Mixing
how to do a conditional decorator in python
Is it possible to decorator a function conditionally. For example, I want to decorate the function foo() with a timer function (timeit) only doing_performance_analysis is True (see the psuedo-code below).
if doing_performance_analysis:
@timeit
def foo():
"""
do something, timeit function will return the time it takes
"""
time.sleep(2)
else:
def foo():
time.sleep(2)
python conditional decorator python-decorators
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
add a comment |
Is it possible to decorator a function conditionally. For example, I want to decorate the function foo() with a timer function (timeit) only doing_performance_analysis is True (see the psuedo-code below).
if doing_performance_analysis:
@timeit
def foo():
"""
do something, timeit function will return the time it takes
"""
time.sleep(2)
else:
def foo():
time.sleep(2)
python conditional decorator python-decorators
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
add a comment |
Is it possible to decorator a function conditionally. For example, I want to decorate the function foo() with a timer function (timeit) only doing_performance_analysis is True (see the psuedo-code below).
if doing_performance_analysis:
@timeit
def foo():
"""
do something, timeit function will return the time it takes
"""
time.sleep(2)
else:
def foo():
time.sleep(2)
python conditional decorator python-decorators
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
Is it possible to decorator a function conditionally. For example, I want to decorate the function foo() with a timer function (timeit) only doing_performance_analysis is True (see the psuedo-code below).
if doing_performance_analysis:
@timeit
def foo():
"""
do something, timeit function will return the time it takes
"""
time.sleep(2)
else:
def foo():
time.sleep(2)
python conditional decorator python-decorators
python conditional decorator python-decorators
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
edited Jan 2 at 10:04
Martijn Pieters♦
722k14125242333
722k14125242333
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
asked May 23 '12 at 17:20
cfpetecfpete
1,38341623
1,38341623
add a comment |
add a comment |
6 Answers
6
active
oldest
votes
Decorators are simply callables that return a replacement, optionally the same function, a wrapper, or something completely different. As such, you could create a conditional decorator:
def conditional_decorator(dec, condition):
def decorator(func):
if not condition:
# Return the function unchanged, not decorated.
return func
return dec(func)
return decorator
Now you can use it like this:
@conditional_decorator(timeit, doing_performance_analysis)
def foo():
time.sleep(2)
The decorator could also be a class:
class conditional_decorator(object):
def __init__(self, dec, condition):
self.decorator = dec
self.condition = condition
def __call__(self, func):
if not self.condition:
# Return the function unchanged, not decorated.
return func
return self.decorator(func)
Here the __call__ method plays the same role as the returned decorator() nested function in the first example, and the closed-over dec and condition parameters here are stored as arguments on the instance until the decorator is applied.
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
1
Thanks! The comment section does not format, so I added the sample code to your original reply. Can you pls explain why the timing function is not called?
– cfpete
May 23 '12 at 19:37
2
The decorator is applied at import time, so instance variables are not being consulted at that time. You'd have to write a different decorator for that, one that inspects self when called. Out of scope for this Q and comment format. :-)
– Martijn Pieters♦
May 23 '12 at 19:42
How would I use it if I want to use this on class based methods, ie Django Class based views. Over there we have to usemethod_decorator. How to make this code compatible with that?
– PythonEnthusiast
Aug 24 '16 at 8:13
@PythonEnthusiast: By just passing in the result of the call:@method_decorator(conditional_decorator(timeit, doing_performance_analysis)).
