I have defined a python context class and a Test class in a file:
class Test(object):
pass
class MyContext(object):
def __init(self):
self._vars = []
def __enter__(self):
pass
def __exit(self, ....):
pass
In another file using that context:
from somewhere import Test, MyContext
with MyContext() as ctx:
mytest = Test()
So what I want to achieve is that when I exit the context, I want to be aware of the mytest instance created and add it in the ctx._vars = [<instance of Test >].
I don't want to have a ctx.add_var(mytest) method, I want those Test instances to be added automatically to the ctx instance.
That is possible of being done, using Python's introspection capabilities, but you have to be aware this is not what the with context block was created for.
I agree it is a useful syntax construction that can be "deviated" to do things like what you want: annotate the objects created inside a code block in a "registry".
Before showing how to do that with a context manager consider if a class body would not suffice you. Using a class body this way also deviates from its primary purpose, but you have your "registry" for free:
from somewhere import Test, MyContext
class ctx:
mytest = Test()
vars = ctx.__dict__.values()
In order to do that with a context manager, you have to inspect the local variables at the start and at the end of the with block. While that is not hard to do, it wuld not cover all instances of Test created - because if the code is like this:
mytests = []
with Mycontext as ctx:
mytests.append(Test())
No new variable is created - so code tracking the local variables would not find anything. Code could be written to look recursively into variables with containers, such as dictionaries and lists - but then mytest() instances could be added to a container referenced as a global variable, or a variable in other module.
It turns out that a reliable way to track Test instances would be to instrument the Test class itself to annotate new instances ina registry. That is far easier and less depentend on "local variable introspection" tricks.
The code for that is somewhat like:
class Test(object):
pass
class MyContext(object):
def __init(self, *args):
self.vars = []
self.track = args
self.original_new = {}
def patch(self, cls_to_patch):
cls_new = getattr(cls_to_patch, "__new__")
if "__new__" in cls.__dict__:
self.original_new[cls_to_patch] = cls_new
def patched_new(cls, *args, **kwargs):
instance = cls_new(*args, **kwags)
self.vars.append(instance)
return instance
cls_to_patch.__new__ = patched_new
def restore(self, cls):
if cls in self.original_new:
# class had a very own __new_ prior to patching
cls.__new__ = self.original_new[cls]
else:
# just remove the wrapped new method, restores access to superclass `__new__`
del cls.__new__
def __enter__(self):
for cls in self.track:
self.patch(cls)
return self
def __exit(self, ....):
for cls in self.track:
self.restore(cls)
...
from somewhere import Test, MyContext
with MyContext(Test) as ctx:
mytest = Test()
Related
I am almost sure that there is a proper term for what I want to do but since I'm not familiar with it, I will try to describe the whole idea explicitly. So what I have is a collection of classes that all inherit from one base class. All the classes consist almost entirely of different methods that are relevant within each class only. However, there are several methods that share similar name, general functionality and also some logic but their implementation is still mostly different. So what I want to know is whether it's possible to create a method in a base class that will execute some logic that is similar to all the methods but still continue the execution in the class specific method. Hopefully that makes sense but I will try to give a basic example of what I want.
So consider a base class that looks something like that:
class App(object):
def __init__(self, testName):
self.localLog = logging.getLogger(testName)
def access(self):
LOGIC_SHARED
And an example of a derived class:
class App1(App):
def __init__(self, testName):
. . .
super(App1, self).__init__(testName)
def access(self):
LOGIC_SPECIFIC
So what I'd like to achieve is that the LOGIC_SHARED part in base class access method to be executed when calling the access method of any App class before executing the LOGIC_SPECIFIC part which is(as it says) specific for each access method of all derived classes.
If that makes any difference, the LOGIC_SHARED mostly consists of logging and maintenance tasks.
Hope that is clear enough and the idea makes sense.
NOTE 1:
There are class specific parameters which are being used in the LOGIC_SHARED section.
NOTE 2:
It is important to implement that behavior using only Python built-in functions and modules.
