Basic Python 31: Decimal | Python смотреть онлайн

Python Decimal:
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Python built-in class float performs some calculations that might amaze us. We all know that the sum of 1.1 and 2.2 is 3.3
ex:
(1.1 + 2.2) == 3.3

it is False

Why it is False?

It turns out that floating-point numbers are implemented in computer hardware as binary fractions as the computer only understands binary (0 and 1). Due to this reason, most of the decimal fractions we know, cannot be accurately stored in our computer.

Let's take an example. We cannot represent the fraction 1/3 as a decimal number. This will give 0.33333333... which is infinitely long, and we can only approximate it.

It turns out that the decimal fraction 0.1 will result in an infinitely long binary fraction of 0.000110011001100110011... and our computer only stores a finite number of it.

This will only approximate 0.1 but never be equal. Hence, it is the limitation of our computer hardware and not an error in Python.

ex:
1.1 + 2.2
3.3000000000000003

we can use the decimal module that comes with Python. While floating-point numbers have precision up to 15 decimal places, the decimal module has user-settable precision.
ex:
import decimal

print(0.1)

print(decimal.Decimal(0.1))

It also preserves significance. We know 25.50 kg is more accurate than 25.5 kg as it has two significant decimal places compared to one.
ex:
from decimal import Decimal as D

print(D('1.1') + D('2.2'))

print(D('1.2') * D('2.50'))

When to use Decimal instead of float?

- When we are making financial applications that need exact decimal representation.
- When we want to control the level of precision required.
- When we want to implement the notion of significant decimal places.

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