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This packages contains some color Palettes that are very important for visualizing graphs and doing other stuffs.

Project description

📘 pigmenta

  • Version: 0.0.2
  • License: MIT
  • Author: Crispen Gari
  • Python Compatibility: Python 3.9+

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🌈 Overview

pigmenta is a lightweight Python package that provides easy access to a curated collection of beautiful color palettes. It is designed for developers, designers, data scientists, and artists who want to use harmonious and theme-based color palettes in visualizations, UI design, machine learning plots, or generative art.

🚀 Features

  • Access over 30 named color palettes.
  • Themes include: pastel, vintage, neon, sunset, earth, skin, space, and more.
  • Easy integration with libraries like Matplotlib, Seaborn, Plotly, or your own app.
  • Simple API via a class or dictionary.
  • Extensible and open-source.

📦 Installation

pip install pigmenta

Note: You can install it directly from a GitHub repo:

pip install git+https://github.com/yourusername/pigmenta.git

🧪 Usage

First you need to start by importing the package.

from pigmenta import PALETTES

You can access the color pallets as follows:

# Get a pastel palette
colors = PALETTES.pastel
print(colors)

Example with Matplotlib

import matplotlib.pyplot as plt
from pigmenta import PALETTES

colors = PALETTES.sunset

plt.bar([1, 2, 3], [3, 5, 2], color=colors[:3])
plt.title("Bar chart using pigmenta")
plt.show()

🎨 Available Palettes

Here are the palette names you can access via PALETTES.<name>:

pastel, vintage, retro, neon, gold, light, dark, warm, cold,
summer, fall, winter, spring, happy, nature, earth, night, space,
rainbow, gradient, sunset, sky, sea, kids, skin, food, cream,
coffee, wedding, christmas, halloween

Access any of them like:

PALETTES.sky
PALETTES.christmas

🛠️ Custom Palettes

You can also register or override palettes by modifying the COLORS dictionary directly if allowed by your API:

from pigmenta.core import COLORS

COLORS['custom'] = ['#111111', '#222222', '#333333']

💡 Use Cases

  • Visualizing data in elegant color themes.
  • Designing dashboards or GUIs.
  • Generative art and graphics programming.
  • Branding and UI prototyping.

🧩 Future Plans

  • Add support for gradient generation.
  • Integration with design tools or Jupyter extensions.

📬 Contributing

Contributions, bug reports, and palette suggestions are welcome! Please open an issue or pull request on the GitHub repository.

📝 License

This project is licensed under the MIT License — see the LICENSE file for details.

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