Python decimal Module

In this guide, you'll explore Python's decimal module, which is used for precise decimal arithmetic. Learn its features and examples for accurate financial calculations.

The decimal module in Python provides support for fast and correctly rounded decimal floating point arithmetic. It offers several advantages over the float data type, including more precision and a configurable rounding mode.

Table of Contents

1. Introduction
2. Creating Decimal Objects
3. Arithmetic Operations
4. Methods and Functions
   • quantize
   • sqrt
   • exp
   • ln
   • log10
5. Decimal Context
   • Precision
   • Rounding
   • Context Functions
6. Examples
   • Basic Arithmetic
   • Working with Decimal Context
   • Rounding and Precision
7. Real-World Use Case
8. Conclusion
9. References

Introduction

The decimal module provides a Decimal data type for decimal floating point arithmetic. Compared to binary floating point (the float type), the Decimal type has more precision and can be configured to use different rounding modes.

Creating Decimal Objects

You can create Decimal objects from integers, strings, or tuples.

from decimal import Decimal

d1 = Decimal(10)
d2 = Decimal('3.14')
d3 = Decimal((0, (3, 1, 4), -2))

print(d1)  # 10
print(d2)  # 3.14
print(d3)  # 3.14

Output:

10
3.14
3.14

Arithmetic Operations

Decimal objects support all the usual arithmetic operations.

from decimal import Decimal

a = Decimal('1.1')
b = Decimal('2.2')

print(a + b)  # 3.3
print(a * b)  # 2.42
print(a / b)  # 0.5
print(a - b)  # -1.1

Output:

3.3
2.42
0.5
-1.1

Methods and Functions

quantize

The quantize method rounds a Decimal to a fixed exponent.

from decimal import Decimal

d = Decimal('1.2345')
q = Decimal('0.01')
print(d.quantize(q))  # 1.23

Output:

1.23

sqrt

The sqrt method returns the square root of a Decimal.

from decimal import Decimal

d = Decimal('16')
print(d.sqrt())  # 4

Output:

4

exp

The exp method returns the exponential of a Decimal.

from decimal import Decimal

d = Decimal('1')
print(d.exp())  # 2.718281828459045

Output:

2.718281828459045235360287471

ln

The ln method returns the natural logarithm of a Decimal.

from decimal import Decimal

d = Decimal('10')
print(d.ln())  # 2.302585092994046

Output:

2.302585092994045684017991455

log10

The log10 method returns the base-10 logarithm of a Decimal.

from decimal import Decimal

d = Decimal('100')
print(d.log10())  # 2

Output:

2

Decimal Context

A Decimal context controls precision, rounding, and other settings. You can use the getcontext function to access and modify the current context.

Precision

You can set the precision for Decimal arithmetic.

from decimal import Decimal, getcontext

getcontext().prec = 5
d = Decimal('1.123456')
print(d)  # 1.1235

Output:

1.123456

Rounding

You can set the rounding mode for Decimal arithmetic.

from decimal import Decimal, getcontext, ROUND_DOWN

getcontext().rounding = ROUND_DOWN
d = Decimal('1.2345')
print(d.quantize(Decimal('0.01')))  # 1.23

Output:

1.23

Context Functions

You can use the context for various operations.

from decimal import Decimal, getcontext

context = getcontext()
d = Decimal('123.456')
print(context.sqrt(d))  # 11.111

Output:

11.11107555549866648462149404

Examples

Basic Arithmetic

Perform basic arithmetic operations with Decimal objects.

from decimal import Decimal

a = Decimal('2.5')
b = Decimal('3.5')

print(a + b)  # 6.0
print(a - b)  # -1.0
print(a * b)  # 8.75
print(a / b)  # 0.7142857142857142857142857143

Output:

6.0
-1.0
8.75
0.7142857142857142857142857143

Working with Decimal Context

Set precision and rounding mode using the Decimal context.

from decimal import Decimal, getcontext, ROUND_HALF_UP

getcontext().prec = 4
getcontext().rounding = ROUND_HALF_UP

d = Decimal('1.23456')
print(d)  # 1.235

Output:

1.23456

Rounding and Precision

Demonstrate different rounding modes and precision settings.

from decimal import Decimal, getcontext, ROUND_UP, ROUND_DOWN

d = Decimal('1.23456')

# ROUND_UP
getcontext().rounding = ROUND_UP
print(d.quantize(Decimal('0.01')))  # 1.24

# ROUND_DOWN
getcontext().rounding = ROUND_DOWN
print(d.quantize(Decimal('0.01')))  # 1.23

Output:

1.24
1.23

Real-World Use Case

Financial Calculations

In financial applications, precise decimal arithmetic is crucial to avoid rounding errors that can occur with binary floating-point arithmetic.

from decimal import Decimal

price = Decimal('19.99')
quantity = Decimal('3')
total = price * quantity

print(total)  # 59.97

Output:

59.97

Conclusion

The decimal module in Python provides used for performing precise decimal arithmetic. It offers more control over precision and rounding compared to binary floating-point arithmetic, making it particularly useful for financial and scientific applications.

References

• Python decimal module documentation