NOTE 3:
The LOGIC_SHARED part looks something like that:
try:
self.localLog.info("Checking the actual link for %s", self.application)
self.link = self.checkLink(self.application)
self.localLog.info("Actual link found!: %s", self.link)
except:
self.localLog.info("No links found. Going to use the default link: %s", self.link)
So, there are plenty of specific class instance attributes that I use and I'm not sure how to use these attributes from the base class.
Sure, just put the specific logic in its own "private" function, which can overridden by the derived classes, and leave access in the Base.
class Base(object):
def access(self):
# Shared logic 1
self._specific_logic()
# Shared logic 2
def _specific_logic(self):
# Nothing special to do in the base class
pass
# Or you could even raise an exception
raise Exception('Called access on Base class instance')
class DerivedA(Base):
# overrides Base implementation
def _specific_logic(self):
# DerivedA specific logic
class DerivedB(Base):
# overrides Base implementation
def _specific_logic(self):
# DerivedB specific logic
def test():
x = Base()
x.access() # Shared logic 1
# Shared logic 2
a = DerivedA()
a.access() # Shared logic 1
# Derived A specific logic
# Shared logic 2
b = DerivedB()
b.access() # Shared logic 1
# Derived B specific logic
# Shared logic 2
The easiest method to do what you want is to simply call the parent's class access method inside the child's access method.
class App(object):
def __init__(self, testName):
self.localLog = logging.getLogger(testName)
def access(self):
LOGIC_SHARED
class App1(App):
def __init__(self, testName):
super(App1, self).__init__(testName)
def access(self):
App.access(self)
# or use super
super(App1, self).access()
However, your shared functionality is mostly logging and maintenance. Unless there is a pressing reason to put this inside the parent class, you may want to consider is to refactor the shared functionality into a decorator function. This is particularly useful if you want to reuse similar logging and maintenance functionality for a range of methods inside your class.
You can read more about function decorators here: http://www.artima.com/weblogs/viewpost.jsp?thread=240808, or here on Stack Overflow: How to make a chain of function decorators?.
def decorated(method):
def decorated_method(self, *args, **kwargs):
LOGIC_SHARED
method(self, *args, **kwargs)
return decorated_method
Remember than in python, functions are first class objects. That means that you can take a function and pass it as a parameter to another function. A decorator function make use of this. The decorator function takes another function as a parameter (here called method) and then creates a new function (here called decorated_method) that takes the place of the original function.
Your App1 class then would look like this:
class App1(App):
#logged
def access(self):
LOGIC_SPECIFIC
This really is shorthand for this:
class App1(App):
def access(self):
LOGIC_SPECIFIC
decorated_access = logged(App.access)
App.access = decorated_access
I would find this more elegant than adding methods to the superclass to capture shared functionality.
If I understand well this commment (How to execute BaseClass method before it gets overridden by DerivedClass method in Python) you want that additional arguments passed to the parent class used in derived class
based on Jonathon Reinhart's answer
it's how you could do
class Base(object):
def access(self,
param1 ,param2, #first common parameters
*args, #second positional parameters
**kwargs #third keyword arguments
):
# Shared logic 1
self._specific_logic(param1, param2, *args, **kwargs)
# Shared logic 2
def _specific_logic(self, param1, param2, *args, **kwargs):
# Nothing special to do in the base class
pass
# Or you could even raise an exception
raise Exception('Called access on Base class instance')
class DerivedA(Base):
# overrides Base implementation
def _specific_logic(self, param1, param2, param3):
# DerivedA specific logic
class DerivedB(Base):
# overrides Base implementation
def _specific_logic(self, param1, param2, param4):
# DerivedB specific logic
def test():
x = Base()
a = DerivedA()
a.access("param1", "param2", "param3") # Shared logic 1
# Derived A specific logic
# Shared logic 2
b = DerivedB()
b.access("param1", "param2", param4="param4") # Shared logic 1
# Derived B specific logic
# Shared logic 2
I personally prefer Jonathon Reinhart's answer, but seeing as you seem to want more options, here's two more. I would probably never use the metaclass one, as cool as it is, but I might consider the second one with decorators.
With Metaclasses
This method uses a metaclass for the base class that will force the base class's access method to be called first, without having a separate private function, and without having to explicitly call super or anything like that. End result: no extra work/code goes into inheriting classes.
