Double Precision Floating Values in Python

Python’s built-in float type actually uses double-precision floating point representation under the hood, adhering to the IEEE 754 standard. This means you typically get about 15–17 decimal digits of precision, which is sufficient for most scientific and financial calculations.

Example:
x = 0.12345678901234567
print(x)

Output:
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0.12345678901234566

You’ll notice the printed output may slightly differ due to how floating point numbers are stored in memory, but Python is using double precision internally.

Alternatives for Higher Precision

If you need greater precision than what double-precision float offers (e.g., for financial calculations or scientific simulations), Python provides the following options:

1. Using decimal.Decimal

The decimal module supports arbitrary precision and is ideal when you need exact decimal representation (e.g., currency):

from decimal import Decimal, getcontext
getcontext().prec = 30  # Set desired precision
x = Decimal('0.123456789012345678901234567890')
print(x)

Output:
0.123456789012345678901234567890

2. Using fractions.Fraction

If you need exact values for rational numbers, the fractions module may help:

from fractions import Fraction
x = Fraction(1, 3)
print(x)

Output:
1/3

This retains mathematical accuracy without floating-point rounding errors.

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