This question already has answers here:
How to overload __init__ method based on argument type?
(10 answers)
Closed 7 years ago.
I have two constructors in one class, but when I call one of them (a one with one argument - only self - instead of a one with 4 arguments), it results in an error, saying it expected more arguments than the 1 given.
The class is the following way:
class Message:
def __init__(self):
self.data = None
def __init__(self, type, length, data):
self.type = type
self.length = length
self.data = data
and the call to it (where I also get the error is at):
msg = Message()
Where might be the problem? Isn't it comparable to C++? If not, how can I still get the same result in another way?
You cannot have two __init__ methods in a single class.
What your code effectively does is override the first method so it is never used, then you get an error because you haven't supplied enough arguments.
One way to get around this would be to supply default values using keyword-arguments. In this way if you create the Message object with no values, it'll use the defaults. The example below uses None as the default value but it could be something more complex:
class Message(object):
def __init__(self, type=None, length=None, data=None):
self.type = type
self.length = length
self.data = data
Python doesn't work that way. Use this:
class Message:
def __init__(self, type=None, length=None, data=None):
self.type = type
self.length = length
self.data = data
Related
I want to pass a default argument to an instance method using the value of an attribute of the instance:
class C:
def __init__(self, format):
self.format = format
def process(self, formatting=self.format):
print(formatting)
When trying that, I get the following error message:
NameError: name 'self' is not defined
I want the method to behave like this:
C("abc").process() # prints "abc"
C("abc").process("xyz") # prints "xyz"
What is the problem here, why does this not work? And how could I make this work?
You can't really define this as the default value, since the default value is evaluated when the method is defined which is before any instances exist. The usual pattern is to do something like this instead:
class C:
def __init__(self, format):
self.format = format
def process(self, formatting=None):
if formatting is None:
formatting = self.format
print(formatting)
self.format will only be used if formatting is None.
To demonstrate the point of how default values work, see this example:
def mk_default():
print("mk_default has been called!")
def myfun(foo=mk_default()):
print("myfun has been called.")
print("about to test functions")
myfun("testing")
myfun("testing again")
And the output here:
mk_default has been called!
about to test functions
myfun has been called.
myfun has been called.
Notice how mk_default was called only once, and that happened before the function was ever called!
In Python, the name self is not special. It's just a convention for the parameter name, which is why there is a self parameter in __init__. (Actually, __init__ is not very special either, and in particular it does not actually create the object... that's a longer story)
C("abc").process() creates a C instance, looks up the process method in the C class, and calls that method with the C instance as the first parameter. So it will end up in the self parameter if you provided it.
Even if you had that parameter, though, you would not be allowed to write something like def process(self, formatting = self.formatting), because self is not in scope yet at the point where you set the default value. In Python, the default value for a parameter is calculated when the function is compiled, and "stuck" to the function. (This is the same reason why, if you use a default like [], that list will remember changes between calls to the function.)
How could I make this work?
The traditional way is to use None as a default, and check for that value and replace it inside the function. You may find it is a little safer to make a special value for the purpose (an object instance is all you need, as long as you hide it so that the calling code does not use the same instance) instead of None. Either way, you should check for this value with is, not ==.
Since you want to use self.format as a default argument this implies that the method needs to be instance specific (i.e. there is no way to define this at class level). Instead you can define the specific method during the class' __init__ for example. This is where you have access to instance specific attributes.
One approach is to use functools.partial in order to obtain an updated (specific) version of the method:
from functools import partial
class C:
def __init__(self, format):
self.format = format
self.process = partial(self.process, formatting=self.format)
def process(self, formatting):
print(formatting)
c = C('default')
c.process()
# c.process('custom') # Doesn't work!
c.process(formatting='custom')
Note that with this approach you can only pass the corresponding argument by keyword, since if you provided it by position, this would create a conflict in partial.
Another approach is to define and set the method in __init__:
from types import MethodType
class C:
def __init__(self, format):
self.format = format
def process(self, formatting=self.format):
print(formatting)
self.process = MethodType(process, self)
c = C('test')
c.process()
c.process('custom')
c.process(formatting='custom')
This allows also passing the argument by position, however the method resolution order becomes less apparent (which can affect the IDE inspection for example, but I suppose there are IDE specific workarounds for that).
