Decorators
Decorators¶
%pylab inline
Populating the interactive namespace from numpy and matplotlib
We’ve seen Python functions and objects. Today, we’ll breifly cover decorators, which are functions that wrap functions, and come with sytactic sugar which lets you write things like
@time_wrapper
def my_function(x):
...
y = my_function(x)
> 1.1 seconds elapsed.
Again, we want to write a function that wraps another function. We can define this as
from time import monotonic
def time_wrapper(f):
def inner_wrapper(*args, **kwargs):
t0 = monotonic()
ret = f(*args, **kwargs)
t1 = monotonic()
print("{} sec. elapsed".format(t1 - t0))
return ret
return inner_wrapper
Here’s how we might use our wrapper:
def generate_random(n):
"""
return a random numpy vector
"""
return np.random.rand(n)
generate_random = time_wrapper(generate_random)
x = generate_random(100000)
len(x)
0.001354997992166318 sec. elapsed
100000
one problem with this is that we had to go through the trouble of wrapping the function. Instead, we can just write
@time_wrapper
def generate_random2(n):
"""
return a random numpy vector
"""
return np.random.rand(n)
generate_random2(100000)
0.0011515039950609207 sec. elapsed
array([0.33319928, 0.004895 , 0.76005218, ..., 0.17565576, 0.96067993,
0.09966051])
This is interpreted like what we did above, but is a bit easier to read.
Another problem we may encounter is that we now can’t access the docstring we wrote
help(generate_random2)
Help on function inner_wrapper in module __main__:
inner_wrapper(*args, **kwargs)
One way to solve this is to use the wraps decorator from the functools package.
from functools import wraps
def time_wrapper2(f):
@wraps(f)
def inner_wrapper(*args, **kwargs):
t0 = monotonic()
ret = f(*args, **kwargs)
t1 = monotonic()
print("{} sec. elapsed".format(t1 - t0))
return ret
return inner_wrapper
@time_wrapper2
def generate_random3(n):
"""
return a random numpy vector
"""
return np.random.rand(n)
generate_random3(100000)
0.001442632987163961 sec. elapsed
array([0.44753162, 0.09087641, 0.57884903, ..., 0.88053606, 0.67266288,
0.79162613])
now, we can access the metadata from generate_random3, such as the docstring
help(generate_random3)
Help on function generate_random3 in module __main__:
generate_random3(n)
return a random numpy vector
As you might guess, the @wraps decorator copies the class metadata from f to the inner_wrapper function.