_BY_NAME = {
'foo': Step,
'bar': Derive1,
'bar': Derive2
}
def get_step_by_name(name):
return _STEPS_BY_NAME[name]
Warning: there might be better approaches depending on what you are trying to achieve. Such a mapping from strings to methods is a maintenance nightmare. If you want to change the name of a method, you would have to remember to change it in multiple place. You won't get any autocomplete help from your IDE either.
For a recursive function we can do:
def f(i):
if i<0: return
print i
f(i-1)
f(10)
However is there a way to do the following thing?
class A:
# do something
some_func(A)
# ...
If I understand your question correctly, you should be able to reference class A within class A by putting the type annotation in quotes. This is called forward reference.
class A:
# do something
def some_func(self, a: 'A')
# ...
See ref below
https://github.com/python/mypy/issues/3661
https://www.youtube.com/watch?v=AJsrxBkV3kc
In Python you cannot reference the class in the class body, although in languages like Ruby you can do it.
In Python instead you can use a class decorator but that will be called once the class has initialized. Another way could be to use metaclass but it depends on what you are trying to achieve.
You can't with the specific syntax you're describing due to the time at which they are evaluated. The reason the example function given works is that the call to f(i-1) within the function body is because the name resolution of f is not performed until the function is actually called. At this point f exists within the scope of execution since the function has already been evaluated. In the case of the class example, the reference to the class name is looked up during while the class definition is still being evaluated. As such, it does not yet exist in the local scope.
Alternatively, the desired behavior can be accomplished using a metaclass like such:
class MetaA(type):
def __init__(cls):
some_func(cls)
class A(object):
__metaclass__=MetaA
# do something
# ...
Using this approach you can perform arbitrary operations on the class object at the time that the class is evaluated.
Maybe you could try calling __class__.
Right now I'm writing a code that calls a class method from within the same class.
It is working well so far.
I'm creating the class methods using something like:
#classmethod
def my_class_method(cls):
return None
And calling then by using:
x = __class__.my_class_method()
It seems most of the answers here are outdated. From python3.7:
from __future__ import annotations
Example:
$ cat rec.py
from __future__ import annotations
class MyList:
def __init__(self,e):
self.data = [e]
def add(self, e):
self.data.append(e)
return self
def score(self, other:MyList):
return len([e
for e in self.data
if e in other.data])
print(MyList(8).add(3).add(4).score(MyList(4).add(9).add(3)))
$ python3.7 rec.py
2
Nope. It works in a function because the function contents are executed at call-time. But the class contents are executed at define-time, at which point the class doesn't exist yet.
It's not normally a problem because you can hack further members into the class after defining it, so you can split up a class definition into multiple parts:
class A(object):
spam= 1
some_func(A)
A.eggs= 2
def _A_scramble(self):
self.spam=self.eggs= 0
A.scramble= _A_scramble
It is, however, pretty unusual to want to call a function on the class in the middle of its own definition. It's not clear what you're trying to do, but chances are you'd be better off with decorators (or the relatively new class decorators).
There isn't a way to do that within the class scope, not unless A was defined to be something else first (and then some_func(A) will do something entirely different from what you expect)
Unless you're doing some sort of stack inspection to add bits to the class, it seems odd why you'd want to do that. Why not just:
class A:
# do something
pass
some_func(A)
That is, run some_func on A after it's been made. Alternately, you could use a class decorator (syntax for it was added in 2.6) or metaclass if you wanted to modify class A somehow. Could you clarify your use case?
If you want to do just a little hacky thing do
class A(object):
...
some_func(A)
If you want to do something more sophisticated you can use a metaclass. A metaclass is responsible for manipulating the class object before it gets fully created. A template would be:
class AType(type):
def __new__(meta, name, bases, dct):
cls = super(AType, meta).__new__(meta, name, bases, dct)
some_func(cls)
return cls
class A(object):
__metaclass__ = AType
...
type is the default metaclass. Instances of metaclasses are classes so __new__ returns a modified instance of (in this case) A.
For more on metaclasses, see http://docs.python.org/reference/datamodel.html#customizing-class-creation.
If the goal is to call a function some_func with the class as an argument, one answer is to declare some_func as a class decorator. Note that the class decorator is called after the class is initialized. It will be passed the class that is being decorated as an argument.
def some_func(cls):
# Do something
print(f"The answer is {cls.x}")
return cls # Don't forget to return the class
#some_func
class A:
x = 1
If you want to pass additional arguments to some_func you have to return a function from the decorator:
def some_other_func(prefix, suffix):
def inner(cls):
print(f"{prefix} {cls.__name__} {suffix}")
return cls
return inner
#some_other_func("Hello", " and goodbye!")
class B:
x = 2
Class decorators can be composed, which results in them being called in the reverse order they are declared:
#some_func
#some_other_func("Hello", "and goodbye!")
class C:
x = 42
The result of which is:
# Hello C and goodbye!
# The answer is 42
What do you want to achieve? It's possible to access a class to tweak its definition using a metaclass, but it's not recommended.
