semvec/pypi-packages huggingface dataset:
ls-r2x4 0.2.0rc1
Interface the R2X4 light source from Industrialise.
Requires Python: <3.14,>=3.8

Driver package for the R2X4 light source from [Industrialise](www.industrialise.be).

# Installation
The package can be installed from the wheel file:
```bash
pip install ls_r2x4-0.2.0-py3-none-any.whl
```

There is an optional Qt based widget available, next to a tkinter based one.
The Qt widget uses `QtPy` to abstract the Qt backend. The package can be installed with:

```bash
pip install qtpy
```

The actual Qt backend needs to be installed separately. For example, to use the PySide2 backend:

```bash
pip install PySide2
```

QtPy5 and PySide6 are also supported. Checkout the `QtPy` [documentation](https://pypi.org/project/QtPy/) for information on which version of backend 
is supported by which version of `QtPy`.

There is also a `R2X4Panel` available for use in [Gamma Desk](https://pypi.org/project/gamma-desk/) which makes use of the Qt widget. Check the 
`ls_r2x4.gui.gdesk_panel` module for more information. To install Gamma Desk:
    
```bash
pip install gamma-desk
```

# Usage
## Demo

A demo is started when the package is run as a script:
```bash
python -m ls_r2x4
```

These top level scripts are available when the python environment is active:

  - `r2x4_gui_tkinter` : Start the GUI using the tkinter backend.
  - `r2x4_gui_qt`: Start the GUI using a Qt backend. This is needs pyqt or pyside to be installed!
  - `r2x4_demo`: Start the same demo as when the package is run as a script.

More demo scripts are available in the ls_r2x4.demo.demo module.

For jupyter lab users there is also a demo jupyter notebook available in the ls_r2x4.demo folder.

## Programming API

The main class to use is the `LightSourceR2X4` class. It is located in the ls_r2x4.r2x4 module.

```python
from ls_r2x4.r2x4 import LightSourceR2X4
ls = LightSourceR2X4()
```

A serial port name can be passed to the constructor, if left None it will try to find the correct port automatically.

Once the instance is created, the light source can be controlled using the methods and attributes of the class.

```python
import time
ls.triggering_force_a_channels()
ls.blue_a.value = 5  # set the blue a channel to 5%
ls.red_b.value = 3  # set the red b channel to 3%
time.sleep(2)
ls.triggering_force_b_channels()
time.sleep(1)
ls.blue_a.value = 0  # turn back off
ls.red_b.value = 0
```

Checkout the demo scripts for more examples.
ind-ls-r2x4 0.2.0rc1
Interface the R2X4 light source from Industrialise.
Requires Python: <3.14,>=3.8

Driver package for the R2X4 light source from [Industrialise](www.industrialise.be).

# Installation
The package can be installed from the wheel file:
```bash
pip install ls_r2x4-0.2.0-py3-none-any.whl
```

There is an optional Qt based widget available, next to a tkinter based one.
The Qt widget uses `QtPy` to abstract the Qt backend. The package can be installed with:

```bash
pip install qtpy
```

The actual Qt backend needs to be installed separately. For example, to use the PySide2 backend:

```bash
pip install PySide2
```

QtPy5 and PySide6 are also supported. Checkout the `QtPy` [documentation](https://pypi.org/project/QtPy/) for information on which version of backend 
is supported by which version of `QtPy`.

There is also a `R2X4Panel` available for use in [Gamma Desk](https://pypi.org/project/gamma-desk/) which makes use of the Qt widget. Check the 
`ls_r2x4.gui.gdesk_panel` module for more information. To install Gamma Desk:
    
```bash
pip install gamma-desk
```

# Usage
## Demo

A demo is started when the package is run as a script:
```bash
python -m ls_r2x4
```

These top level scripts are available when the python environment is active:

  - `r2x4_gui_tkinter` : Start the GUI using the tkinter backend.
  - `r2x4_gui_qt`: Start the GUI using a Qt backend. This is needs pyqt or pyside to be installed!
  - `r2x4_demo`: Start the same demo as when the package is run as a script.

More demo scripts are available in the ls_r2x4.demo.demo module.

For jupyter lab users there is also a demo jupyter notebook available in the ls_r2x4.demo folder.

## Programming API

The main class to use is the `LightSourceR2X4` class. It is located in the ls_r2x4.r2x4 module.

```python
from ls_r2x4.r2x4 import LightSourceR2X4
ls = LightSourceR2X4()
```

A serial port name can be passed to the constructor, if left None it will try to find the correct port automatically.

Once the instance is created, the light source can be controlled using the methods and attributes of the class.

```python
import time
ls.triggering_force_a_channels()
ls.blue_a.value = 5  # set the blue a channel to 5%
ls.red_b.value = 3  # set the red b channel to 3%
time.sleep(2)
ls.triggering_force_b_channels()
time.sleep(1)
ls.blue_a.value = 0  # turn back off
ls.red_b.value = 0
```

Checkout the demo scripts for more examples.
fscolor 0.1.2
Color formatting for f-strings
Requires Python: >=3.6

# 🌈 fscolor - F-String Color Formatting for Python

[![PyPI Version](https://img.shields.io/pypi/v/fscolor.svg)](https://pypi.org/project/fscolor/)
[![Python Versions](https://img.shields.io/pypi/pyversions/fscolor.svg)](https://pypi.org/project/fscolor/)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/Kunlex58/fscolor/blob/main/LICENSE)


**fscolor** is a lightweight Python package that brings effortless color formatting to f-strings using ANSI escape codes. Designed for simplicity and readability, it enables developers to create vibrant console output with minimal code changes.

## Features ✨


- 🎨 **8 Basic Colors**: Black, Red, Green, Yellow, Blue, Magenta, Cyan, White
- 🔄 **Automatic Reset**: No need to manually reset colors

- 💻 **Cross-Platform**: Works on most modern terminals
- 🚀 **Zero Dependencies**: Pure Python implementation

- 📦 **F-String Ready**: Designed specifically for Python 3.6+ formatted strings
- 🔧 **Extensible Architecture**: Easily add custom colors or styles

## Installation 📦

```bash
pip install fscolor
```

## Use Cases

Examples - See [Jupyter Notebook](https://github.com/Kunlex58/fscolor/blob/main/fscolor.ipynb) for various use cases.


## Compatibility Notes ⚠️


- Requires terminal supporting ANSI escape codes  
- Colors may appear different based on terminal theme  

- Not recommended for file output or non-TTY devices  

## Roadmap 🗺️


- 256-color support  
- Background colors  

- Text styles (bold, italic, underline)  
- Windows compatibility layer  

## Contributing 🤝

Contributions welcome! Please check later for details.

## License 📄

MIT License - See [LICENSE](https://github.com/Kunlex58/fstrcolor/blob/main/LICENSE) for details.
manzara 0.1.2
A Python package for simulating fitness landscapes
Requires Python: >=3.12

<h1 align="center">
<img src="logo.png" height="150">
</h1><br>

Manzara is a Python (>=3.12) package for simulating and analyzing fitness landscapes.
It's designed in terms of three main classes: sequences (`manzara.Seq`), sequence spaces (`manzara.Space`), and fitness landscapes (`manzara.FitnessLandscape`), the last of which is the superclass of specific fitness landscape models.
See [demo.ipynb](demo.ipynb) for more.
To install, run `pip install manzara` at the command line.
Feel free to make pull requests if you'd like to contribute e.g. new models or landscape properties.