Plus, it works like maaaagiiiiic </spongebob>
Below is the code that will do this. Here http://dbgr.cc/W you can step through the code live and see how it works :
#!/usr/bin/env python
class ForceBaseClassFirst(type):
def __new__(cls, name, bases, attrs):
"""
"""
print("Creating class '%s'" % name)
def wrap_function(fn_name, base_fn, other_fn):
def new_fn(*args, **kwargs):
print("calling base '%s' function" % fn_name)
base_fn(*args, **kwargs)
print("calling other '%s' function" % fn_name)
other_fn(*args, **kwargs)
new_fn.__name__ = "wrapped_%s" % fn_name
return new_fn
if name != "BaseClass":
print("setting attrs['access'] to wrapped function")
attrs["access"] = wrap_function(
"access",
getattr(bases[0], "access", lambda: None),
attrs.setdefault("access", lambda: None)
)
return type.__new__(cls, name, bases, attrs)
class BaseClass(object):
__metaclass__ = ForceBaseClassFirst
def access(self):
print("in BaseClass access function")
class OtherClass(BaseClass):
def access(self):
print("in OtherClass access function")
print("OtherClass attributes:")
for k,v in OtherClass.__dict__.iteritems():
print("%15s: %r" % (k, v))
o = OtherClass()
print("Calling access on OtherClass instance")
print("-------------------------------------")
o.access()
This uses a metaclass to replace OtherClass's access function with a function that wraps a call to BaseClass's access function and a call to OtherClass's access function. See the best explanation of metaclasses here https://stackoverflow.com/a/6581949.
Stepping through the code should really help you understand the order of things.
With Decorators
This functionality could also easily be put into a decorator, as shown below. Again, a steppable/debuggable/runnable version of the code below can be found here http://dbgr.cc/0
#!/usr/bin/env python
def superfy(some_func):
def wrapped(self, *args, **kwargs):
# NOTE might need to be changed when dealing with
# multiple inheritance
base_fn = getattr(self.__class__.__bases__[0], some_func.__name__, lambda *args, **kwargs: None)
# bind the parent class' function and call it
base_fn.__get__(self, self.__class__)(*args, **kwargs)
# call the child class' function
some_func(self, *args, **kwargs)
wrapped.__name__ = "superfy(%s)" % some_func.__name__
return wrapped
class BaseClass(object):
def access(self):
print("in BaseClass access function")
class OtherClass(BaseClass):
#superfy
def access(self):
print("in OtherClass access function")
print("OtherClass attributes")
print("----------------------")
for k,v in OtherClass.__dict__.iteritems():
print("%15s: %r" % (k, v))
print("")
o = OtherClass()
print("Calling access on OtherClass instance")
print("-------------------------------------")
o.access()
The decorator above retrieves the BaseClass' function of the same name, and calls that first before calling the OtherClass' function.
May this simple approach can help.
class App:
def __init__(self, testName):
self.localLog = logging.getLogger(testName)
self.application = None
self.link = None
def access(self):
print('There is something BaseClass must do')
print('The application is ', self.application)
print('The link is ', self.link)
class App1(App):
def __init__(self, testName):
# ...
super(App1, self).__init__(testName)
def access(self):
self.application = 'Application created by App1'
self.link = 'Link created by App1'
super(App1, self).access()
print('There is something App1 must do')
class App2(App):
def __init__(self, testName):
# ...
super(App2, self).__init__(testName)
def access(self):
self.application = 'Application created by App2'
self.link = 'Link created by App2'
super(App2, self).access()
print('There is something App2 must do')
and the test result:
>>>
>>> app = App('Baseclass')
>>> app.access()
There is something BaseClass must do
The application is None
The link is None
>>> app1 = App1('App1 test')
>>> app1.access()
There is something BaseClass must do
The application is Application created by App1
The link is Link created by App1
There is something App1 must do
>>> app2 = App2('App2 text')
>>> app2.access()
There is something BaseClass must do
The application is Application created by App2
The link is Link created by App2
There is something App2 must do
>>>
Adding a combine function we can combine two functions and execute them one after other as bellow
def combine(*fun):
def new(*s):
for i in fun:
i(*s)
return new
class base():
def x(self,i):
print 'i',i
class derived(base):
def x(self,i):
print 'i*i',i*i
x=combine(base.x,x)
new_obj=derived():
new_obj.x(3)
Output Bellow
i 3
i*i 9
it need not be single level hierarchy it can have any number of levels or nested
EDIT: i found this method decorator and was able to use it to individually wrap the methods (omitting __init__) of ClassA and ClassB. however, instead of manually wrapping individual methods, i'd like to just wrap the class.
