feat(bokeh): implement gantt-basic (#2415)

## Implementation: `gantt-basic` - bokeh

Implements the **bokeh** version of `gantt-basic`.

**File:** `plots/gantt-basic/implementations/bokeh.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20543282696)*

---------

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/gantt-basic/implementations/bokeh.py

@@ -0,0 +1,166 @@
+""" pyplots.ai
+gantt-basic: Basic Gantt Chart
+Library: bokeh 3.8.1 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-27
+"""
+
+import pandas as pd
+from bokeh.io import export_png, save
+from bokeh.models import ColumnDataSource, Legend, LegendItem
+from bokeh.palettes import Category10
+from bokeh.plotting import figure
+from bokeh.resources import CDN
+
+
+# Data - Software Development Project
+tasks = [
+    {"task": "Requirements Analysis", "start": "2025-01-06", "end": "2025-01-17", "category": "Planning"},
+    {"task": "System Design", "start": "2025-01-13", "end": "2025-01-31", "category": "Planning"},
+    {"task": "Database Schema", "start": "2025-01-27", "end": "2025-02-07", "category": "Development"},
+    {"task": "Backend API", "start": "2025-02-03", "end": "2025-02-28", "category": "Development"},
+    {"task": "Frontend UI", "start": "2025-02-10", "end": "2025-03-14", "category": "Development"},
+    {"task": "Integration", "start": "2025-03-03", "end": "2025-03-21", "category": "Development"},
+    {"task": "Unit Testing", "start": "2025-02-17", "end": "2025-03-14", "category": "Testing"},
+    {"task": "System Testing", "start": "2025-03-17", "end": "2025-03-28", "category": "Testing"},
+    {"task": "User Acceptance", "start": "2025-03-24", "end": "2025-04-04", "category": "Testing"},
+    {"task": "Documentation", "start": "2025-03-10", "end": "2025-04-04", "category": "Deployment"},
+    {"task": "Deployment", "start": "2025-04-01", "end": "2025-04-11", "category": "Deployment"},
+    {"task": "Training", "start": "2025-04-07", "end": "2025-04-18", "category": "Deployment"},
+]
+
+df = pd.DataFrame(tasks)
+df["start"] = pd.to_datetime(df["start"])
+df["end"] = pd.to_datetime(df["end"])
+
+# Sort by start date for chronological order
+df = df.sort_values(["start", "category"], ascending=[True, True]).reset_index(drop=True)
+
+# Convert dates to numeric for plotting (milliseconds since epoch)
+df["start_ms"] = df["start"].astype("int64") // 10**6
+df["end_ms"] = df["end"].astype("int64") // 10**6
+
+# Assign y positions (inverted so first task is at top)
+df["y"] = list(range(len(df) - 1, -1, -1))
+
+# Color mapping by category
+categories = df["category"].unique().tolist()
+color_map = {cat: Category10[10][i % 10] for i, cat in enumerate(categories)}
+# Override with Python colors for first two categories
+color_map[categories[0]] = "#306998"  # Python Blue
+if len(categories) > 1:
+    color_map[categories[1]] = "#FFD43B"  # Python Yellow
+df["color"] = df["category"].map(color_map)
+
+# Create ColumnDataSource
+source = ColumnDataSource(
+    data={
+        "task": df["task"],
+        "y": df["y"],
+        "left": df["start_ms"],
+        "right": df["end_ms"],
+        "color": df["color"],
+        "category": df["category"],
+    }
+)
+
+# Create figure with extra left margin for task labels
+p = figure(
+    width=4800,
+    height=2700,
+    title="gantt-basic · bokeh · pyplots.ai",
+    x_axis_type="datetime",
+    y_range=(-0.5, len(df) - 0.5),
+    tools="",
+    toolbar_location=None,
+)
+
+# Bar height
+bar_height = 0.65
+
+# Draw Gantt bars using hbar
+p.hbar(
+    y="y",
+    left="left",
+    right="right",
