semvec/pypi-packages huggingface dataset:
jjz 0.0.1
Powerful CLI tool with multiple aliases (jujutsu/jutsu/jjz/jj2) - Lightning Fast Commands
Requires Python: >=3.9

# JJZ - Lightning Fast Commands ⚡

A powerful CLI tool with multiple aliases for different workflows.

## Features

- **Multiple Aliases**: Use `jjz`, `jujutsu`, `jutsu`, or `jj2` - they all work the same way!
- **Lightning Fast**: Optimized for speed and efficiency ⚡
- **Cross-Platform**: Works on Mac, Linux, and Windows
- **Easy Installation**: Available via PyPI and npm

## Installation

### From PyPI

```bash
pip install jjz
```

### From npm

```bash
npm install -g jjz
```

## Usage

All aliases work identically:

```bash
# Initialize a new project
jjz init
jujutsu init
jutsu init
jj2 init

# Check status
jjz status
jujutsu status

# Show help
jjz help
jj2 --help

# Show version
jjz --version
jujutsu -v
```

## Available Commands

- `init` - Initialize a new project
- `status` - Show project status
- `help` - Show help information
- `--version` - Show version information

## Lightning Fast Features ⚡

JJZ is designed for developers who need:
- Quick project initialization
- Fast status checks
- Efficient workflow management

## Development

To install for development:

```bash
# Clone the repository
git clone https://github.com/dai-motoki/jujutsu.git
cd jujutsu

# Install in development mode
pip install -e .
```

## License

MIT License

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.
moviessdk-Pricile 0.0.3
Software Development Kit (SDK) for MovieLens API
Requires Python: >=3.11

# MovieLens SDK - `moviessdk_Pricile`

Un SDK Python simple pour interagir avec l’API REST MovieLens. Il est conçu pour les **Data Analysts** et **Data Scientists**, avec une prise en charge native de **Pydantic**, **dictionnaires** et **DataFrames Pandas**.

[![PyPI version](https://badge.fury.io/py/moviesdk.svg)](https://badge.fury.io/py/moviesdk)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

---

## Installation

```bash
pip install moviessdk_Pricile
```

---

## Configuration

```python
from moviessdk_Pricile import MovieClient, MovieConfig

# Configuration avec l’URL de votre API (Render ou locale)
config = MovieConfig(movie_base_url="https://movie-backend-fdte.onrender.com")
client = MovieClient(config=config)
```

---

## Tester le SDK

### 1. Health check

```python
client.health_check()
# Retourne : {"status": "ok"}
```

### 2. Récupérer un film

```python
movie = client.get_movie(1)
print(movie.title)
```

### 3. Liste de films au format DataFrame

```python
df = client.list_movies(limit=5, output_format="pandas")
print(df.head())
```

---

## Modes de sortie disponibles

Toutes les méthodes de liste (`list_movies`, `list_ratings`, etc.) peuvent retourner :

- des objets **Pydantic** (défaut)
- des **dictionnaires**
- des **DataFrames Pandas**

Exemple :

```python
client.list_movies(limit=10, output_format="dict")
client.list_ratings(limit=10, output_format="pandas")
```

---

## Tester en local

Vous pouvez aussi utiliser une API locale :

```python
config = MovieConfig(movie_base_url="http://localhost:8000")
client = MovieClient(config=config)
```

---

## Public cible

- Data Analysts
- Data Scientists
- Étudiants et curieux en Data
- Développeurs Python

---

## Licence

MIT License

---

## Liens utiles
- API Render : [https://movie-backend-fdte.onrender.com/](https://movie-backend-fdte.onrender.com/)
- PyPI : [https://pypi.org/project/moviessdk-Pricile/0.0.2/](https://pypi.org/project/moviessdk-Pricile/0.0.2/)