{"categories":[{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities/8"},{"label":"Graphics","url":"https://skillfed.io/packages/category/multimedia-graphics/2"},{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"}],"enrichment":{"capability":"Generates lists of visually distinct colors of any length, with each new color maximally different from existing ones, and provides utilities to work with those colors including colorblind simulation.","skillfed_tags":["color-generation","visualization","accessibility"],"use_cases":["Generate a large color palette for a visualization with many categories or clusters that need distinct colors.","Create a colormap for matplotlib plots when standard qualitative colormaps don't have enough distinct colors.","Design interfaces or dashboards where many data series or groups must be color-coded and easily distinguishable.","Simulate how a visualization appears to someone with colorblindness (e.g., Deuteranomaly) to ensure accessibility.","Select a contrasting font color (black or white) automatically for any given background color in a UI."],"what_it_does":"distinctipy generates palettes of many visually distinct colors by iteratively adding each new color to maximize perceptual distance from existing ones in the palette. It wraps a color distance metric and provides utilities to work with the generated colors: converting them to matplotlib colormaps, selecting contrasting text colors for backgrounds, inverting colors, and simulating how they appear to people with different types of colorblindness.\n\nThe package is designed for applications that need more than the typical 20 colors available in standard qualitative colormaps. It depends only on numpy at runtime, making it lightweight to install. Optional dependencies (matplotlib, pandas) are needed only for visualization and examples. The code is stable and dormant rather than actively maintained, but suitable for the straightforward task it performs.","worth_installing":"Yes, if you need to generate many visually distinct colors or work with color palettes programmatically. The package is lightweight, has no security vulnerabilities, and solves a specific problem well. Dormant maintenance is acceptable here because the core algorithm is stable and the package has no complex dependencies. Not necessary if you only need standard matplotlib colormaps or a small fixed palette."},"id":"distinctipy","links":{"html":"https://skillfed.io/packages/distinctipy","md":"https://skillfed.io/packages/distinctipy.md","pypi":"https://pypi.org/project/distinctipy/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-01-10","license_spdx":null,"license_treatment":"permissive","name":"distinctipy","python_support":"supports_current","summary":"A lightweight package for generating visually distinct colours."},"popularity":{"monthly_downloads":207042,"position":9558,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.3.4"}