semvec/pypi-packages huggingface dataset:
tinycio 0.8.1
A primitive, lightweight color management framework for PyTorch-involved projects
Requires Python: >=3.8

![tinycio](https://raw.githubusercontent.com/Sam-Izdat/tinycio/main/doc/images/tinycio_sm.png)

* [Project site & docs](https://sam-izdat.github.io/tinycio/) 
* [PyPi](https://pypi.org/project/tinycio/)

# About

Primitive, lightweight Python color library for PyTorch-involved projects. It implements color space conversion, tone mapping, LUT usage and creation, basic color correction and color balancing, and HDR-LDR encoding/decoding. 

# Getting started

* Recommended: set up a clean Python environment
* [Install PyTorch  as instructed here](https://pytorch.org/get-started/locally/)
* Run  `pip install tinycio`
* Run  `tcio-setup` (installs freeimage binaries; [iio docs on fi](https://imageio.readthedocs.io/en/stable/_autosummary/imageio.plugins.freeimage.html#module-imageio.plugins.freeimage))

[See the docs](https://sam-izdat.github.io/tinycio/) for the rest.
cas-qweqweaklsdjaslkdjal-do-util 0.1.0
Package for DO utilities
Requires Python: >=3.12


This package is developed and maintained by [Poetry](https://python-poetry.org/) with
[Poe the Poet](https://github.com/nat-n/poethepoet).

- [Prerequisite](#prerequisite)
- [Setup](#setup)
- [Usage](#usage)


## Prerequisite
```sh
pip install --upgrade pip
pip install pipx

pipx install poetry
pipx ensurepath
# pipx completions
```

## Setup
```sh
# set up pre-commit
poetry add pre-commit --dev
poetry run pre-commit install
poetry run pre-commit autoupdate

# set up wily
poetry add wily --dev
poetry run wily setup

poetry run pre-commit run --all-files
```

## Usage
```sh
# config the package repo
poetry config repositories.do-pe-repo https://pypi.org/
poetry config pypi-token.pypi ${PYPI_TOKEN}

# build the package
poetry build
# publish package to 
poetry publish
```
crc64fast 0.1.0
Python bindings for crc64fast-nvme Rust library
Requires Python: >=3.9

# python-crc64fast

Hashlib compatible Python bindings for [crc64fast-nvme](https://github.com/awesomized/crc64fast-nvme).  

## Usage

```Python
import crc64fast

hasher = crc64fast.crc64fast()

hasher.update(b"hello ")
hasher.update(b"world!")

print(hasher.hexdigest())
```

## License

`python-crc64fast` is dual-licensed under

* Apache 2.0 license ([LICENSE-Apache](./LICENSE-Apache) or <http://www.apache.org/licenses/LICENSE-2.0>)
* MIT license ([LICENSE-MIT](./LICENSE-MIT) or <https://opensource.org/licenses/MIT>)
snakemake-logger-plugin-sqlite 0.1.1
Snakemake logger plugin that writes logs to SQLite database.
Requires Python: <4.0,>=3.11

# Snakemake Logger Plugin: SQLite

## Introduction

The **Snakemake Logger Plugin: SQLite** is a custom logger plugin for Snakemake that writes workflow execution logs to a SQLite database. This plugin enables detailed tracking of workflows, rules, jobs, and associated files, providing a structured and queryable format for analyzing workflow execution.

## Usage
1. Install via pip: `pip install snakemake-logger-plugin-sqlite`
2. Run Snakemake with the `--logger sqlite` option to enable the SQLite logger. 

## Options
TODO

## Design

The plugin integrates with Snakemake's logging system and processes log events using SQLAlchemy models. It uses event handlers to parse and store log records in the database. The database schema is designed to capture key entities such as workflows, rules, jobs, and files, along with their relationships.

1. **Log Handler**:
   - The `sqliteLogHandler` class processes log records and delegates them to event handlers.
   - Manages database sessions and ensures transactional consistency.

