feat(plotly): implement sankey-basic (#5603)

## Implementation: `sankey-basic` - python/plotly

Implements the **python/plotly** version of `sankey-basic`.

**File:** `plots/sankey-basic/implementations/python/plotly.py`

**Parent Issue:** #810

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/25156267074)*

---------

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

Author: github-actions[bot]

plots/sankey-basic/implementations/python/plotly.py

@@ -1,91 +1,83 @@
-""" pyplots.ai
+""" anyplot.ai
 sankey-basic: Basic Sankey Diagram
-Library: plotly 6.5.0 | Python 3.13.11
-Quality: 93/100 | Created: 2025-12-23
+Library: plotly 6.7.0 | Python 3.13.13
+Quality: 90/100 | Updated: 2026-04-30
 """
 
+import os
+
 import plotly.graph_objects as go
 
 
-# Data - Energy flow from sources to end-use sectors (in TWh)
+# 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"
+
+# Okabe-Ito palette for source nodes (positions 1-4)
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7"]
+SOURCE_RGBA = ["rgba(0,158,115,0.4)", "rgba(213,94,0,0.4)", "rgba(0,114,178,0.4)", "rgba(204,121,167,0.4)"]
+
+# Data - Energy flow from sources to sectors (TWh)
 sources = ["Coal", "Natural Gas", "Nuclear", "Renewables"]
 targets = ["Residential", "Commercial", "Industrial", "Transportation"]
-
-# Node labels (sources first, then targets)
 labels = sources + targets
 
-# Define flows: (source_index, target_index, value)
-# Indices: Coal=0, Gas=1, Nuclear=2, Renewables=3
-# Residential=4, Commercial=5, Industrial=6, Transportation=7
 flows = [
-    # Coal flows
-    (0, 4, 5),  # Coal -> Residential
-    (0, 5, 8),  # Coal -> Commercial
-    (0, 6, 25),  # Coal -> Industrial
-    # Natural Gas flows
-    (1, 4, 22),  # Gas -> Residential
-    (1, 5, 18),  # Gas -> Commercial
-    (1, 6, 15),  # Gas -> Industrial
-    (1, 7, 3),  # Gas -> Transportation
-    # Nuclear flows
-    (2, 4, 12),  # Nuclear -> Residential
-    (2, 5, 10),  # Nuclear -> Commercial
-    (2, 6, 8),  # Nuclear -> Industrial
-    # Renewables flows
-    (3, 4, 8),  # Renewables -> Residential
-    (3, 5, 6),  # Renewables -> Commercial
-    (3, 6, 5),  # Renewables -> Industrial
-    (3, 7, 4),  # Renewables -> Transportation
+    (0, 4, 5),
+    (0, 5, 8),
+    (0, 6, 25),
+    (1, 4, 22),
+    (1, 5, 18),
+    (1, 6, 15),
+    (1, 7, 3),
+    (2, 4, 12),
+    (2, 5, 10),
+    (2, 6, 8),
+    (3, 4, 8),
+    (3, 5, 6),
+    (3, 6, 5),
+    (3, 7, 4),
 ]
 
 source_indices = [f[0] for f in flows]
 target_indices = [f[1] for f in flows]
 values = [f[2] for f in flows]
 
-# Colors for source nodes (Python Blue variations and Yellow)
-node_colors = [
-    "#306998",  # Coal - Python Blue
-    "#4A90C2",  # Natural Gas - Light Blue
-    "#FFD43B",  # Nuclear - Python Yellow
-    "#7AB648",  # Renewables - Green
-    "#8FA8BD",  # Residential
-    "#A3B8CC",  # Commercial
-    "#B8C9DB",  # Industrial
-    "#CCD9E8",  # Transportation
-]
-
-# Link colors with transparency (based on source)
-link_colors = [
-    "rgba(48, 105, 152, 0.5)"
-    if s == 0
-    else "rgba(74, 144, 194, 0.5)"
-    if s == 1
-    else "rgba(255, 212, 59, 0.5)"
-    if s == 2
-    else "rgba(122, 182, 72, 0.5)"
-    for s in source_indices
-]
+# Source nodes use Okabe-Ito colors; target nodes use INK_SOFT
+node_colors = OKABE_ITO + [INK_SOFT] * 4
+link_colors = [SOURCE_RGBA[s] for s in source_indices]
 
-# Create Sankey diagram
+# Plot
 fig = go.Figure(
     data=[
         go.Sankey(
-            node=dict(pad=25, thickness=35, line=dict(color="white", width=2), label=labels, color=node_colors),
-            link=dict(source=source_indices, target=target_indices, value=values, color=link_colors),
+            node={
+                "pad": 25,
+                "thickness": 35,
+                "line": {"color": PAGE_BG, "width": 1},
+                "label": labels,
+                "color": node_colors,
+            },
+            link={"source": source_indices, "target": target_indices, "value": values, "color": link_colors},
         )
     ]
 )
 
-# Update layout for 4800x2700 px output
 fig.update_layout(
-    title=dict(
-        text="Energy Distribution · sankey-basic · plotly · pyplots.ai", font=dict(size=36), x=0.5, xanchor="center"
-    ),
-    font=dict(size=22),
-    template="plotly_white",
-    margin=dict(l=80, r=80, t=120, b=60),
+    title={
+        "text": "Energy Distribution · sankey-basic · plotly · anyplot.ai",
+        "font": {"size": 28, "color": INK},
+        "x": 0.5,
+        "xanchor": "center",
+    },
+    paper_bgcolor=PAGE_BG,
+    plot_bgcolor=PAGE_BG,
+    font={"size": 22, "color": INK},
+    margin={"l": 80, "r": 80, "t": 120, "b": 60},
 )
 
-# Save outputs
-fig.write_image("plot.png", width=1600, height=900, scale=3)
-fig.write_html("plot.html")
+# Save
+fig.write_image(f"plot-{THEME}.png", width=1600, height=900, scale=3)
+fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")