semvec/pypi-packages huggingface dataset:
covador 0.10.2
Python data validation with web in-mind
License: MIT

covador
=======

|travis| |coverage| |pyver|

.. |travis| image:: https://travis-ci.org/baverman/covador.svg?branch=master
   :target: https://travis-ci.org/baverman/covador

.. |coverage| image:: https://img.shields.io/badge/coverage-100%25-brightgreen.svg

.. |pyver| image:: https://img.shields.io/badge/python-2.6%2C_2.7%2C_3.4%2C_3.5%2C_3.6%2C_3.7%2C_3.8%2C_pypy-blue.svg


Validation library for processing http endpoint arguments.

.. code:: python

    from flask import Flask

    from covador import split, opt
    from covador.flask import query_string

    app = Flask(__name__)

    @app.route('/')
    @query_string(foo=opt(split(int), []))
    def csv_argument(foo):
        return repr(foo)

    # GET /?foo=1,2,3 -> [1, 2, 3]

    if __name__ == '__main__':
        app.run()


* Support for flask(0.x, 1.0.x, 1.1.x), django(1.x, 2.x), aiohttp(2.x, 3.x),
  tornado(3.x, 4.x, 5.x, 6.x) and sanic(0.x, 18.x, 19.x).
* Simple creating of custom ``query_string``/``form``/``params``/``json_body``/``args`` wrappers.
* Multi dict support via item ``multi`` param.
* Multi dict keys support via item ``src`` param.
* Simple interface for custom validators/processors it's just a callable.
* Maps, typed Maps, Lists, Tuples, Enums.
* Validation chains: ``opt(default=[]) | split(separator=' ') | List(int) | (lambda it: it[:10])``
  or more concise ``opt(split(int, separator=' '), []) | operator.itemgetter(slice(10))`` —
  an optional argument of space separated integers and we need top 10 items from it and it
  is empty by default.
* Literal schema: ``schema(foo=[{'boo': int}])``, validates ``{'foo': [{'boo': 10}, {'boo': 20}]}``.
* Bytes/unicode aware.
derevo 0.1.2
Collection of methods to generate stable plants collections based on their cohabitation and outer limitations
License: MIT
Requires Python: >=3.9

# Derevo library

This is a standalone module which can be installed and used without plants backend and frontend.

It contains methods to generate stable plants compotions.

## Installation

0. Prepare virtual environment with `venv` if you need
1. Install with `python -m pip install .`

Wheel can be built the same way, by running `python -m build .` (you would need to install `build` package before that).
To install package from .wheel, use `python -m wheel install dist/derevo-0.1.0-py3-none-any.whl`.

Following packages are need to be installed on your system to successfully build the module: `build virtualenv`

All commands are presented in Makefile for reference.

## Running an example

1. Set environment variables from [envfile](.env.example), you would need a database with plants, limitations and others
2. launch `make run-example` or launch manually with `python -m example`

## Packing in docker for a backend service

For the backend docker image to build, `derevo` must be installed in it. As they are in different directories,
  and `derevo` is not on PyPi yet, it was decided to be a best way to store built wheel rosource in a dummy
  container called `local/derevo`. It should be built using `make docker-build` before building backend image.


## Development

For development purposes it is better to use _editable install_ with `python -m pip install -e .` - so when you change
  the content of the module, there is no need to perform reinstall.

In some cases VS Code Pylance and other analyzer tools report missing module, then you need to either configure them
  properly (in case of Pylance, add `"python.analysis.extraPaths": ["<project_dir>/method"]`
  to .vscode/settings.json) or make a strict installation:
  `python -m pip install -e . --config-settings editable_mode=strict`.
  The second option is better, in case of adding new files a reinstallation will be needed
harmon 0.2.0
A chess engine that considers human mistakes
License: MIT
Requires Python: >=3.9,<4.0

# Harmon Chess Engine

<!-- ![Harmon Chess Engine Logo](./images/logo.png) -->

Harmon Chess Engine is a cutting-edge chess engine that leverages the power of transformer-based machine learning models to revolutionize the world of computer chess. Unlike traditional chess engines, Harmon is designed to understand and exploit human mistakes, making it a formidable opponent for chess players of all levels.

## Features

- **Transformer-Powered Chess Engine**: Harmon uses state-of-the-art transformer models to predict human moves, allowing it to adapt its strategy based on the tendencies and mistakes commonly made by human players.

- **Human Mistake Exploitation**: Harmon's unique approach allows it to identify and capitalize on common human errors, giving it a strategic advantage in games.

- **Game Analysis**: Analyze your chess games to gain insights into your playing style and improve your skills. Harmon can provide detailed game summaries, identify key turning points, and suggest areas for improvement.

- **Elo Prediction**: Harmon can estimate the Elo rating of chess players based on their game performance, helping players gauge their progress and understand their strengths and weaknesses.

- **Game Outcome Prediction**: Harmon can predict the likely outcome of a chess game, providing players with valuable insights into the flow and dynamics of the match.

## Getting Started

### Installation

```bash
pip install harmon
```

### Usage

1. Train the model with your preferred dataset, such as PGN files from lichess.

2. Configure Harmon's settings and model parameters to suit your needs.

3. Run Harmon to analyze games, predict outcomes, or play chess against it.

### Example Usage

#### Train the model

```bash
python -m harmon.train
```

#### Generate

```bash
python -m harmon.generate
```

## Contributing

We welcome contributions from the open-source community! If you're interested in improving Harmon Chess Engine or adding new features, please see our [Contribution Guidelines](CONTRIBUTING.md) for details on how to get started.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Acknowledgments

- The Harmon Chess Engine project is inspired by the fascinating world of chess and the advancements in machine learning and artificial intelligence.

- Special thanks to the contributors and developers who have made this project possible.

---

**Disclaimer:** Harmon Chess Engine is a research project and may not be suitable for professional or competitive chess use. Use it for educational and recreational purposes, and have fun exploring the world of chess!
zondocs-theme 1.0.8
Sphinx theme for ZEIT ONLINE docs
License: MIT
Requires Python: >=3.7

======================================
New shiny Sphinx Theme for ZEIT ONLINE
======================================

Usage
-----

Install the package

.. code-block:: text

    $ pip install zondocs_theme

Then set ``html_theme = 'zondocs_theme'`` in your Sphinx ``conf.py``.

Features
--------

* Automatically uses the ZON logo.
* Adds an "edit this page" link to the sidebar. To customize how this link is
  created, you can set the following::

    html_theme_options = {
        'editme_link': (
            'https://github.com/zeitonline/{project}/edit/master/{page}')
    }

  (This is the default value, it supports two variables, ``project`` is taken
   directly from ``conf.py``, and ``page`` evaluates to
   ``path/to/current/page.suffix``)


Local testing
-------------

Run ``bin/build`` to build whl and use ``pip install zondocs_theme...whl`` to use it in your project.


Release process
---------------

`pipenv` is needed to run the release process.

Update the version in ``pyproject.toml``.

For a `test <https://test.pypi.org/project/zondocs-theme/>`_ release run

.. code-block:: text

    $ bin/release test

For a offical release run

.. code-block:: text

    $ bin/release prod