+    height=bar_height,
+    color="color",
+    alpha=0.9,
+    source=source,
+    line_color="#444444",
+    line_width=3,
+)
+
+# Add task labels on the left side with larger font
+x_range_span = df["end_ms"].max() - df["start_ms"].min()
+for i, row in df.iterrows():
+    y_pos = df.loc[i, "y"]
+    task_name = row["task"]
+    p.text(
+        x=[df["start_ms"].min() - x_range_span * 0.015],
+        y=[y_pos],
+        text=[task_name],
+        text_font_size="32pt",
+        text_align="right",
+        text_baseline="middle",
+        text_color="#333333",
+    )
+
+# Title styling
+p.title.text_font_size = "48pt"
+p.title.text_font_style = "bold"
+p.title.text_color = "#333333"
+
+# X-axis styling
+p.xaxis.axis_label = "Timeline"
+p.xaxis.axis_label_text_font_size = "36pt"
+p.xaxis.major_label_text_font_size = "28pt"
+p.xaxis.axis_label_text_color = "#333333"
+p.xaxis.major_label_text_color = "#333333"
+p.xaxis.axis_line_width = 3
+p.xaxis.major_tick_line_width = 3
+p.xaxis.minor_tick_line_color = None
+
+# Hide y-axis (task labels are added as text)
+p.yaxis.visible = False
+
+# Grid styling
+p.xgrid.grid_line_color = "#cccccc"
+p.xgrid.grid_line_alpha = 0.5
+p.xgrid.grid_line_dash = [8, 4]
+p.xgrid.grid_line_width = 2
+p.ygrid.grid_line_color = None
+
+# Background
+p.background_fill_color = "#fafafa"
+p.border_fill_color = "white"
+p.outline_line_color = None
+
+# Extend x-range to accommodate task labels
+x_min = df["start_ms"].min()
+x_max = df["end_ms"].max()
+x_padding = (x_max - x_min) * 0.22
+p.x_range.start = x_min - x_padding
+p.x_range.end = x_max + (x_max - x_min) * 0.03
+
+# Add legend manually using dummy glyphs
+legend_items = []
+for cat in categories:
+    dummy = p.hbar(y=[-100], left=[0], right=[1], height=0.1, color=color_map[cat], visible=False)
+    legend_items.append(LegendItem(label=cat, renderers=[dummy]))
+
+legend = Legend(items=legend_items, location="top_right")
+legend.label_text_font_size = "30pt"
+legend.glyph_height = 40
+legend.glyph_width = 50
+legend.spacing = 25
+legend.padding = 30
+legend.background_fill_alpha = 0.85
+legend.border_line_color = "#cccccc"
+legend.border_line_width = 2
+p.add_layout(legend, "right")
+
+# Save as PNG
+export_png(p, filename="plot.png")
+
+# Save as HTML for interactivity
+save(p, filename="plot.html", resources=CDN, title="gantt-basic")

plots/gantt-basic/metadata/bokeh.yaml

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+library: bokeh
+specification_id: gantt-basic
+created: '2025-12-27T19:24:09Z'
+updated: '2025-12-27T19:33:32Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20543282696
+issue: 0
+python_version: 3.13.11
+library_version: 3.8.1
+preview_url: https://storage.googleapis.com/pyplots-images/plots/gantt-basic/bokeh/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/gantt-basic/bokeh/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/gantt-basic/bokeh/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent visual clarity with well-sized task labels and bars
+  - Perfect color coding by category with Python-themed blue/yellow for first two
+    categories
+  - Professional layout with proper canvas utilization at 4800x2700
+  - Realistic software development project data showing overlapping and sequential
+    tasks
+  - Clean datetime handling with proper x-axis formatting
+  - Good use of Bokeh ColumnDataSource pattern
+  weaknesses:
+  - Missing HoverTool for task details on hover (Bokeh key interactive feature)
+  - Generates both PNG and HTML but only PNG is required
+  - Axis label Timeline could be more descriptive