#classmethod and method without self - python

Let's suppose we have this class:
class Demo:
def __init__(self, str):
self.str = str
def fromBytes1(bytes):
return Demo(bytes2str(bytes))
#classmethod
def fromBytes2(cls, bytes):
return cls(bytes2str(bytes))
What is the difference between fromBytes1 and fromBytes2, except for the fact that you can't call the 1st method in the following way?
Demo().fromBytes1(bytes)
Is there something more subtle that I cannot see here?

Assuming that you only intend to call the methods from a class object, all the important differences are in inheritance. Say you have
class Test(Demo):
pass
If you do Test.fromBytes1(b'ar'), you get an instance of Demo.
If you do Test.fromBytes2(b'ar'), you get an instance of Test.
The second method is more flexible because you can hard code Demo or __class__ into it directly, but you must hard code it in the first case.

Related

Python: How to initialise a OOP List with some values already known?

I am trying to get into Object Oriented Programming but am getting stuck on something which is probably very simple. I want to have an object which is a list, but which starts with having some values passed into it.
Example:
class superList(list):
def __init__(self,startingValues):
self = startingValues
myList = superList([1,2,3])
myList.append(4)
print(myList)
I want the output of this to be [1,2,3,4]. If anyone could help, I would be very thankful!
Assigning to self isn't useful; you are just assigning to a local name that goes away after __init__ returns. Instead, you need to use __new__, and call the parent's class's __new__ method.
class SuperList(list):
def __new__(cls, starting_values):
return list.__new__(cls, starting_values)
Another approach is to use __init__, and just append the values in place:
class SuperList(list):
def __init__(self, starting_values):
self.extend(starting_values)
As pointed out in the comments, though, you would get the exact same result by not overriding either method:
class SuperList(list):
pass
because you aren't doing anything except invoking parent-class behavior in either method. In the absence of a defined SuperList.__new__, for example, SuperList([1,2,3]) just calls list.__new__(SuperList, [1,2,3]) anyway.
More interesting is when the class itself (at least, in part) determines behavior beyond using the values passed by the caller. For example:
class SuperList(list):
def __init__(self, starting_values):
self.extend([2*x for x in starting_values])
or
def __init__(self):
self.extend([1,2,3])
Don't inherit from built-in types, at least not as a beginner and without having read the actual implementation of those built-in's.
What you could do is writting a wrapper, something along the lines of this:
class MyList(object):
def __init__(self, init_values):
self.myList = []
self.myList.extend(init_values)
def append(self, value):
self.myList.append(value)
def __getitem__(self, _slice):
return self.myList[_slice]
NOTE: this is just to give you an idea of how you could do what you wanted to do, you would have to implement some additional cases and methods to actually have most functionalities of the builtin.

How can I refer to the currently being defined class? [duplicate]

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.

Multiple ways to define a class method in Python?

In Dive Into Python, Mark Pilgrim says that:
When defining your class methods, you must explicitly list self as the first argument for each method
He then gives a few examples of this in code:
def clear(self): self.data.clear()
def copy(self):
if self.__class__ is UserDict:
return UserDict(self.data)
import copy
return copy.copy(self)
While going through some Python code online, I came across the #classmethod decorator. An example of that is:
class Logger:
#classmethod
def debug(msg):
print "DEBUG: " + msg
(Notice that there is no self parameter in the debug function)
Is there any difference in defining class methods using self as the first parameter and using the #classmethod decorator? If not, is one way of defining class methods more commonly used/preferred over another?
#classmethod isn't the same as defining an instance method. Functions defined with #classmethod receive the class as the first argument, as opposed to an instance method which receives a specific instance. See the Python docs here for more information.
self is not and will never will be implicit.
"self will not become implicit.
Having self be explicit is a good thing. It makes the code clear by removing ambiguity about how a variable resolves. It also makes the difference between functions and methods small."
http://www.python.org/dev/peps/pep-3099/

python pass object as argument

How can I pass an object as an argument to a class method and call the method of the passed object when the class method is called?
Say I have:
class myclass:
def __init__(self):
pass
def myfunc(self, something):
something.do()
anobject = blah.xyz()
another_obj = myclass()
another_obj.myfunc(anobject)
So long as something has a .do method, that should work as given (once you fix your indentation and order of declaration). Have you tried running it?
This is (more or less) how a lot of standard functions work - for example, the built-in len function is pretty much
def len(obj):
return obj.__len__()
Which method of the past object do you want to call?
By the way, myfunc is an instance method.
class student :
ID=0
name=""
def fun(s=student()):
print (s.id)
print (s.name)
st=student()
fun(st)

