semvec/pypi-packages huggingface dataset:
ragtastic 0.1.2
Python bindings for the Ragtastic API
Requires Python: >=3.8

# Project description

A Python library for Stripe’s API.

## Setup

You can install this package by using the pip tool and installing:

    $ pip install ragtastic

Or:

    $ uv add ragtastic

## Setting up a Ragtastic Account

Sign up for Ragtastic at https://useragtastic.com/register

## Using the Ragtastic API

Documentation for the python bindings can be found alongside Ragtastic’s other bindings here:

    https://useragtastic.com/docs
tlaloc-es-mcp 0.1.6
Add your description here
Requires Python: >=3.12

# Tlaloc Es MCP

This repository provides several ready-to-use MCP (Model Context Protocol) implementations that can be used as custom MCP servers.

## What is MCP?

MCP (Model Context Protocol) is a protocol that allows VS Code and other tools to communicate with servers that provide context, analysis, and other features for code models.

## What does this repository include?

- Ready-to-use MCP implementations (for example, `file-handler`).
- An extensible structure to easily add new implementations.

## How to use in VS Code?

You can add this MCP server to your VS Code configuration by editing your `mcp.json` file like this:

```json
"files_handler": {
  "command": "uvx",
  "args": [
    "--from",
    "tlaloc-es-mcp",
    "tlalocesmcp",
    "--mcp-selected",
    "file-handler"
  ],
  "env": {}
}
```

This will run the `file-handler` implementation included in this repository.

______________________________________________________________________

> Based on [mcp](https://github.com/modelcontext/model-context-protocol) and compatible with its CLI.
cinesdk 0.0.2
Software Development Kit (SDK) for MovieLens API
Requires Python: >=3.12

# MovieLens SDK - `cinesdk`

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 cinesdk
```

---

## Configuration

```python
from filmsdk import MovieClient, MovieConfig

# Configuration avec l’URL de votre API (Render ou locale)
config = MovieConfig(movie_base_url="https://movie-backend-7wya.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-xelv.onrender.com](https://movie-backend-xelv.onrender.com)
- PyPI : [https://pypi.org/project/filmsdk](https://pypi.org/project/filmsdk)