semvec/pypi-packages huggingface dataset:
stFormer 0.1.3a0
A flexible framework for transformer-based analysis of spatial transcriptomics data.
Requires Python: >=3.8

# stFormer

A flexible framework for transformer-based analysis of spatial transcriptomics data. stFormer provides tools for data tokenization, pretraining, embedding extraction, in silico perturbation, and downstream classification.

- Keep up to date on [Github](https://github.com/istrope/stFormer)
- Browse model files on [Hugging-Face](https://huggingface.co/Istrope/stFormer)

# Install
```bash
pip install --upgrade stformer
```
> **Prerequisites:** Python3.8+, OpenMPI (for deepspeed only)

# Features
- Data Tokenization
- Pretraining
- Token/Sequence Classification
- In Silico Perturbation
- Network Dynamic Predictions

## Contributing

Contributions are welcome! Please open issues at our [Github](https://github.com/istrope/stFormer) or submit pull requests for bug fixes and new features.

## Models
Pretrained models and datasets are available through our [hugging-face](https://huggingface.co/Istrope/stFormer) model card 

## License

This project is licensed under the MIT License. See [LICENSE](https://github.com/istrope/stFormer/blob/main/LICENSE) for details.
napari-cci-annotator 0.7.1
Plugin to simplify annotations of datasets
Requires Python: >=3.9

# napari-cci-annotator

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

Plugin to simplify annotations of datasets

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

This [napari] plugin was generated with [copier] using the [napari-plugin-template].

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and review the napari docs for plugin developers:
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## Installation

You can install `napari-cci-annotator` via [pip]:

    pip install napari-cci-annotator




## 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-cci-annotator" 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
[copier]: https://copier.readthedocs.io/en/stable/
[@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
[napari-plugin-template]: https://github.com/napari/napari-plugin-template

[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/
pymqttusb-tk 1.0.1
Connexion USB <-> MQTT (SSL ou WSS) avec interface Tkinter
Requires Python: >=3.6

#pymqttusb-tk

Permet la connexion d'un microprocesseur branché sur un port usb vers un serveur MQTT.<br />

L'affichage graphique permet de configurer le broker <br />
Contenu du fichier "arduino_mqtt_data.json" :<br />

-----------<br />

Le topic de réception sera : salle/KEY/out<br />

Le topic d'envoi sera : salle/KEY/in<br />

Les protocoles possibles sont "wss" websockets sécurisés avec login et mot de passe ( pas de certificat)
ou "tcp" pour ssl avec login et mot de passe ( pas de certificats client) <br />

Lancement du programme :<br />

	py -m pymqttusb-tk.main <br />

<br />