semvec/pypi-packages huggingface dataset:
csmpy 0.2
Color scheme manager package for your projects
License: MIT
Requires Python: >=3

# csmpy

The csmpy python package (color scheme manager) for your projects enabling customization and management of color schemes.

## Installation

Install the package:

> With pip or pip3

```python
pip install csmpy
```

Add it to your `requirements.txt` file:

```python
csmpy>=<version>
```

Now you can install it by running:

```python
pip install -r requirements.txt
```

## Usage

> Feel free to customize the variable name according to your preference!

### Without YAML file

```python
from csmpy import ColorSchemeManager

# Define values (required)
DEFAULT_COLORS = {
    'logo': 'red',
    'text': 'blue',
    'result': 'light_white',
}

# Load all colors
all_colors = ColorSchemeManager.load_colors(DEFAULT_COLORS)

# Example usage
logo_color = all_colors['logo']
text_color = all_colors['text']
result_color = all_colors['result']

print(f"This is a {logo_color} example of {text_color} using {result_color} colors.")

```

### With a YAML file

```python
from csmpy import ColorSchemeManager

# Define values (required)
DEFAULT_COLORS = {
    'logo': 'red',
    'text': 'blue',
    'result': 'light_white',
}

# Load custom colors from a YAML file
custom_colors = ColorSchemeManager.load_custom_yaml_file('examples/custom_settings.yaml')

# Merge default and custom colors
all_colors = ColorSchemeManager.load_colors(DEFAULT_COLORS, custom_colors)

# Example usage
logo_color = all_colors['logo']
text_color = all_colors['text']
result_color = all_colors['result']

print(f"This is a {logo_color} example of {text_color} using {result_color} colors.")
```

Both of these examples can be found in the `examples` folder.

## License

The source code is released under the [MIT License](LICENSE).
scope-ml 0.9.5
SCoPe: ZTF Source Classification Project
License: MIT
Requires Python: <3.12,>=3.9

# SCoPe: ZTF Source Classification Project

[![PyPI version](https://badge.fury.io/py/scope-ml.svg)](https://badge.fury.io/py/scope-ml)
[![arXiv](https://img.shields.io/badge/arXiv-2102.11304-blue)](https://arxiv.org/abs/2102.11304)
[![arXiv](https://img.shields.io/badge/arXiv-2009.14071-blue)](https://arxiv.org/abs/2009.14071)
[![arXiv](https://img.shields.io/badge/arXiv-2312.00143-blue)](https://arxiv.org/abs/2312.00143)

`scope-ml` uses machine learning to classify light curves from the Zwicky Transient Facility ([ZTF](https://www.ztf.caltech.edu)). The documentation is hosted at [https://zwickytransientfacility.github.io/scope-docs/](https://zwickytransientfacility.github.io/scope-docs/). To generate HTML files of the documentation locally, clone the repository and run `scope-doc` after installing.

## Funding
 We gratefully acknowledge previous and current support from the U.S. National Science Foundation (NSF) Harnessing the Data Revolution (HDR) Institute for <a href="https://a3d3.ai">Accelerated AI Algorithms for Data-Driven Discovery (A3D3)</a> under Cooperative Agreement No. <a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=2117997">PHY-2117997</a>.

 <p align="center">
 <img src="https://github.com/ZwickyTransientFacility/scope/raw/main/assets/a3d3.png" alt="A3D3" width="200"/>
 <img src="https://github.com/ZwickyTransientFacility/scope/raw/main/assets/nsf.png" alt="NSF" width="200"/>