Browser-based GLM workbench for actuarial pricing
Project description
Atelier
Browser-based GLM workbench for actuarial pricing
Build, fit, diagnose, and iterate on Generalized Linear Models - without leaving your browser.
Why Atelier?
Traditional actuarial pricing tools like Emblem are expensive, opaque, and tied to legacy platforms. Atelier is a modern, open-source alternative that wraps rustystats - a high-performance Rust-backed GLM engine - in a clean, interactive UI. It runs locally, stores everything on your machine, and follows the same explore-build-fit-iterate workflow actuaries already know.
Installation
uv add atel
# or
pip install atel
Installs everything - backend, frontend, engine. No separate build steps.
Quick start
atel # starts server, opens browser
atel --port 9000 # custom port
atel --no-browser # start server only
The atelier command works too - atel is just shorter.
How it works
Workflow
Atelier follows the standard actuarial modelling workflow:
- Upload - drag-and-drop a CSV or Parquet file, column types are auto-detected
- Configure - select the response variable, GLM family, link function, offset, weights, and train/test split
- Explore - pre-fit analysis runs automatically: response distribution, score tests ranking every candidate factor by expected deviance contribution, and a null (intercept-only) baseline model
- Build - add terms from the factor sidebar: right-click any factor to choose categorical, linear, spline, target encoding, or other term types
- Fit - hit fit, review the results: coefficient table, A/E charts, lift, calibration, VIF, and model diagnostics
- Iterate - modify terms and re-fit. Every fit is auto-versioned so you can compare metrics across iterations and restore any previous version
Architecture
┌─────────────────────────────────────────────┐
│ Browser (React 19 + Tailwind + shadcn/ui) │
└──────────────────┬──────────────────────────┘
│ HTTP/JSON
┌──────────────────▼──────────────────────────┐
│ FastAPI backend │
│ ├── /api/datasets upload, validate │
│ ├── /api/explore EDA + null model │
│ ├── /api/fit GLM fitting │
│ ├── /api/models save, history, restore │
│ └── /api/projects project CRUD │
├──────────────────────────────────────────────┤
│ rustystats Rust GLM engine │
├──────────────────────────────────────────────┤
│ SQLite (async) projects, models, specs │
└──────────────────────────────────────────────┘
All data stays local at ~/.atelier/ - the database, uploaded datasets, and serialized models.
Features
Model building
- 8 GLM families - Gaussian, Poisson, Binomial, Gamma, Tweedie, Quasi-Poisson, Quasi-Binomial, Negative Binomial
- Rich term types - categorical, linear, B-splines, natural splines, target encoding, frequency encoding, expressions
- Monotonic constraints - enforce increasing/decreasing effects on splines and linear terms
- Interactions - standard product terms, target-encoded interactions, frequency-encoded interactions
- Regularization - Ridge, Lasso, Elastic Net with cross-validated alpha selection
- Train/test split - holdout validation with stratified splitting
Diagnostics
- Factor-level A/E - actual vs expected charts for every factor, fitted or not
- Score tests - chi-squared significance for candidate factors before fitting
- Lift charts - Gini, AUC, KS statistics with decile breakdown
- Calibration - Hosmer-Lemeshow test, decile calibration with confidence intervals
- Residual analysis - deviance, Pearson, and working residuals
- VIF & multicollinearity - variance inflation factors with severity coloring
- Model comparison - side-by-side train/test metrics against a base model
Data exploration
- Pre-fit analysis - response distribution, zero inflation, overdispersion detection
- Correlation matrix - numeric correlations and Cramer's V for categoricals
- Interaction detection - greedy residual-based search for potential interactions
Version control
- Auto-versioning - every fit is saved as a new version with full spec, coefficients, and diagnostics
- Change tracking - history panel shows terms added, removed, or modified between versions
- Restore - click any version to restore its terms and results, then continue iterating
License
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file atel-0.2.0.tar.gz.
File metadata
- Download URL: atel-0.2.0.tar.gz
- Upload date:
- Size: 38.7 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.18 {"installer":{"name":"uv","version":"0.9.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":null,"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c6f62a2cfb642082d9f6fab9dc6758cd22d86636881bf16255fd1b6e5e71c106
|
|
| MD5 |
6eb721eeb7705a5baa0b110f88da448d
|
|
| BLAKE2b-256 |
fbe86f305a908be0133becd0bca4d7ea1c8af7cfe6027c099c08736821951610
|
File details
Details for the file atel-0.2.0-py3-none-any.whl.
File metadata
- Download URL: atel-0.2.0-py3-none-any.whl
- Upload date:
- Size: 296.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.18 {"installer":{"name":"uv","version":"0.9.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":null,"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b2c39e5814217f5b413574dff01b86c85c4f8d664edd44c6db4f74e1695d163a
|
|
| MD5 |
1a615300e20a92915c74c7d88fae084d
|
|
| BLAKE2b-256 |
01f45121f385971ae81c4d142f1a48e073fb25cc251c7059195bcd0d5e26c760
|