Not many are aware of this feature, but Python's functions (and methods) can have attributes. Behold:
>>> def foo(x):
... pass
...
>>> foo.score = 10
>>> dir(foo)
['__call__', '__class__', '__delattr__', '__dict__', '__doc__', '__get__', '__getattribute__', '__hash__', '__init__', '__module__', '__name__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__str__', 'func_closure', 'func_code', 'func_defaults', 'func_dict', 'func_doc', 'func_globals', 'func_name', 'score']
>>> foo.score
10
>>> foo.score += 1
>>> foo.score
11
What are the possible uses and abuses of this feature in Python ? One good use I'm aware of is PLY's usage of the docstring to associate a syntax rule with a method. But what about custom attributes ? Are there good reasons to use them ?
This question is related to
python
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You can do objects the JavaScript way... It makes no sense but it works ;)
>>> def FakeObject():
... def test():
... print "foo"
... FakeObject.test = test
... return FakeObject
>>> x = FakeObject()
>>> x.test()
foo
I was always of the assumption that the only reason this was possible was so there was a logical place to put a doc-string or other such stuff. I know if I used it for any production code it'd confuse most who read it.
Sometimes I use an attribute of a function for caching already computed values. You can also have a generic decorator that generalizes this approach. Be aware of concurrency issues and side effects of such functions!
I was always of the assumption that the only reason this was possible was so there was a logical place to put a doc-string or other such stuff. I know if I used it for any production code it'd confuse most who read it.
Function attributes can be used to write light-weight closures that wrap code and associated data together:
#!/usr/bin/env python
SW_DELTA = 0
SW_MARK = 1
SW_BASE = 2
def stopwatch():
import time
def _sw( action = SW_DELTA ):
if action == SW_DELTA:
return time.time() - _sw._time
elif action == SW_MARK:
_sw._time = time.time()
return _sw._time
elif action == SW_BASE:
return _sw._time
else:
raise NotImplementedError
_sw._time = time.time() # time of creation
return _sw
# test code
sw=stopwatch()
sw2=stopwatch()
import os
os.system("sleep 1")
print sw() # defaults to "SW_DELTA"
sw( SW_MARK )
os.system("sleep 2")
print sw()
print sw2()
1.00934004784
2.00644397736
3.01593494415
Sometimes I use an attribute of a function for caching already computed values. You can also have a generic decorator that generalizes this approach. Be aware of concurrency issues and side effects of such functions!
I've created this helper decorator to easily set function attributes:
def with_attrs(**func_attrs):
"""Set attributes in the decorated function, at definition time.
Only accepts keyword arguments.
E.g.:
@with_attrs(counter=0, something='boing')
def count_it():
count_it.counter += 1
print count_it.counter
print count_it.something
# Out:
# >>> 0
# >>> 'boing'
"""
def attr_decorator(fn):
@wraps(fn)
def wrapper(*args, **kwargs):
return fn(*args, **kwargs)
for attr, value in func_attrs.iteritems():
setattr(wrapper, attr, value)
return wrapper
return attr_decorator
A use case is to create a collection of factories and query the data type they can create at a function meta level.
For example (very dumb one):
@with_attrs(datatype=list)
def factory1():
return [1, 2, 3]
@with_attrs(datatype=SomeClass)
def factory2():
return SomeClass()
factories = [factory1, factory2]
def create(datatype):
for f in factories:
if f.datatype == datatype:
return f()
return None
I use them sparingly, but they can be pretty convenient:
def log(msg):
log.logfile.write(msg)
Now I can use log throughout my module, and redirect output simply by setting log.logfile. There are lots and lots of other ways to accomplish that, but this one's lightweight and dirt simple. And while it smelled funny the first time I did it, I've come to believe that it smells better than having a global logfile variable.
Sometimes I use an attribute of a function for caching already computed values. You can also have a generic decorator that generalizes this approach. Be aware of concurrency issues and side effects of such functions!
You can do objects the JavaScript way... It makes no sense but it works ;)
>>> def FakeObject():
... def test():
... print "foo"
... FakeObject.test = test
... return FakeObject
>>> x = FakeObject()
>>> x.test()
foo
I've used them as static variables for a function. For example, given the following C code:
int fn(int i)
{
static f = 1;
f += i;
return f;
}
I can implement the function similarly in Python:
def fn(i):
fn.f += i
return fn.f
fn.f = 1
This would definitely fall into the "abuses" end of the spectrum.
You can do objects the JavaScript way... It makes no sense but it works ;)
>>> def FakeObject():
... def test():
... print "foo"
... FakeObject.test = test
... return FakeObject
>>> x = FakeObject()
>>> x.test()
foo
I've created this helper decorator to easily set function attributes:
def with_attrs(**func_attrs):
"""Set attributes in the decorated function, at definition time.
Only accepts keyword arguments.
