A Python 3 script running on a Linux server needs to determine whether a newly-calculated metric is equal to an expected value. The developer tried:
if 0.1 + 0.2 == 0.3:
send_alert()
but discovered that the condition evaluates to False because of binary floating-point representation. Which standard-library function, added in Python 3.5, offers a reliable way to test whether two floating-point numbers are approximately equal within a user-defined tolerance?
Binary floating-point values such as 0.1 and 0.2 cannot be represented exactly, so their sum is slightly larger than 0.3. The math.isclose() function compares two floats using relative and/or absolute tolerances, so it correctly treats 0.1 + 0.2 as close enough to 0.3 for most practical purposes. The other answers are not valid: math.equal() and sys.float_compare() do not exist, and statistics.close() is not part of the statistics module.
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What does binary floating-point representation mean, and why does it cause issues in Python calculations?
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