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Creating methods on the fly for a class instance

The following program is unable to create a function of a class
class MyClass(object):
def __init__(self, name=""):
self.name = name
def read_name(self):
return self.name
# First argument should be a ref to class
def callback(fcn, arg):
fcn.name=arg
# Create a instance of class
a = MyClass("Blue")
# Lets add new member functions
setattr(a, 'callback1', callback)
setattr(a, 'callback2', callback)
print a.read_name()
print a.callback1("purple") #! FAILS
print a.callback2("cyan") #! FAILS
What is the right way of creating a class member function automatically?
I want to create 'N' callback functions, they all will modify some common/uncommon class data (A shared dict)
EDIT 1
I wish to collect information from 'N' separate/parallel threads by passing callback functions. I do not know beforehand how many callback functions I need thus I want to create them on fly.
EDIT 2
I have a dictionary(d) where I am storing the information of different processes. The dictionary(d) is accessed within the callback. But because the same callback function is called at different threads, the dictionary data gets garbled. As a quickfix, I thought of creating separate callbacks.

If you know what you're doing, you'd want to try
import types
setattr(a, 'callback1', types.MethodType(callback, a, MyClass))

In short: when grafting a method, assign it to the class, not to the instance.
Here's an elucidating example.
class A(object):
"""As trivial as a class can get."""
def foo(self):
return self.bar(1) + self.baz()
# Rework everything!
def new_bar(self, x):
return 'I got %r' % x
def new_baz(self):
return ' and I\'m okay!'
A.bar = new_bar
A.baz = new_baz
print A().foo()
Now grafting method to an instance.
a = A()
# An instance attribute is a bound method;
# when we replace it with a function, we lose access to self.
a.bar = lambda x: x * 100
A.baz = lambda self: 42
assert a.foo() == 142
# We can do better, though.
from types import MethodType
a2 = A()
a2.foo = MethodType(lambda self: 'I know myself, my class is %s' % self.__class__.__name__, a2)
print a2.foo()
Note how you don't need setattr to set an attribute, even an unknown attribute. You may remember that you don't use setattr in __init__ either.

You can't add a class method to an instance; you have to add it to the class:
setattr(MyClass, 'callback1', callback)
But it's still a terrible idea. Why would you want this functionality?
Edit: keep your callbacks in a container instead:
class MyClass(object):
def __init__(self, name=""):
self.name = name
self.callbacks = []
def callback(self, idx, arg):
self.callbacks[idx](self, arg)
# First argument should be a ref to class
def callback(fcn, arg):
fcn.name=arg
# Create a instance of class
a = MyClass("Blue")
# Lets add new member functions
a.callbacks.append(callback)
a.callbacks.append(callback)
print a.name
a.callback(0, "purple")
print a.name
a.callback(1, "cyan")
print a.name

How To Call A Class Function From A Variable

I need a class router (for lack of a better word). The router needs to instantiate a class & call a function of that class instance based on variables passed to it.
How do I properly define the class function?
How do I properly call the class function?
Example code:
class ClassWorker1:
def function_1(self):
print('1a')
def function_2(self):
print('2a')
def function_3(self):
print('3a')
class ClassWorker2:
def function_1(self):
print('1b')
def function_2(self):
print('2b')
def function_3(self):
print('3b')
class ClassRouter(object):
def __init__(self, class_name, class_function):
self.class_instance = class_name()
self.class_function = class_function
self.main()
def main(self):
# how should I call the class function here?
self.class_instance.class_function()
return
a = 1
b = 1
if a == 1:
class_name = ClassWorker1
else:
class_name = ClassWorker1
if b == 1:
# Strings won't work as class function definition
# I won't know the class at this point. I will only know
# the shared function name at this point.
# how could this class function be defined directly?
class_function = 'function_1'
elif b == 2:
class_function = 'function_2'
else:
class_function = 'function_3'
ClassRouter(class_name, class_function)

