semvec/pypi-packages huggingface dataset:
gera2ld-pyserve 0.3.2
Start serving an asyncio.Server
License: MIT
Requires Python: <4.0,>=3.6

gera2ld.pyserve
===============

.. image:: https://img.shields.io/pypi/v/gera2ld-pyserve.svg

Serve asyncio and aiohttp servers, and show information for development.

Installation
------------

.. code-block:: sh

    $ pip install gera2ld-pyserve

    # or with extra `aio` if aiohttp applications are to be served
    $ pip install gera2ld-pyserve[aio]

Usage
-----

Run an asynchronous function in an infinite event loop:

.. code-block:: python

    from gera2ld.pyserve import run_forever

    async def main():
        # do stuff

    run_forever(main())

Start a server:

.. code-block:: python

    from gera2ld.pyserve import run_forever, start_server_asyncio

    def handle(reader, writer):
        # add more code here...

    run_forever(start_server_asyncio(handle, ':4000'))

Start a server with `aiohttp`:

.. code-block:: python

    from gera2ld.pyserve import run_forever, start_server_aiohttp
    from aiohttp import web

    app = web.Application()
    # add more code here...

    run_forever(start_server_aiohttp(app, ':4000'))
zensols-clinicamr 0.1.1
This package parses clinical notes in to Abstract Meaning Representation Graphs (AMR).
License: MIT
Requires Python: <3.13,>=3.11
Keywords: tooling

# Clincial Domain Abstract Meaning Representation Graphs

[![PyPI][pypi-badge]][pypi-link]
[![Python 3.11][python311-badge]][python311-link]
[![Python 3.12][python311-badge]][python312-link]
[![Build Status][build-badge]][build-link]

This package parses clinical notes in to Abstract Meaning Representation Graphs
(AMR).  It uses the following packages to create the graphs and features:

* THYME [AMR SPRING parser] to create the graphs
* [MedCAT] for entity linking `CUI` attribution nodes
* [MedSecId] for the clinical note sectioning
* [Zensols Natural Language Parsing] for language parsing and feature creation


## Documentation

See the [full documentation](https://plandes.github.io/clinicamr/index.html).
The [API reference](https://plandes.github.io/clinicamr/api.html) is also
available.


## Obtaining

The library can be installed with pip from the [pypi] repository:
```bash
pip3 install zensols.clinicamr
```


## Changelog

An extensive changelog is available [here](CHANGELOG.md).


## Citation

This package and the [amrspring Docker image] uses the original [AMR SPRING
parser] source code base from the paper *"One SPRING to Rule Them Both:
Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline"*:

```bibtex
@inproceedings{bevilacquaOneSPRINGRule2021,
  title = {One {{SPRING}} to {{Rule Them Both}}: {{Symmetric AMR Semantic Parsing}} and {{Generation}} without a {{Complex Pipeline}}},
  shorttitle = {One {{SPRING}} to {{Rule Them Both}}},
  booktitle = {Proceedings of the {{AAAI Conference}} on {{Artificial Intelligence}}},
  author = {Bevilacqua, Michele and Blloshmi, Rexhina and Navigli, Roberto},
  date = {2021-05-18},
  volume = {35},
  number = {14},
  pages = {12564--12573},
  location = {Virtual},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/17489},
  urldate = {2022-07-28}
}
```


## License

[MIT License](LICENSE.md)

Copyright (c) 2024 - 2025 Paul Landes


<!-- links -->
[pypi]: https://pypi.org/project/zensols.clinicamr/
[pypi-link]: https://pypi.python.org/pypi/zensols.clinicamr
[pypi-badge]: https://img.shields.io/pypi/v/zensols.clinicamr.svg
[python311-badge]: https://img.shields.io/badge/python-3.11-blue.svg
[python311-link]: https://www.python.org/downloads/release/python-3110
[python312-badge]: https://img.shields.io/badge/python-3.12-blue.svg
[python312-link]: https://www.python.org/downloads/release/python-3120
[build-badge]: https://github.com/plandes/datdesc/workflows/CI/badge.svg
[build-link]: https://github.com/plandes/datdesc/actions

[AMR SPRING parser]: https://github.com/SapienzaNLP/spring
[MedCAT]: https://github.com/CogStack/MedCAT
[MedSecId]: https://github.com/plandes/mimicsid
[Zensols Natural Language Parsing]: https://github.com/plandes/nlparse

[amrspring Docker image]: https://github.com/plandes/amrspring?tab=readme-ov-file#docker
extremal-packings 0.2.1
Análisis geométrico y espectral de configuraciones extremales de discos tangentes
License: MIT
Requires Python: >=3.8
Keywords: geometry, disk packing, rigid configurations, spectral analysis, contact graphs

# Extremal Packings - Análisis de Discos Tangentes

Paquete Python para análisis geométrico y espectral de configuraciones de discos unitarios tangentes en el plano.

## Características

- Catálogo de configuraciones predefinidas de 3 a 6 discos
- Calculo de Matriz de contacto, rolling space, gradiente proyectado, Hessiano intrínseco
- Visualización en plots
- API y utilidad CLI

## Instalación

### Desde PyPI
```bash
pip install extremal-packings
```

### Desde el repositorio
```bash
git clone https://github.com/fhenr/disk-packing-analysis.git
cd disk-packing-analysis
pip install -e .
```

## Uso Rápido

### Desde Python

```python
from extremal_packings import load_configuration, analyze_configuration

# Cargar configuración del catálogo
config = load_configuration("D5-7")  # Pentágono regular

# Análisis completo
result = analyze_configuration(config)

# Ver resultados
print(f"Rolling space dimension: {result.R.shape[1]}")
print(f"Eigenvalues: {result.eigenvalues}")
print(f"Perimeter: {result.perimeter_disks:.4f}")
```

### Desde CLI (Línea de Comandos)

```bash
# Listar configuraciones disponibles
epack list

# Analizar una configuración específica
epack analyze D5-7

# Comparar configuraciones de 5 discos
epack compare -s 5

# Ver información detallada
epack info D5-7

# Visualizar con gráficos
epack plot D5-7
```
## Docs

- **[Docs](docs/index.md)** - Guía completa de uso. Incluye fundamentos matemáticos.
- **[CLI](docs/cli.md)** - Guía de la interfaz de línea de comandos.
- **[Ejemplos Básicos](examples/basic_usage.py)**
- **[Ejemplos Avanzados](examples/advanced_usage.py)**

Ver [`examples/basic_usage.py`](examples/basic_usage.py) para casos de uso completos:

## Estructura del Proyecto

```
extremal_packings/        
├── __init__.py            # API pública
├── analysis.py            # Pipeline de análisis
├── catalog.py             # Catálogo de configuraciones
├── cli.py                 # Interfaz de línea de comandos
├── configurations.py      # Clase Configuration
├── constraints.py         # Matriz A y rolling space
├── contact_graphs.py      # Validación de grafos
├── hessian.py             # Hessiano K y H
├── interface.py           # Funciones de alto nivel
├── json_loader.py         # Carga desde JSON
├── perimeter.py           # Perímetros y convex hull
└── plotting.py            # Visualización
```

## Testing

```bash
pytest tests/
```

## Licencia

MIT License. [LICENSE](LICENSE).

## Autores

- **Fabián Andrés Henry Vilaxa**
- **Jose Ayala Hoffman**