Another approach would be to create a custom type for these kind of "instance attribute defaults" together with a special decorator that performs the corresponding getattr argument filling:
import inspect
class Attribute:
def __init__(self, name):
self.name = name
def decorator(method):
signature = inspect.signature(method)
def wrapper(self, *args, **kwargs):
bound = signature.bind(*((self,) + args), **kwargs)
bound.apply_defaults()
bound.arguments.update({k: getattr(self, v.name) for k, v in bound.arguments.items()
if isinstance(v, Attribute)})
return method(*bound.args, **bound.kwargs)
return wrapper
class C:
def __init__(self, format):
self.format = format
#decorator
def process(self, formatting=Attribute('format')):
print(formatting)
c = C('test')
c.process()
c.process('custom')
c.process(formatting='custom')
You can't access self in the method definition. My workaround is this -
class Test:
def __init__(self):
self.default_v = 20
def test(self, v=None):
v = v or self.default_v
print(v)
Test().test()
> 20
Test().test(10)
> 10
"self" need to be pass as the first argument to any class functions if you want them to behave as non-static methods.
it refers to the object itself. You could not pass "self" as default argument as it's position is fix as first argument.
In your case instead of "formatting=self.format" use "formatting=None" and then assign value from code as below:
[EDIT]
class c:
def __init__(self, cformat):
self.cformat = cformat
def process(self, formatting=None):
print "Formating---",formatting
if formatting == None:
formatting = self.cformat
print formatting
return formatting
else:
print formatting
return formatting
c("abc").process() # prints "abc"
c("abc").process("xyz") # prints "xyz"
Note : do not use "format" as variable name, 'cause it is built-in function in python
Instead of creating a list of if-thens that span your default arguements, one can make use of a 'defaults' dictionary and create new instances of a class by using eval():
class foo():
def __init__(self,arg):
self.arg = arg
class bar():
def __init__(self,*args,**kwargs):
#default values are given in a dictionary
defaults = {'foo1':'foo()','foo2':'foo()'}
for key in defaults.keys():
#if key is passed through kwargs, use that value of that key
if key in kwargs: setattr(self,key,kwargs[key])
#if no key is not passed through kwargs
#create a new instance of the default value
else: setattr(self,key, eval(defaults[key]))
I throw this at the beginning of every class that instantiates another class as a default argument. It avoids python evaluating the default at compile... I would love a cleaner pythonic approach, but lo'.
I have the following problem and I need advice on how to solve it the best technically in Python. As I am new to programming I would like to have some advice.
So I will have the following object and they should store something. Here is an example:
object 1: cash dividends (they will have the following properties)
exdate (will store a list of dates)
recorddate (will store a list of dates)
paydate (will store a list of dates)
ISIN (will store a list of text)
object 2: stocksplits (they will have the following prpoerties)
stockplitratio (will be some ration)
exdate(list of dates)
...
I have tried to solve it like this:
class cashDividends(object):
def __init__(self, _gross,_net,_ISIN, _paydate, _exdate, _recorddate, _frequency, _type, _announceddate, _currency):
self.gross = _gross
self.net = _net
self.ISIN = _ISIN
self.paydate = _paydate
self.exdate = _exdate
self.recorddate = _recorddate
self.frequency = _frequency
self.type = _type
self.announceddate = _announceddate
self.currency = _currency
So if I have this I would have to create another class named stockplits and then define an __init__ function again.
However is there a way where I can have one class like "Corporate Actions" and then have stock splits and cashdividends in there ?
Sure you can! In python you can pass classes to other classes.
Here a simple example:
class A():
def __init__(self):
self.x = 0
class B():
def __init__(self):
self.x = 1
class Container():
def __init__(self, objects):
self.x = [obj.x for obj in objects]
a = A()
b = B()
c = Container([a,b])
c.x
[0,1]
If I understood correctly what you want is an object that has other objects from a class you created as property?
class CorporateActions(object):
def __init__(self, aCashDividend, aStockSplit):
self.cashDividend = aCashDividend
self.stockSplit = aStockSplit
myCashDividends = CashDividends(...) #corresponding parameters here
myStockSplit = StockSplit(...)
myCorporateActions = CorporateActions(myCashDividends, myStockSplit)
Strictly speaking this answer isn't an answer for the final question. However, it is a way to make your life slightly easier.