I need a class router (for lack of a better word).
Are you sure you need a class for this ?
The router needs to instantiate a class & call a function of that class instance
When it belongs to a class or instance, a function is usually named a "method". Not really important but it makes things clearer. Also, an "instance" is obviously always, by definition, an instance of a class ;)
How do I properly define the class function?
How do I properly call the class function?
Does the router really have to be a class ? But anyway...
There are a couple distinct issues here (I of course assume you need something that's generic enough).
The first one is that your class (the one that will be instanciated by the "router") constructor may need some args - position or named or both. If it's the router's duty to instanciate the class (but should it be ?), you'll have to pass those args (both position and named) to the router. And since your router has to be generic (else it's useless) you cannot explicitely name these args in your router's constructor.
Hopefully, Python has a way to "unpack" tuples (for position args) and dicts (for named args) when calling a function, using respectively the * and ** operators at call time, ie:
def somefunc(arg1, arg2, arg3="foo", arg4=None):
print arg1, arg2, arg3, arg4
args = ("one", "two", "three")
kwargs = {"arg4": "four"}
somefunc(*args, **kwargs)
This let you pass arguments to a function in a generic way.
So if you want your router to be in charge of instanciating the "target" class, you'll have to support this:
class Router(object):
def __init__(self, cls, clsargs=None, clskwargs=None):
if clsargs is None:
clsargs = ()
if clskwargs is None:
clskwargs = {}
self._obj = cls(*clsargs, **clskwargs)
class Worker(object):
def __init__(self, name):
self.name = name
print self.name
r = Router(Worker, clsargs=("foo",))
# or
r = Router(Worker, clskwargs={"name":"foo"})
Now note that at this point you really don't gain anything (except for more code) from having the router instanciating the Worker - since you need to have the Worker class and it's constructor's args to instanciate the router, you could as well just instanciate the Worker yourself and pass the Worker instance to the router:
Since you must have a reference to the class passed to the router (else you can't pass it ), you could as well
class Router(object):
def __init__(self, obj):
self._obj = obj
class Worker(object):
def __init__(self, name):
self.name = name
print self.name
r = Router(Worker("foo"))
# or
r = Router(Worker(name="foo"))
The cases where it would make sense to have the router instanciate the worker are:
1/ if the Worker's constructor arguments are not known when the router is instanciated and are to be passed later (which requires a distinct router method to pass those args)
2/ if the Worker's instanciation is very costly and you're not even sure you'll really need it, in which case you want to wait until the router's "main" method is called to instanciate the worker.
The second issue is "how do I get the worker's method by name". This one has already been answered by Lukas: you use getattr(obj, attrname).
The third issue is "if my worker method needs arguments, how do I pass them". This is the same problem as with the worker's constructor arguments, so the solution is obviously the same. Depending on the concrete use case, you'll have to pass those args either when instanciating the router or when calling it's "main" method.
wrt/ this "main" method, remember that you can define your own callable types by implementing the __call__ method, ie
class NotAFunc(object):
def __init__(self, wot):
self.wot = wot
def __call__(self, count):
print self.wot * count
notafunc = NotAFunc("wot ? ")
notafunc(42)
So it might make sense to use this as your router's "main" method
Now do you really need a router class at all ? Python functions are object on their own (so a function can take a function and/or return a function), and moreover act as closures (a closure is a function that "captures" part of the environment where it's been defined):
def route(instance, methodname, methargs=None, methkwargs=None):
method = getattr(instance, methodname)
if methargs is None:
methargs = ()
if methkwargs is None:
methkwargs = {}
def func():
return method(*methargs, **methkwargs)
return func
class Worker(object):
def __init__(self, name):
self.name = name
def work(self, count):
return [self.name for i in range(count)]
r = route(Worker("foo"), "work", (42,))
print r()
Note that while I kept your "router" term, most of what I described above are known patterns. You may want to search for "proxy", "proxy method", and (for the last exemple) "partial evaluation".

You are looking for dynamic attribute lookup.
class C:
def c1(self, x):
return 2*x
instance = C()
method_name = 'c1'
method = getattr(instance, method_name)
print(method(1)) # call method and print result

You'll need to override the __new__ method of your (new-style!) class.
class ClassRouter(object):
def __new__(self, class_name, *args):
if arg=="Class1":
new_instance = ClassWorker1(*args)
new_instance.method()
return new_instance
elif arg=="Class2":
return ClassWorker2(*args)

Create multiple classes or multiple objects in Python?

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>) )

Mapping obj.method({argument:value}) to obj.argument(value)

