For decimal floating-point arithmetic python provides the decimal module. This module itself has hundreds of functions that help in the efficient processing of decimal calculations. We will look at the important and most widely used ones on this topic.
compare()
This function compares decimal numbers. Returns 1 if 1st Decimal argument is greater than 2nd, -1 if 1st Decimal argument is smaller than 2nd and 0 if both are equal.
Example
import decimal
val1 = decimal.Decimal(2.6)
val2 = decimal.Decimal(2.61)
# compare decimals
print("The result is : ",val1.compare(val2))
# resetting the values
val1 = decimal.Decimal(2.6)
val2 = decimal.Decimal(-2.6)
# compare decimals
print("The result is : ",val1.compare(val2))
# resetting the values
val1 = decimal.Decimal(2.6)
val2 = decimal.Decimal(2.6)
# compare decimals
print("The result is : ",val1.compare(val2))Output
Running the above code gives us the following result −
The result is : -1 The result is : 1 The result is : 0
max() and min()
They find the maximum and minimum of two decimal numbers respectively.
Example
import decimal
val1 = decimal.Decimal(2.6)
val2 = decimal.Decimal(2.61)
# compare decimals
print("The max value is : ",round(val1.max(val2),2))
print("The min value is : ",round(val1.min(val2),2))Output
Running the above code gives us the following result −
The max value is : 2.61 The min value is : 2.60
getcontext()
We can change the precision of arithmetic operations by using this method. The default precision is 28. In the below example we carry out an arithmetic operation which shows the result as per the precision set by getcontext().prec.
Example
from decimal import * print(Decimal(13) / Decimal(7)) getcontext().prec = 6 print(Decimal(13) / Decimal(7)) getcontext().prec = 10 print(Decimal(13) / Decimal(7))
Output
Running the above code gives us the following result −
1.857142857142857142857142857 1.85714 1.857142857
exp()
Return the value of the (natural) exponential function e**x at the given number.
Example
from decimal import * #Finding e print(Decimal(1).exp()) #Finding e raised to 2 print(Decimal(2).exp()) #Finding e raised to 4 print(Decimal(4).exp())
Output
Running the above code gives us the following result −
2.718281828459045235360287471 7.389056098930650227230427461 54.59815003314423907811026120
as_integer_ratio()
Sometimes we need the integers whose division gives us the decimal we are dealing with. This we can obtain by using the as_integer_ratio ().
Example
from decimal import *
v = Decimal('2.1834').as_integer_ratio()
print(v)
v = Decimal('-1.92').as_integer_ratio()
print(v)Output
Running the above code gives us the following result −
(10917, 5000) (-48, 25)
ln() and log10()
We can calculate the natural logarithm ( with a base as e) as well as the base 10 logarithm using these functions. We supply the decimal value whose logarithms are required.
Example
from decimal import *
ln_val = Decimal('2.1').ln()
print(ln_val)
log_val = Decimal('2.1').log10()
print(log_val)Output
Running the above code gives us the following result −
0.7419373447293773124826065257 0.3222192947339192680072441618
fma(a,b)
This is a special function that is called fused multiply and add. The supplied decimal gets multiplied with the first argument a and then the result gets added to the second argument b.
Example
from decimal import * # Same as (2.1*2)+5 fma_val = Decimal(2.1).fma(2,5) print(fma_val) # Same as (8.1*3)+5 fma_val = Decimal(8.1).fma(3,5) print(fma_val) re class="prettyprint notranslate" >
Output
Running the above code gives us the following result −
9.200000000000000177635683940 29.29999999999999893418589636