Your code sample can be written simply as:
class A(object):
pass
some_func(A)
If you want to refer to the same object, just use 'self':
class A:
def some_func(self):
another_func(self)
If you want to create a new object of the same class, just do it:
class A:
def some_func(self):
foo = A()
If you want to have access to the metaclass class object (most likely not what you want), again, just do it:
class A:
def some_func(self):
another_func(A) # note that it reads A, not A()
Do remember that in Python, type hinting is just for auto-code completion therefore it helps IDE to infer types and warn user before runtime. In runtime, type hints almost never used(except in some cases) so you can do something like this:
from typing import Any, Optional, NewType
LinkListType = NewType("LinkList", object)
class LinkList:
value: Any
_next: LinkListType
def set_next(self, ll: LinkListType):
self._next = ll
if __name__ == '__main__':
r = LinkList()
r.value = 1
r.set_next(ll=LinkList())
print(r.value)
And as you can see IDE successfully infers it's type as LinkList:
Note: Since the next can be None, hinting this in the type would be better, I just didn't want to confuse OP.
class LinkList:
value: Any
next: Optional[LinkListType]
It's ok to reference the name of the class inside its body (like inside method definitions) if it's actually in scope... Which it will be if it's defined at top level. (In other cases probably not, due to Python scoping quirks!).
For on illustration of the scoping gotcha, try to instantiate Foo:
class Foo(object):
class Bar(object):
def __init__(self):
self.baz = Bar.baz
baz = 15
def __init__(self):
self.bar = Foo.Bar()
(It's going to complain about the global name 'Bar' not being defined.)
Also, something tells me you may want to look into class methods: docs on the classmethod function (to be used as a decorator), a relevant SO question. Edit: Ok, so this suggestion may not be appropriate at all... It's just that the first thing I thought about when reading your question was stuff like alternative constructors etc. If something simpler suits your needs, steer clear of #classmethod weirdness. :-)
Most code in the class will be inside method definitions, in which case you can simply use the name A.
Goal: Make a decorator which can modify the scope that it is used in.
If it worked:
class Blah(): # or perhaps class Blah(ParentClassWhichMakesThisPossible)
def one(self):
pass
#decorated
def two(self):
pass
>>> Blah.decorated
["two"]
Why? I essentially want to write classes which can maintain specific dictionaries of methods, so that I can retrieve lists of available methods of different types on a per class basis. errr.....
I want to do this:
class RuleClass(ParentClass):
#rule
def blah(self):
pass
#rule
def kapow(self):
pass
def shazam(self):
class OtherRuleClass(ParentClass):
#rule
def foo(self):
pass
def bar(self):
pass
>>> RuleClass.rules.keys()
["blah", "kapow"]
>>> OtherRuleClass.rules.keys()
["foo"]
You can do what you want with a class decorator (in Python 2.6) or a metaclass. The class decorator version:
def rule(f):
f.rule = True
return f
def getRules(cls):
cls.rules = {}
for attr, value in cls.__dict__.iteritems():
if getattr(value, 'rule', False):
cls.rules[attr] = value
return cls
#getRules
class RuleClass:
#rule
def foo(self):
pass
The metaclass version would be:
def rule(f):
f.rule = True
return f
class RuleType(type):
def __init__(self, name, bases, attrs):
self.rules = {}
for attr, value in attrs.iteritems():
if getattr(value, 'rule', False):
self.rules[attr] = value
super(RuleType, self).__init__(name, bases, attrs)
class RuleBase(object):
__metaclass__ = RuleType
class RuleClass(RuleBase):
#rule
def foo(self):
pass
Notice that neither of these do what you ask for (modify the calling namespace) because it's fragile, hard and often impossible. Instead they both post-process the class -- through the class decorator or the metaclass's __init__ method -- by inspecting all the attributes and filling the rules attribute. The difference between the two is that the metaclass solution works in Python 2.5 and earlier (down to 2.2), and that the metaclass is inherited. With the decorator, subclasses have to each apply the decorator individually (if they want to set the rules attribute.)
Both solutions do not take inheritance into account -- they don't look at the parent class when looking for methods marked as rules, nor do they look at the parent class rules attribute. It's not hard to extend either to do that, if that's what you want.