I don't know if this will make sense, but...
I'm trying to dynamically assign methods to an object.
#translate this
object.key(value)
#into this
object.method({key:value})
To be more specific in my example, I have an object (which I didn't write), lets call it motor, which has some generic methods set, status and a few others. Some take a dictionary as an argument and some take a list. To change the motor's speed, and see the result, I use:
motor.set({'move_at':10})
print motor.status('velocity')
The motor object, then formats this request into a JSON-RPC string, and sends it to an IO daemon. The python motor object doesn't care what the arguments are, it just handles JSON formatting and sockets. The strings move_at and velocity are just two of what might be hundreds of valid arguments.
What I'd like to do is the following instead:
motor.move_at(10)
print motor.velocity()
I'd like to do it in a generic way since I have so many different arguments I can pass. What I don't want to do is this:
# create a new function for every possible argument
def move_at(self,x)
return self.set({'move_at':x})
def velocity(self)
return self.status('velocity')
#and a hundred more...
I did some searching on this which suggested the solution lies with lambdas and meta programming, two subjects I haven't been able to get my head around.
UPDATE:
Based on the code from user470379 I've come up with the following...
# This is what I have now....
class Motor(object):
def set(self,a_dict):
print "Setting a value", a_dict
def status(self,a_list):
print "requesting the status of", a_list
return 10
# Now to extend it....
class MyMotor(Motor):
def __getattr__(self,name):
def special_fn(*value):
# What we return depends on how many arguments there are.
if len(value) == 0: return self.status((name))
if len(value) == 1: return self.set({name:value[0]})
return special_fn
def __setattr__(self,attr,value): # This is based on some other answers
self.set({attr:value})
x = MyMotor()
x.move_at = 20 # Uses __setattr__
x.move_at(10) # May remove this style from __getattr__ to simplify code.
print x.velocity()
output:
Setting a value {'move_at': 20}
Setting a value {'move_at': 10}
10
Thank you to everyone who helped!

What about creating your own __getattr__ for the class that returns a function created on the fly? IIRC, there's some tricky cases to watch out for between __getattr__ and __getattribute__ that I don't recall off the top of my head, I'm sure someone will post a comment to remind me:
def __getattr__(self, name):
def set_fn(self, value):
return self.set({name:value})
return set_fn
Then what should happen is that calling an attribute that doesn't exist (ie: move_at) will call the __getattr__ function and create a new function that will be returned (set_fn above). The name variable of that function will be bound to the name parameter passed into __getattr__ ("move_at" in this case). Then that new function will be called with the arguments you passed (10 in this case).
Edit
A more concise version using lambdas (untested):
def __getattr__(self, name):
return lambda value: self.set({name:value})

There are a lot of different potential answers to this, but many of them will probably involve subclassing the object and/or writing or overriding the __getattr__ function.
Essentially, the __getattr__ function is called whenever python can't find an attribute in the usual way.
Assuming you can subclass your object, here's a simple example of what you might do (it's a bit clumsy but it's a start):
class foo(object):
def __init__(self):
print "initting " + repr(self)
self.a = 5
def meth(self):
print self.a
class newfoo(foo):
def __init__(self):
super(newfoo, self).__init__()
def meth2(): # Or, use a lambda: ...
print "meth2: " + str(self.a) # but you don't have to
self.methdict = { "meth2":meth2 }
def __getattr__(self, name):
return self.methdict[name]
f = foo()
g = newfoo()
f.meth()
g.meth()
g.meth2()
Output:
initting <__main__.foo object at 0xb7701e4c>
initting <__main__.newfoo object at 0xb7701e8c>
5
5
meth2: 5

You seem to have certain "properties" of your object that can be set by
obj.set({"name": value})
and queried by
obj.status("name")
A common way to go in Python is to map this behaviour to what looks like simple attribute access. So we write
obj.name = value
to set the property, and we simply use
obj.name
to query it. This can easily be implemented using the __getattr__() and __setattr__() special methods:
class MyMotor(Motor):
def __init__(self, *args, **kw):
self._init_flag = True
Motor.__init__(self, *args, **kw)
self._init_flag = False
def __getattr__(self, name):
return self.status(name)
def __setattr__(self, name, value):
if self._init_flag or hasattr(self, name):
return Motor.__setattr__(self, name, value)
return self.set({name: value})
Note that this code disallows the dynamic creation of new "real" attributes of Motor instances after the initialisation. If this is needed, corresponding exceptions could be added to the __setattr__() implementation.

Instead of setting with function-call syntax, consider using assignment (with =). Similarly, just use attribute syntax to get a value, instead of function-call syntax. Then you can use __getattr__ and __setattr__:
class OtherType(object): # this is the one you didn't write
# dummy implementations for the example:
def set(self, D):
print "setting", D
def status(self, key):
return "<value of %s>" % key
class Blah(object):
def __init__(self, parent):
object.__setattr__(self, "_parent", parent)
def __getattr__(self, attr):
return self._parent.status(attr)
def __setattr__(self, attr, value):
self._parent.set({attr: value})
obj = Blah(OtherType())
obj.velocity = 42 # prints setting {'velocity': 42}
print obj.velocity # prints <value of velocity>

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)