– Martijn Pieters♦
Aug 24 '16 at 10:53
add a comment |
A decorator is simply a function applied to another function. You can apply it manually:
def foo():
# whatever
time.sleep(2)
if doing_performance_analysis:
foo = timeit(foo)
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
add a comment |
How about:
def foo():
...
if doing_performance_analysis:
foo = timeit(foo)
I imagine you could even wrap this into a decorator that would take a boolean flag and another decorator, and would only apply the latter if the flag is set to True:
def cond_decorator(flag, dec):
def decorate(fn):
return dec(fn) if flag else fn
return decorate
@cond_decorator(doing_performance_analysis, timeit)
def foo():
...
answered May 23 '12 at 17:22
NPENPE
356k67759889
add a comment |
Blckknght's answer is great if you want to do the check every time you call the function, but if you have a setting that you can read once and never changes you may not want to check the setting every time the decorated function is called. In some of our high performance daemons at work I have written a decorator that checks a setting file once when the python file is first loaded and decides if it should wrap it or not.
Here is a sample
def timed(f):
def wrapper(*args, **kwargs):
start = datetime.datetime.utcnow()
return_value = f(*args, **kwargs)
end = datetime.datetime.utcnow()
duration = end - start
log_function_call(module=f.__module__, function=f.__name__, start=__start__, end=__end__, duration=duration.total_seconds())
if config.get('RUN_TIMED_FUNCTIONS'):
return wrapper
return f
Assuming that log_function_call logs your call to a database, logfile, or whatever and that config.get('RUN_TIMED_FUNCTIONS') checks your global configuration, then adding the @timed decorator to a function will check once on load to see if you are timing on this server, environment, etc. and if not then it won't change the execution of the function on production or the other environments where you care about performance.
answered Jan 16 '14 at 22:15
noblednobled
8527
add a comment |
use_decorator = False
class myDecorator(object):
def __init__(self, f):
self.f = f
def __call__(self):
print "Decorated running..."
print "Entering", self.f.__name__
self.f()
print "Exited", self.f.__name__
def null(a):
return a
if use_decorator == False :
myDecorator = null
@myDecorator
def CoreFunction():
print "Core Function running"
CoreFunction()
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
add a comment |
Here is what worked for me:
def timeit(method):
def timed(*args, **kw):
if 'usetimer' not in kw:
return method(*args, **kw)
elif ('usetimer' in kw and kw.get('usetimer') is None):
return method(*args, **kw)
else:
import time
ts = time.time()
result = method(*args, **kw)
te = time.time()
if 'log_time' in kw:
name = kw.get('log_name', method.__name__.upper())
kw['log_time'][name] = int((te - ts) * 1000)
else:
print '%r took %2.2f ms' %
(method.__name__, (te - ts) * 1000)
return result
return timed
def some_func(arg1, **kwargs):
#do something here
some_func(param1, **{'usetimer': args.usetimer})
answered Nov 21 '18 at 14:23
user336558user336558
1616
add a comment |
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6 Answers
6
active
oldest
votes
6 Answers
6
active
oldest
votes
active
oldest
votes
active
oldest
votes
Decorators are simply callables that return a replacement, optionally the same function, a wrapper, or something completely different. As such, you could create a conditional decorator:
def conditional_decorator(dec, condition):
def decorator(func):
if not condition:
# Return the function unchanged, not decorated.
return func
return dec(func)
return decorator
Now you can use it like this:
@conditional_decorator(timeit, doing_performance_analysis)
def foo():
time.sleep(2)
The decorator could also be a class:
class conditional_decorator(object):
def __init__(self, dec, condition):
self.decorator = dec
self.condition = condition
def __call__(self, func):
if not self.condition:
# Return the function unchanged, not decorated.
return func
return self.decorator(func)
Here the __call__ method plays the same role as the returned decorator() nested function in the first example, and the closed-over dec and condition parameters here are stored as arguments on the instance until the decorator is applied.
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
1
Thanks! The comment section does not format, so I added the sample code to your original reply. Can you pls explain why the timing function is not called?
– cfpete
May 23 '12 at 19:37
2
The decorator is applied at import time, so instance variables are not being consulted at that time. You'd have to write a different decorator for that, one that inspects self when called. Out of scope for this Q and comment format. :-)
– Martijn Pieters♦
May 23 '12 at 19:42
How would I use it if I want to use this on class based methods, ie Django Class based views. Over there we have to usemethod_decorator. How to make this code compatible with that?
