feat(pygal): implement dumbbell-basic

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

@@ -1,36 +1,36 @@
 """ anyplot.ai
 dumbbell-basic: Basic Dumbbell Chart
-Library: pygal 3.1.0 | Python 3.14.4
-Quality: 87/100 | Updated: 2026-04-26
+Library: pygal 3.1.3 | Python 3.13.14
+Quality: 88/100 | Updated: 2026-06-30
 """
 
 import os
 import sys
 from pathlib import Path
 
 
-# Remove script directory from path to avoid name collision with the pygal package
+# Remove script dir from sys.path to avoid name collision with the pygal package
 _script_dir = str(Path(__file__).parent)
 sys.path = [p for p in sys.path if p != _script_dir]
 
 import pygal  # noqa: E402
 from pygal.style import Style  # noqa: E402
 
 
-# Theme-adaptive chrome tokens
+# Theme tokens
 THEME = os.getenv("ANYPLOT_THEME", "light")
 PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
 INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
 INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
 INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
 
-# Okabe-Ito data colors (theme-independent)
-BEFORE = "#009E73"  # position 1 — brand
-AFTER = "#C475FD"  # position 2
-CONNECTOR = INK_SOFT  # neutral chrome that adapts to theme
+# Imprint categorical palette — positions 1 and 2 for two-series dumbbell
+BEFORE = "#009E73"  # Imprint position 1 — brand green, always first series
+AFTER = "#C475FD"  # Imprint position 2 — lavender
+CONNECTOR = INK_SOFT  # theme-adaptive neutral connector line
+LOSS_COLOR = "#AE3030"  # Imprint matte red — semantic anchor for regression/bad outcomes
 
-# Data — Employee satisfaction scores before and after policy changes.
-# Hand-picked values include one regression (Legal) to exercise full data range.
+# Data — employee satisfaction scores before and after new workplace policy
 categories = [
     "Engineering",
     "Sales",
@@ -45,19 +45,31 @@
 before = [62, 71, 58, 45, 68, 52, 64, 73, 70]
 after = [78, 82, 75, 69, 74, 71, 79, 85, 67]
 
-# Sort by improvement (largest at top)
+# Sort by improvement (largest gain at top; Legal regression ends up at bottom)
 data = sorted(zip(categories, before, after, strict=True), key=lambda x: x[2] - x[1], reverse=True)
 categories = [d[0] for d in data]
 before = [d[1] for d in data]
 after = [d[2] for d in data]
 n = len(categories)
 
-# Y positions: top row = biggest improvement (first sorted item)
+# Top row = biggest improvement; y=n at top, y=1 at bottom
 y_positions = list(range(n, 0, -1))
 
-# Series colors map 1:1 to the order series are added below:
-#   n connector series (drawn first, underneath) then 2 dot series.
-colors_tuple = (CONNECTOR,) * n + (BEFORE, AFTER)
+# Category labels include delta for at-a-glance storytelling (e.g. "Customer Support (+24)")
+y_labels = [
+    {"label": f"{cat}  ({a - b:+d})", "value": pos}
+    for cat, b, a, pos in zip(categories, before, after, y_positions, strict=True)
+]
+
+# Title — include language token; scale font size for title length
+title = "Employee Satisfaction · dumbbell-basic · python · pygal · anyplot.ai"
+n_chars = len(title)  # 70 chars
+ratio = 67 / n_chars if n_chars > 67 else 1.0
+title_font_size = max(44, round(66 * ratio))  # ≈ 63
+
+# Color sequence: neutral connectors (red for negative deltas), then dot colors
+connector_colors = tuple(LOSS_COLOR if a < b else CONNECTOR for b, a in zip(before, after, strict=True))
+colors_tuple = connector_colors + (BEFORE, AFTER)
 
 custom_style = Style(
     background=PAGE_BG,
@@ -66,57 +78,56 @@
     foreground_strong=INK,
     foreground_subtle=INK_MUTED,
     colors=colors_tuple,
-    title_font_size=32,
-    label_font_size=22,
-    major_label_font_size=20,
-    legend_font_size=20,
-    value_font_size=16,
-    stroke_width=4,
+    title_font_size=title_font_size,
+    label_font_size=56,
+    major_label_font_size=44,
+    legend_font_size=44,
+    value_font_size=36,
+    stroke_width=2.5,
     opacity=1.0,
     opacity_hover=0.85,
 )
 
 chart = pygal.XY(
-    width=4800,
-    height=2700,
+    width=3200,
+    height=1800,
     style=custom_style,
-    title="Employee Satisfaction · dumbbell-basic · pygal · anyplot.ai",
+    title=title,
     x_title="Satisfaction Score (out of 100)",
     y_title="Department",
     show_legend=True,
     legend_at_bottom=True,
     legend_at_bottom_columns=2,
-    legend_box_size=36,
+    legend_box_size=44,
     margin=80,
-    show_x_guides=True,
+    margin_bottom=20,
+    show_x_guides=False,
     show_y_guides=False,
     xrange=(35, 95),
-    range=(0, n + 1),
-    y_labels=[{"label": cat, "value": pos} for cat, pos in zip(categories, y_positions, strict=True)],
+    range=(0.5, n + 0.5),
+    y_labels=y_labels,
     truncate_legend=-1,
     truncate_label=-1,
-    dots_size=22,
     stroke=False,
 )
 
-# Connector lines first so they sit underneath the dots.
-# title=None suppresses the legend entry while still rendering the series.
+# Connector lines drawn first so they sit underneath the dots
 for b, a, pos in zip(before, after, y_positions, strict=True):
     chart.add(None, [(b, pos), (a, pos)], stroke=True, show_dots=False, stroke_style={"width": 5, "linecap": "round"})
 
-# Before dots — Okabe-Ito green
+# Before dots — Imprint brand green (position 1)
 before_points = [
     {"value": (b, pos), "label": f"{cat}: {b}"} for cat, b, pos in zip(categories, before, y_positions, strict=True)
 ]
 chart.add("Before policy change", before_points, stroke=False, dots_size=24)
 
-# After dots — Okabe-Ito vermillion
+# After dots — Imprint lavender (position 2)
 after_points = [
     {"value": (a, pos), "label": f"{cat}: {a}"} for cat, a, pos in zip(categories, after, y_positions, strict=True)
 ]
 chart.add("After policy change", after_points, stroke=False, dots_size=24)
 
-# Save outputs
+# Save PNG and interactive HTML
 chart.render_to_png(f"plot-{THEME}.png")
 with open(f"plot-{THEME}.html", "wb") as f:
     f.write(chart.render())