How can I truncate a float value in Python without rounding the result?

How to truncate float values without rounding?

To remove digits from a float and have a fixed number of digits after the decimal point, such as converting 1.923328437452 to 1.923, you can use the following function:

def truncate(f, n):
    '''Truncates/pads a float f to n decimal places without rounding'''
    s = '{}'.format(f)
    if 'e' in s or 'E' in s:
        return '{0:.{1}f}'.format(f, n)
    i, p, d = s.partition('.')
    return '.'.join([i, (d+'0'*n)[:n]])

This function achieves truncation by converting the float to a string, splitting it into integer, decimal point, and decimal digit components, and then recombining them with the desired number of decimal digits. If the float is too large or small to be represented without exponential notation, it is first converted to that format.

Note: This function is compatible with Python 2.7 and 3.1 . For earlier versions, a slightly less precise workaround involving rounding to 12 decimal places before truncation can be used.

Understanding the Method

To understand the method behind the truncation function, it is important to recognize that floating-point numbers are stored in the computer's memory as a binary representation, which may not always match the exact decimal representation intended. For example, both 0.3 and 0.29999999999999998 are stored using the same binary representation.

To resolve this ambiguity, the function employs sophisticated algorithms to choose the "nicest" decimal representation for truncation. This is achieved by converting the float to a string using the default string formatting operation, which mimics "g" format specifications and automatically chooses the best representation.

However, there are certain edge cases where even this method can result in "false positives," where numbers that should not be rounded are. In these cases, specifying a fixed precision before truncation can be necessary.

Additional Notes

Truncating a float without rounding is essential when dealing with very specific floating-point values that are intentionally close to round numbers but are not equal to them. For most practical applications, rounding is typically sufficient.

The function presented here also ignores lost digits during truncation, which differs from rounding, which adjusts the remaining digits. This approach ensures that the truncated value retains its original precision at the specified decimal places.

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