semvec/pypi-packages huggingface dataset:
img2txtio 0.0.4
A simple SDK for using the Img2Txt API.
Requires Python: >=3.12

# img2txt.io Python Package

A Python Package for the [img2txt.io](https://img2txt.io) API. Easily upload images and convert them to plain text or structured output programmatically.

## Installation

```bash
pip install img2txtio
```

Or install directly from source:

```bash
git clone https://github.com/Astro-gram/img2txt-python-package.git
cd img2txt-python-sdk
pip install .
```

## Quick Start

```python
from img2txtio import Img2TxtClient

# Initialize client with your API key
token = "YOUR_API_KEY_HERE"
client = Img2TxtClient(api_key=token)

# Convert an image to plain text
result = client.process(
    image_path="path/to/image.jpg",
    output_type="raw",           # default: raw text
    description="Receipt from grocery",  # optional
    outputStructure=""           # optional JSON string for structured output
)

# `result` is a dict containing the API response
print(result)
```

## API Reference

### Class: `Img2TxtClient`

#### `__init__(api_key: str)`

Create a new client instance.
- `api_key` (str): Your img2txt.io API key. You can generate one from the [img2txt.io dashboard](https://img2txt.io/dashboard?api-settings=true).

#### `process(image_path: str, output_type: str = "raw", description: str = "", outputStructure: str = "") -> dict`

Uploads the image at `image_path` and converts it to text or structured output.

Parameters:

- `image_path` (str): Local path to the image file. Must exist, otherwise raises `FileNotFoundError`.
- `output_type` (str): The output format. Defaults to `raw`. Other valid types depend on the API (e.g., `json`, `structured`).
- `description` (str): Optional description or context to improve text extraction.
- `outputStructure` (str): Optional JSON string defining a structure/schema for the output. Must be valid JSON or raises `ValueError`.

Returns:

- `dict`: Parsed JSON response from the API. On failure, raises `RuntimeError`.  
- Example response:
    ```python
    {
        'text_output': [
            'Los Angeles', 'Florida', '$235', 'Round trip', 'Economy',
            '1 passenger', 'Lowest total price'
        ],
        'job_id': '16e2364a-e1e2-468e-9be9-e07b695b2afd',
        'creditsLeft': 86.115,
        'success': True,
        'message': 'Image processed successfully.'
    }
    ```


## Error Handling

- Network or HTTP errors raise `requests.exceptions.HTTPError`.
- Missing files raise `FileNotFoundError`.
- Invalid JSON in `outputStructure` raises `ValueError`.
- API failures raise `RuntimeError`.

## License

This project is licensed under the MIT License. See the [`LICENSE`](LICENSE) file for details.
certbot-plugin-dns-loopia 0.1.0
A Certbot plugin for certificate renewal using Loopia DNS

# Certbot Loopia DNS Plugin

A Certbot plugin for automatic completion of Certbot DNS challenges when your domain is managed by Loopia DNS.

## Installing

```sh
$ pip install certbot-plugin-dns-loopia
```

## Loopa API Permissions

Your Loopa API user must have access to the following methods:

-   addZoneRecord
-   getZoneRecords
-   removeZoneRecord

## Credentials

A .ini-file with your Loopia API user must be provided. Required entries in the file:

```ini
dns_loopia_username = <your-username>@loopiapi
dns_loopia_password = <your password>
```

The path to the file is provided via the `--dns-loopia-credentials` parameter to certbot.

## Disclaimer

The plugin has no affiliation to Loopia AB.
ed-webhook-service 0.1.9
EasyDrop auth model Package
Requires Python: >=3.12
Keywords: ed_webhook, pypi, package

# py
Template class for python backend servers.

## Features
- [x] RabbitMQ
- [x] Logging
- [X] Generic Helpers
- [ ] Kafka
- [ ] Redis
- [x] API: RequestHandler, FastAPI
- [x] Dockerfile
- [x] Makefile
- [x] CI/CD
- [x] Entry point file
- [x] Configfile / Configuration
- [x] Websockets

## Usage
The project's dependencies are managed by `poetry`. You can install the dependencies with:
```bash
poetry install
```

`package.py` is the entry point file.

### Running the package
You can run the package inside of a virtual environment:
```bash
poetry shell
make run
```

or with `docker`:
```bash
make run_docker
```


### Running the tests
You can run the tests inside of a virtual environment:
```bash
poetry shell
make test
```
or with `docker`:
```bash
make test_docker
```
boe-mcp 0.1.0
BOE API integration with MCP (Model Context Protocol)
Requires Python: >=3.10

# BOE-MCP. MCP Integration with the BOE API

[![es](https://img.shields.io/badge/lang-es-yellow.svg)](README_es.md)
[![en](https://img.shields.io/badge/lang-en-red.svg)](README.md)

## DESCRIPTION

**BOE is the Official State Gazette of Spain.**

**Boe-mcp** enables querying consolidated legislation, BOE/BORME summaries, and legal reference data directly through Claude AI and other MCP-compatible clients using the **Model Context Protocol (MCP)**.

Boe-mcp is an MCP server that exposes tools for LLMs to access:
- Consolidated legislation of the Spanish legal system
- Daily BOE and BORME summaries
- Auxiliary tables for legal domains, jurisdictions, and government departments

## KEY FEATURES

- Advanced search of consolidated legislation with date, jurisdiction, and validity filters
- Full legal text retrieval in XML/JSON formats
- Historical BOE and BORME summary queries
- Access to legal reference tables (domains, departments, legal relationships)
- Block-level navigation of legal texts
- Automatic consolidation status validation

## INSTALLATION

### Install with uv

### Prerequisites

- Python 3.10 or higher.
- [uv](https://docs.astral.sh/uv/getting-started/installation/) package manager.

### Installing uv

The first step is to install `uv`, a package manager for Python.  
**It can be installed from the command line**.

On macOS and Linux:

```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```

On Windows:  

```bash
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```

You can also install it with pip:  

```bash
pip install uv
```

For more information about installing uv, visit the [uv documentation](https://docs.astral.sh/uv/getting-started/installation/).

## INTEGRATION WITH CLIENTS LIKE CLAUDE FOR DESKTOP

1. Go to **Claude > Settings > Developer > Edit Config > `claude_desktop_config.json`**.
2. Add this configuration block under `"mcpServers"`:

```json
"boe_mcp": {
    "command": "uvx",
    "args": [
        "boe_mcp"
    ]
}
```

3. If you have other MCP servers configured, separate them with commas `,`.

## USAGE EXAMPLES

Once configured, you can make queries like:

- "List current state laws on data protection"
- "Show the BOE summary for June 14, 2024"
- "Display the BOE legal domains table"
text2insights 0.1.2
Extract sentiment, keywords, and entities from text.
Requires Python: >=3.7

# text2insights

A Python package to extract:

-  Sentiment (positive / negative / neutral)
-  Keywords (using TF-IDF)
- Named Entities (ORG, PERSON, GPE, MONEY)

##  Installation

```bash
pip install text2insights

## Usage
```from text2insights import analyze_text

text = "South African Reserve Bank raised interest rates to fight inflation."
print(analyze_text(text))
``