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View All on GitHubYou pick the colors. We make them readable.
AI Summary: Implement command-line tools for analyzing CSS color palettes for accessibility, generating reports (console output and optional JSON) showing before/after comparisons, identifying unfixable colors, and providing summary statistics. The tools should use the existing CM-Colors library to perform the analysis and color adjustments.
You pick the colors. We make them readable.
AI Summary: The task involves creating a function within the CM-Colors library to generate updated CSS files. This function should take existing CSS as input, incorporate color changes suggested by the library's accessibility improvements, and output a new CSS file maintaining the original structure, comments, and handling cases where colors could not be improved. The output CSS must be syntactically valid.
You pick the colors. We make them readable.
AI Summary: Develop a command-line interface (CLI) tool that parses CSS files, identifies color pairs (text and background), processes them using the CM-Colors library to improve accessibility while minimizing brand impact, generates updated CSS with accessible colors, and provides a report detailing changes made. The tool should handle various CSS formats, nested selectors, media queries, and color inheritance, while maintaining original CSS formatting and offering options for in-place modification, new file generation, and report-only modes.
You pick the colors. We make them readable.
AI Summary: Document the helper functions within the `cm-colors` Python library's `helper.py` file, focusing on their standalone usage. This involves clearly explaining each function's purpose, parameters, return values, and providing example usage, following a specified documentation style guide. The goal is to make these functions easily accessible and understandable for users who want to utilize them independently, rather than solely as part of the library's main workflow.
You pick the colors. We make them readable.