semvec/pypi-packages huggingface dataset:
glasswool 1.0.2
Outlier filter
Requires Python: >=3.10,<3.11

# glasswool

Outlier filter

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Recursively filter outliers

## Installation

`pip install glasswool`
installer 0.7.0
A library for installing Python wheels.
Requires Python: >=3.7

# installer

<!-- start readme-pitch -->

This is a low-level library for installing a Python package from a
[wheel distribution](https://packaging.python.org/glossary/#term-Wheel). It
provides basic functionality and abstractions for handling wheels and installing
packages from wheels.

- Logic for "unpacking" a wheel (i.e. installation).
- Abstractions for various parts of the unpacking process.
- Extensible simple implementations of the abstractions.
- Platform-independent Python script wrapper generation.

<!-- end readme-pitch -->

You can read more in the [documentation](https://installer.rtfd.io/).
paradime 1.1.0
A framework for parametric dimensionality reduction
Requires Python: >=3.7

ParaDime: A Framework for Parametric Dimensionality Reduction
=============================================================

|ReadTheDocs Badge|  |License Badge|  |PyPi Badge|  |Black Badge|

ParaDime is a modular framework for specifying and training parametric dimensionality reduction (DR) models. These models allow you to add new data points to existing low-dimensional representations of high-dimensional data. ParaDime DR models are constructed from simple building blocks (such as the relations between data points), so that experimentation with novel DR techniques becomes easy.

Installation
============

ParaDime is available via PyPi through:

.. code-block:: text

    pip install paradime

ParaDime requires `Numpy <https://numpy.org/>`_, `SciPy <https://scipy.org/>`_, `scikit-learn <https://scikit-learn.org/>`_, and `PyNNDescent <https://github.com/lmcinnes/pynndescent>`_  (see |req text|_ file), all of which are installed auomatically when installing ParaDime.

ParaDime also requires `PyTorch <https://pytorch.org/>`_, which must be installed separately. If you want to train ParaDime routines on the GPU, make sure to install CUDA along with the correct ``cudatoolkit`` version. See the `PyTorch docs <https://pytorch.org/get-started/locally/>`_ for detailed installation info.

If you want to use ParaDime's plotting utilities, `Matplotlib <https://matplotlib.org/>`_ has to be installed additionally.

.. |req text| replace:: ``requirements.txt``
.. _req text: https://github.com/einbandi/paradime/blob/master/requirements.txt

Documentation
=============

For a simple example with one of the predefined ParaDime routines, see `Simple Usage <https://paradime.readthedocs.io/en/latest/simple_usage.html>`_ in the documentation.

More detailed information about how to set up cusom routines can be found in `Building Blocks of a ParaDime Routine <https://paradime.readthedocs.io/en/latest/building_blocks.html>`_.

For additional examples of varying complexity, see `Examples <https://paradime.readthedocs.io/en/latest/examples.html>`_.

References
==========

.. [1] Van Der Maaten, L., Hinton, G. `“Visualizing data using t-SNE” <http://www.jmlr.org/papers/volume9/vandermaaten08a/vandermaaten08a.pdf>`__, Journal of Machine Learning Research (2008).

.. [2] LeCun, Y., Cortes, C., Burges, C.J.C. `“The MNIST database of handwritten digits” <http://yann.lecun.com/exdb/mnist/>`__ (1998).


.. |ReadTheDocs Badge| image:: https://readthedocs.org/projects/paradime/badge/?version=latest&style=flat-square
   :target: https://paradime.readthedocs.io/en/latest/index.html
   :alt: Documentation Status

.. |License Badge| image:: https://img.shields.io/github/license/einbandi/paradime?style=flat-square
   :target: https://mit-license.org/
   :alt: License

.. |PyPi Badge| image:: https://img.shields.io/pypi/v/paradime?style=flat-square
   :target: https://pypi.org/project/paradime/
   :alt: PyPi Version

.. |Black Badge| image:: https://img.shields.io/badge/code%20style-black-black?&style=flat-square
   :target: https://github.com/psf/black
   :alt: Code Style
ChatChess 1.0.12
A package to play chess with ChatGPT

# ChatChess
A simple python package to play chess with ChatGPT

## Installation

```python
pip install chatchess
```

## Usage

Import the package:

```python

import ChatChess
```

First a `Game` object needs to be decalerd as follows:
```python
bot = ChatChess.Game("OPENAI_API_KEY")
```

### Additional parameters:

- `bot.maxTokens = 10`: Set max_tokens passed to ChatGPT on each move
- `bot.maxFails = 5`: Amount of times to retry sending prompt to ChatGPT when invalid move is returned
- `bot.prompt = {"normal" : "", "failed" : "", "start" : ""}`: The prompts to send to ChatGPt at each game state
- `bot.board = chess.Board()`: Chess board object
- `bot.message = ""`: Set to move into after each GPT move
- `bot.printDebug = False`: Print debug info - occaisonaly useful

### Functions

**Main functions**

- `move = bot.play("e4")`: Plays the player's move, then ChatGPT's response - returns ChatGPT's move
- `move = getGPTMove()`: Plays ChatGPT's move in the current position - returns ChatGPT's move

**Other functions**

- `bot.pushPlayerMove("e4")`: Push a move without ChatGPT responding
- `prompt = bot.createPrompt()`: Creates prompt to send to ChatGPT based on current position and previous fails - returns prompt
- `response = bot.askGPT(prompt)`: Queries ChatGPT prompt based on set parameters
- `move = bot.handleResponse(response)`: Gets move from reponse - returns move

## Examples

### Simple player vs ChatGPT game

```python

import ChatChess

bot = ChatChess.Game("OPENAI_API_KEY")  # Set API key

while True:
    print(bot.board())  # Print the board
    bot.play(input("Make a move: "))  # Ask player to make a move, then ChatGPT responds
    if bot.board.is_game_over():  # Break if game over
        break
```

### Simple ChatGPT vs ChatGPT game from a set position

```python
import chess
import chess.fen
import ChatChess

bot = ChatChess.Game("OPENAI_API_KEY")  # Set API key
bot.board = chess.Board("rnbq1bnr/ppppkppp/8/4p3/4P3/8/PPPPKPPP/RNBQ1BNR w - - 2 3")  # Set position

while True:
    bot.getGPTMove()  # Ask ChatGPT to make a move
    print(bot.message)  # Print move and info
    if bot.board.is_game_over():  # Break if game over
        print(str(chess.pgn.Game.from_board(bot.board)))
        break
```

## Info
### Uses
- python-chess - https://github.com/niklasf/python-chess
- openai-python - https://github.com/openai/openai-python