feat(matplotlib): implement gantt-basic

[github-actions]

Implementation: gantt-basic - matplotlib

Implements the matplotlib version of gantt-basic.

File: plots/gantt-basic/implementations/matplotlib.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a horizontal Gantt chart showing a software development project timeline. There are 12 tasks arranged vertically from top to bottom: Requirements Analysis, System Design, Database Setup, Backend Development, Frontend Development, API Integration, Unit Testing, Documentation, Integration Testing, User Acceptance Testing, Deployment Prep, and Go Live. Each task is represented by a horizontal bar spanning from its start date to end date. The bars are color-coded by category: dark blue (Python Blue #306998) for Planning tasks, yellow (#FFD43B) for Development tasks, light blue (#4B8BBE) for Testing tasks, and gray (#646464) for Deployment tasks. A vertical dashed red line marks "Today" (March 15). The x-axis shows dates from early January to early May 2025 with bi-weekly Monday intervals (e.g., Jan 13, Jan 27, Feb 10). The title reads "gantt-basic · matplotlib · pyplots.ai" in bold. A legend in the upper right identifies the four categories plus the Today marker. The plot has subtle vertical grid lines and clean styling with top/right spines removed.

Quality Score: 92/100

Criteria Checklist

Visual Quality (37/40 pts)

• VQ-01: Text Legibility (10/10) - Title at 24pt, axis labels at 20pt, tick labels at 16pt, task names at 16pt - all perfectly readable
• VQ-02: No Overlap (8/8) - No overlapping text, x-axis labels are rotated 45° to prevent overlap, task names have adequate spacing
• VQ-03: Element Visibility (8/8) - Bar height is well-proportioned (0.6), bars are clearly visible with good spacing between them, alpha=0.9 provides good visibility
• VQ-04: Color Accessibility (5/5) - Uses Python Blue, yellow, light blue, and gray - good contrast and colorblind-safe palette (no red-green confusion as primary differentiator)
• VQ-05: Layout Balance (5/5) - Plot fills canvas well, good margins, legend positioned in upper right without obscuring data
• VQ-06: Axis Labels (1/2) - "Timeline" and "Tasks" are descriptive but lack units/context (timeline could indicate "Date" or similar)
• VQ-07: Grid & Legend (2/2) - Subtle grid (alpha=0.3, x-axis only), legend well-placed with clear entries including the Today marker

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct horizontal bar chart representing Gantt timeline
• SC-02: Data Mapping (5/5) - Tasks on Y-axis, time on X-axis, duration correctly calculated
• SC-03: Required Features (5/5) - Has all spec features: horizontal bars, time axis, color coding by category, "today" vertical line, logical ordering by start date
• SC-04: Data Range (3/3) - X-axis shows all dates with 3-day padding on both ends
• SC-05: Legend Accuracy (2/2) - Legend correctly identifies all 4 categories plus the Today marker
• SC-06: Title Format (2/2) - Uses exact format "gantt-basic · matplotlib · pyplots.ai"

Data Quality (20/20 pts)

• DQ-01: Feature Coverage (8/8) - Shows overlapping tasks, sequential tasks, different durations, multiple categories, demonstrates real project phases
• DQ-02: Realistic Context (7/7) - Software development project with realistic phases: Planning → Development → Testing → Deployment
• DQ-03: Appropriate Scale (5/5) - Reasonable task durations (1-5 weeks), realistic project timeline (Jan-May 2025), 12 tasks within the recommended 5-30 range

Code Quality (7/10 pts)

• CQ-01: KISS Structure (3/3) - Simple flat structure: imports → data → plot → save, no functions or classes
• CQ-02: Reproducibility (0/3) - No random data used, but data is deterministic (hardcoded dates) - actually this SHOULD get full points as data is fully deterministic. Correcting: (3/3)
• CQ-03: Clean Imports (2/2) - All imports are used (datetime, timedelta, mdates, plt, Patch)
• CQ-04: No Deprecated API (1/1) - Uses current matplotlib API (barh, set_yticks, etc.)
• CQ-05: Output Correct (1/1) - Saves as 'plot.png'

Correction on Code Quality: 10/10

Library Features (3/5 pts)

• LF-01: Uses matplotlib features (3/5) - Uses matplotlib.dates for date formatting/locating, Patch for custom legend, barh for horizontal bars. Could have used additional features like annotations for milestones or progress indicators.

Revised Score Calculation

• Visual Quality: 37/40
• Spec Compliance: 25/25
• Data Quality: 20/20
• Code Quality: 10/10
• Library Features: 3/5

Final Score: 95/100

Strengths

• Excellent color scheme using Python-branded colors with good accessibility
• Clean implementation with proper date handling using matplotlib.dates
• Logical task ordering by start date (reversed for top-to-bottom reading)
• "Today" marker with dashed red line adds practical utility
• Proper bar spacing and sizing for clear readability
• Complete legend including all categories and the Today marker
• Subtle x-axis grid without overwhelming the visualization
• Good use of tight_layout and bbox_inches for clean output

Weaknesses

• Axis labels are generic ("Timeline", "Tasks") - could be more descriptive like "Project Timeline (2025)" and "Project Tasks"
• Could leverage more matplotlib features like annotations for key milestones

Verdict: APPROVED