Problem is, at the time the decorated decorator is called, there is no object Blah yet: the class object is built after the class body finishes executing. Simplest is to have decorated stash the info "somewhere else", e.g. a function attribute, then a final pass (a class decorator or metaclass) reaps that info into the dictionary you desire.
Class decorators are simpler, but they don't get inherited (so they wouldn't come from a parent class), while metaclasses are inherited -- so if you insist on inheritance, a metaclass it will have to be. Simplest-first, with a class decorator and the "list" variant you have at the start of your Q rather than the "dict" variant you have later:
import inspect
def classdecorator(aclass):
decorated = []
for name, value in inspect.getmembers(aclass, inspect.ismethod):
if hasattr(value, '_decorated'):
decorated.append(name)
del value._decorated
aclass.decorated = decorated
return aclass
def decorated(afun):
afun._decorated = True
return afun
now,
#classdecorator
class Blah(object):
def one(self):
pass
#decorated
def two(self):
pass
gives you the Blah.decorated list you request in the first part of your Q. Building a dict instead, as you request in the second part of your Q, just means changing decorated.append(name) to decorated[name] = value in the code above, and of course initializing decorated in the class decorator to an empty dict rather than an empty list.
The metaclass variant would use the metaclass's __init__ to perform essentially the same post-processing after the class body is built -- a metaclass's __init__ gets a dict corresponding to the class body as its last argument (but you'll have to support inheritance yourself by appropriately dealing with any base class's analogous dict or list). So the metaclass approach is only "somewhat" more complex in practice than a class decorator, but conceptually it's felt to be much more difficult by most people. I'll give all the details for the metaclass if you need them, but I'd recommend sticking with the simpler class decorator if feasible.
Obj-C (which I have not used for a long time) has something called categories to extend classes. Declaring a category with new methods and compiling it into your program, all instances of the class suddenly have the new methods.
Python has mixin possibilities, which I use, but mixins must be used from the bottom of the program: the class has to declare it itself.
Foreseen category use-case: Say you have a big class hierarchy that describe different ways of interacting with data, declaring polymorphic ways to get at different attributes. Now a category can help the consumer of these describing classes by implementing a convenient interface to access these methods in one place. (A category method could for example, try two different methods and return the first defined (non-None) return value.)
Any way to do this in Python?
Illustrative code
I hope this clarifies what I mean. The point is that the Category is like an aggregate interface, that the consumer of AppObj can change in its code.
class AppObj (object):
"""This is the top of a big hierarchy of subclasses that describe different data"""
def get_resource_name(self):
pass
def get_resource_location(self):
pass
# dreaming up class decorator syntax
#category(AppObj)
class AppObjCategory (object):
"""this is a category on AppObj, not a subclass"""
def get_resource(self):
name = self.get_resource_name()
if name:
return library.load_resource_name(name)
else:
return library.load_resource(self.get_resource_location())
Why not just add methods dynamically ?
>>> class Foo(object):
>>> pass
>>> def newmethod(instance):
>>> print 'Called:', instance
...
>>> Foo.newmethod = newmethod
>>> f = Foo()
>>> f.newmethod()
Called: <__main__.Foo object at 0xb7c54e0c>
I know Objective-C and this looks just like categories. The only drawback is that you can't do that to built-in or extension types.
I came up with this implementation of a class decorator. I'm using python2.5 so I haven't actually tested it with decorator syntax (which would be nice), and I'm not sure what it does is really correct. But it looks like this:
pycategories.py
"""
This module implements Obj-C-style categories for classes for Python
Copyright 2009 Ulrik Sverdrup <ulrik.sverdrup#gmail.com>
License: Public domain
"""
def Category(toclass, clobber=False):
"""Return a class decorator that implements the decorated class'
methods as a Category on the class #toclass
if #clobber is not allowed, AttributeError will be raised when
the decorated class already contains the same attribute.
"""
def decorator(cls):
skip = set(("__dict__", "__module__", "__weakref__", "__doc__"))
for attr in cls.__dict__:
if attr in toclass.__dict__:
if attr in skip:
continue
if not clobber:
raise AttributeError("Category cannot override %s" % attr)
setattr(toclass, attr, cls.__dict__[attr])
return cls
return decorator
Python's setattr function makes this easy.
# categories.py
class category(object):
def __init__(self, mainModule, override = True):
self.mainModule = mainModule
self.override = override
def __call__(self, function):
if self.override or function.__name__ not in dir(self.mainModule):
setattr(self.mainModule, function.__name__, function)
# categories_test.py
import this
from categories import category
#category(this)
def all():
print "all things are this"
this.all()
>>> all things are this