human
Solve the following python programming problem given the following code:
# First we write our timer function
import time
def timer(f):
    def inner(*args):
        t0 = time.time()
        output = f(*args)
        elapsed = time.time() - t0
        print("Time Elapsed", elapsed)
        return output
    return inner

# Now we prepare to use our timer function

import numpy as np # Import numpy

# User-defined functions
def allocate1(x, N):
    return [x]*N

def allocate2(x, N):
    ones = np.ones(N)
    return np.multiply(x, ones)

x = 1.0

# Time allocation with lists
my_alloc = timer(allocate1)
l1 = my_alloc(x, 10000000)

# Time allocation with numpy array
my_alloc2 = timer(allocate2)
l2 = my_alloc2(x, 10000000)
Given the above code, generate some markdown instructions for it.
assistant
#Here is the Python program you requested.

We can make this a little bit more explicit.  In the line k = make_statement('name: '), make_statement() has returned the inner function key and the inner function has been given the name k.  Now, when we call k() the inner function returns the desired tuple.
The reason this works is that in addition to the environment in which a user-defined function is running, that function has access to a second environment: the environment in which the function was defined.  Here, key has access to the environment of make_statement. In this sense the environment of make_statement is the parent of the environment of key.
This enables two things:

Names inside the inner functions (or the outer ones for that matter) do not interfere with names in the global scope. Inside the outer and inner functions, the "most lexically local" names are the ones that matter
An inner function can access the environment of its enclosing (outer) function

Closures
Since the inner functions can "capture" information from an outer function's environment, the inner function is sometimes called a closure.
Notice that s, once captured by the inner function, cannot now be changed: we have lost direct access to its manipulation. This process is called encapsulation, and is a cornerstone of object oriented programming.

Augmenting Functions
Since functions are first class, we might want to augment them to put out, for example, call information, time information, etc.
Example 1
In the following, timer() accepts a function f as it's argument and returns an inner function called inner.
inner accepts a variable argument list and wraps the function f with timers to time how long it takes f to execute.
Note that f is passed a variable argument list (try to recall what Python does with that).