semvec/pypi-packages huggingface dataset:
hyfi-chain 0.1.0
A wrapper library integrating LangChain's language model chaining with HyFI framework for building robust, scalable, and maintainable NLP applications.
License: MIT
Requires Python: <3.13,>=3.9

# HyFI-Chain

[![pypi-image]][pypi-url]
[![version-image]][release-url]
[![release-date-image]][release-url]
[![license-image]][license-url]
[![codecov][codecov-image]][codecov-url]
[![jupyter-book-image]][docs-url]

<!-- Links: -->
[codecov-image]: https://codecov.io/gh/entelecheia/hyfi-chain/branch/main/graph/badge.svg?token=rdfiKAmEr8
[codecov-url]: https://codecov.io/gh/entelecheia/hyfi-chain
[pypi-image]: https://img.shields.io/pypi/v/hyfi-chain
[license-image]: https://img.shields.io/github/license/entelecheia/hyfi-chain
[license-url]: https://github.com/entelecheia/hyfi-chain/blob/main/LICENSE
[version-image]: https://img.shields.io/github/v/release/entelecheia/hyfi-chain?sort=semver
[release-date-image]: https://img.shields.io/github/release-date/entelecheia/hyfi-chain
[release-url]: https://github.com/entelecheia/hyfi-chain/releases
[jupyter-book-image]: https://jupyterbook.org/en/stable/_images/badge.svg

[repo-url]: https://github.com/entelecheia/hyfi-chain
[pypi-url]: https://pypi.org/project/hyfi-chain
[docs-url]: https://hyfi-chain.entelecheia.ai
[changelog]: https://github.com/entelecheia/hyfi-chain/blob/main/CHANGELOG.md
[contributing guidelines]: https://github.com/entelecheia/hyfi-chain/blob/main/CONTRIBUTING.md
<!-- Links: -->

A wrapper library integrating LangChain's language model chaining with HyFI framework for building robust, scalable, and maintainable NLP applications.

- Documentation: [https://hyfi-chain.entelecheia.ai][docs-url]
- GitHub: [https://github.com/entelecheia/hyfi-chain][repo-url]
- PyPI: [https://pypi.org/project/hyfi-chain][pypi-url]

HyFI-Chain is a wrapper library that integrates the language model chaining capabilities of LangChain with the HyFI (Hydra Fast Interface) framework. It enables developers to build robust, scalable, and maintainable natural language processing (NLP) applications with ease.
By combining the power of LangChain's flexible language model chaining with HyFI's streamlined configuration and execution capabilities, HyFI-Chain simplifies the development process and allows developers to focus on the core logic of their NLP applications.
HyFI-Chain inherits the scaling capabilities of HyFI, enabling effortless scaling of NLP applications to handle larger workloads. It provides a solid foundation for exploring the possibilities of language model chaining and unlocking the potential of NLP in various domains.

## Changelog

See the [CHANGELOG] for more information.

## Contributing

Contributions are welcome! Please see the [contributing guidelines] for more information.

## License

This project is released under the [MIT License][license-url].
hyfi-lpg 0.1.0
HyFI-LPG is an LLM powered gleaning tool for HyFI.
License: MIT
Requires Python: <3.13,>=3.9

# HyFI-LPG

[![pypi-image]][pypi-url]
[![version-image]][release-url]
[![release-date-image]][release-url]
[![license-image]][license-url]
[![codecov][codecov-image]][codecov-url]
[![jupyter-book-image]][docs-url]

<!-- Links: -->
[codecov-image]: https://codecov.io/gh/entelecheia/hyfi-lpg/branch/main/graph/badge.svg?token=wwvt5uOSYi
[codecov-url]: https://codecov.io/gh/entelecheia/hyfi-lpg
[pypi-image]: https://img.shields.io/pypi/v/hyfi-lpg
[license-image]: https://img.shields.io/github/license/entelecheia/hyfi-lpg
[license-url]: https://github.com/entelecheia/hyfi-lpg/blob/main/LICENSE
[version-image]: https://img.shields.io/github/v/release/entelecheia/hyfi-lpg?sort=semver
[release-date-image]: https://img.shields.io/github/release-date/entelecheia/hyfi-lpg
[release-url]: https://github.com/entelecheia/hyfi-lpg/releases
[jupyter-book-image]: https://jupyterbook.org/en/stable/_images/badge.svg

