Make division by zero equal to zero

How can I ignore ZeroDivisionError and make n / 0 == 0?

Check if the denominator is zero before dividing. This avoids the overhead of catching the exception, which may be more efficient if you expect to be dividing by zero a lot.

def weird_division(n, d):
    return n / d if d else 0

You can use a try/except block for this.

def foo(x,y):
    try:
        return x/y
    except ZeroDivisionError:
        return 0

>>> foo(5,0)
0

>>> foo(6,2)
3.0

I think try except (as in Cyber's answer) is usually the best way (and more pythonic: better to ask forgiveness than to ask permission!), but here's another:

def safe_div(x,y):
    if y == 0:
        return 0
    return x / y

One argument in favor of doing it this way, though, is if you expect ZeroDivisionErrors to happen often, checking for 0 denominator ahead of time will be a lot faster (this is python 3):

import time

def timing(func):
    def wrap(f):
        time1 = time.time()
        ret = func(f)
        time2 = time.time()
        print('%s function took %0.3f ms' % (f.__name__, int((time2-time1)*1000.0)))
        return ret
    return wrap

def safe_div(x,y):
    if y==0: return 0
    return x/y

def try_div(x,y):
    try: return x/y
    except ZeroDivisionError: return 0

@timing
def test_many_errors(f):
    print("Results for lots of caught errors:")
    for i in range(1000000):
        f(i,0)

@timing
def test_few_errors(f):
    print("Results for no caught errors:")
    for i in range(1000000):
        f(i,1)

test_many_errors(safe_div)
test_many_errors(try_div)
test_few_errors(safe_div)
test_few_errors(try_div)

Output:

Results for lots of caught errors:
safe_div function took 185.000 ms
Results for lots of caught errors:
try_div function took 727.000 ms
Results for no caught errors:
safe_div function took 223.000 ms
Results for no caught errors:
try_div function took 205.000 ms

So using try except turns out to be 3 to 4 times slower for lots of (or really, all) errors; that is: it is 3 to 4 times slower for iterations that an error is caught. The version using the if statement turns out to be slightly slower (10% or so) when there are few (or really, no) errors.

Solution

When you want to efficient handle ZeroDivisionError (division by zero) then you should not use exceptions or conditionals.

result = b and a / b or 0  # a / b

How it's works?

• When b != 0 we have True and a / b or 0. True and a / b is equal to a / b. a / b or 0 is equal to a / b.
• When b == 0 we have False and a / b or 0. False and a / b is equal to False. False or 0 is equal to 0.

Benchmark

Timer unit: 1e-06 s

Total time: 118.362 s
File: benchmark.py
Function: exception_div at line 3

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
     3                                           @profile
     4                                           def exception_div(a, b):
     5 100000000   23419098.5      0.2     19.8      try:
     6 100000000   40715642.9      0.4     34.4          return a / b
     7 100000000   28910860.8      0.3     24.4      except ZeroDivisionError:
     8 100000000   25316209.7      0.3     21.4          return 0

Total time: 23.638 s
File: benchmark.py
Function: conditional_div at line 10

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
    10                                           @profile
    11                                           def conditional_div(a, b):
    12 100000000   23638033.3      0.2    100.0      return a / b if b else 0

Total time: 23.2162 s
File: benchmark.py
Function: logic_div at line 14

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
    14                                           @profile
    15                                           def logic_div(a, b):
    16 100000000   23216226.0      0.2    100.0      return b and a / b or 0