I am trying to get correct function name while using 2 decorators.
1> profile - from memory_profiler import profile
2> custom timing decorator
def timing(f):
#wraps(f)
def wrapper(*args, **kwargs):
start = time()
result = f(*args, **kwargs)
end = time()
print 'Elapsed time: {} - {}'.format(wrapper.__name__, end - start)
return result
return wrapper
They are used in the following order as defined below
#timing
#profile
def my_function():
something.....
Problem is both functions work well individually but when used together I don't get correct name via the timing decorator. I always get wrapper instead of the actual function name.
How do I get the actual function name instead of getting "wrapper" as the function name?
Dealt with the same problem today. In my case, I have a few decorators that extend other decorators by composition, and also take input arguments themselves. I needed to log some contextual information about the function being decorated, so I was naturally inclined to use the func.__name__ attribute, and I was getting the "wrapper" string like you.
My solution might not be the most elegant one (by far) but it's legal and it worked 🤷
def log_context(logger):
def decorator(func):
def wrapper(*args, **kwargs):
logger.debug({
func.__name__: {
"args": args,
"kwargs": kwargs,
},
})
# Persist the name of the original function
# throughout the stack
wrapper.__name__ = func.__name__
return wrapper
return decorator
Then I can have something like this without a problem:
#log_context(logger)
#a_similar_decorator(logger)
def foo(x, y=None):
pass
foo(1, y=123)
This would output something like this:
{'foo': {'args': (1,), 'kwargs': {'y': 123}}}
Related
I have a really simple function, defined as
def test(x):
return x
I would like to wrap it with a decorator, that returns a function that expects another kwargs param.
#simple_dec
def test(x):
return x
Inside that decorator function, i would pop that param from the kwargs dict, and that just call test function with the params test would expect to get, without breaking it:
def simple_dec():
def simple_dec_logic(func, *args, **kwargs):
kwargs.pop("extra_param")
return func(*args, **kwargs)
return decorator.decorate(_func, simple_dec_logic)
My issue is - after wrapping it, if I call:
test(1, extra_param=2)
It fails on "test got unexpected param extra_param", although if the code would actually run, the decorator would handle this and call test func, without that param. If I get it correctly, the interpreter just fails it, before running the code and knowing it's defined with a decorator.
Is there any way to work around this? I would like the decorator to let me call the test function with more params, without defining them in the test function.
This works fine:
import functools
def decorator(func):
#functools.wraps(func)
def wrapper_decorator(*args, **kwargs):
kwargs.pop('extra_param')
value = func(*args, **kwargs)
return value
return wrapper_decorator
#decorator
def test(x):
return x
test(1, extra_param=2)
I'm trying to replace the marshal_with decorator from flask-restful with a decorator that does something before calling marshal_with. My approach is to try to implement a new decorator that wraps marshal_with.
My code looks like:
from flask.ext.restful import marshal_with as restful_marshal_with
def marshal_with(fields, envelope=None):
def wrapper(f):
print("Do something with fields and envelope")
#wraps(f)
def inner(*args, **kwargs):
restful_marshal_with(f(*args, **kwargs))
return inner
return wrapper
Unfortunately this seems to break things... no error messages but my API returns a null response when it shouldn't be. Any insights on what I'm doing wrong?
I don't know the specifics of marshal_with, but it's entirely possible to use multiple decorators on a single function. For instance:
def decorator_one(func):
def inner(*args, **kwargs):
print("I'm decorator one")
func(*args, **kwargs)
return inner
def decorator_two(text):
def wrapper(func):
def inner(*args, **kwargs):
print(text)
func(*args, **kwargs)
return inner
return wrapper
#decorator_one
#decorator_two("I'm decorator two")
def some_function(a, b):
print(a, b, a+b)
some_function(4, 7)
The output this gives is:
I'm decorator one
I'm decorator two
4 7 11
You can modify this little script by adding print statements after each inner function call to see the exact flow control between each decorator as well.
I was doing a couple things wrong here, first, failing to return the output of restful_marshal_with as jonrsharpe pointed out, secondly, failing to understand a decorator written as a class instead of a function, and how to properly pass values to it. The correct code ended up being:
def marshal_with(fields, envelope=None):
def wrapper(f):
print("Do something with fields and envelope")
#wraps(f)
def inner(*args, **kwargs):
rmw = restful_marshal_with(fields, envelope)
return rmw(f)(*args, **kwargs)
return inner
return wrapper
As you can see, in addition to not returning rmw(), I needed to properly initialize the request_marshal_with class before calling it. Finally, it is important to remember that decorators return functions, therefore the arguments of the original function should be passed to the return value of rmw(f), hence the statement return rmw(f)(*args, **kwargs). This is perhaps more apparent if you take a look at the flask_restful.marshal_with code here.