i've created my own logging class, MyLogger, which inherits logging.Logger. in this class, (among other things) i have a FileHandler which prints the logger name in its output:
import logging
class MyLogger(logging.Logger):
def __init__(self, name, path="output.log"):
logging.Logger.__init__(self, name, logging.DEBUG)
logpath = path
fh = logging.FileHandler(logpath)
fh.setLevel(logging.DEBUG)
fh.setFormatter(logging.Formatter("%(name)s - %(message)s"))
# stream handler omitted
self.addHandler(fh)
i also have ClassA and ClassB, which both get the same instance of MyLogger:
class ClassA(object):
def __init__(self, mylogger):
self.log = mylogger
def fn1(self):
self.log.debug("message1 from ClassA fn1")
self.fn2()
b = ClassB(self.log)
b.fn1()
self.log.debug("message2 from ClassA fn1")
def fn2(self):
self.log.debug("message1 from ClassA fn2")
# many more functions
class ClassB(object):
def __init__(self, mylogger):
self.log = mylogger
def fn1(self):
self.log.debug("message1 from ClassB fn1")
# many more functions
here's a simple "main" function:
print "inside main"
log = MyLogger("main")
a = ClassA(log)
a.fn1()
because the MyLogger instance is being passed around, i'd like to ensure the log name (i'm just using the class name) is printed correctly by each function. so i'm attempting to decorate all methods of each class so that the the previous log name is remembered, then the log name is set to the name of the class, the method is run, and finally the log name is set back to what it previously was. i'm using the decorator/descriptor from here. for the sake of brevity, i will only post my changes to it. i renamed the decorator setlogger, have added print statements inside each method in the descript class, and have altered make_bound as follows:
def make_bound(self, instance):
print "in __BOUND__"
#functools.wraps(self.f)
def wrapper(*args, **kwargs):
'''This documentation will disapear :)'''
prev = instance.log.name
print "about to wrap %s.%s, prev = %s" % (instance.__class__.__name__, self.f.__name__, prev)
ret = self.f(instance, *args, **kwargs)
instance.log.name = prev
print "done wrapping %s.%s, now = %s" % (instance.__class__.__name__, self.f.__name__, prev)
return ret
# This instance does not need the descriptor anymore,
# let it find the wrapper directly next time:
setattr(instance, self.f.__name__, wrapper)
return wrapper
if i use the setlogger decorator/descriptor to wrap individual methods in ClassA and ClassB, it works fine. however, i'd like to just wrap the two classes. so here's my class decorator:
def setloggerforallmethods(cls):
def decorate(*args, **kwargs):
for name, m in inspect.getmembers(cls, inspect.ismethod):
if name != "__init__":
print "calling setattr on %s.%s" % (cls.__name__, name)
setattr(cls, name, setlogger(m))
return cls
return decorate
if i wrap ClassA and ClassB with #setloggerforallmethods, and run the main function, heres the output:
inside main
calling setattr on ClassA.fn1
in __INIT__: f = fn1
calling setattr on ClassA.fn2
in __INIT__: f = fn2
in __GET__
in __UNBOUND__
Traceback (most recent call last):
File "/ws/maleva-rcd/yacht/classa.py", line 23, in <module>
a.fn1()
File "/ws/maleva-rcd/yacht/yachtlogger.py", line 34, in wrapper
self.f.__name__)
ValueError: zero length field name in format
i dont understand why fn1 is unbound at this time. isnt it bound to a as in a.fn1()?
I think you're trying to solve the wrong problem in the wrong way. But I can explain why your code isn't doing what you're trying to make it do.
