feat(matplotlib): implement dumbbell-basic (#5415)

## Implementation: `dumbbell-basic` - python/matplotlib

Implements the **python/matplotlib** version of `dumbbell-basic`.

**File:** `plots/dumbbell-basic/implementations/python/matplotlib.py`

**Parent Issue:** #945

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/24944791960)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/dumbbell-basic/implementations/python/matplotlib.py

@@ -1,50 +1,78 @@
-""" pyplots.ai
+""" anyplot.ai
 dumbbell-basic: Basic Dumbbell Chart
-Library: matplotlib 3.10.8 | Python 3.13.11
-Quality: 95/100 | Created: 2025-12-15
+Library: matplotlib 3.10.9 | Python 3.14.4
+Quality: 85/100 | Created: 2026-04-26
 """
 
+import os
+
 import matplotlib.pyplot as plt
 import numpy as np
 
 
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+RULE = (0.10, 0.10, 0.09, 0.18) if THEME == "light" else (0.94, 0.94, 0.91, 0.22)
+
+BEFORE_COLOR = "#009E73"  # Okabe-Ito 1 — first series
+AFTER_COLOR = "#D55E00"  # Okabe-Ito 2
+
 # Data: Employee satisfaction scores before and after workplace policy changes
 categories = ["Engineering", "Marketing", "Sales", "HR", "Finance", "Operations", "Customer Support", "Product"]
 before_scores = [65, 58, 72, 45, 68, 52, 40, 75]
 after_scores = [82, 71, 78, 73, 75, 68, 62, 88]
 
-# Sort by difference (largest improvement first)
+# Sort by improvement (largest at top)
 differences = [a - b for a, b in zip(after_scores, before_scores, strict=True)]
-sorted_indices = np.argsort(differences)[::-1]
+sorted_indices = np.argsort(differences)
 categories = [categories[i] for i in sorted_indices]
 before_scores = [before_scores[i] for i in sorted_indices]
 after_scores = [after_scores[i] for i in sorted_indices]
 
 # Plot
-fig, ax = plt.subplots(figsize=(16, 9))
+fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)
+ax.set_facecolor(PAGE_BG)
 
 y_positions = np.arange(len(categories))
 
-# Draw connecting lines (thin and subtle)
+# Connecting lines
 for i, (start, end) in enumerate(zip(before_scores, after_scores, strict=True)):
-    ax.plot([start, end], [i, i], color="#888888", linewidth=2, zorder=1)
+    ax.plot([start, end], [i, i], color=INK_SOFT, linewidth=2.5, alpha=0.55, zorder=1)
 
-# Draw dots with distinct colors
+# Dots
+ax.scatter(
+    before_scores, y_positions, s=320, color=BEFORE_COLOR, label="Before", zorder=2, edgecolors=PAGE_BG, linewidths=2
+)
 ax.scatter(
-    before_scores, y_positions, s=300, color="#306998", label="Before", zorder=2, edgecolors="white", linewidths=2
+    after_scores, y_positions, s=320, color=AFTER_COLOR, label="After", zorder=2, edgecolors=PAGE_BG, linewidths=2
 )
-ax.scatter(after_scores, y_positions, s=300, color="#FFD43B", label="After", zorder=2, edgecolors="white", linewidths=2)
 
-# Labels and styling
+# Style
 ax.set_yticks(y_positions)
-ax.set_yticklabels(categories)
-ax.set_xlabel("Satisfaction Score", fontsize=20)
-ax.set_ylabel("Department", fontsize=20)
-ax.set_title("dumbbell-basic · matplotlib · pyplots.ai", fontsize=24)
-ax.tick_params(axis="both", labelsize=16)
+ax.set_yticklabels(categories, color=INK_SOFT)
+ax.set_xlabel("Satisfaction Score", fontsize=20, color=INK)
+ax.set_ylabel("Department", fontsize=20, color=INK)
+ax.set_title("dumbbell-basic · matplotlib · anyplot.ai", fontsize=24, fontweight="medium", color=INK)
+ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)
 ax.set_xlim(30, 100)
-ax.grid(True, axis="x", alpha=0.3, linestyle="--")
-ax.legend(fontsize=16, loc="lower right")
+
+ax.spines["top"].set_visible(False)
+ax.spines["right"].set_visible(False)
+for s in ("left", "bottom"):
+    ax.spines[s].set_color(INK_SOFT)
+
+ax.xaxis.grid(True, color=RULE, linewidth=0.8)
+ax.set_axisbelow(True)
+
+leg = ax.legend(fontsize=16, loc="lower right", frameon=True)
+leg.get_frame().set_facecolor(ELEVATED_BG)
+leg.get_frame().set_edgecolor(INK_SOFT)
+leg.get_frame().set_linewidth(0.8)
+plt.setp(leg.get_texts(), color=INK_SOFT)
 
 plt.tight_layout()
-plt.savefig("plot.png", dpi=300, bbox_inches="tight")
+plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)

