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vizlychart

Professional data visualization library with advanced features: 3D plotting, animations, scientific charts, and matplotlib-level control

pipPyPI
Version
2.4.4
Maintainers
1

VizlyChart

A Python visualization library focused on performance and professional output quality.

Features

  • Fast rendering: Optimized SVG generation with performance improvements over baseline matplotlib workflows
  • Professional output: Clean typography with customizable fonts and spacing
  • GPU acceleration support: Optional CuPy integration for data processing acceleration
  • Multiple chart types: Line charts, scatter plots, bar charts, and 3D surfaces
  • Engineering utilities: Specialized charts for technical applications

Installation

pip install vizlychart

For GPU acceleration (requires NVIDIA GPU):

pip install vizlychart[gpu]

For extended functionality with matplotlib integration:

pip install vizlychart[extended]

Quick Start

import vizlychart as vc
import numpy as np

# Generate sample data
x = np.linspace(0, 10, 100)
y = np.sin(x)

# Create and customize chart
chart = vc.LineChart()
chart.plot(x, y, label='sin(x)')
chart.set_title('Sample Chart')
chart.set_labels('X-axis', 'Y-axis')

# Save as SVG
chart.save('output.svg')

Performance

VizlyChart focuses on practical performance improvements:

  • SVG-first rendering for scalable output
  • Memory-efficient processing for large datasets
  • Optional GPU acceleration for data preprocessing

Requirements

  • Python 3.7+
  • NumPy 1.24+

Optional dependencies:

  • CuPy (GPU acceleration)
  • Matplotlib (extended compatibility)
  • SciPy (engineering functions)

Contributing

We welcome contributions! Here's how to get started:

Development Setup

  • Clone the repository:
git clone https://github.com/vizlychart/vizlychart.git
cd vizlychart
  • Create a virtual environment:
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
  • Install in development mode:
pip install -e .[dev]

Running Tests

pytest

Code Style

We use Black for formatting and Ruff for linting:

black src tests
ruff check src tests

Ways to Contribute

  • Bug reports: Open an issue describing the problem with minimal reproduction steps
  • Feature requests: Suggest new chart types or functionality improvements
  • Documentation: Help improve examples, docstrings, or tutorials
  • Code contributions: Fix bugs, implement features, or optimize performance
  • Testing: Add test cases or improve test coverage

Pull Request Guidelines

  • Fork the repository and create a feature branch
  • Write tests for new functionality
  • Ensure all tests pass and code follows style guidelines
  • Update documentation if needed
  • Submit a pull request with a clear description

Areas We'd Love Help With

  • Additional chart types (violin plots, heat maps, etc.)
  • Performance optimizations
  • Better error messages and validation
  • Cross-platform testing
  • Documentation and examples

License

MIT License - see LICENSE file for details.

Support

  • Issues: Report bugs or request features via GitHub Issues
  • Discussions: Community discussion and questions
  • Documentation: More examples and API documentation coming soon

Built with focus on practical performance and professional output quality.

Keywords

visualization

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