E.g.:
@with_attrs(counter=0, something='boing')
def count_it():
count_it.counter += 1
print count_it.counter
print count_it.something
# Out:
# >>> 0
# >>> 'boing'
"""
def attr_decorator(fn):
@wraps(fn)
def wrapper(*args, **kwargs):
return fn(*args, **kwargs)
for attr, value in func_attrs.iteritems():
setattr(wrapper, attr, value)
return wrapper
return attr_decorator
A use case is to create a collection of factories and query the data type they can create at a function meta level.
For example (very dumb one):
@with_attrs(datatype=list)
def factory1():
return [1, 2, 3]
@with_attrs(datatype=SomeClass)
def factory2():
return SomeClass()
factories = [factory1, factory2]
def create(datatype):
for f in factories:
if f.datatype == datatype:
return f()
return None
I was always of the assumption that the only reason this was possible was so there was a logical place to put a doc-string or other such stuff. I know if I used it for any production code it'd confuse most who read it.
I've used them as static variables for a function. For example, given the following C code:
int fn(int i)
{
static f = 1;
f += i;
return f;
}
I can implement the function similarly in Python:
def fn(i):
fn.f += i
return fn.f
fn.f = 1
This would definitely fall into the "abuses" end of the spectrum.
You can do objects the JavaScript way... It makes no sense but it works ;)
>>> def FakeObject():
... def test():
... print "foo"
... FakeObject.test = test
... return FakeObject
>>> x = FakeObject()
>>> x.test()
foo
Function attributes can be used to write light-weight closures that wrap code and associated data together:
#!/usr/bin/env python
SW_DELTA = 0
SW_MARK = 1
SW_BASE = 2
def stopwatch():
import time
def _sw( action = SW_DELTA ):
if action == SW_DELTA:
return time.time() - _sw._time
elif action == SW_MARK:
_sw._time = time.time()
return _sw._time
elif action == SW_BASE:
return _sw._time
else:
raise NotImplementedError
_sw._time = time.time() # time of creation
return _sw
# test code
sw=stopwatch()
sw2=stopwatch()
import os
os.system("sleep 1")
print sw() # defaults to "SW_DELTA"
sw( SW_MARK )
os.system("sleep 2")
print sw()
print sw2()
1.00934004784
2.00644397736
3.01593494415
I've used them as static variables for a function. For example, given the following C code:
int fn(int i)
{
static f = 1;
f += i;
return f;
}
I can implement the function similarly in Python:
def fn(i):
fn.f += i
return fn.f
fn.f = 1
This would definitely fall into the "abuses" end of the spectrum.
Function attributes can be used to write light-weight closures that wrap code and associated data together:
#!/usr/bin/env python
SW_DELTA = 0
SW_MARK = 1
SW_BASE = 2
def stopwatch():
import time
def _sw( action = SW_DELTA ):
if action == SW_DELTA:
return time.time() - _sw._time
elif action == SW_MARK:
_sw._time = time.time()
return _sw._time
elif action == SW_BASE:
return _sw._time
else:
raise NotImplementedError
_sw._time = time.time() # time of creation
return _sw
# test code
sw=stopwatch()
sw2=stopwatch()
import os
os.system("sleep 1")
print sw() # defaults to "SW_DELTA"
sw( SW_MARK )
os.system("sleep 2")
print sw()
print sw2()
1.00934004784
2.00644397736
3.01593494415
I was always of the assumption that the only reason this was possible was so there was a logical place to put a doc-string or other such stuff. I know if I used it for any production code it'd confuse most who read it.
I use them sparingly, but they can be pretty convenient:
def log(msg):
log.logfile.write(msg)
Now I can use log throughout my module, and redirect output simply by setting log.logfile. There are lots and lots of other ways to accomplish that, but this one's lightweight and dirt simple. And while it smelled funny the first time I did it, I've come to believe that it smells better than having a global logfile variable.
Function attributes can be used to write light-weight closures that wrap code and associated data together:
#!/usr/bin/env python
SW_DELTA = 0
SW_MARK = 1
SW_BASE = 2
def stopwatch():
import time
def _sw( action = SW_DELTA ):
if action == SW_DELTA:
return time.time() - _sw._time
elif action == SW_MARK:
_sw._time = time.time()
return _sw._time
elif action == SW_BASE:
return _sw._time
else:
raise NotImplementedError
_sw._time = time.time() # time of creation
return _sw
# test code
sw=stopwatch()
sw2=stopwatch()
import os
os.system("sleep 1")
print sw() # defaults to "SW_DELTA"
sw( SW_MARK )
os.system("sleep 2")
print sw()
print sw2()
1.00934004784
2.00644397736
3.01593494415
I've used them as static variables for a function. For example, given the following C code:
int fn(int i)
{
static f = 1;
f += i;
return f;
}
I can implement the function similarly in Python:
def fn(i):
fn.f += i
return fn.f
fn.f = 1
This would definitely fall into the "abuses" end of the spectrum.
Sometimes I use an attribute of a function for caching already computed values. You can also have a generic decorator that generalizes this approach. Be aware of concurrency issues and side effects of such functions!
Source: Stackoverflow.com