[repo-url]: https://github.com/entelecheia/hyfi-lpg
[pypi-url]: https://pypi.org/project/hyfi-lpg
[docs-url]: https://hyfi-lpg.entelecheia.ai
[changelog]: https://github.com/entelecheia/hyfi-lpg/blob/main/CHANGELOG.md
[contributing guidelines]: https://github.com/entelecheia/hyfi-lpg/blob/main/CONTRIBUTING.md
<!-- Links: -->

HyFI-LPG is a powerful HyFI plugin for seamless integration and utilization of large language models in text processing and analysis tasks, enabling efficient workflows for researchers and practitioners.

- Documentation: [https://hyfi-lpg.entelecheia.ai][docs-url]
- GitHub: [https://github.com/entelecheia/hyfi-lpg][repo-url]
- PyPI: [https://pypi.org/project/hyfi-lpg][pypi-url]

HyFI-LPG is a powerful plugin for the HyFI framework, designed to streamline the integration and utilization of large language models (LLMs) in text processing and analysis tasks. This plugin aims to provide researchers and practitioners with a seamless and efficient workflow, enabling them to harness the full potential of LLMs for various applications.

With HyFI-LPG, users can easily incorporate state-of-the-art language models into their projects, leveraging their advanced capabilities for natural language understanding, generation, and manipulation. The plugin offers a user-friendly interface and a comprehensive set of tools and utilities, making it accessible to both novice and experienced users.

## Changelog

See the [CHANGELOG] for more information.

## Contributing

Contributions are welcome! Please see the [contributing guidelines] for more information.

## License

This project is released under the [MIT License][license-url].
nbb-api 0.1.11
Python package for easy access to Brazilian basketball data: NBB (Novo Basquete Brasil), Liga Ouro and LDB
License: MIT
Requires Python: >=3.6
Keywords: nbb, novo basquete brasil, scraper, basketball, international basketball, brazil, ldb, liga-ouro

<p align="center">
<img src="https://user-images.githubusercontent.com/57769272/224566374-c8c748c7-c663-489f-8b98-d7041ab4092a.png" width="150">
</p>
<p align="center">
    <a href="https://pypi.org/project/nbb-api/">
        <img src="https://img.shields.io/pypi/v/nbb-api" alt="pypi" />
    </a>
    <a href="https://pypi.org/project/nbb-api/">
        <img src="https://img.shields.io/pypi/pyversions/nbb-api" alt="python version" />
    </a>
    <a href="https://pypi.org/project/nbb-api/">
        <img src="https://img.shields.io/pypi/l/nbb-api" alt="license" />
    </a>
</p>

# nbb_api

Python package for easy access to Brazilian basketball data through scraping of [LNB](https://lnb.com.br/) website.

This allows users to obtain statistics, standings, and scores for various seasons and phases of the following tournaments:
- **NBB** (Novo Basquete Brasil)
- **LDB** (Liga de Desenvolvimento de Basquete)
- **Liga Ouro**

## Installing
### Via `pip`
This library was written as an exercise for creating my first PyPi package. Hopefully you will find it valuable!
Install with the following command:

```
pip install nbb-api
```

## Documentation
For documentation about the API methods refer to [the documentation](https://github.com/GabrielPastorello/nbb_api/blob/main/API.md).