– PythonEnthusiast
Aug 24 '16 at 8:13
@PythonEnthusiast: By just passing in the result of the call:@method_decorator(conditional_decorator(timeit, doing_performance_analysis)).
– Martijn Pieters♦
Aug 24 '16 at 10:53
add a comment |
Decorators are simply callables that return a replacement, optionally the same function, a wrapper, or something completely different. As such, you could create a conditional decorator:
def conditional_decorator(dec, condition):
def decorator(func):
if not condition:
# Return the function unchanged, not decorated.
return func
return dec(func)
return decorator
Now you can use it like this:
@conditional_decorator(timeit, doing_performance_analysis)
def foo():
time.sleep(2)
The decorator could also be a class:
class conditional_decorator(object):
def __init__(self, dec, condition):
self.decorator = dec
self.condition = condition
def __call__(self, func):
if not self.condition:
# Return the function unchanged, not decorated.
return func
return self.decorator(func)
Here the __call__ method plays the same role as the returned decorator() nested function in the first example, and the closed-over dec and condition parameters here are stored as arguments on the instance until the decorator is applied.
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
1
Thanks! The comment section does not format, so I added the sample code to your original reply. Can you pls explain why the timing function is not called?
– cfpete
May 23 '12 at 19:37
2
The decorator is applied at import time, so instance variables are not being consulted at that time. You'd have to write a different decorator for that, one that inspects self when called. Out of scope for this Q and comment format. :-)
– Martijn Pieters♦
May 23 '12 at 19:42
How would I use it if I want to use this on class based methods, ie Django Class based views. Over there we have to usemethod_decorator. How to make this code compatible with that?
– PythonEnthusiast
Aug 24 '16 at 8:13
@PythonEnthusiast: By just passing in the result of the call:@method_decorator(conditional_decorator(timeit, doing_performance_analysis)).
– Martijn Pieters♦
Aug 24 '16 at 10:53
add a comment |
Decorators are simply callables that return a replacement, optionally the same function, a wrapper, or something completely different. As such, you could create a conditional decorator:
def conditional_decorator(dec, condition):
def decorator(func):
if not condition:
# Return the function unchanged, not decorated.
return func
return dec(func)
return decorator
Now you can use it like this:
@conditional_decorator(timeit, doing_performance_analysis)
def foo():
time.sleep(2)
The decorator could also be a class:
class conditional_decorator(object):
def __init__(self, dec, condition):
self.decorator = dec
self.condition = condition
def __call__(self, func):
if not self.condition:
# Return the function unchanged, not decorated.
return func
return self.decorator(func)
Here the __call__ method plays the same role as the returned decorator() nested function in the first example, and the closed-over dec and condition parameters here are stored as arguments on the instance until the decorator is applied.
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
Decorators are simply callables that return a replacement, optionally the same function, a wrapper, or something completely different. As such, you could create a conditional decorator:
def conditional_decorator(dec, condition):
def decorator(func):
if not condition:
# Return the function unchanged, not decorated.
return func
return dec(func)
return decorator
Now you can use it like this:
@conditional_decorator(timeit, doing_performance_analysis)
def foo():
time.sleep(2)
The decorator could also be a class:
class conditional_decorator(object):
def __init__(self, dec, condition):
self.decorator = dec
self.condition = condition
def __call__(self, func):
if not self.condition:
# Return the function unchanged, not decorated.
return func
return self.decorator(func)
Here the __call__ method plays the same role as the returned decorator() nested function in the first example, and the closed-over dec and condition parameters here are stored as arguments on the instance until the decorator is applied.
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
edited Sep 27 '18 at 13:06
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
answered May 23 '12 at 17:24
Martijn Pieters♦Martijn Pieters
722k14125242333
722k14125242333
1
Thanks! The comment section does not format, so I added the sample code to your original reply. Can you pls explain why the timing function is not called?
