Skip to content

Latest commit

 

History

History
80 lines (50 loc) · 2.33 KB

File metadata and controls

80 lines (50 loc) · 2.33 KB

data_visualization - Functional Specification

Version: v1.2.3 | Status: Active | Last Updated: March 2026

Purpose

The data_visualization module provides tools to transform raw data (logs, metrics, analysis results) into human-interpretable visual formats (tables, charts, graphs). It supports both terminal-based output (ASCII/Rich) and web-based or image-based rendering for reports.

Design Principles

Modularity

  • Backend Agnostic: Visualization logic should be separate from data sources.
  • Renderer Abstraction: Support multiple renderers (Console, HTML, PNG).

Internal Coherence

  • Consistent Styling: All visualizations should share a common color palette and style guide (Codomyrmex branding).

Parsimony

  • Simple API: plot(data, type='bar') style ease of use.

Architecture

graph TD
    Data[Raw Data] --> Adapter[Data Adapter]
    Adapter --> Engine[Vis Engine]
    Engine --> Renderer{Renderer}
    Renderer -->|Terminal| Console[Rich Output]
    Renderer -->|File| Image[PNG/SVG]
    Renderer -->|Browser| Web[HTML/JS]
Loading

Functional Requirements

Core Capabilities

  1. Rich Terminal Output: Tables, progress bars, syntax highlighting (wrapping rich).
  2. Charting: Line charts, bar graphs, scatter plots.
  3. Report Generation: Embed charts into Markdown or HTML reports.
  4. Visualization Engine (Consolidated): Core rendering engine for complex plotting and theme management.

Quality Standards

  • Responsiveness: Terminal output must respect terminal width.
  • Accessibility: Colors should be distinguishable.

Interface Contracts

Public API

  • render_table(data: List[Dict], title: str) -> None
  • render_chart(data: Any, type: str) -> Path: Returns path to generated image/file.

Dependencies

  • External: rich, matplotlib (optional), plotly (optional).

Implementation Guidelines

Usage Patterns

  • Use rich for all real-time CLI feedback.
  • Use matplotlib/plotly for static artifacts generated for artifacts/reports.

Navigation

Testing

uv run python -m pytest src/codomyrmex/tests/ -k data_visualization -v