Looking before you leap with processor-intensive function

A program can easily waste time by calling a processor-intensive function multiple times.

For example, take a function which looks like this: it returns an integer if the input value can produce one, else None:

def intensive_f(value): # int -> Optional[int]
   # complex, and time-consuming code
   if process_has_failed:
       return None
   return integer_output

And it could be used in the following way:

x = 5
if intensive_f(x) is not None:
    print(intensive_f(x) / 2)
else:
    print(x, "could not be processed")

print(x)

Whilst this will work, it has the problem of calling intensive_f, which doubles the length of time for the code to run. A better solution would be to get the return value of the function beforehand.

x = 5
result = intensive_f(x)
if result is not None:
    print(result / 2)
else:
    print(x, "could not be processed")

However, a clearer and possibly more pythonic way is to use exceptions, for example:

x = 5
try:
    print(intensive_f(x) / 2)
except TypeError: # The exception raised if None + 1 is attempted
    print(x, "could not be processed")

Here no temporary variable is needed. It may often be preferable to use a assert statement, and to catch the AssertionError instead.

Dictionary keys

A common example of where this may be found is accessing dictionary keys. For example compare:

bird_speeds = get_very_long_dictionary()

if "european swallow" in bird_speeds:
    speed = bird_speeds["european swallow"]
else:
    speed = input("What is the air-speed velocity of an unladen swallow?")

print(speed)

with:

bird_speeds = get_very_long_dictionary()

try:
    speed = bird_speeds["european swallow"]
except KeyError:
    speed = input("What is the air-speed velocity of an unladen swallow?")

print(speed)

The first example has to look through the dictionary twice, and as this is a long dictionary, it may take a long time to do so each time. The second only requires one search through the dictionary, and thus saves a lot of processor time.

An alternative to this is to use dict.get(key, default)**, however many circumstances may require more complex operations to be done in the case that the key is not present