– cfpete
May 23 '12 at 19:37
2
The decorator is applied at import time, so instance variables are not being consulted at that time. You'd have to write a different decorator for that, one that inspects self when called. Out of scope for this Q and comment format. :-)
– Martijn Pieters♦
May 23 '12 at 19:42
How would I use it if I want to use this on class based methods, ie Django Class based views. Over there we have to usemethod_decorator. How to make this code compatible with that?
– PythonEnthusiast
Aug 24 '16 at 8:13
@PythonEnthusiast: By just passing in the result of the call:@method_decorator(conditional_decorator(timeit, doing_performance_analysis)).
– Martijn Pieters♦
Aug 24 '16 at 10:53
add a comment |
1
Thanks! The comment section does not format, so I added the sample code to your original reply. Can you pls explain why the timing function is not called?
– cfpete
May 23 '12 at 19:37
2
The decorator is applied at import time, so instance variables are not being consulted at that time. You'd have to write a different decorator for that, one that inspects self when called. Out of scope for this Q and comment format. :-)
– Martijn Pieters♦
May 23 '12 at 19:42
How would I use it if I want to use this on class based methods, ie Django Class based views. Over there we have to usemethod_decorator. How to make this code compatible with that?
– PythonEnthusiast
Aug 24 '16 at 8:13
@PythonEnthusiast: By just passing in the result of the call:@method_decorator(conditional_decorator(timeit, doing_performance_analysis)).
– Martijn Pieters♦
Aug 24 '16 at 10:53
1
1
Thanks! The comment section does not format, so I added the sample code to your original reply. Can you pls explain why the timing function is not called?
– cfpete
May 23 '12 at 19:37
Thanks! The comment section does not format, so I added the sample code to your original reply. Can you pls explain why the timing function is not called?
– cfpete
May 23 '12 at 19:37
2
2
The decorator is applied at import time, so instance variables are not being consulted at that time. You'd have to write a different decorator for that, one that inspects self when called. Out of scope for this Q and comment format. :-)
– Martijn Pieters♦
May 23 '12 at 19:42
The decorator is applied at import time, so instance variables are not being consulted at that time. You'd have to write a different decorator for that, one that inspects self when called. Out of scope for this Q and comment format. :-)
– Martijn Pieters♦
May 23 '12 at 19:42
How would I use it if I want to use this on class based methods, ie Django Class based views. Over there we have to use
method_decorator. How to make this code compatible with that?– PythonEnthusiast
Aug 24 '16 at 8:13
How would I use it if I want to use this on class based methods, ie Django Class based views. Over there we have to use
method_decorator. How to make this code compatible with that?– PythonEnthusiast
Aug 24 '16 at 8:13
@PythonEnthusiast: By just passing in the result of the call:
@method_decorator(conditional_decorator(timeit, doing_performance_analysis)).– Martijn Pieters♦
Aug 24 '16 at 10:53
@PythonEnthusiast: By just passing in the result of the call:
@method_decorator(conditional_decorator(timeit, doing_performance_analysis)).– Martijn Pieters♦
Aug 24 '16 at 10:53
add a comment |
A decorator is simply a function applied to another function. You can apply it manually:
def foo():
# whatever
time.sleep(2)
if doing_performance_analysis:
foo = timeit(foo)
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
add a comment |
A decorator is simply a function applied to another function. You can apply it manually:
def foo():
# whatever
time.sleep(2)
if doing_performance_analysis:
foo = timeit(foo)
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
add a comment |
A decorator is simply a function applied to another function. You can apply it manually:
def foo():
# whatever
time.sleep(2)
if doing_performance_analysis:
foo = timeit(foo)
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
A decorator is simply a function applied to another function. You can apply it manually:
def foo():
# whatever
time.sleep(2)
if doing_performance_analysis:
foo = timeit(foo)
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
answered May 23 '12 at 17:23
BlckknghtBlckknght
64.4k557107
64.4k557107
add a comment |
add a comment |
How about:
def foo():
...