plots/dumbbell-basic/metadata/python/matplotlib.yaml

@@ -1,37 +1,252 @@
 library: matplotlib
+language: python
 specification_id: dumbbell-basic
 created: 2025-12-15 16:43:15+00:00
-updated: 2025-12-15 16:43:15+00:00
-generated_by: claude-opus-4-5-20251101
-workflow_run: 20240004346
+updated: '2026-04-26T01:13:04Z'
+generated_by: claude-opus
+workflow_run: 24944791960
 issue: 945
-python_version: 3.13.11
-library_version: 3.10.8
-preview_url: https://storage.googleapis.com/anyplot-images/plots/dumbbell-basic/matplotlib/plot.png
-preview_html: null
-quality_score: 95
+python_version: 3.14.4
+library_version: 3.10.9
+preview_url_light: https://storage.googleapis.com/anyplot-images/plots/dumbbell-basic/python/matplotlib/plot-light.png
+preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/dumbbell-basic/python/matplotlib/plot-dark.png
+preview_html_light: null
+preview_html_dark: null
+quality_score: 85
+review:
+  strengths:
+  - 'Full theme-adaptation: backgrounds, text, connecting lines, legend frame, and
+    dot halos (edgecolors=PAGE_BG) all flip correctly between light and dark renders'
+  - Correct Okabe-Ito palette with Before=#009E73 as first series and After=#D55E00
+    as second
+  - Data sorting by improvement size (largest at top) creates a natural visual narrative
+  - Connecting lines intentionally muted (alpha=0.55) so they do not overpower the
+    dots, per spec recommendation
+  - Deterministic, realistic, neutral example data (employee satisfaction across 8
+    departments, before/after policy changes)
+  - 'Perfect spec compliance: horizontal orientation, distinct colors, sorted by difference,
+    subtle connecting line, correct title format'
+  weaknesses:
+  - X-axis label 'Satisfaction Score' lacks a scale indicator — should be 'Satisfaction
+    Score (0-100)' to satisfy the units rubric
+  - No visual emphasis on notable data points — the highest-improvement department
+    (HR, +28 pts) and lowest (Sales, +6 pts) receive identical visual treatment; color
+    intensity variation, line thickness by improvement, or a value difference label
+    on the widest gap would elevate storytelling
+  - Library Mastery could be stronger — auto-generated legend from scatter labels
+    rather than custom handles (plt.scatter([], [], ...) or mlines.Line2D) misses
+    a matplotlib-specific opportunity for more control
+  - Data storytelling is limited to sorting; consider a subtle annotation or dot-size
+    variation to create a focal point and guide the viewer to the key insight
+  image_description: |-
+    Light render (plot-light.png):
+      Background: Warm off-white #FAF8F1 — confirmed, not pure white
+      Chrome: Title "dumbbell-basic · matplotlib · anyplot.ai" in dark ink, clearly readable. X-axis label "Satisfaction Score" and Y-axis label "Department" in dark ink, readable. Y-axis tick labels (HR, Customer Support, Engineering, Operations, Marketing, Product, Finance, Sales) and X-axis tick labels (30-100 range) all readable against the light background. Legend in lower right with warm elevated-BG frame and dark text.
+      Data: Before dots in #009E73 (Okabe-Ito 1), After dots in #D55E00 (Okabe-Ito 2). Connecting lines in muted gray with alpha=0.55. Dots have white/PAGE_BG halos. Data sorted with HR (largest improvement) at top, Sales (smallest improvement) at bottom.
+      Legibility verdict: PASS — all text readable, no light-on-light issues
+
+    Dark render (plot-dark.png):
+      Background: Warm near-black #1A1A17 — confirmed, not pure black
+      Chrome: Title in light off-white, clearly readable against dark background. Axis labels and tick labels all rendered in light colors, fully readable. Legend uses elevated dark background (#242420) with light edge and light text. No dark-on-dark failures detected.
+      Data: Before dots still #009E73 (identical to light render), After dots still #D55E00 (identical). Connecting lines appear as medium gray against dark surface. Dot halos use PAGE_BG (#1A1A17) so halos blend into background — intentional adaptive behavior.
+      Legibility verdict: PASS — all text readable, no dark-on-dark issues detected
+  criteria_checklist:
+    visual_quality:
+      score: 28
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 7
+        max: 8
+        passed: true
+        comment: Font sizes explicitly set (title=24, labels=20, ticks=16), all text
+          readable in both themes
+      - id: VQ-02
+        name: No Overlap
+        score: 6
+        max: 6
+        passed: true
+        comment: All elements well-spaced, no collisions with 8 categories
+      - id: VQ-03
+        name: Element Visibility
+        score: 6
+        max: 6
+        passed: true
+        comment: Dot size s=320 optimal for 8 data points; connecting lines at linewidth=2.5
+          alpha=0.55 visible but appropriately subtle
+      - id: VQ-04
+        name: Color Accessibility
+        score: 2
+        max: 2
+        passed: true
+        comment: Okabe-Ito palette CVD-safe; green vs vermillion distinguishable by
+          luminance
+      - id: VQ-05
+        name: Layout & Canvas
+        score: 4
+        max: 4
+        passed: true
+        comment: 16:9 canvas well-utilized, tight_layout applied, legend near data,
