semvec/pypi-packages huggingface dataset:
ksvian 0.0.1
A custom library with various functions and models for ANN labouratory
License: MIT
Requires Python: >=3.6

# Example Package

This is a simple example Python package. It includes a basic function `print` that print the all thre academic labouratory programs. The package is designed to demonstrate how to create, package, and distribute Python libraries.

## Installation

You can install the package directly from PyPI using pip:

```bash
pip install ksvian
idea-bio 0.2.6
Integrated Differential Expression and Annotation
License: MIT
Requires Python: <4.0,>=3.8
Keywords: bioinformatics, differential expression, annotation, networks

# IDEA

## Integrated Differential Expression and Annotation

<p align="center">
    <img src="https://github.com/noamteyssier/idea/blob/main/assets/logo.png?raw=true" width="50%" />
</p>

This is a python module to perform GO analysis using [Enrichr](https://maayanlab.cloud/Enrichr/)
and visualize the [bipartite graph](https://en.wikipedia.org/wiki/Bipartite_graph)
of terms and genes as an interactive force-directed graph.

This uses [`pvsvg`](https://github.com/noamteyssier/pvsvg) as the python wrapper to the
force-directed graph visualization javascript library [`vis.js`](https://visjs.github.io/vis-network/docs/network/)
and [`ggetrs`](https://noamteyssier.github.io/ggetrs)
to perform the gene set enrichment using the [`Enrichr`](https://maayanlab.cloud/Enrichr/) API.

## Installation and Usage

Checkout my [documentation](https://idea-bio.readthedocs.io/en/latest/index.html)
for information on installation, usage, and recipes for analysis.
sigmaa-crawler 0.0.2
Este proyecto permite obtener datos del SIGMAA, el sistema educativo de la Universidad del Caribe. Facilita la obtención de información del estudiante, calificaciones, cárdex, oferta académica, información de pagos de estudiantes, entre otros datos, a través de un SDK de Python.
License: MIT

# SIGMMA Crawler

SIGMMA Crawler es una biblioteca para extraer datos de la plataforma SIGMMA de la Universidad del Caribe.

## Características

- Extracción de datos académicos.
- Soporte para métodos.
- Fácil de usar e integrar.

## Instalación

Puedes instalar la biblioteca usando pip:

```bash
pip install sigmma-crawler
```

## Uso

Aquí tienes un ejemplo básico de cómo usar la biblioteca:

```python
from sigmma_crawler import SigmmaCrawler

crawler = SigmmaCrawler(usuario='matricula', contraseña='contraseña')
datos = crawler.academic_offer()
print(datos)
```

## Contribuciones

Las contribuciones son bienvenidas. Por favor, abre un issue o envía un pull request.

## Licencia

Este proyecto está licenciado bajo la Licencia MIT. Consulta el archivo `LICENSE` para más detalles.

## Contacto

Para más información, puedes contactar a Kenneth en [kennethdiazgonzalez@hotmail.com](mailto:kennethdiazgonzalez@hotmail.com).
jupyterlite-clojure-kernel-canary 0.1.1
A Clojure Kernel for JupyterLite using `sci`
License: MIT
Requires Python: >=3.8
Keywords: clojure, jupyter, jupyterlab, jupyterlite

# JupyterLite Clojure Kernel

A Clojure kernel for JupyterLite powered by [sci](https://github.com/babashka/sci) —— Small Clojure Interpreter, enabling Clojure code execution directly in the browser.

## Features

- Browser-based Clojure REPL
- No server-side dependencies
- Core Clojure functions support

## Installation

```bash
pip install jupyterlite-clojure-kernel-canary
```

## Usage

1. Install JupyterLite
2. Add the Clojure kernel
3. Create a new notebook with Clojure kernel

## Examples

```clojure
;; Basic calculations
(+ 1 2 3)

;; Define functions
(defn square [x] (* x x))

;; Data structures
(def data {:name "Alice" :scores [98 92 85]})
```

## License

MIT
houdiniutils 0.1.6
All related tools and utilities
License: MIT
Requires Python: <4.0.0,>=3.10.10


# houdiniUtils

This package provides a collection of utilities for Houdini, including tools for managing texture IDs and renaming textures based on specified patterns.

## Installation

### 1. Ensure Python is Installed

Before installing the `houdiniUtils` package, make sure Python is installed on your system. You can check this by running the following command in your terminal (macOS) or PowerShell (Windows):

```bash
python --version
```

or

```bash
python3 --version
```

If Python is not installed, you can download and install it from the official [Python website](https://www.python.org/downloads/).

### 2. Install the Package

You can install the `houdiniUtils` package either globally or within a virtual environment. However, we recommend using a virtual environment to avoid any potential conflicts, especially since Houdini 20.5.XXX uses Python 3.11.7.

#### 2.1 Using a Virtual Environment

To create and activate a virtual environment, follow the instructions provided in the [Python documentation on venv](https://docs.python.org/3/library/venv.html).

After activating your virtual environment, you can install the package by running:

```bash
pip install houdiniutils
```

### 3. Run the Post-Installation Script

Once the package is installed, you need to generate and copy `houdiniUtils.shelf` to the toolbar directory and `houdiniUtils.json` to the packages directory within your Houdini user preferences directory. This can be done by running the following post-installation command:

```bash
houdiniutils_post_install
```

This command will automatically detect your Houdini user preferences directory, create the necessary files, and place them in the appropriate locations.

By following these steps, you will have successfully set up the `houdiniUtils` package and configured the necessary environment variables for Houdini.