2. **Event Handlers**:
   - Specialized handlers process specific log events (e.g., workflow start, job info, errors).
   - Handlers parse log records and update the database models accordingly.

3. **Database Models**:
   - SQLAlchemy models represent key entities such as workflows, rules, jobs, files, and errors.
   - Models capture attributes and relationships for comprehensive logging.

4. **Parsers**:
   - Parsers extract structured data from log records for storage in the database.

### Database Schema

The database schema is designed to capture the following entities:

- **Workflow**: Tracks workflow metadata (e.g., `id`, `snakefile`, `status`, `started_at`, `end_time`) and relationships to rules, jobs, and errors.
- **Rule**: Represents Snakemake rules with attributes like `id`, `name`, and relationships to jobs and errors.
- **Job**: Captures job execution details (e.g., `id`, `status`, `started_at`, `end_time`) and relationships to files.
- **File**: Represents input/output files with attributes like `path` and `file_type`.
- **Error**: Logs errors with details such as `exception`, `traceback`, and relationships to workflows and rules.

### Database Versions and Migrations

TODO

## Development

TODO

## Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository and create a new branch.
2. Make your changes and ensure all tests pass.
3. Submit a pull request with a detailed description of your changes.

## License

This project is licensed under the MIT License. See the `LICENSE` file for details.
mkdocs-gemini-chat 0.1.4
A Material for MkDocs plugin that adds a Gemini-powered chat window to documentation pages
Requires Python: >=3.8

# MkDocs Gemini Chat Plugin

A Material for MkDocs plugin that adds a Gemini-powered chat window to your documentation pages.

## Features

- Interactive chat window powered by Google's Gemini 2.5 Pro
- Chat history and context support
- Multiple language support
- Version-specific documentation support
- File path specification
- Copy/download functionality
- Customizable UI position

## Installation

```bash
pip install mkdocs-gemini-chat
```

## Configuration

1. First, obtain a Gemini API key from [Google AI Studio](https://makersuite.google.com/app/apikey).

2. Add your API key to your environment:
   ```bash
   # In your .env file or export in your shell
   export GEMINI_API_KEY=your_api_key_here
   ```

3. Add the plugin to your `mkdocs.yml`:
   ```yaml
   plugins:
     - gemini-chat:
         # Optional: Configure UI position
         position: bottom-right  # Options: bottom-right, bottom-left, top-right, top-left
         # Optional: Set default language
         default_language: en
         # Optional: Set documentation version
         version: latest
   ```

## Usage

Once configured, the chat window will appear on your documentation pages. Users can:

- Ask questions about the documentation
- Specify file paths for context
- Change language settings
- Access version-specific information
- Copy or download chat responses

## Requirements

- Python 3.8 or higher
- A valid Gemini API key
- MkDocs 1.0.0 or higher

## Development

To contribute or run tests:

```bash
# Clone the repository
git clone https://github.com/nolanblevins/mkdocs-gemini-chat.git
cd mkdocs-gemini-chat

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/
```

## License

MIT License - see LICENSE file for details.

## Original Requirements

<details>
<summary>Click to expand</summary>

Requirements:
As a user, I can use a chat window to ask questions about the documentation on the Material for MkDocs project.
UX Features:
- The chat window should be able to use the chat history.
- The chat window should be able to use the chat context.
- The chat windows should use Gemini 2.5 Pro as the LLM.
- The chat window should allow follow up questions.
- The chat window should allow the user to specify the file path to the documentation.
- The chat window should allow the user to specify the language of the documentation.
- The chat window should allow the user to specify the version of the documentation.
- The chat window should allow the user to copy the output to the clipboard.
- The chat window should allow the user to download the output as a file. 

Implementation:
- The implementation should be done as a Material for MkDocs plugin.
- The plugin should be able to be added to the documentation site by adding it to the `mkdocs.yml` file.
- The plugin should allow the user to specify where the UI box should be placed in the documentation site.

</details>

## References

- [DeepWiki](https://deepwiki.com)
- [DeepSeek Chat](https://www.deepseek.com/chat/)