+          nothing cut off
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 1
+        max: 2
+        passed: false
+        comment: Satisfaction Score is descriptive but lacks units/scale indicator
+          (0-100)
+      - id: VQ-07
+        name: Palette Compliance
+        score: 2
+        max: 2
+        passed: true
+        comment: 'First series #009E73, second #D55E00; backgrounds #FAF8F1/#1A1A17
+          correct; full theme-adaptive chrome'
+    design_excellence:
+      score: 12
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 5
+        max: 8
+        passed: false
+        comment: 'Above default: correct palette, theme-adaptive dot halos, data sorting,
+          clean spine removal. Not yet publication-ready.'
+      - id: DE-02
+        name: Visual Refinement
+        score: 4
+        max: 6
+        passed: false
+        comment: Top/right spines removed, subtle x-axis grid (alpha~0.18), connecting
+          lines muted, legend frame styled
+      - id: DE-03
+        name: Data Storytelling
+        score: 3
+        max: 6
+        passed: false
+        comment: Sorting by improvement reveals pattern but no visual emphasis on
+          top/bottom performer; viewer must identify insights themselves
+    spec_compliance:
+      score: 15
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 5
+        passed: true
+        comment: Correct dumbbell/connected dot chart
+      - id: SC-02
+        name: Required Features
+        score: 4
+        max: 4
+        passed: true
+        comment: Horizontal orientation, distinct Before/After colors, sorted by difference,
+          subtle connecting line
+      - id: SC-03
+        name: Data Mapping
+        score: 3
+        max: 3
+        passed: true
+        comment: Categories on y-axis, satisfaction values on x-axis, all data visible
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Title: dumbbell-basic · matplotlib · anyplot.ai; legend labels Before/After'
+    data_quality:
+      score: 15
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 6
+        max: 6
+        passed: true
+        comment: 8 departments with varying Before/After gaps, small and large improvements,
+          full range of dumbbell distances
+      - id: DQ-02
+        name: Realistic Context
+        score: 5
+        max: 5
+        passed: true
+        comment: Employee satisfaction scores before/after workplace policy changes
+          — realistic, neutral business scenario
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: Values 40-88 on 30-100 axis, plausible for 0-100 satisfaction scale
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: No functions or classes; clean Imports → Data → Sort → Plot → Save
+          flow
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: Fully deterministic hardcoded data
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: Only os, matplotlib.pyplot, numpy — all used
+      - id: CQ-04
+        name: Code Elegance
+        score: 2
+        max: 2
+        passed: true
+        comment: Clean Pythonic code; zip with strict=True; no fake UI elements
+      - id: CQ-05
+        name: Output & API
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot-{THEME}.png with facecolor; current matplotlib API
+    library_mastery:
+      score: 5
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 3
+        max: 5
+        passed: true
+        comment: Correct Axes API throughout; legend frame manipulation; tick_params;
+          set_axisbelow
+      - id: LM-02
+        name: Distinctive Features
+        score: 2
+        max: 5
+        passed: false
+        comment: Theme-adaptive edgecolors=PAGE_BG for dot halos is distinctive; zorder
+          used intentionally. Auto-generated legend rather than custom handles limits
+          score.
+  verdict: REJECTED
 impl_tags:
   dependencies: []
   techniques:
-    - manual-ticks
+  - manual-ticks
+  - custom-legend
   patterns:
-    - data-generation
+  - data-generation
+  - explicit-figure
+  - iteration-over-groups
   dataprep: []
   styling:
-    - edge-highlighting
-review:
-  strengths: []
-  weaknesses: []
-  improvements: []
-  image_description: 'The plot shows a horizontal dumbbell chart displaying employee
-    satisfaction scores before and after workplace policy changes across 8 departments.
-    Each row represents a department (Sales, Finance, Product, Marketing, Operations,
-    Engineering, Customer Support, HR) with the y-axis showing "Department" and x-axis
-    showing "Satisfaction Score" ranging from 30 to 100. Two colored dots are connected
-    by a thin gray line for each department: blue dots (labeled "Before") on the left
-    and yellow dots (labeled "After") on the right. The data is sorted by the magnitude
-    of change, with HR showing the largest improvement at the bottom. The title follows
-    the correct format "dumbbell-basic · matplotlib · pyplots.ai". The legend is positioned
-    in the lower right corner. All dots are clearly visible with white edge colors,
-    and the grid lines are subtle vertical dashed lines.'
-  verdict: APPROVED
+  - alpha-blending
+  - edge-highlighting
+  - grid-styling