Metadata-Version: 2.4
Name: statsim
Version: 0.1.0
Summary: StatSim — probabilistic programming and statistical computing
Project-URL: Documentation, https://statsim.com/docs
Project-URL: Source, https://github.com/statsim/statsim-py
Author: Anton Zemlyansky
License-Expression: MIT
License-File: LICENSE
Keywords: bayesian,probabilistic-programming,pymc,stan,statistics
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.9
Requires-Dist: statsim-compiler>=0.1.0
Provides-Extra: all
Requires-Dist: cmdstanpy>=1.0.0; extra == 'all'
Requires-Dist: pymc>=5.0.0; extra == 'all'
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == 'dev'
Provides-Extra: pymc
Requires-Dist: pymc>=5.0.0; extra == 'pymc'
Provides-Extra: stan
Requires-Dist: cmdstanpy>=1.0.0; extra == 'stan'
Description-Content-Type: text/markdown

# statsim

StatSim — probabilistic programming and statistical computing for Python.

## Install

```bash
# Basic installation
pip install statsim

# With PyMC backend
pip install statsim[pymc]

# With Stan backend
pip install statsim[stan]

# With all backends
pip install statsim[all]
```

## Usage

```python
from statsim import compile, run

# Compile .sm model
model = compile('''
  mu ~ Normal(0, 10)
  sigma ~ HalfNormal(5)
  y ~ Normal(mu, sigma)
''', target='pymc')

# Run inference
result = run(model, backend='pymc')
```

## Backends

- **PyMC**: Full Bayesian inference with MCMC and variational methods
- **Stan**: High-performance HMC/NUTS sampling

## Learn more

- [Documentation](https://statsim.com/docs)
- [Examples](https://statsim.com/examples)
- [GitHub](https://github.com/statsim)
