burning-cost

One install. The full Burning Cost toolkit.

pip install burning-cost

That single command installs all 10 flagship libraries for insurance pricing with modern ML.

The problem this solves

The Burning Cost ecosystem has 10 libraries. They are designed to work together — causal inference to estimate treatment effects, conformal to put intervals on predictions, monitoring to track whether those predictions are still valid in production. But you should not have to remember which libraries to include in a requirements file when setting up a new pricing project or Colab notebook.

burning-cost is a meta-package: it has no code of its own. It is a single dependency that pulls in everything.

What you get

Usage

You do not import from burning_cost directly. Each library has its own namespace:

from insurance_causal import CausalPricingModel
from insurance_conformal import InsuranceConformalPredictor
from insurance_monitoring import MonitoringReport
from insurance_fairness import FairnessAudit

The meta-package just ensures they are all installed.

For new pricing projects

Add to your pyproject.toml:

[project]
dependencies = [
    "burning-cost",
]

Or for a requirements file:

burning-cost
catboost
polars

Resources

• Website: burning-cost.github.io
• Examples: github.com/burning-cost/burning-cost-examples
• 30-minute demo: Colab notebook

License

MIT