I am Trying to emulate the following code with something more elegant:
def makeHomeFunc(axisNumber):
def fClosure(null_pass):
stage.home(axisNumber)
return fClosure
In short this is a function factory, that acts like functools.partial with the additional property of discarding the values passed to the produced function, and running the inner wrapped function with the factory's call.
Thanks
Related
Let us give an example.
If we have a function def f(func): ..., where func is a parameter corresponding to a function.
If we make the following call f(merge), I would like to return another function name (not a text) merge_ext that could be then executed.
I have identified the fact that a function name col be extract with the syntax my_function.__name__, but how can I generate the new function name that could be used as a function?
It looks like you're after decorators.
A decorator is a function that takes a function as arguments, and returns a function. Simple example :
def simple_decorator(func):
return func
You can use it with the # syntax :
#simple_decorator
def decorated_function(some_arg):
return something
In that case, calling function will call the function returned by the call simple_decorator(function), which means you cannot access the orginal function anymore.
But this can also be expressed like this :
def no_yet_decorated_function(some_arg):
return something
decorated_function = simple_decorator(no_yet_decorated_function)
Now, you can access both your functions.
I am attempting to integrate a very old system and a newer system at work. The best I can do is to utilize an RSS firehouse type feed the system utilizes. The goal is to use this RSS feed to make the other system perform certain actions when certain people do things.
My idea is to wrap a decorator around certain functions to check if the user (a user ID provided in the RSS feed) has permissions in the new system.
My current solution has a lot of functions that look like this, which are called based on an action field in the feed:
actions_dict = {
...
'action1': function1
}
actions_dict[RSSFEED['action_taken']](RSSFEED['user_id'])
def function1(user_id):
if has_permissions(user_id):
# Do this function
I want to create a has_permissions decorator that takes the user_id so that I can remove this redundant has_permissions check in each of my functions.
#has_permissions(user_id)
def function1():
# Do this function
Unfortunately, I am not sure how to write such a decorator. All the tutorials I see have the #has_permissions() line with a hardcoded value, but in my case it needs to be passed at runtime and will be different each time the function is called.
How can I achieve this functionality?
In your question, you've named both, the check of the user_id, as well as the wanted decorator has_permissions, so I'm going with an example where names are more clear: Let's make a decorator that calls the underlying (decorated) function when the color (a string) is 'green'.
Python decorators are function factories
The decorator itself (if_green in my example below) is a function. It takes a function to be decorated as argument (named function in my example) and returns a function (run_function_if_green in the example). Usually, the returned function calls the passed function at some point, thereby "decorating" it with other actions it might run before or after it, or both.
Of course, it might only conditionally run it, as you seem to need:
def if_green(function):
def run_function_if_green(color, *args, **kwargs):
if color == 'green':
return function(*args, **kwargs)
return run_function_if_green
#if_green
def print_if_green():
print('what a nice color!')
print_if_green('red') # nothing happens
print_if_green('green') # => what a nice color!
What happens when you decorate a function with the decorator (as I did with print_if_green, here), is that the decorator (the function factory, if_green in my example) gets called with the original function (print_if_green as you see it in the code above). As is its nature, it returns a different function. Python then replaces the original function with the one returned by the decorator.
So in the subsequent calls, it's the returned function (run_function_if_green with the original print_if_green as function) that gets called as print_if_green and which conditionally calls further to that original print_if_green.
Functions factories can produce functions that take arguments
The call to the decorator (if_green) only happens once for each decorated function, not every time the decorated functions are called. But as the function returned by the decorator that one time permanently replaces the original function, it gets called instead of the original function every time that original function is invoked. And it can take arguments, if we allow it.
I've given it an argument color, which it uses itself to decide whether to call the decorated function. Further, I've given it the idiomatic vararg arguments, which it uses to call the wrapped function (if it calls it), so that I'm allowed to decorate functions taking an arbitrary number of positional and keyword arguments:
#if_green
def exclaim_if_green(exclamation):
print(exclamation, 'that IS a nice color!')
exclaim_if_green('red', 'Yay') # again, nothing
exclaim_if_green('green', 'Wow') # => Wow that IS a nice color!
The result of decorating a function with if_green is that a new first argument gets prepended to its signature, which will be invisible to the original function (as run_function_if_green doesn't forward it). As you are free in how you implement the function returned by the decorator, it could also call the original function with less, more or different arguments, do any required transformation on them before passing them to the original function or do other crazy stuff.
Concepts, concepts, concepts
Understanding decorators requires knowledge and understanding of various other concepts of the Python language. (Most of which aren't specific to Python, but one might still not be aware of them.)
For brevity's sake (this answer is long enough as it is), I've skipped or glossed over most of them. For a more comprehensive speedrun through (I think) all relevant ones, consult e.g. Understanding Python Decorators in 12 Easy Steps!.
The inputs to decorators (arguments, wrapped function) are rather static in python. There is no way to dynamically pass an argument like you're asking. If the user id can be extracted from somewhere at runtime inside the decorator function however, you can achieve what you want..
In Django for example, things like #login_required expect that the function they're wrapping has request as the first argument, and Request objects have a user attribute that they can utilize. Another, uglier option is to have some sort of global object you can get the current user from (see thread local storage).
The short answer is no: you cannot pass dynamic parameters to decorators.
