semvec/pypi-packages huggingface dataset:
hierarchical-review-plots 0.1.6
Module of hierarchical review plots
Requires Python: >=3.9

<a href="https://www.nies.futbol/"><img
src="https://raw.githubusercontent.com/niesfutbol/hierarchical_review_plots/develop/static/logo_nies.png" align="right" width="256"
/></a>

# Module of hierarchical review plots

## Step to use
### Local app
``` sh
docker-compose up -d app
```
Open http://localhost:8101/
### Develop Environment
``` sh
docker-compose run nies
```
proximityqol 1.0
library code execute various proximity analyses using ArcPy for qol proximity analyses


# Note
This package requires 'arcpy' which is part of Esri's ArcGIS software and 
cannot be installed via pip. Please ensure you have ArcGIS installed and 
configured correctly. You can get arcpy if you install ArcGIS Pro

# Proximity Analysis with ArcPy for Urban Institute's Quality of Life Explorer

This package provides a Python class `proximity` tailored for analyzing spatial relationships in GIS, specifically designed for Urban Institute's Quality of Life explorer (QOL) spatial variables.

## Installation

Install `qolproximity` from PyPI using pip:

pip install qolproximity

## Usage

import qolproximity as qol

# Example usage for proximity to Pharmacy:
P = qol.proximity('TaxData2023', 'Pharmacy2024')

# Merge pharmacy data 
P.merge('Pharmacy', 'PharmacyUnmatched')

# Add a new field for residential proximity to pharmacy
P.addfield('ResNearPharmacy')

# Summarize the results
P.summarize('r', 'd', ProjectGDB)

# Export summarized results to a text file
P.exportcsv(path, 'QOL_46_2023.csv')

## Methods

__init__(self, tax_parcel_feature_class, proximity_feature_class): Initialize the proximity class with the tax parcel feature class and proximity feature class.

merge(self, *feature_classes_to_be_merged): Merge proximity feature classes from multiple sources into one feature class for analysis.

addfield(self, new_field_name): Add a new field to the tax parcel feature class.

summarize(self, near_residential_output_table, housing_units_table, geodatabase): Summarize residential units near the proximity feature class and export results to a geodatabase.

exporttxt(self, output_directory, final_txt_name): Export summarized results to a text file in the specified directory.

## License

This project is licensed under the MIT License - see the LICENSE file for details.
echostream-function-context 0.1.0
Micro library for typing function contexts in EchoStream functions
Requires Python: >=3.12

# echostream-function-context

Micro library for typing function contexts in EchoStream functions

> Note: Version >= 0.1.0 requires Python 3.12
 
## Installation

### For production
```shell
pip install echostream-function-context
```

Production install has no requirements.

### For development
```shell
pip install echostream-function-context[dev]
```

Development install will also install `boto3-stubs[dynamodb]`.

## Usage
```python
def processor(*, context, message, source, **kwargs):

    from typing import TYPE_CHECKING, cast

    if TYPE_CHECKING:
        from echostream_function_context import Context
    else:
        Context = object

    context = cast(Context, context)
```
pynovnc 1.1.8
Python Package made by Mhadhbi Issam .

# pynovnc

<a href="https://colab.research.google.com/drive/1SMHc4PmG9AjnotQD6R5KQQfL7dNvvyE0" style="background-color: #007bff; color: white; padding: 10px 20px; border-radius: 5px; text-decoration: none; display: inline-block;width:100%;text-align:center;font-weight:900;font-size:30">Colab</a>

## Install Requiements  : 
```bash 
apt install -y --fix-missing xserver-xephyr  x11vnc xvfb novnc  net-tools x11-apps x11-xkb-utils gedit tightvncserver x11-utils gnumeric
```

## Installation : 
```bash
pip install pynovnc 
```

## Quick start : 
```python
from pynovnc import VirtualDisplay
with  VirtualDisplay(h = 1040 , w = 1920 ) as x :
    app = x.run(["gedit"])
    port = x.vncport
    app.wait()
```
checkpadis 0.3
Viabilidad 01

# Prototipo Funcional

Este prototipo tiene como objetivo principal probar distintas funcionalidades relacionadas con la creaciÃ³n y ejecuciÃ³n de comandos de entrada, llamadas HTTP, y la interacciÃ³n con repositorios de GitHub. A continuaciÃ³n, se detallan los objetivos especÃ­ficos y los pasos a seguir para cada uno de ellos.

## Objetivos

1. **Probar las entradas y que me devuelva una salida con consola y con color de manera local.**
2. **Probar llamadas HTTP y que salga por consola un resultado.**
3. **Ejecutar un comando que vaya a buscar a un repo de GitHub otro archivo Python donde haya una funciÃ³n a ejecutar (un ping, que devuelva pong).**
4. **Subir una librerÃ­a en Python.**
5. **Bajar una librerÃ­a en Codespaces y ejecutar las pruebas anteriores.**

## Funciones Utilizadas

### Base64

#### `base64.b64decode(s)`

- **DescripciÃ³n**: Decodifica una cadena codificada en base64.
- **Uso en el Prototipo**: Decodifica el contenido del archivo descargado desde GitHub antes de guardarlo localmente.
- **Ejemplo**:

  ```python
  import base64

  encoded_string = 'ZGVmIHBpbmcoKToKICAgIHJldHVybiAicG9uZyIK'
  decoded_bytes = base64.b64decode(encoded_string)
  decoded_string = decoded_bytes.decode('utf-8')
  print(decoded_string)
  ```

## tempfile

### `tempfile.TemporaryDirectory()`

- **DescripciÃ³n**: Crea un directorio temporal que se puede usar para almacenar archivos de manera temporal durante la ejecuciÃ³n del script. El directorio y su contenido se eliminan automÃ¡ticamente cuando se sale del bloque `with`.
- **Uso en el Prototipo**: Se utiliza para crear un espacio temporal seguro donde se pueden descargar o crear archivos necesarios durante la ejecuciÃ³n del script. Esto asegura que los archivos temporales no queden en el sistema despuÃ©s de su uso.