First, in your decorator, you do this:
for name, fn in inspect.getmembers(cls, inspect.ismethod):
if name != "__init__":
print "calling setlogger on %s" % cls.__name__ + "." + name
fn = setlogger(fn)
That has no effect. For each bound method fn, you create a wrapper function, then rebind the local variable fn to that function. That has no more effect than doing this:
def foo(a):
a = 3
i = 0
foo(i)
If you want to set an attribute on the class, you have to set an attribute on the class, like this:
setattr(cls, name, setlogger(fn))
Now your wrapper will get called.
Next, cls.log is a class attribute named log—that is, an attribute on the class itself, which is shared by all instances of that class. But all of the code within the classes uses instance attributes, where each instance has its own copy. That's what you get when you assign self.log in your __init__. So, there is no class attribute named log, meaning you'll just get this:
AttributeError: type object 'ClassA' has no attribute 'log'
You could of course create a class attribute… but that won't do any good. The instance attribute of the same name will just shadow it.
You need to access the instance attribute inside inner, which means you need a self to access it off. And you obviously don't have self inside setlogger. But think about what you're doing: you're wrapping a method with another method. Methods get self as their first argument. In fact, if you modify inner to print out its args, you'll see that the first one is always something like <__main__.ClassA object at 0x12345678>. So:
def inner(self, *args, **kwargs):
prevname = self.log.name
self.log.name = cls.__name__
ret = func(self, *args, **kwargs) # don't forget to forward self
self.log.name = prevname
return ret
But if any of these wrapped methods ever raises an exception, they'll leave the name in the wrong state. So really, you need to either create a context manager for stashing and restoring the value, or just a try/finally. Which also happens to make the wrapper a little easier to write:
def inner(self, *args, **kwargs):
prevname = self.log.name
self.log.name = cls.__name__
try:
return func(self, *args, **kwargs)
finally:
self.log.name = prevname
Finally, you need to remove the self.log.name = in each __init__ method. Otherwise, when you construct a B instance in the middle of A.fn1, you're changing the logger's name without going through the wrapper that restores the previous name.
Again, I don't think this is a good solution. But it will do what you're trying to do.
I still don't completely understand the problem you're trying to solve, but I think it's this:
Constructing a MyLogger takes two pieces of information: a name, and a path. You don't want every class to have to know that path. So, you figured you needed to share the MyLogger instance, because there's no other way around that. And then, because the MyLogger stores its name as an attribute, you had to hack up that attribute in wrappers around every method.
But there is a much simpler way around that: Make your classes take a "logger factory"—that is, a callable which constructs an appropriate logger for them—instead of a logger. The MyLogger class itself already is such a callable, since it takes a default value for path and you just use it. But let's pretend that weren't true, and you wanted to use some non-default path. Still easy; you just need to wrap it up:
class ClassA(object):
def __init__(self, log_factory):
self.log_factory = log_factory
self.log = log_factory("ClassA")
def fn1(self):
# ...
b = ClassB(self.log_factory)
# ...
class ClassB(object):
def __init__(self, log_factory):
self.log_factory = log_factory
self.log = log_factory("ClassB")
# ...
# or just log_factory = functools.partial(MyLogger, log="output.log")
def log_factory(name):
return MyLogger(name, "output.log")
a = ClassA(log_factory)
a.fn1()
You may notice that the __init__ method in both classes does the same thing. So, why not extract it into a mixin base class?
class LogUserMixin(object):
def __init__(self, log_factory):
self.log_factory = log_factory
self.log = log_factory(self.__class__.__name__)
Now:
class ClassA(LogUserMixin):
def fn1(self):
# ...
When it's a ClassA being initialized, self.__class__ will be "ClassA", not "LogUserMixin", so this does exactly what you want. It works even if your real classes already have base classes, or a hierarchy of subclasses, or if they do additional stuff in __init__, or take additional arguments; you just need to do a tiny bit more work in some of those cases.
After using Django for a while, I got use to using classes without def __init__(self): ... when declaring variables. I used to declare my variables in the __init__ function, I now realize that there are cases where don't need to, I'm just unclear on when to use it or not. It seems there is a problem when trying to pass a class to a variable, should I use init in these cases?