if doing_performance_analysis:
foo = timeit(foo)
I imagine you could even wrap this into a decorator that would take a boolean flag and another decorator, and would only apply the latter if the flag is set to True:
def cond_decorator(flag, dec):
def decorate(fn):
return dec(fn) if flag else fn
return decorate
@cond_decorator(doing_performance_analysis, timeit)
def foo():
...
answered May 23 '12 at 17:22
NPENPE
356k67759889
add a comment |
How about:
def foo():
...
if doing_performance_analysis:
foo = timeit(foo)
I imagine you could even wrap this into a decorator that would take a boolean flag and another decorator, and would only apply the latter if the flag is set to True:
def cond_decorator(flag, dec):
def decorate(fn):
return dec(fn) if flag else fn
return decorate
@cond_decorator(doing_performance_analysis, timeit)
def foo():
...
answered May 23 '12 at 17:22
NPENPE
356k67759889
add a comment |
How about:
def foo():
...
if doing_performance_analysis:
foo = timeit(foo)
I imagine you could even wrap this into a decorator that would take a boolean flag and another decorator, and would only apply the latter if the flag is set to True:
def cond_decorator(flag, dec):
def decorate(fn):
return dec(fn) if flag else fn
return decorate
@cond_decorator(doing_performance_analysis, timeit)
def foo():
...
answered May 23 '12 at 17:22
NPENPE
356k67759889
How about:
def foo():
...
if doing_performance_analysis:
foo = timeit(foo)
I imagine you could even wrap this into a decorator that would take a boolean flag and another decorator, and would only apply the latter if the flag is set to True:
def cond_decorator(flag, dec):
def decorate(fn):
return dec(fn) if flag else fn
return decorate
@cond_decorator(doing_performance_analysis, timeit)
def foo():
...
answered May 23 '12 at 17:22
NPENPE
356k67759889
edited May 23 '12 at 17:27
answered May 23 '12 at 17:22
NPENPE
356k67759889
answered May 23 '12 at 17:22
NPENPE
356k67759889
answered May 23 '12 at 17:22
NPENPE
356k67759889
356k67759889
add a comment |
add a comment |
Blckknght's answer is great if you want to do the check every time you call the function, but if you have a setting that you can read once and never changes you may not want to check the setting every time the decorated function is called. In some of our high performance daemons at work I have written a decorator that checks a setting file once when the python file is first loaded and decides if it should wrap it or not.
Here is a sample
def timed(f):
def wrapper(*args, **kwargs):
start = datetime.datetime.utcnow()
return_value = f(*args, **kwargs)
end = datetime.datetime.utcnow()
duration = end - start
log_function_call(module=f.__module__, function=f.__name__, start=__start__, end=__end__, duration=duration.total_seconds())
if config.get('RUN_TIMED_FUNCTIONS'):
return wrapper
return f
Assuming that log_function_call logs your call to a database, logfile, or whatever and that config.get('RUN_TIMED_FUNCTIONS') checks your global configuration, then adding the @timed decorator to a function will check once on load to see if you are timing on this server, environment, etc. and if not then it won't change the execution of the function on production or the other environments where you care about performance.
answered Jan 16 '14 at 22:15
noblednobled
8527
add a comment |
Blckknght's answer is great if you want to do the check every time you call the function, but if you have a setting that you can read once and never changes you may not want to check the setting every time the decorated function is called. In some of our high performance daemons at work I have written a decorator that checks a setting file once when the python file is first loaded and decides if it should wrap it or not.