How to cast object in Python

I have two classes (let's call them Working and ReturnStatement) which I can't modify, but I want to extend both of them with logging. The trick is that the Working's method returns a ReturnStatement object, so the new MutantWorking object also returns ReturnStatement unless I can cast it to MutantReturnStatement. Saying with code:
# these classes can't be changed
class ReturnStatement(object):
def act(self):
print "I'm a ReturnStatement."
class Working(object):
def do(self):
print "I am Working."
return ReturnStatement()
# these classes should wrap the original ones
class MutantReturnStatement(ReturnStatement):
def act(self):
print "I'm wrapping ReturnStatement."
return ReturnStatement().act()
class MutantWorking(Working):
def do(self):
print "I am wrapping Working."
# !!! this is not working, I'd need that casting working !!!
return (MutantReturnStatement) Working().do()
rs = MutantWorking().do() #I can use MutantWorking just like Working
print "--" # just to separate output
rs.act() #this must be MutantReturnState.act(), I need the overloaded method
The expected result:
I am wrapping Working.
I am Working.
--
I'm wrapping ReturnStatement.
I'm a ReturnStatement.
Is it possible to solve the problem? I'm also curious if the problem can be solved in PHP, too. Unless I get a working solution I can't accept the answer, so please write working code to get accepted.
There is no casting as the other answers already explained. You can make subclasses or make modified new types with the extra functionality using decorators.
Here's a complete example (credit to How to make a chain of function decorators?). You do not need to modify your original classes. In my example the original class is called Working.
# decorator for logging
def logging(func):
def wrapper(*args, **kwargs):
print func.__name__, args, kwargs
res = func(*args, **kwargs)
return res
return wrapper
# this is some example class you do not want to/can not modify
class Working:
def Do(c):
print("I am working")
def pr(c,printit): # other example method
print(printit)
def bla(c): # other example method
c.pr("saybla")
# this is how to make a new class with some methods logged:
class MutantWorking(Working):
pr=logging(Working.pr)
bla=logging(Working.bla)
Do=logging(Working.Do)
h=MutantWorking()
h.bla()
h.pr("Working")
h.Do()
this will print
h.bla()
bla (<__main__.MutantWorking instance at 0xb776b78c>,) {}
pr (<__main__.MutantWorking instance at 0xb776b78c>, 'saybla') {}
saybla
pr (<__main__.MutantWorking instance at 0xb776b78c>, 'Working') {}
Working
Do (<__main__.MutantWorking instance at 0xb776b78c>,) {}
I am working
In addition, I would like to understand why you can not modify a class. Did you try? Because, as an alternative to making a subclass, if you feel dynamic you can almost always modify an old class in place:
Working.Do=logging(Working.Do)
ReturnStatement.Act=logging(ReturnStatement.Act)
Update: Apply logging to all methods of a class
As you now specifically asked for this. You can loop over all members and apply logging to them all. But you need to define a rule for what kind of members to modify. The example below excludes any method with __ in its name .
import types
def hasmethod(obj, name):
return hasattr(obj, name) and type(getattr(obj, name)) == types.MethodType
def loggify(theclass):
for x in filter(lambda x:"__" not in x, dir(theclass)):
if hasmethod(theclass,x):
print(x)
setattr(theclass,x,logging(getattr(theclass,x)))
return theclass
With this all you have to do to make a new logged version of a class is:
#loggify
class loggedWorker(Working): pass
Or modify an existing class in place:
loggify(Working)
There is no "casting" in Python.
Any subclass of a class is considered an instance of its parents. Desired behavior can be achieved by proper calling the superclass methods, and by overriding class attributes.
update: with the advent of static type checking, there is "type casting" - check bellow.
What you can do on your example, is to have to have a subclass initializer that receives the superclass and copies its relevant attributes - so, your MutantReturnstatement could be written thus:
class MutantReturnStatement(ReturnStatement):
def __init__(self, previous_object=None):
if previous_object:
self.attribute = previous_object.attribute
# repeat for relevant attributes
def act(self):
print "I'm wrapping ReturnStatement."
return ReturnStatement().act()
And then change your MutantWorking class to:
class MutantWorking(Working):
def do(self):
print "I am wrapping Working."
return MutantReturnStatement(Working().do())
There are Pythonic ways for not having a lot of self.attr = other.attr lines on the __init__method if there are lots (like, more than 3 :-) ) attributes you want to copy -
the laziest of which wiuld be simply to copy the other instance's __dict__ attribute.
Alternatively, if you know what you are doing, you could also simply change the __class__ attribute of your target object to the desired class - but that can be misleading and carry you to subtle errors (the __init__ method of the subclass would not be called, would not work on non-python defined classes, and other possible problems), I don't recomment this approach - this is not "casting", it is use of introspection to bruteforce an object change and is only included for keeping the answer complete:
class MutantWorking(Working):
def do(self):
print "I am wrapping Working."
result = Working.do(self)
result.__class__ = MutantReturnStatement
return result
Again - this should work, but don't do it - use the former method.
By the way, I am not too experienced with other OO languages, that allow casting - but is casting to a subclass even allowed in any language? Does it make sense? I think casting s only allowed to parentclasses.
update: When one works with type hinting and static analysis in the ways describd in PEP 484, sometimes the static analysis tool can't figure out what is going on. So, there is the typing.cast call: it does absolutely nothing in runtime, just return the same object that was passed to it, but the tools then "learn" that the returned object is of the passed type, and won't complain about it. It will remove typing errors in the helper tool, but I can't emphasise enough it does not have any effect in runtime:
In [18]: from typing import cast
In [19]: cast(int, 3.4)
Out[19]: 3.4
No direct way.
You may define MutantReturnStatement's init like this:
def __init__(self, retStatement):
self.retStatement = retStatement
and then use it like this:
class MutantWorking(Working):
def do(self):
print "I am wrapping Working."
# !!! this is not working, I'd need that casting working !!!
return MutantReturnStatement(Working().do())
And you should get rid from inheriting ReturnStatement in your wrapper, like this
class MutantReturnStatement(object):
def act(self):
print "I'm wrapping ReturnStatement."
return self.retStatement.act()
You don't need casting here. You just need
class MutantWorking(Working):
def do(self):
print "I am wrapping Working."
Working().do()
return MutantReturnStatement()
This will obviously give the correct return and desired printout.
What you do is not a casting, it is a type conversion. Still, you could write something like
def cast_to(mytype: Type[any], obj: any):
if isinstance(obj, mytype):
return obj
else:
return mytype(obj)
class MutantReturnStatement(ReturnStatement):
def __init__(self, *args, **kwargs):
if isinstance(args[0], Working):
pass
# your custom logic here
# for the type conversion.
Usage:
cast_to(MutantReturnStatement, Working()).act()
# or simply
MutantReturnStatement(Working()).act()
(Note that in your example MutantReturnStatement does not have .do() member function.)

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