Consider creating a sort-of template class (I'm using this term loosely; there's no such thing in Python) that does the __init__ work for you. Like this:
class KwargAttrs():
def __init__(self, **kwargs):
for k,v in kwargs.items():
setattr(self, k, v)
def _update(self, **kwargs):
args_dict = {k:(kwargs[k] if k in kwargs else self.__dict__[k]) for k in self.__dict__}
self.__dict__.update(args_dict)
This class uses every supplied keyword argument as an object attribute. Use it this way:
class CashDividends(KwargAttrs):
def __init__(self, gross, net, ISIN, paydate, exdate, recorddate, frequency, type, announceddate, currency):
# save the namespace before it gets polluted
super().__init__(**locals())
# work that might pollute local namespace goes here
# OPTIONAL: update the argument values in case they were modified:
super()._update(**locals())
Using a method like this, you don't have to go through the argument list and assign every single object attribute; it happens automatically.
We bookend everything you need to accomplish in the __init__ method with method calls to the parent-class via super(). We do this because locals() returns a dict every variable in the function's current namespace, so you need to 1.) capture that namespace before any other work pollutes it and 2.) update the namespace in case any work changes the argument values.
The call to update is optional, but the values of the supplied arguments will not be updated if something is done to them after the call to super().__init__() (that is, unless you change the values using setattr(self, 'argname, value)`, which is not a bad idea).
You can continue using this class like so:
class StockSplits(KwargAttrs):
def __init__(self, stocksplitratio, gross, net, ISIN, paydate, exdate, recorddate, frequency, type, announceddate, currency):
super().__init__(**locals())
As mentioned in the other answers you can create a container for our other classes, but you can even do that using this same template class:
class CorporateActions(KwargAttrs):
def __init__(self, stock_splits , cash_dividends):
super().__init__(**locals())
ca = CorporateActions(stock_splits = StockSplits(<arguments>), cash_dividends = CashDividends(<arguments>) )
This question already has answers here:
Adding a method to an existing object instance in Python
(19 answers)
Closed 7 years ago.
In my model I have a class containing a rather generic function, which calls a higher order function. I put together a simple example of it:
class AClass(object):
def __init__(self, prop, fun):
self.prop = prop
self.fun = fun
def do_sth(self):
self.fun()
def namely_this_(context):
print 2*context.prop
obj1 = AClass(3, namely_this_)
obj1.do_sth()
This snippet contains everything to know, just note, that it could be continued by something like:
def namely_this_2(self):
print 4*self.prop
obj2 = AClass(2, namely_this_2)
obj2.do_sth()
The above code does not run, instead it throws a
TypeError: namely_this_() takes exactly 1 argument (0 given)
Instead, I have to change the do_sth to
def do_sth(self):
self.fun(self) # the *self* in the parenthesis added
Question: In what way does the namely_this_ differ from functions defined inside a class and is my workaround a viable solution?
An instance method is a property of the class, not the instance itself. If you changed your init to assign fun to self.__class__.fun, it would work; except then of course all instances would share the same function, which is clearly not what you want.
In order to make it an actual method, you need to make it an instance of types.MethodType:
def __init__(self, prop, fun):
self.prop = prop
self.fun = types.MethodType(fun, self)
I want to serialize some object with yaml.safe_dump(). How can I serialize Python objects with add_representer() and add_constructor() ...
I can not add yaml.YAMLObject to Thing (third party module) and not want use.
I do such dump:
import yaml
class Thing(object):
def __init__(self, name):
self.name = name
def Thing_representer(dumper, data):
return dumper.represent_mapping('!Thing', data.__dict__)
yaml.SafeDumper.add_representer(Thing, Thing_representer)
safe_dump = yaml.safe_dump(t)
print safe_dump
It works fine but I have no idea how to do constructor?
def Thing_constructor(loader, data):
thing = Thing()
return thing.__dict__.update(loader.construct_mapping(data))
yaml.SafeLoader.add_constructor('!Thing', Thing_constructor)
yaml.safe_load(safe_dump)
It throws exception TypeError: __init__() takes exactly 2 arguments (1 given) and should throw since constructor requires parameters. Maybe there is another option to construct object skipping constructor?
You cannot construct Thing() without handing in the name. You can solve that
in various ways, but the following should work.
def thing_constructor(self, node):
name = None
for x in node.value:
if x[0].value == 'name':
name = x[1].value
return Thing(name)
yaml.SafeLoader.add_constructor('!Thing', thing_constructor)
res = yaml.safe_load(safe_dump)
print res.name
You can simplify the setting of the name parameter, but this way it is more extensible if Thing would have taken more parameters.
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)