## Example of use
```
from nbb_api import nbb
```

```
nbb.get_stats('2022-23','regular','cestinhas').head()
```
Output:
|     | Jogador       | Equipe          | JO | Min   | Pts   | 3P      | 2P    | LL   | Camisa | Temporada |
| --- | ------------- | --------------- | -- | ----- | ----- | ------- | ----- | ---- | ------ | --------- |
| 0   | McClanahan    | Fortaleza B. C. | 27 | 34.11 | 20.89 | 6.11    | 10.89 | 3.89 | 22     | 2022-23   |
| 1   | Antonio       | UNIFACISA       | 26 | 31.74 | 17.96 | 6.00    | 8.85  | 3.12 | 11     | 2022-23   |
| 2   | Thomas        | Corinthians     | 27 | 32.13 | 17.67 | 5.44    | 8.15  | 4.07 | 0      | 2022-23   |
| 3   | Lucas Mariano | Sesi Franca     | 22 | 27.41 | 17.59 | 7.23    | 7.64  | 2.73 | 28     | 2022-23   |
| 4   | Lucas Dias    | Sesi Franca     | 20 | 30.65 | 17.50 | 5.85    | 8.60  | 3.05 | 9      | 2022-23   |

Use it wisely!
armaclass 0.2.2
Python parser and generator for Arma class definitions (e.g. sqm files)
License: MIT
Keywords: arma pbo sqm class parser generator

## Status

[![Build Status](https://travis-ci.org/overfl0/Armaclass.svg?branch=master)](https://travis-ci.org/overfl0/Armaclass)

## About
This is a Python parser for Arma 3 class definitions such as those appearing inside unrapified mission files.

It's based on [Fusselwurm's arma-class-parser](https://github.com/Fusselwurm/arma-class-parser) that is written
JavaScript.

I grew tired of using it in conjunction with PyExecJS (complicated to set up and needing to patch things up on
Windows) and py2js (too slow to parse even 300KB sqm files) and decided to port the original JavaScript code to
Python.

## Installation

```
pip install armaclass
```

## Usage
#### Parse the values from a string
```python
In [1]: import armaclass

In [2]: armaclass.parse('version=12;\n\nclass Moo  {\r\n value = 1; };')
Out[2]: {'Moo': {'value': 1.0}, 'version': 12.0}
```

#### Keep the values ordered as they were in the original file
```python
In [3]: armaclass.parse('version=12;\n\nclass Moo  {\r\n value = 1; };', keep_order=True)
Out[3]: OrderedDict([('version', 12.0), ('Moo', OrderedDict([('value', 1.0)]))])
```

Note: Starting with Python 3.7 onwards, dicts are always ordered so it
doesn't matter if you use `keep_order` or not.

#### Generate the files based on a parsed (or manually created) structure
```python
In [4]: from collections import OrderedDict
In [5]: structure = OrderedDict([('version', 12.0), ('Moo', OrderedDict([('value', 1.0)]))])
In [6]: print(armaclass.generate(structure))
version=12;

class Moo
{
    value=1;
};
```

#### Indent with tabs instead of spaces
```python
In [7]: print(armaclass.generate(structure, indent=1, use_tabs=True))
version=12;

class Moo
{
        value=1;
};
```

## Extending the generator
You can use this library to write a program that will port your Arma class files to DayZ, for example.
To do so, you will need to create your own generator by subclassing `armaclass.generator.Generator` and implementing
your own methods (the ones raising `NotImplemented`).

## Development
### Notes
The naming conventions may not match Python's pep8 as I was trying to stay close to the original parsing names to
facilitate porting. Those (internal) names may be changed in the future.

### Making code changes 
- Create a virtualenv using your preferred method (mkvirtualenv, venv, etc...)
- `pip install -r requirements.txt`
- Write code AND tests
- `pytest` to test run your tests
- `ptw -n` if you want `pytest` to automatically be called whenever
  you save any file from the project

## Contributing
If you feel something is missing or plain wrong, feel free to submit a Pull Request. You are encouraged to submit the
same PR/suggestion to the original [arma-class-parser](https://github.com/Fusselwurm/arma-class-parser) as well.