Here is a sample
def timed(f):
def wrapper(*args, **kwargs):
start = datetime.datetime.utcnow()
return_value = f(*args, **kwargs)
end = datetime.datetime.utcnow()
duration = end - start
log_function_call(module=f.__module__, function=f.__name__, start=__start__, end=__end__, duration=duration.total_seconds())
if config.get('RUN_TIMED_FUNCTIONS'):
return wrapper
return f
Assuming that log_function_call logs your call to a database, logfile, or whatever and that config.get('RUN_TIMED_FUNCTIONS') checks your global configuration, then adding the @timed decorator to a function will check once on load to see if you are timing on this server, environment, etc. and if not then it won't change the execution of the function on production or the other environments where you care about performance.
answered Jan 16 '14 at 22:15
noblednobled
8527
add a comment |
Blckknght's answer is great if you want to do the check every time you call the function, but if you have a setting that you can read once and never changes you may not want to check the setting every time the decorated function is called. In some of our high performance daemons at work I have written a decorator that checks a setting file once when the python file is first loaded and decides if it should wrap it or not.
Here is a sample
def timed(f):
def wrapper(*args, **kwargs):
start = datetime.datetime.utcnow()
return_value = f(*args, **kwargs)
end = datetime.datetime.utcnow()
duration = end - start
log_function_call(module=f.__module__, function=f.__name__, start=__start__, end=__end__, duration=duration.total_seconds())
if config.get('RUN_TIMED_FUNCTIONS'):
return wrapper
return f
Assuming that log_function_call logs your call to a database, logfile, or whatever and that config.get('RUN_TIMED_FUNCTIONS') checks your global configuration, then adding the @timed decorator to a function will check once on load to see if you are timing on this server, environment, etc. and if not then it won't change the execution of the function on production or the other environments where you care about performance.
answered Jan 16 '14 at 22:15
noblednobled
8527
Blckknght's answer is great if you want to do the check every time you call the function, but if you have a setting that you can read once and never changes you may not want to check the setting every time the decorated function is called. In some of our high performance daemons at work I have written a decorator that checks a setting file once when the python file is first loaded and decides if it should wrap it or not.
Here is a sample
def timed(f):
def wrapper(*args, **kwargs):
start = datetime.datetime.utcnow()
return_value = f(*args, **kwargs)
end = datetime.datetime.utcnow()
duration = end - start
log_function_call(module=f.__module__, function=f.__name__, start=__start__, end=__end__, duration=duration.total_seconds())
if config.get('RUN_TIMED_FUNCTIONS'):
return wrapper
return f
Assuming that log_function_call logs your call to a database, logfile, or whatever and that config.get('RUN_TIMED_FUNCTIONS') checks your global configuration, then adding the @timed decorator to a function will check once on load to see if you are timing on this server, environment, etc. and if not then it won't change the execution of the function on production or the other environments where you care about performance.
answered Jan 16 '14 at 22:15
noblednobled
8527
answered Jan 16 '14 at 22:15
noblednobled
8527
answered Jan 16 '14 at 22:15
noblednobled
8527
answered Jan 16 '14 at 22:15
noblednobled
8527
8527
add a comment |
add a comment |
use_decorator = False
class myDecorator(object):
def __init__(self, f):
self.f = f
def __call__(self):
print "Decorated running..."
print "Entering", self.f.__name__
self.f()
print "Exited", self.f.__name__
def null(a):
return a
if use_decorator == False :
myDecorator = null
@myDecorator
def CoreFunction():
print "Core Function running"
CoreFunction()
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
add a comment |
use_decorator = False
class myDecorator(object):
def __init__(self, f):
self.f = f
def __call__(self):
print "Decorated running..."
print "Entering", self.f.__name__
self.f()
print "Exited", self.f.__name__
def null(a):
return a
if use_decorator == False :
myDecorator = null
@myDecorator
def CoreFunction():
print "Core Function running"
CoreFunction()
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
add a comment |
use_decorator = False
class myDecorator(object):
def __init__(self, f):
self.f = f
def __call__(self):
print "Decorated running..."