But... you can certainly invoke them programmatically:
First let's create a decorator that can perform a permission check before executing a function:
import functools
def check_permissions(user_id):
def decorator(f):
#functools.wraps(f)
def wrapper(*args, **kw):
if has_permissions(user_id):
return f(*args, **kw)
else:
# what do you want to do if there aren't permissions?
...
return wrapper
return decorator
Now, when extracting an action from your dictionary, wrap it using the decorator to create a new callable that does an automatic permission check:
checked_action = check_permissions(RSSFEED['user_id'])(
actions_dict[RSSFEED['action_taken']])
Now, when you call checked_action it will first check the permissions corresponding to the user_id before executing the underlying action.
You may easily work around it, example:
from functools import wraps
def some_function():
print("some_function executed")
def some_decorator(decorator_arg1, decorator_arg2):
def decorate(func):
#wraps(func)
def wrapper(*args, **kwargs):
print(decorator_arg1)
ret = func(*args, **kwargs)
print(decorator_arg2)
return ret
return wrapper
return decorate
arg1 = "pre"
arg2 = "post"
decorated = some_decorator(arg1, arg2)(some_function)
In [4]: decorated()
pre
some_function executed
post
I'm just starting to learn Python and I have the following problem.
Using a package with method "bind", the following code works:
def callback(data):
print data
channel.bind(callback)
but when I try to wrap this inside a class:
class myclass:
def callback(data):
print data
def register_callback:
channel.bind(self.callback)
the call_back method is never called. I tried both "self.callback" and just "callback". Any ideas?
It is not clear to me how your code works, as (1) you did not post the implementation of channel.bind, and (2) your second example is incorrect in the definition of register_callback (it is using a self argument that is not part of the list of parameters of the method, and it lacks parentheses).
Nevertheless, remember that methods usually require a "self" parameter, which is implicitly passed every time you run self.function(), as this is converted internally to a function call with self as its first parameter: function(self, ...). Since your callback has just one argument data, this is probably the problem.
You cannot declare a method bind that is able to accept either a function or a class method (the same problem happens with every OOP language I know: C++, Pascal...).
There are many ways to do this, but, again, without a self-contained example that can be compiled, it is difficult to give suggestions.
You need to pass the self object as well:
def register_callback(self):
channel.bind(self.callback)
What you're doing is entirely possible, but I'm not sure exactly what your issue is, because your sample code as posted is not even syntactically valid. (The second method has no argument list whatsoever.)
Regardless, you might find the following sample code helpful:
def send_data(callback):
callback('my_data')
def callback(data):
print 'Free function callback called with data:', data
# The follwing prints "Free function callback called with data: my_data"
send_data(callback)
class ClassWithCallback(object):
def callback(self, data):
print 'Object method callback called with data:', data
def apply_callback(self):
send_data(self.callback)
# The following prints "Object method callback called with data: my_data"
ClassWithCallback().apply_callback()
# Indeed, the following does the same
send_data(ClassWithCallback().callback)
In Python it is possible to use free functions (callback in the example above) or bound methods (self.callback in the example above) in more or less the same situations, at least for simple tasks like the one you've outlined.
I want to have a function in main class which has parameters not only self.
class Ui_Form(object):
def clearTextEdit(self, x):
self.plainTextEdit.setPlainText(" ")
print("Script in Textbox is Cleaned!",)
x will be my additional parameter and I want clearTextEdit to be called by click.
self.pushButton_3.clicked.connect(self.clearTextEdit(x))
it does not allow me to write x as parameter in clicked. Can you help me!
Solution
This is a perfect place to use a lambda:
self.pushButton_3.clicked.connect(lambda: self.clearTextEdit(x))
Remember, connect expects a function of no arguments, so we have to wrap up the function call in another function.
Explanation
Your original statement
self.pushButton_3.clicked.connect(self.clearTextEdit(x)) # Incorrect
was actually calling self.clearTextEdit(x) when you made the call to connect, and then you got an error because clearTextEdit doesn't return a function of no arguments, which is what connect wanted.
Lambda?
Instead, by passing lambda: self.clearTextEdit(x), we give connect a function of no arguments, which when called, will call self.clearTextEdit(x). The code above is equivalent to
def callback():
return self.clearTextEdit(x)
self.pushButton_3.clicked.connect(callback)
But with a lambda, we don't have to name "callback", we just pass it in directly.
If you want to know more about lambda functions, you can check out this question for more detail.
On an unrelated note, I notice that you don't use x anywhere in clearTextEdit. Is it necessary for clearTextEdit to take an argument in the first place?
I am using a block like this:
def served(fn) :
def wrapper(*args, **kwargs):
p = xmlrpclib.ServerProxy(SERVER, allow_none=True )
return (p.__getattr__(fn.__name__)(*args, **kwargs)) # do the function call
return functools.update_wrapper(wrapper,fn)
#served
def remote_function(a, b):
pass
to wrap a series of XML-RPC calls into a python module. The "served" decorator gets called on stub functions to expose operations on a remote server.
I'm creating stubs like this with the intention of being able to inspect them later for information about the function, specifically its arguments.
As listed, the code above does not transfer argument information from the original function to the wrapper. If I inspect with inspect.getargspec( remote_function ) then I get essentially an empty list, instead of args=['a','b'] that I was expecting.
I'm guessing I need to give additional direction to the functools.update_wrapper() call via the optional assigned parameter, but I'm not sure exactly what to add to that tuple to get the effect I want.
The name and the docstring are correctly transferred to the new function object, but can someone advise me on how to transfer argument definitions?
Thanks.
Previous questions here and here suggest that the decorator module can do this.