Monepy 0.2

Currency classes to work with monetary values

Monepy

A python package that implements currency classes to work with monetary values.

Install

From PyPI using pip:

pip install monepy

Behavior

The currency classes behave like a numeric type, with a formatted() method that returns the value in the currency format:

>>> from monepy import USD
>>> x = USD(10)
>>> x
<USD 10.00>
>>> x.formatted()
'$10.00'
>>> x == 1
False
>>> x == 10
True
>>> x > 10
False
>>> x < 10.1
True

The class constructor does not round the values recieved. If a value with more significant digits than the currency supports is provided, a ValueError will be raised.

Operators

Only supported operators are +, -, * and /.

The + and -

Operations with + and - can only be done with currencies of the same type and will return an object of the same currency:

>>> x = USD(10)
>>> y = USD(0.1)
>>> x + y
<USD 10.10>
>>> x - y
<USD 9.90>

The *

The * is only possible with a numeric value:

>>> x = USD(1.99)
>>> x * 1.23
<USD 2.44>

The /

The / operator is possible with both numeric and a currency of the same type:

>>> x = USD(10)
>>> x / 2
<USD 5.00>
>>> y = USD(3)
>>> x / y
3.3333333333333335

The %

The % is only supports numeric values

>>> x = USD(100)
>>> x / 15
<USD 6.66>
>>> x % 15
<USD 0.10>

Pandas integration

Currency classes can be used with the pandas library:

>>> import pandas as pd
>>> from monepy import EUR
>>> df = pd.DataFrame({
... "product": ["x", "y", "z"],
... "price": [10, 0.99, 25],
... "quantity": [8, 50, 200]
... })
>>> df
  product  price  quantity
0       x  10.00         8
1       y   0.99        50
2       z  25.00       200
>>> df["price"] = df["price"].map(EUR, na_action="ignore")
>>> df
  product  price  quantity
0       x  10,00         8
1       y   0,99        50
2       z  25,00       200
>>> df["subtotal"] = df["price"] * df["quantity"]
>>> df
  product  price  quantity  subtotal
0       x  10,00         8     80,00
1       y   0,99        50     49,50
2       z  25,00       200  5 000,00
>>> df[df["price"] >= 10]
  product  price  quantity  subtotal
0       x  10,00         8     80,00
2       z  25,00       200  5 000,00
>>> total = df["subtotal"].sum()
>>> print(f"The total is {total.formatted()}.")
The total is 5 129,50 €.