print "Entering", self.f.__name__
self.f()
print "Exited", self.f.__name__
def null(a):
return a
if use_decorator == False :
myDecorator = null
@myDecorator
def CoreFunction():
print "Core Function running"
CoreFunction()
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
use_decorator = False
class myDecorator(object):
def __init__(self, f):
self.f = f
def __call__(self):
print "Decorated running..."
print "Entering", self.f.__name__
self.f()
print "Exited", self.f.__name__
def null(a):
return a
if use_decorator == False :
myDecorator = null
@myDecorator
def CoreFunction():
print "Core Function running"
CoreFunction()
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
answered Sep 17 '16 at 0:10
Lawrence CherninLawrence Chernin
7329
7329
add a comment |
add a comment |
Here is what worked for me:
def timeit(method):
def timed(*args, **kw):
if 'usetimer' not in kw:
return method(*args, **kw)
elif ('usetimer' in kw and kw.get('usetimer') is None):
return method(*args, **kw)
else:
import time
ts = time.time()
result = method(*args, **kw)
te = time.time()
if 'log_time' in kw:
name = kw.get('log_name', method.__name__.upper())
kw['log_time'][name] = int((te - ts) * 1000)
else:
print '%r took %2.2f ms' %
(method.__name__, (te - ts) * 1000)
return result
return timed
def some_func(arg1, **kwargs):
#do something here
some_func(param1, **{'usetimer': args.usetimer})
answered Nov 21 '18 at 14:23
user336558user336558
1616
add a comment |
Here is what worked for me:
def timeit(method):
def timed(*args, **kw):
if 'usetimer' not in kw:
return method(*args, **kw)
elif ('usetimer' in kw and kw.get('usetimer') is None):
return method(*args, **kw)
else:
import time
ts = time.time()
result = method(*args, **kw)
te = time.time()
if 'log_time' in kw:
name = kw.get('log_name', method.__name__.upper())
kw['log_time'][name] = int((te - ts) * 1000)
else:
print '%r took %2.2f ms' %
(method.__name__, (te - ts) * 1000)
return result
return timed
def some_func(arg1, **kwargs):
#do something here
some_func(param1, **{'usetimer': args.usetimer})
answered Nov 21 '18 at 14:23
user336558user336558
1616
add a comment |
Here is what worked for me:
def timeit(method):
def timed(*args, **kw):
if 'usetimer' not in kw:
return method(*args, **kw)
elif ('usetimer' in kw and kw.get('usetimer') is None):
return method(*args, **kw)
else:
import time
ts = time.time()
result = method(*args, **kw)
te = time.time()
if 'log_time' in kw:
name = kw.get('log_name', method.__name__.upper())
kw['log_time'][name] = int((te - ts) * 1000)
else:
print '%r took %2.2f ms' %
(method.__name__, (te - ts) * 1000)
return result
return timed
def some_func(arg1, **kwargs):
#do something here
some_func(param1, **{'usetimer': args.usetimer})
answered Nov 21 '18 at 14:23
user336558user336558
1616
Here is what worked for me:
def timeit(method):
def timed(*args, **kw):
if 'usetimer' not in kw:
return method(*args, **kw)
elif ('usetimer' in kw and kw.get('usetimer') is None):
return method(*args, **kw)
else:
import time
ts = time.time()
result = method(*args, **kw)
te = time.time()
if 'log_time' in kw:
name = kw.get('log_name', method.__name__.upper())
kw['log_time'][name] = int((te - ts) * 1000)
else:
print '%r took %2.2f ms' %
(method.__name__, (te - ts) * 1000)
return result
return timed
def some_func(arg1, **kwargs):
#do something here
some_func(param1, **{'usetimer': args.usetimer})
answered Nov 21 '18 at 14:23
user336558user336558
1616
answered Nov 21 '18 at 14:23
user336558user336558
1616
answered Nov 21 '18 at 14:23
user336558user336558
1616
answered Nov 21 '18 at 14:23
user336558user336558
1616
1616
add a comment |
add a comment |
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