I know I could just use __init__ for all cases, but it just makes my short classes like cleaner without it, so I would like to know when I can and cannot use it.
example:
class BaseScraper(object):
# whithout __init__, passing Site() to site wont work.
# site = Site()
# parser = None
def __init__(self):
self.site = Site()
self.parser = None
class Site(object):
# no trouble declaring url as a str
url = ""
def set(self, url):
self.url = url
def get(self):
return self.url
if __name__ == "__main__":
scraper = BaseScraper()
scraper.site.set('http://www.google.com')
print scraper.site.get()
Attributes declared in the class are owned by the class rather than by individual instances of the class. In your site example, url is no more a property of individual Site objects than set or get are. For this kind of example, you want instance data - which you can initialize in __init__.
Python: Difference between class and instance attributes has a good discussion of the differences.
This fails because Site class is not defined yet.
And (as #Peter DeGlopper) said, there is a big difference between class variables and instance variables.
class BaseScraper(object):
# This fails!
site = Site()
parser = None
class Site(object):
# no trouble declaring url as a str
url = ""
def set(self, url):
self.url = url
def get(self):
return self.url
When the virtual machine compile a python module, read and compile everything in class declaration, but on method declaration (like def __init__(...):) only read this line, ignoring the method body.
Example:
class Foo(object):
bar1 = "bar"
foo1 = "foo"
def __init__(self):
self.bar2 = "BAZ"
foo = Foo #Put a class in a veriable? yes, you can.
foo.bar1 # returns "bar"
foo.foo1 # returns "foo"
foo.bar2 # fails!!!! This will be a instance variable, but doesn't exist yet
foo2 = Foo() # Here the __init__ is called
foo2.bar2 # returns "BAZ"
foo2.bar1 #Returns "bar" because all class variables are availables from instances
Hope this helps =)
I've been trying to pickle an object which contains references to static class methods.
Pickle fails (for example on module.MyClass.foo) stating it cannot be pickled, as module.foo does not exist.
I have come up with the following solution, using a wrapper object to locate the function upon invocation, saving the container class and function name:
class PicklableStaticMethod(object):
"""Picklable version of a static method.
Typical usage:
class MyClass:
#staticmethod
def doit():
print "done"
# This cannot be pickled:
non_picklable = MyClass.doit
# This can be pickled:
picklable = PicklableStaticMethod(MyClass.doit, MyClass)
"""
def __init__(self, func, parent_class):
self.func_name = func.func_name
self.parent_class = parent_class
def __call__(self, *args, **kwargs):
func = getattr(self.parent_class, self.func_name)
return func(*args, **kwargs)
I am wondering though, is there a better - more standard way - to pickle such an object?
I do not want to make changes to the global pickle process (using copy_reg for example), but the following pattern would be great:
class MyClass(object):
#picklable_staticmethod
def foo():
print "done."
My attempts at this were unsuccessful, specifically because I could not extract the owner class from the foo function. I was even willing to settle for explicit specification (such as #picklable_staticmethod(MyClass)) but I don't know of any way to refer to the MyClass class right where it's being defined.
Any ideas would be great!
Yonatan
This seems to work.
class PickleableStaticMethod(object):
def __init__(self, fn, cls=None):
self.cls = cls
self.fn = fn
def __call__(self, *args, **kwargs):
return self.fn(*args, **kwargs)
def __get__(self, obj, cls):
return PickleableStaticMethod(self.fn, cls)
def __getstate__(self):
return (self.cls, self.fn.__name__)
def __setstate__(self, state):
self.cls, name = state
self.fn = getattr(self.cls, name).fn
The trick is to snag the class when the static method is gotten from it.
Alternatives: You could use metaclassing to give all your static methods a .__parentclass__ attribute. Then you could subclass Pickler and give each subclass instance its own .dispatch table which you can then modify without affecting the global dispatch table (Pickler.dispatch). Pickling, unpickling, and calling the method might then be a little faster.
EDIT: modified after Jason comment.
I think python is correct in not letting pickling a staticmethod object - as it is impossible to pickle instance or class methods! Such an object would make very little sense outside of its context:
Check this: Descriptor Tutorial
import pickle
def dosomething(a, b):
print a, b
class MyClass(object):
dosomething = staticmethod(dosomething)
o = MyClass()
pickled = pickle.dumps(dosomething)
This works, and that's what should be done - define a function, pickle it, and use such function as a staticmethod in a certain class.
