semvec/pypi-packages huggingface dataset:
oneNeuron-pypi-sureshs96 0.0.2
its an implimentation of Perceptron
Requires Python: >=3.7

# oneNeuron_pypi
oneNeuron python package creation

## How to use -
```python
    from oneNeuron.perceptron import Perceptron
    from utils.common_utils import prepare_data, save_model, save_plot
    ## Get X and y from dataframe
    X,y = prepare_data(df)
    model = Perceptron(eta, epochs)
    model.fit(X,y)
    _ = model.total_loss()
    save_model(model, modelname)
    save_plot(df , plotfilename, model)
```
# Reference -
[official python docs](https://packaging.python.org/tutorials/packaging-projects/)

[github docs for github actions](https://docs.github.com/en/actions/guides/building-and-testing-python#publishing-to-package-registeries)
epubgen 0.4.2
Tiny library to programmatically generate .epub files
Requires Python: >=3.7

# epub-generator

Small library to generate epub files easily

## Usage:

```python
from epubgen import EPUB
import xml.etree.ElementTree as ET

book = EPUB("Test EPUB", "author-test", "en")
first_page = ET.Element("p")
first_page.text = "first-page" + 10000 * "hello "
book.add_page(first_page, toc_title="First chapter")

second_page = ET.Element("p")
second_page.text = "second-page" + 10000 * "good morning ! "
book.add_page(second_page, toc_title="Second chapter")
book.generate_epub("test.epub")
```
smiles-encoder 0.1.1
One-hot encoding for simple molecular-input line-entry system (SMILES) strings
Requires Python: >=3.11

# smiles-encoder: One-hot encoding for simple molecular-input line-entry system (SMILES) strings

[![GitHub version](https://badge.fury.io/gh/tjkessler%2Fsmiles-encoder.svg)](https://badge.fury.io/gh/tjkessler%2Fsmiles-encoder)
[![PyPI version](https://badge.fury.io/py/smiles-encoder.svg)](https://badge.fury.io/py/smiles-encoder)
[![GitHub license](https://img.shields.io/badge/license-MIT-blue.svg)](https://raw.githubusercontent.com/tjkessler/smiles-encoder/master/LICENSE.txt)

smiles-encoder is a Python package used to generate one-hot vectors representing SMILES strings (each string element is a one-hot vector).

## Installation

Installation via pip:

```
$ pip install smiles-encoder
```

Installation via cloned repository:

```
$ git clone https://github.com/tjkessler/smiles-encoder
$ cd smiles-encoder
$ python setup.py install
```

smiles-encoder does not require any dependencies.

## Basic Usage

First, assemble a list of SMILES strings:

```python
smiles_strings = [
    'O=Cc1ccc(O)c(OC)c1',  # Vanillin
    'CC(=O)NCCC1=CNc2c1cc(OC)cc2',  # Melatonin
    'C1CCCCC1',  # Cyclohexane
    'C1=CC=CC=C1'  # Benzene
]
```

Import the SmilesEncoder object, and pass it the list of SMILES strings during initialization to construct the element dictionary:

```python
from smiles_encoder import SmilesEncoder

encoder = SmilesEncoder(smiles_strings)
```

Use the encoder to encode SMILES strings:

```python
encoded_smiles = encoder.encode_many(smiles_strings)

# OR

encoded_smiles = [encoder.encode(s) for s in smiles_strings]
```

Use the encoder to decode encoded SMILES strings:

```python
decoded_smiles = encoder.decode_many(encoded_smiles)

# OR

decoded_smiles = [encoder.decode(e) for e in encoded_smiles]
```

## Contributing, Reporting Issues and Other Support

To contribute to smiles-encoder, make a pull request. Contributions should include extensive documentation.

To report problems with the software or feature requests, file an issue. When reporting problems, include information such as error messages, your OS/environment and Python version.

For additional support/questions, contact Travis Kessler (travis.j.kessler@gmail.com).
hassfeld 0.3.13a2
Integration of Raumfeld into Home Assistant
Requires Python: >=3.5


hassfeld
========

|Language grade Python|

hassfeld is a module primarily aimed to integrated Teufel Smart Speaker (aka Raumfeld Multiroom) into https://www.home-assistant.io/. However, the design is not tailored to Home Assistant and can be used as a module to any Pyhton program to control the Teufel Smart Speaker. The module also provides corresponding asyncio methods.

Look how it is to use with asyncrhonous I/O::

    import asyncio
    import aiohttp
    import hassfeld


    async def main():
        host = "teufel-host.example.com"
        port = 47365
        session = aiohttp.ClientSession()
        raumfeld = hassfeld.RaumfeldHost(host, port, session=session)

        asyncio.create_task(raumfeld.async_update_all(session))
        await raumfeld.async_wait_initial_update()

        zone = ["Master Bedroom"]

        media_info = await raumfeld.async_get_media_info(zone)
        print(f"Media info: {media_info}")

        await session.close()


    asyncio.run(main())

The use with blocking I/O was supported too but is currently broken::

    import hassfeld
    raumfeld_host = "teufel-host.example.com"
    zone = [ "Living room", "Kitchen" ]
    raumfeld = hassfeld.RaumfeldHost(raumfeld_host)
    raumfeld.start_update_thread()
    raumfeld.search_and_zone_play(zone, 'raumfeld:any contains "Like a Rolling Stone"')


Features
--------

- Management and snapshot of zones.
- Search and play songs.

Install hassfeld by running::

    python3 -m pip install hassfeld

Contribute
----------

- Issue Tracker: https://github.com/B5r1oJ0A9G/hassfeld/issues
- Source Code: https://github.com/B5r1oJ0A9G/hassfeld

License
-------

The project is licensed under the GNU General Public License v3 (GPLv3).


.. |Language grade Python| image:: https://github.com/B5r1oJ0A9G/hassfeld/actions/workflows/github-code-scanning/codeql/badge.svg?branch=master
   :target: https://github.com/B5r1oJ0A9G/hassfeld/actions/workflows/github-code-scanning/codeql