#### Ejemplo de Uso

```python
import tempfile

# Crear un directorio temporal
with tempfile.TemporaryDirectory() as temp_dir:
    print(f"Directorio temporal creado: {temp_dir}")
    # Puedes realizar operaciones con el directorio temporal aquÃ­

# El directorio y su contenido se eliminan automÃ¡ticamente al salir del bloque
```

# Observaciones

- **DescripciÃ³n**: Se pudo realizar la prueba existosamente, en todas las fases. Queda como criterio la seguridad como punto a definir en caso de los template de la solucion. Se baja el archivo y ese archivo deberia estar encodeado con alguna libreria de hasheo. Punto a destactar es la autorizacion con el PAT. Tener algun instructivo de como generado y advertencias de riesgo.
python-selve 1.4.1
Python library for interfacing with selve devices using the USB-RF controller
Keywords: selve blind awning shutter usb rf

Python control of selve devices through USB-RF Gateway
======================================================

|PyPI version|

A simple Python API for controlling RF Blinds / shutters / awning from selve using a USB-RF Gateway.
At present, only Iveo devices are supported.

The complete protocol specification can be found at `selve <https://www.selve.de/de/service/software-updates/service-entwicklungstool-commeo-usb-rf-gateway/>`_

Example of use
--------------

Create a new instance of the gateway:

.. code-block:: python

    gat = Gateway(portname)


portname is the name of the serial port where the usb rf gateway is listed on the os. Please refer to the serial library documentation.

By default the gateway will discover all Iveo devices already registered onto the gateway.

To access them:

.. code-block:: python

    gat.devices()

Will return a list of IveoDevices()

Each IveoDevice can be controlled by using the already defined commands: stop() moveUp() moveToIntermediatePosition1() and moveToIntermediatePosition2()

The library also allows to send directly commands to the gateway without the need of using the IveoDevice abstraction just create the command and execute using the gateway:

.. code-block:: python

    command = IveoCommandGetIds()
    command.execute(gat)

Once executed the response is stored in the command instance for later user or just to discard.

.. |PyPI version| image:: https://badge.fury.io/py/python-selve.svg
   :target: https://badge.fury.io/py/python-selve
steam-openid 1.0.6
A simple package for integrating Steam OpenID authentication in applications.
Requires Python: >=3.6

# steam-openid

steam-openid provides a straightforward implementation for integrating Steam OpenID authentication into applications.

## Requirements

- Python 3.6 or higher
- python3-openid

You can install the required dependencies with:

```bash
pip install -r requirements.txt
```

## Example usage
```python
from steam_openid import SteamOpenID

steam = SteamOpenID(
    realm="http://localhost:8080/steam/login",
    return_to="http://localhost:8080/steam/callback"
)


@app.route("/steam/login")
def login():
    redirect_url = steam.get_redirect_url()
    return redirect(redirect_url)


@app.route("/steam/callback")
def callback(request):
    steam_id = steam.validate_results(request.query_params)
    if steam_id:
        return 200, f"Your steam id is: {steam_id}"
    else:
        return 403, "Failed to authenticate"
```

## Contributions

Pull requests are welcome! If you find a bug or have a feature request, please open an issue or submit a pull request.

## License

This project is licensed under the MIT License.
mksite 0.1.1
Static site generator that supports markdown and html.
Requires Python: >=3.11

# mksite

---

[![builds.sr.ht status](https://builds.sr.ht/~loges/mksite.svg)](https://builds.sr.ht/~loges/mksite?)
[![PyPI - Version](https://img.shields.io/pypi/v/mksite.svg)](https://pypi.org/project/mksite)
[![License: AGPL v3](https://img.shields.io/badge/License-AGPL_v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)

> like mkdir but for websites

`mksite` helps you to quickly generate static websites with markdown.

## Installation

```console
pip install mksite
```

## Quickstart

Create site directory structure and change into `site` directory:

```console
mkdir -p site/content site/static
cd site
```

Add some site files:

```console
echo "<h1>Hello, world!</h1>" > content/index.md
echo "h1 {color: darkblue;}" > static/style.css
```

Add `config.toml` inside `site` directory:

```toml
base = "https://mksite.com"
lang = "en-us"

[directories]
content = "content"
static = "static"

[nav]
[[nav.items]]
name = "home"
uri = "/"
```

Build static site using `mksite` CLI:

```console
mksite build
```

Serve website using Python's http server:

```console
python -m http.server -d public 8000
```

Navigate to port [8000](http://localhost:8000).

## License

`mksite` is distributed under the terms of the [AGPLv3](https://spdx.org/licenses/AGPL-3.0-or-later.html) license.
embed-service 0.1.0
A simple command-line tool for testing srv-embed-service.

### Syntax

```bash
python main.py -b=bucket_name -p=file_prefix -a=app_url -o=operation
```

Where:
- **bucket_name**: GCS Bucket name where files are
- **file_prefix**: [Optional] GCS File prefix where files are.
- **app_url**: Cloud Run app url.
- **operation**: delete, embed or summarize