Python ZeroDivisionError (tested)

ZeroDivisionError is Python refusing to divide any number by zero, which is mathematically undefined. Unlike some languages that silently produce infinity or NaN, Python always raises — even for floats. The exact message changes depending on the operator and type involved, which is useful for telling at a glance which line failed. We reproduced every common variant on a live interpreter.

1. Eight reproduced variants

The message text differs by operator (/ vs // vs %) and by operand type (int vs float), but every plain-Python case is some form of ZeroDivisionError. decimal.Decimal is the one exception: it raises its own DivisionByZero, which is actually a subclass of both ZeroDivisionError and ArithmeticError, so except ZeroDivisionError: still catches it.

2. Why 0.0 / 0.0 raises instead of giving NaN

In IEEE 754 floating point (the standard C, JavaScript, and many other languages use directly), 0.0 / 0.0 produces NaN and 5.0 / 0.0 produces inf, with no exception. Python deliberately overrides this and raises ZeroDivisionError for both cases instead, on the reasoning that a silent NaN propagating through a calculation is a worse outcome than failing loudly at the exact division that caused it.

>>> 0.0 / 0.0
ZeroDivisionError: float division by zero
>>> 5.0 / 0.0
ZeroDivisionError: float division by zero

If you specifically want IEEE 754 behavior (producing inf/nan instead of raising), use math.inf directly or construct it explicitly — plain division will not give it to you.

3. // and % fail together because they're related

Floor division and modulo both raise with the same underlying message for ints, because divmod() computes them as one operation internally:

>>> 5 // 0
ZeroDivisionError: integer division or modulo by zero
>>> 5 % 0
ZeroDivisionError: integer modulo by zero
>>> divmod(5, 0)
ZeroDivisionError: integer division or modulo by zero

If your code checks "is the divisor zero" before / but a different code path reaches % or // unchecked (a common bug when refactoring from one operator to another), you'll still hit this.

4. The fix: check before dividing, don't catch after

The clearest fix is a guard before the division, especially when zero is an expected input (e.g. an empty dataset, a rate with zero total requests):

def safe_divide(a, b, default=0):
    if b == 0:
        return default
    return a / b

Use try/except ZeroDivisionError: instead when the divisor comes from a complex expression and checking it ahead of time would mean computing it twice:

try:
    rate = successes / total_requests
except ZeroDivisionError:
    rate = 0.0  # no requests yet, not a 0% rate

Catching ZeroDivisionError also transparently catches decimal.DivisionByZero, since it's a subclass — one except clause covers both int/float and Decimal math.

5. Common real causes

• Averages and rates over an empty collection. total / len(items) when items is empty. Check if items: first.
• Percentages computed before any data exists. A dashboard computing completed / total * 100 on day one, when total is still 0.
• User input used directly as a divisor without validation (a denominator field, a scale factor).
• Normalizing by a range that collapses to zero, e.g. (x - min_val) / (max_val - min_val) when every value in a dataset happens to be identical.

This is unrelated to ValueError: math domain error (raised by functions like math.sqrt(-1) or math.log(0) for a different reason: the input is out of the function's valid domain, not a division). Interestingly, math.fmod(5, 0) raises ValueError: math domain error rather than ZeroDivisionError, because math module functions generally report invalid-domain input that way regardless of whether division is involved. If the error instead comes from indexing past the end of a list, see IndexError: list index out of range.

Written with AI assistance. Measured on 2026-10-03 with Python 3.13.5 on Linux using plain python3 one-liners. Every error below is copy-pasted output, not paraphrased. PlainHeaders is our extension; Python is free.