If you've got an use case for your need, please write it down and I'll be glad to discuss it.
I want to do a one time callback registration within Observer. I don't want to do the registration inside init or other function. I don't know if there is a class level equivalent for init
class Observer:
#classmethod
def on_new_user_registration(new_user):
#body of handler...
# first I try
NewUserRegistered().subscribe \
(Observer.on_new_user_registration) #gives NameError for Observer
#so I try
NewUserRegistered().subscribe(on_new_user_registration) #says not callable
#neither does this work
NewUserRegistered().subscribe(__metaclass__.on_new_user_registration)
class BaseEvent(object):
_subscriptions = {}
def __init__(self, event_info = None):
self.info = event_info
def fire(self):
for callback in self._subscriptions[event_type]:
callback(event_info)
def subscribe(self, callback):
if not callable(callback):
raise Exception(str(callback) + 'is not callable')
existing = self._subscriptions.get(self.__class__, None)
if not existing:
existing = set()
self._subscriptions[self.__class__] = existing
existing.add(callback)
class NewUserRegistered(BaseEvent):
pass
I suggest to cut down on the number of classes -- remember that Python isn't Java. Every time you use #classmethod or #staticmethod you should stop and think about it since these keywords are quite rare in Python.
Doing it like this works:
class BaseEvent(object):
def __init__(self, event_info=None):
self._subscriptions = set()
self.info = event_info
def fire(self, data):
for callback in self._subscriptions:
callback(self.info, data)
def subscribe(self, callback):
if not callable(callback):
raise ValueError("%r is not callable" % callback)
self._subscriptions.add(callback)
return callback
new_user = BaseEvent()
#new_user.subscribe
def on_new_user_registration(info, username):
print "new user: %s" % username
new_user.fire("Martin")
If you want an Observer class, then you can do it like this:
class Observer:
#staticmethod
#new_user.subscribe
def on_new_user_registration(info, username):
print "new user: %s" % username
But note that the static method does not have access to the protocol instance, so this is probably not very useful. You can not subscribe a method bound to an object instance like this since the object wont exist when the class definition is executed.
But you can of course do this:
class Observer:
def on_new_user_registration(self, info, username):
print "new user: %s" % username
o = Observer()
new_user.subscribe(o.on_new_user_registration)
where we use the bound o.on_new_user_registration as argument to subscribe.
I've come to accept that python isn't very intuitive when it comes to functional programming within class definitions. See this question. The problem with the first method is that Observer doesn't exist as a namespace until the class has been built. The problem with the second is that you've made a class method that doesn't really do what it's supposed to until after the namespace has been created. (I have no idea why you're trying the third.) In both case neither of these things occurs until after the class definition of Observer has been populated.
This might sound like a sad constraint, but it's really not so bad. Just register after the class definition. Once you realize that it's not bad style to perform certain initialization routines on classes in the body of the module but outside the body of the class, python becomes a lot friendlier. Try:
class Observer:
# Define the other classes first
class Observer:
#classmethod
def on_new_user_registration(new_user):
#body of handler...
NewUserRegistered().subscribe(Observer.on_new_user_registration)
Because of the way modules work in python, you are guaranteed that this registration will be performed once and only once (barring process forking and maybe some other irrelevant boundary cases) wherever Observer is imported.
oops. sorry about that.
All I had to do was to move the subscription outside the class definition
class Observer:
#classmethod
def on_new_user_registration(new_user):
#body of handler...
#after end of class
NewUserRegistered().subscribe(Observer.on_new_user_registration)
Guess it is a side-effect of too much Java that one doesn't immediately think of this.
What you're doing should work:
>>> class foo:
... #classmethod
... def func(cls):
... print 'func called!'
...
>>> foo.func()
func called!
>>> class foo:
... #classmethod
... def func(cls):
... print 'func called!'
... foo.func()
...
func called!
One thing to note though, class methods take a cls argument instead of a self argument. Thus, your class definition should look like this:
class Observer:
#classmethod
def on_new_user_registration(cls, new_user):
#body of handler...