semvec/pypi-packages huggingface dataset:
inbox4us-pos-printer 0.1.4
Inbox4us POS printer service
License: MIT
Requires Python: >=3.6
Keywords: printer, fastapi, escpos, network-printer

# Inbox4us POS Printer Service

A FastAPI-based service for handling ESC/POS printer operations. This service allows you to send base64-encoded images to network printers using the ESC/POS protocol.

## Features

- Send images to network printers
- Support for ESC/POS protocol
- Simple REST API interface
- CORS support
- SSL/TLS support

## Installation

Install using pip:

```bash
pip install inbox4us-pos-printer
```

## Usage

### Basic Usage

```python
from pos_printer import create_app
import uvicorn

app = create_app()

if __name__ == '__main__':
    uvicorn.run(
        app, 
        host='0.0.0.0', 
        port=8100
    )
```

### With SSL

```python
from pos_printer import create_app
import uvicorn

app = create_app()

if __name__ == '__main__':
    uvicorn.run(
        app, 
        host='0.0.0.0', 
        port=8100, 
        ssl_certfile="./ssl/certificate.crt",
        ssl_keyfile="./ssl/private.key",
        ssl_ca_certs="./ssl/ca_bundle.crt" 
    )
```

## API Documentation

### POST /print

Send an image to a network printer.

#### Request Body

```json
{
    "printer_ip": "192.168.1.100",
    "port": 9100,
    "data": "base64_encoded_image_data"
}
```

#### Parameters

- `printer_ip` (string, required): IP address of the network printer
- `port` (integer, optional, default: 9100): Printer port
- `data` (string, required): Base64 encoded image data

#### Response

Success:
```json
{
    "status": "success"
}
```

Error:
```json
{
    "status": "error",
    "message": "Error message details"
}
```

## Requirements

- Python >= 3.8
- FastAPI >= 0.68.0
- python-escpos >= 3.0
- Pillow >= 8.0.0
- pydantic >= 1.8.0
## License

MIT License

## Support

For support, please create an issue on the [GitHub repository](https://github.com/Inbox-Team/pos-printer/issues).
napari-bigfish 0.8
A napari-plugin providing an alternative GUI for Big-FISH. Big-FISH is a python package for the analysis of smFISH images.
License: MIT
Requires Python: >=3.8

 # napari-bigfish

[![License MIT](https://img.shields.io/pypi/l/napari-bigfish.svg?color=green)](https://github.com/MontpellierRessourcesImagerie/napari-bigfish/raw/main/LICENSE)
[![PyPI](https://img.shields.io/pypi/v/napari-bigfish.svg?color=green)](https://pypi.org/project/napari-bigfish)
[![Python Version](https://img.shields.io/pypi/pyversions/napari-bigfish.svg?color=green)](https://python.org)
[![tests](https://github.com/MontpellierRessourcesImagerie/napari-bigfish/workflows/tests/badge.svg)](https://github.com/MontpellierRessourcesImagerie/napari-bigfish/actions)
[![codecov](https://codecov.io/gh/MontpellierRessourcesImagerie/napari-bigfish/branch/main/graph/badge.svg)](https://codecov.io/gh/MontpellierRessourcesImagerie/napari-bigfish)
[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-bigfish)](https://napari-hub.org/plugins/napari-bigfish)

A napari-plugin providing an alternative GUI for [Big-FISH](https://github.com/fish-quant/big-fish). Big-FISH is a python package for the analysis of smFISH images.

The plugin provides a graphical user interface for some of the functionality in Big-FISH. Currently implemented are:

 * Gaussian-background subtraction
 * FISH-spot detection with 
	* Elimination of duplicates
	* Auto-detection of threshold
* Dense-region decomposition

The plugin further implements by itself:

* Counting of spots per cell, inside and outside of the nucleus
* Batch processing on a list of images


You can find the user and the api-documentation of napari-bigfish [here](https://montpellierressourcesimagerie.github.io/napari-bigfish/).
 

----------------------------------

This [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.

## Installation

You can install `napari-bigfish` via [pip]:

    pip install napari-bigfish


## Contributing

Contributions are very welcome. Tests can be run with [tox], please ensure
the coverage at least stays the same before you submit a pull request.


## License

Distributed under the terms of the [MIT] license,
"napari-bigfish" is free and open source software


## Issues

If you encounter any problems, please [file an issue] along with a detailed description.

[napari]: https://github.com/napari/napari
[Cookiecutter]: https://github.com/audreyr/cookiecutter
[@napari]: https://github.com/napari
[MIT]: http://opensource.org/licenses/MIT
[BSD-3]: http://opensource.org/licenses/BSD-3-Clause
[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt
[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt
[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0
[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt
[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin

[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/