I'm trying to invoke a python function from robotframework keyword. The python function has been decorated to be invoked using run_keyword from Builtin library. This is because robot logs appear well structured if library functions are invoked via run_keyword function from built in library. rather than invoked directly. However this is resulting in an infinite loop. Is there a solution to gracefully accomplish the goal?
robotkeyword :
do something
#creates a user by calling a function from python based library
create user
python function
#wrap_with_run_keyword
def create_user():
pass
def wrap_with_run_keyword(func):
def func_wrapper(*args, **kwargs):
return run_keyword(func, *args, **kwargs)
return func_wrapper
I couldn't solve the problem using partial application.
However, I broker the recursive loop by setting and unsetting an attribute as give below.
def wrap_with_run_keyword(func):
def func_wrapper(*args, **kwargs):
if not hasattr(func, 'second'):
setattr(func, "second", True)
return run_keyword(func, *args, **kwargs)
else:
delattr(func, "second")
return func(*args, **kwargs)
return func_wrapper
I have however run into another problem. I defined create_user as follows
def create_user(properties):
#some code
pass
On Calling this function in the way below
create_user("name=abc")
I'm getting the following error : got an unexpected keyword argument 'name'
I did run in the same issue, but solved it, only wondering if i can detect the caller...if the call is done from robotframework or by python in case that the call is done by the rf it should do only the second call
#wraps(function)
def wrapper(self, *args, **kwargs):
if not hasattr(function, 'second'):
setattr(function, 'second', True)
ar= list(args)
for key, value in kwargs.items():
ar.append(value)
return BuiltIn().run_keyword('Mylib.' + function.__name__, ar)
else:
delattr(function, 'second')
return function(self,*args[0])
return wrapper
Take a look at the partial class from the functools module. I think this might help you.
Or take a look at how decorators work in python.
I currently have the following code which uses a python library:
f = Foo(original_method, parameters)
I would like to augment original_method, and have a decorator add a few lines of code. Let's call the new decorated method decorated_method. Finally I would like to have something like this:
f = Foo(decorated_method(original_method), parameters)
My questions are: is this possible? how would the decorator look like?
I must say that I can't extend original_method, since it is part of an external library.
Edit: original_method is not executed, is only passed to Foo as a parameter. decorated_method function should do some logging and gather some statistics of the number of calls.
Later edit: the code in examples below works fine. I had a few additional problems because original_method had a few attributes, so this is the final code:
def decorated_method(method):
def _reporter(*args, **kwargs):
addmetric('apicall', method.__name__)
return method(*args, **kwargs)
_reporter.original_method_attribute = method.original_method_attribute
return _reporter
You don't mention what you want decorated_method to do, but this is certainly possible:
def decorated_method(f):
def _wrapped(*args, **kwargs):
print "About to call f!"
ret = f(*args, **kwargs)
print "Just got finished with f, ret = %r" % (ret,)
return ret
return _wrapped
This is just standard decorator structure: A decorator is a function which accepts a function and returns a function.
Absolutely:
def decorated_method(fn):
def inner_method(*args, **kwargs):
print("before calling")
result = fn(*args, **kwargs)
print("after calling")
return result
return inner_method
Once you've got this working, you should look at signature-preserving decorators.
This is what i want to do:
#MyDecorator
def f():
pass
for d in f.decorators:
print d
This is not generally possible without the cooperation of the decorators. For example,
def my_decorator(f):
def wrapper(*args, **kwargs):
return f(*args, **kwargs)
wrapper.decorators = [wrapper]
if hasattr(f, 'decorators'):
wrapper.decorators.extend[f.decorators]
return wrapper
Essentially, all the decorator does is wrap the function as usual and then put a decorators attribute on the wrapper function. It then checks the wrapped function for a similar list and propagates it upwards.
This is pretty useless though
What I think you want is
def my_decorator(f):
def wrapper(args):
return f(args)
wrapper.decorated = f
return wrapper
This will allow you to do stuff like
#my_other_decorator # another decorator following the same pattern
#my_decorator
def foo(args):
print args
foo.decorated(args) # calls the function with the inner decorated function (my_decorator)
foo.decorated.decorated(args) # original function
You can actually abstract this pattern into a decorator
def reversable(decorator):
def wrapper(func):
ret = decorator(func) # manually apply the decorator
ret.decorated = func # save the original function
return ret
return wrapper
Now when you are writing your decorator:
#reversable
def my_decorator(f):
def wrapper(x):
return f(x + 1)
return wrapper
The #MyDecorator syntax is just shorthand for writing the following Python code:
def f():
pass
f = MyDecorator(f)
Written in this form, you can see that the decorators applied to the function are not kept track of in any way. You could make your decorators remember when they're applied (Aaron's answer has a couple good ideas on how to do this), but you'd have to wrap all third-party decorators with your own.