semvec/pypi-packages huggingface dataset:
PyDocSmith 0.1.5
It parses and composes docstrings in Google, Numpydoc, ReST and Epydoc.
Requires Python: >=3.6

The project is a fork from the original project - https://github.com/rr-/docstring_parser/



# PyDocSmith

PyDocSmith is a versatile Python package designed for parsing, detecting, and composing docstrings in various styles. It supports multiple docstring conventions, including reStructuredText (reST), Google, NumPydoc, and Epydoc, providing flexibility in documentation practices for Python developers.

## Features

- **Docstring Style Detection:** Automatically detect the style of docstrings (e.g., reST, Google, NumPydoc, Epydoc) using simple heuristics.
- **Docstring Parsing:** Convert docstrings into structured representations, making it easier to analyze and manipulate documentation.
- **Docstring Composition:** Render structured docstrings back into text, allowing for automated docstring generation and modification.
- **Attribute Docstrings:** Parse attribute docstrings defined at class and module levels, enhancing the documentation of class properties and module-level variables.

## Installation

```bash
pip install PyDocSmith
```

## Usage

### Detecting Docstring Style

Detect the docstring style of a given text:

```python
from PyDocSmith import detect_docstring_style, DocstringStyle

docstring = """
This is an example docstring.
:param param1: Description of param1
:return: Description of return value
"""
style = detect_docstring_style(docstring)
print(style)  # Outputs: DocstringStyle.EPYDOC
```

### Parsing Docstrings

Parse a docstring into its components:

```python
from PyDocSmith import parse, DocstringStyle

parsed_docstring = parse(docstring, style=DocstringStyle.AUTO)
print(parsed_docstring)
```

### Composing Docstrings

Render a parsed docstring back into text:

```python
from PyDocSmith import compose

docstring_text = compose(parsed_docstring, style=DocstringStyle.REST)
print(docstring_text)
```

## Advanced Features

- **Parse From Object:** PyDocSmith can parse docstrings directly from Python objects, including classes and modules, incorporating attribute docstrings into the structured representation.
- **Custom Rendering Styles:** Customize the rendering of docstrings with compact or detailed styles, and specify custom indentation for the generated docstring text.

## Things that have been modified wrt to docstring_parser

1. Better heuristics to detect docstring style
2. Google Docstring has been modified to accommodate Notes, Examples
3. Sometime GoogleDoc string doesn't have proper indentation specially when generated from LLMs like GPT or Mistral. PyDocSmith can fix those bad docstrings.
4. Additional test-cases were added to accommodate a different style of GoogleDocstring

I have updated it based on use case for - https://www.penify.dev

## Contributing

Contributions are welcome! Please submit pull requests or report issues on the project's GitHub page.
zftracker 0.0.8
Python library for tracking group of zebrafish
Requires Python: >=3.9

# zftracker

![Python Version](https://img.shields.io/badge/python-3.9-blue.svg)

![License](https://img.shields.io/badge/license-GPLv3-blue.svg)

![Development Status](https://img.shields.io/badge/status-PreAlpha-orange.svg)

`zftracker` is a Python library for tracking groups of zebrafish. This tool is designed to help researchers and scientists easily track and analyze the behavior of zebrafish in a group setting. The project is still under development and models are currently not available to the public. We plan to release model files in the future.

## Features

- Track multiple zebrafish simultaneously
- Export data for further analysis
- Easy-to-use API
- 10~20x performance compared to previous systems

## Status

**Note:** This project is in the Alpha stage. The main functionality has been tested, but there are still many features to be implemented. Use with caution and report any issues you encounter.

## Installation

You can install `zftracker` using pip:

```bash
pip install zftracker
```

## License

This project is licensed under the GNU General Public License v3.0 - see the [LICENSE](LICENSE) file for details.

## Contact

For any questions or issues, please open an issue on [GitHub](https://github.com/yourusername/zftracker/issues) or contact the author:

- **Author:** Junhao An
- **Email:** anjunhao_23@163.com

## AI-Generated Code

Please note that part of the code in this project has been generated with the assistance of Language Learning Models (LLMs). While every effort has been made to ensure the accuracy and functionality of the code, further testing and review are recommended.

## Update Log

`0.0.7` First release.

---

*This project is maintained by Junhao An.*
libschrodinger 1.3.2
A small package for simulating quantum-scale physics.
Requires Python: >=3.8

# A Python library/web app to simulate quantum-scale physics

Features include (but not limited to):

- create particles in a simulated environment
- create potential fields to account for external forces
- propagate particles (using the titular Schrödinger's equation)
- draw and animate graphs
- ~~access boundary error, core dumped~~ totally not run out of memory
  - on the other hand, Python.

# Library

[examples](./examples/README.md)

## Instalation

```
pip install --upgrade libschrodinger
```

# Web UI

![schreenshot showing app UI where people can create and edit particles](https://github.com/1p22geo/schrodinger/raw/master/static/media/png/screenshot.png)

## Static deployment

[github pages](https://1p22geo.github.io/schrodinger)

[docs](https://1p22geo.github.io/schrodinger/doc/)

Includes everything except for the user experiment engine.
All static files and tutorials included.

## Deploying it yourself

- Install python 3.10 or newer
- First install the required libraries:
  - flask
  - numpy
  - scipy
  - matplotlib
- Install [ffmpeg](https://ffmpeg.org)
- Run the app

```shell
$ python -m flask run -h 0.0.0.0
```

## Running tests

All the dependencies for regular running are needed, together with `pytest`.

Run in your terminal:

```shell
$ python -m pytest
```