Metadata-Version: 2.4
Name: varistar
Version: 0.1.13
Summary: varistar is a Python package helps users manage and interact with possible variable star's data.
Author-email: Juan José Sánchez <pip@jjsm.science>
License: MIT License
        
        Copyright (c) 2026 Juan José Sánchez Medina
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://docs.jjsm.science/varistar
Project-URL: Repository, https://github.com/jj-sm/varistar
Project-URL: Issues, https://github.com/jj-sm/varistar/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Astronomy
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.md
License-File: AUTHORS.md
Requires-Dist: numpy
Requires-Dist: astropy
Requires-Dist: scipy>=1.10.1
Requires-Dist: scikit-learn>=1.3.2
Requires-Dist: pandas>=2.0.3
Requires-Dist: polars>=1.8.2
Requires-Dist: seaborn>=0.13.2
Requires-Dist: matplotlib>=3.7.5
Requires-Dist: plotly>=6.6.0
Requires-Dist: hdbscan>=0.8.40
Requires-Dist: tqdm>=4.67.3
Requires-Dist: chime>=0.7.0
Dynamic: license-file

# varistar 🌟


[![PyPI - Version](https://img.shields.io/pypi/v/varistar?style=flat-round)](https://pypi.org/project/varistar/)
[![PyPI - License](https://img.shields.io/pypi/l/varistar?style=flat-round)](https://pypi.org/project/varistar/)
[![Python Versions](https://img.shields.io/pypi/pyversions/varistar.svg?style=flat-round)](https://pypi.org/project/varistar/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.22772940.svg)](https://doi.org/10.5281/zenodo.22772940)


**varistar** is a Python package designed to simplify the management and interaction with timeseries and lightcurve data 
coming from multiple sources.

---

## Features

* **Data Retrieval**: Automated utilities to fetch data from varistar databases.
* **Format Conversion**: Seamlessly convert varistar-specific data into `astropy` tables or `pandas` DataFrames.
* **Analysis Tools**: Functions for processing gravitational lensing light-curves.
* **Modern Workflow**: Full support for `uv`, `pip`, and type-hinting for high-performance research.

## Installation

Install the stable version from [PyPI](https://pypi.org/project/varistar/):

```bash
pip install varistar
```

Or, if you prefer using [uv](https://github.com/astral-sh/uv):

```bash
uv add varistar
```

## Documentation and Usage

All the docs can be found at [docs.jjsm.science/varistar](https://docs.jjsm.science/varistar)

## Development

This project is built using the latest Python standards. If you are using this as a template or contributing:

1.  **Clone the repo**:
    ```bash
    git clone https://github.com/jj-sm/varistar.git
    cd varistar
    ```
2.  **Sync the environment (using uv)**:
    ```bash
    uv sync
    ```
3.  **Run the test suite**:
    ```bash
    uv run pytest
    ```

### Releasing

Releases are cut with the `Makefile`, which runs lint + tests locally, bumps
the version, pushes, tags, waits for the PyPI publish workflow to succeed,
and only then creates the GitHub release:

```bash
make check              # ruff check + pytest (same gate as CI)
make lint                # ruff check only
make test                # pytest only
make format-check        # ruff format --check (advisory, not release-blocking)

make release VERSION=0.1.12
```

`make release` requires a clean working tree on `main`, up to date with
`origin/main`. It bumps the version in `pyproject.toml` and
`src/varistar/__init__.py`, commits (`chore: release vX.Y.Z`), pushes,
tags `vX.Y.Z`, pushes the tag (which triggers
[`.github/workflows/publish.yml`](.github/workflows/publish.yml) to test
and publish to PyPI), watches that workflow, and creates the GitHub
release only if it succeeds — a release is never created for a version
that failed to publish.

See [CHANGELOG.md](CHANGELOG.md) for release history.

## License

This project is licensed under the **MIT License**. See the [LICENSE.md](LICENSE.md) file for details.

## Contributing

1. Check out the [Contributing Guidelines](CONTRIBUTING.md).
2. Adhere to the [Code of Conduct](CODE_OF_CONDUCT.md).
3. Open a [Feature Request](https://github.com/jj-sm/varistar/issues) for new ideas.

## Citation

If you use **varistar** in your research or publications, please cite it using the metadata provided in the `CITATION.cff` file, or click the **"Cite this repository"** button in the GitHub sidebar.

---
*Maintained by [Juan José Sánchez Medina](mailto:pip@jjsm.science), BSc. Astronomy Student (Pontificia Universidad Católica de Chile)*
