semvec/pypi-packages huggingface dataset:
TorchClassifierData 0.0.1
Small pytorch utility to Import,Split,Normalize and Visualize custom dataset for classification tasks
Keywords: Computer-vision,pytorch,preprocessing,Images,Dataset,TorchClassifierData

## TorchClassifierData 

A Small pytorch utility to Import,Split,Normalize and Visualize custom dataset for classification tasks.

## Install

### From main branch

```bash
pip install git+https://github.com/shellordie/TorchClassifierData.git@main

```

### From pypi

```bash
pip install TorchClassifierData
```

## Usage 

Check [https://github.com/shellordie/TorchClassifierDataExample/](https://github.com/shellordie/TorchClassifierDataExample/)
datasmith 0.0.4
A brief description of your package

# TypeBuild

TypeBuild is a powerful Python package that empowers domain experts to develop their own frontend with just natural language input. This tool is designed to help users perform data analysis and visualization with tabular data (csv, xlsx, .db, .sqlite, .parquet). It also allows users to upload and interact with text documents for summarization, classification, and Q&A.

TypeBuild leverages the power of OpenAI's GPT models, but also provides the flexibility for users to upload their own llm function. Users can create projects and new views using the chat feature in the tool.

## Installation

You can install TypeBuild using pip:

```bash
pip install typebuild
```

After installation, you can run the command 'typebuild' from your command line to launch the Streamlit app.

## Features

- **Data Analysis and Visualization**: Analyze and visualize tabular data from various formats including csv, xlsx, .db, .sqlite, .parquet.
- **Document Interaction**: Upload and interact with text documents for tasks such as summarization, classification, and Q&A.
- **Customizable AI Models**: Use OpenAI's GPT models or upload your own llm function.
- **Project Creation**: Create and manage projects using the chat feature in the tool.

## Usage

After installing the package, you can launch the Streamlit app by running:

```bash
typebuild
```

This will open a new browser window where you can start creating projects, uploading data, and interacting with your documents.

## Contributing

We welcome contributions to TypeBuild. Please see our [Contributing Guide](CONTRIBUTING.md) for more details.

## License

Shield: [![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa]

This work is licensed under a
[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png
[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg

## Support

If you encounter any issues or have any questions about TypeBuild, please open an issue on our [GitHub page](https://github.com/project-typebuild/typebuild).

## Acknowledgements

We would like to thank the OpenAI team for their GPT models which have been instrumental in the development of TypeBuild.
ahk-json 0.1.0rc2
Auto-Hotkey-JSON for Python
Requires Python: >=3.8.0
Keywords: ahk,autohotkey,jxon,json,python

# ahk-json

This is an extension package intended to be used with the Python [ahk](https://github.com/spyoungtech/ahk) package.

It provides interfaces from [cocobelgica/AutoHotkey-JSON](https://github.com/cocobelgica/AutoHotkey-JSON) for
working with JSON in AutoHotkey. The extensions in this package do not provide any additional methods,
but simply provide a convenient way to include `Jxon.ahk` and/or `JSON.ahk` into other extensions.

This package provides two extensions: `JXON` and `JSON`. It also registers a JSON message type (`ahk_json.message.JsonResponseMessage`)

## Installation

Install this extension using `pip`

```python
pip install ahk-json
```

# Usage

Typically, you use this as a dependency when building your own extensions.

In the following example, a simple extension (`my_extension`) is created. It implements an AHK function `MyTestFunction`
-- the registered to the extension using the Python function `my_test_function`.
```python
from ahk.extensions import Extension
from ahk import AHK

from ahk_json import JXON  # importing is necessary for ``extensions='auto'`` to work, even if this is not used

ext_script = '''\
MyTestFunction(ByRef command) {
    arg := command[2]
    obj := Object("test", arg)
    res := Jxon_Dump(obj) ; this is available thanks to the extension
    return FormatResponse("ahk_json.message.JsonResponseMessage", res)
}
'''

my_extension = Extension(script_text=ext_script)

@my_extension.register
def my_test_function(ahk: AHK, arg: str):
    return ahk.function_call('MyTestFunction', [arg])


def main():
    ahk = AHK(extensions='auto')  # automatically use all imported/created extensions
    # or use the extensions explicitly:
    # ahk = AHK(extensions=[JXON, my_extension])

    # now ``.my_test_function`` is a method on the `ahk` instance:
    assert ahk.my_test_function('foo') == {'test': 'foo'}
```


# License

This work is licensed under the MIT license.

This package includes substantial portions of the [original AutoHotkey-JSON](https://github.com/cocobelgica/AutoHotkey-JSON).
The code included from AutoHotkey-JSON is owned and copyrighted by its original author(s) and is used/redistributed
under the terms of the [WTFPL](http://www.wtfpl.net).
ninebot-ble 0.0.6
Ninebot scooter BLE client
Requires Python: >=3.9

# Ninebot Scooter BLE Python client

Python client for interfacing with a Ninebot scooter using bluetooth low energy (BLE).

It is primarely using the BLE UART characteristic for communication with the scooter. It is also
using the new encrypted protocol using [miauth](https://github.com/dnandha/miauth) library. Old
scooter firmwares might therefore not work.

The projects primary objective is to support Home Assistant integration but will work for more
use-cases as well.

## Usage

Installation:

```
pip install ninebot-ble
```

A command-line client for testing purposes are shipped:

```
ninebot-ble --help
```

## Troubleshoot

I only have access to a Ninebot F-series scooter, if you have problems with other models, I will
need help with debugging.
cbcbeat 2023.2.0
An adjoint-enabled framework for computational cardiac electrophysiology

# cbcbeat: an adjoint-enabled framework for computational cardiac electrophysiology

[![image](https://codecov.io/gh/ComputationalPhysiology/cbcbeat/branch/master/graph/badge.svg?token=Z4BCNQRRPU)](https://codecov.io/gh/ComputationalPhysiology/cbcbeat)

[![image](https://circleci.com/gh/ComputationalPhysiology/cbcbeat.svg?style=shield)](https://circleci.com/gh/ComputationalPhysiology/cbcbeat)

cbcbeat is a collection of Python-based solvers for cardiac
electrophysiology models. cbcbeat offers basic and optimized solvers for
the bidomain and monodomain equations coupled with cardiac cell models.
cbcbeat is based on the FEniCS Project and dolfin-adjoint.

For more information visit https://computationalphysiology.github.io/cbcbeat/

## Installation:

See separate file ./INSTALL for how to install the cbcbeat module and a
list of dependencies.

## Documentation:

The cbcbeat documention is availble on readthedocs, see:

> https://computationalphysiology.github.io/cbcbeat/

For manually updating the API and demo documentation, run:

> cd doc make html

assuming that cbcbeat and the optional dependency Sphinx
(sphinx-doc.org) is installed.

## Automated Testing:

cbcbeat uses GitHub Actions for automated and continuous testing:

> https://github.com/ComputationalPhysiology/cbcbeat/actions

## License:

cbcbeat is free software: you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License as published by the
Free Software Foundation, either version 3 of the License, or (at your
option) any later version.

cbcbeat is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public
License for more details.

You should have received a copy of the GNU Lesser General Public License
along with this program. If not, see \<<http://www.gnu.org/licenses/>\>.