In Python, the built‑in float type already stores numbers in 64‑bit double precision (IEEE 754). It can hold roughly 15 – 17 decimal digits without a separate double keyword as in C or Java.
When you need higher precision or exact values (finance, scientific work, ratios), Python provides additional tools.
Below are practical methods from the default float to higher‑precision options—each with short code examples.
Use Python’s Default float Type (Double Precision)
value = 3.141592653589793
print(type(value)) # <class ‘float’>
Python’s float type stores values using 64 bits (double precision).
You can confirm its precision with:
import sys
print(sys.float_info.dig) # Typically outputs: 15
Best for general‑purpose numeric operations where ~15‑digit precision is enough.
Advanced Precision Handling in Python
1. Use decimal for High‑Precision Decimal Math
Ideal for financial and scientific applications that require exact decimal results.
from decimal import Decimal, getcontextgetcontext().prec = 30 # Set precision to 30 digits
a = Decimal(“0.1”)
b = Decimal(“0.2”)
c = a + b
print(c) # 0.3 (exact)
Also Read: Python Developer Hourly Rate in 2025
2. Use fractions.Fraction for Exact Rational Values
Great for representing ratios, probabilities, or any computation where an exact fraction is preferred over a rounded decimal.
from fractions import Fractionf = Fraction(1, 3)
print(f) # 1/3
print(float(f)) # 0.3333333333333333
Tip
Python’s float is already double precision. Switch to decimal or fractions.Fraction only when you need exact or higher‑precision arithmetic beyond about 15–17 decimal digits.
