Curo Python

Curo Python is a powerful, open-source library for performing instalment credit financial calculations, from simple loans to complex leasing and hire purchase agreements. Built from the ground up in Python, it leverages pandas DataFrames for cash flow management and SciPy for efficient solving of unknown values or rates using Brent's method.

Explore the documentation, or try it in action with the Curo Calculator, a Flutter app showcasing similar functionality.

Why Curo Python?

Curo Python is designed for developers and financial professionals who need robust tools for fixed-term credit calculations. It goes beyond basic financial algebra, offering features typically found in commercial software, such as:

• Solving for unknown cash flow values (e.g., instalment amounts).
• Calculating implicit interest rates (e.g., IRR or APR).
• Support for multiple day count conventions, including EU and US regulatory standards.
• Flexible handling of cash flow series for loans, leases, and investment scenarios.

Check out the examples folder for practical use cases and accompanying cash flow diagrams that visualise inflows and outflows.

Getting Started

Installation

Install Curo Python using your preferred package manager:

With pip:

$ pip install --user curo

With uv:

$ uv add curo

Basic Usage

Curo Python makes financial calculations intuitive. Below are two examples demonstrating how to solve for an unknown cash flow value and an implicit interest rate.

Example 1: Solving for an Unknown Cash Flow Value

Calculate the monthly instalment for a $10,000 loan over 6 months at an 8.25% annual interest rate.

from curo import Calculator, Mode, SeriesAdvance, SeriesPayment, US30360

# Step 1: Create a calculator instance
calculator = Calculator()

# Step 2: Define cash flow series
calculator.add(
    SeriesAdvance(label="Loan", amount=10000.0)
)
calculator.add(
    SeriesPayment(
        number_of=6,
        label="Instalment",
        amount=None,  # Set to None for unknown value
        mode=Mode.ARREAR
    )
)

# Step 3: Solve for the instalment amount
result = calculator.solve_value(
    convention=US30360(),
    interest_rate=0.0825
)
print(f"Monthly instalment: ${result:.2f}")  # Output: $1707.00

Example 2: Solving for the Implicit Interest Rate

Find the internal rate of return (IRR) for a €10,000 loan repaid in 6 monthly instalments of €1,707.

from curo import Calculator, EU200848EC, Mode, SeriesAdvance, SeriesPayment, US30360

# Step 1: Create a calculator instance
calculator = Calculator()

# Step 2: Define cash flow series
calculator.add(
    SeriesAdvance(label="Loan", amount=10000.0)
)
calculator.add(
    SeriesPayment(
        number_of=6,
        label="Instalment",
        amount=1707.00,
        mode=Mode.ARREAR
    )
)

# Step 3: Calculate the IRR and APR
irr = calculator.solve_rate(convention=US30360())
apr = calculator.solve_rate(convention=EU200848EC())

print(f"IRR: {irr * 100:.6f}")  # Output: 8.250040%
print(f"APR: {apr * 100:.6f}")  # Output: 8.569257%

Key Features

Day Count Conventions

Day count conventions determine how time intervals between cash flows are measured. Curo Python supports a wide range of conventions to meet global financial standards:

For XIRR-style calculations (referencing the first drawdown date), pass use_xirr_method=True to the convention constructor. When used with Actual/365, this matches Microsoft Excel’s XIRR function.

Cash Flow Diagrams

Cash flow diagrams visually represent the timing and direction of financial transactions. For example, a €10,000 loan repaid in 6 monthly instalments would look like this:

• Down arrows: Money received (e.g., loan advance).
• Up arrows: Money paid (e.g., instalments).
• Time line: Represents the contract term, divided into compounding periods.

License

Copyright © 2026, Andrew Murphy. Released under the MIT License.

Learn More

• Examples: Dive into practical use cases in the examples folder.
• Documentation: Refer to the code documentation for detailed class and method descriptions.
• Issues & Contributions: Report bugs or contribute on GitHub.