chainladder (python)

chainladder: Property and Casualty Loss Reserving in Python

Welcome! The chainladder package was built to be able to handle all of your actuarial needs in python. It consists of popular actuarial tools, such as triangle data manipulation, link ratios calculation, and IBNR estimates with both deterministic and stochastic models. We build this package so you no longer have to rely on outdated softwares and tools when performing actuarial pricing or reserving indications.

This package strives to be minimalistic in needing its own API. The syntax mimics popular packages pandas for data manipulation and scikit-learn for model construction. An actuary that is already familiar with these tools will be able to pick up this package with ease. You will be able to save your mental energy for actual actuarial work.

Chainladder is built by a group of volunteers, and we need *YOUR* help!

This package is written in Python, if you are looking for a similar package written in R, please visit chainladder.

Documentation Site

We have a documentation website, where you can find installation instructions, tutorials, example galleries, sample datasets, API references, change log history, and more.

Visit Chainladder-Python on Read the Docs.

Contributors Working Group

We also have a Contributors Working Group that meets for one hour approximately every two weeks. We are part of the CAS volunteer groups and are supported by the CAS. If you are interested, you are welcome to join us through the Open-Source Projects Working Group.

We currently meet on Fridays 11:00am - Noon ET, but we periodically adjust meeting times to accommodate contributors across time zones around the globe. Our meetings are relaxed and collaborative, with discussions around milestones, package design ideas, open issues, and other behind-the-scenes work on GitHub.

We welcome contributors of all skill levels, including CAS members, its affiliate members, industry researchers, educators, students, and CAS candidates. To join us, you may respond to the CAS annual Volunteer Interest and Participation (VIP) Survey, reach out to a CAS staff persons (Heather Davis <hdavis@casact.org>, Elizabeth Smith <esmith@casact.org>), or the working group chair (Kenneth Hsu <kennethshsu@gmail.com>), and we will be happy to welcome you into the group.

Licenses

This package is released under Mozilla Public License 2.0.

Metadata

Release files for chainladder 0.10.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for chainladder 0.10.1
File	Size	Uploaded
chainladder-0.10.1.tar.gz	2.2 MB	Sep 15, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for chainladder 0.10.1
File	Interpreter	ABI	Platform	Reset
chainladder-0.10.1-py3-none-any.whl 2.3 MB Sep 15, 2026	Python 3	none	any	Details

Total release size: 4.4 MB

Release files / chainladder-0.10.1.tar.gz

Download URL	chainladder-0.10.1.tar.gz
Size	2.2 MB
Tags	Source
SHA-256 checksum How to use checksums	`5346c942dcaa9cd4b5118c0fcb2db298de615eb066cde7a31f18b439c0e1fc15`
BLAKE2b-256 checksum How to use checksums	`4e812b38e9a4a8f12c20204f30fb4fa91fa00c0f41b80435863ba59e91e722db`
Upload date	Sep 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/casact/chainladder-python
Publishing commit: github.com/casact/chainladder-python/tree/bb44c1a977f82ff0f6fd83169b9cf2971bdaf8eb

Workflow

Publishing configuration: github.com/casact/chainladder-python/blob/bb44c1a977f82ff0f6fd83169b9cf2971bdaf8eb/.github/workflows/pythonpublish.yml
Publishing logs: github.com/casact/chainladder-python/actions/runs/35036266934/attempts/1

Artifact

Subject: chainladder-0.10.1.tar.gz
SHA-256 checksum: 5346c942dcaa9cd4b5118c0fcb2db298de615eb066cde7a31f18b439c0e1fc15 Verifying attestations

Release files / chainladder-0.10.1-py3-none-any.whl

Download URL	chainladder-0.10.1-py3-none-any.whl
Size	2.3 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`ca1181d80ef9df0668d0dec5d3d9442c03c07cba142d76a286cc3a9700922175`
BLAKE2b-256 checksum How to use checksums	`dbdfc0300f9229996e1f3ef8147c8239e0b72302a9e7ff3d21fd5c0a38d3c65c`
Upload date	Sep 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/casact/chainladder-python
Publishing commit: github.com/casact/chainladder-python/tree/bb44c1a977f82ff0f6fd83169b9cf2971bdaf8eb

Workflow

Publishing configuration: github.com/casact/chainladder-python/blob/bb44c1a977f82ff0f6fd83169b9cf2971bdaf8eb/.github/workflows/pythonpublish.yml
Publishing logs: github.com/casact/chainladder-python/actions/runs/35036266934/attempts/1

Artifact

Subject: chainladder-0.10.1-py3-none-any.whl
SHA-256 checksum: ca1181d80ef9df0668d0dec5d3d9442c03c07cba142d76a286cc3a9700922175 Verifying attestations