feat(bokeh): implement line-interactive (#2825)

## Implementation: `line-interactive` - bokeh

Implements the **bokeh** version of `line-interactive`.

**File:** `plots/line-interactive/implementations/bokeh.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20602452572)*

---------

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

Author: github-actions[bot]

plots/line-interactive/implementations/bokeh.py

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+""" pyplots.ai
+line-interactive: Interactive Line Chart with Hover and Zoom
+Library: bokeh 3.8.1 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import pandas as pd
+from bokeh.io import export_png
+from bokeh.models import BoxZoomTool, ColumnDataSource, HoverTool, PanTool, ResetTool, WheelZoomTool
+from bokeh.plotting import figure, output_file, save
+
+
+# Data - Daily temperature readings for a year
+np.random.seed(42)
+dates = pd.date_range("2024-01-01", periods=365, freq="D")
+
+# Simulate realistic temperature pattern with seasonal variation
+day_of_year = np.arange(365)
+seasonal = 15 * np.sin(2 * np.pi * (day_of_year - 80) / 365)  # Peak in summer
+noise = np.random.normal(0, 3, 365)
+temperature = 12 + seasonal + noise  # Base temp ~12°C
+
+# Create DataFrame
+df = pd.DataFrame({"date": dates, "temperature": temperature})
+
+# Create ColumnDataSource with formatted date for hover
+source = ColumnDataSource(
+    data={
+        "date": df["date"],
+        "temperature": df["temperature"],
+        "date_str": df["date"].dt.strftime("%Y-%m-%d"),
+        "temp_str": [f"{t:.1f}" for t in df["temperature"]],
+    }
+)
+
+# Create figure with 4800×2700 px dimensions
+p = figure(
+    width=4800,
+    height=2700,
+    title="line-interactive · bokeh · pyplots.ai",
+    x_axis_label="Date",
+    y_axis_label="Temperature (°C)",
+    x_axis_type="datetime",
+    tools="",  # Start with empty tools, add custom ones
+    toolbar_location="right",
+)
+
+# Add interactive tools
+wheel_zoom = WheelZoomTool()
+pan = PanTool()
+box_zoom = BoxZoomTool()
+reset = ResetTool()
+
+p.add_tools(wheel_zoom, pan, box_zoom, reset)
+p.toolbar.active_scroll = wheel_zoom
+
+# Add hover tool with detailed tooltip
+hover = HoverTool(
+    tooltips=[("Date", "@date_str"), ("Temperature", "@temp_str °C")], mode="vline", line_policy="nearest"
+)
+p.add_tools(hover)
+
+# Plot line with Python Blue color
+p.line(
+    x="date",
+    y="temperature",
+    source=source,
+    line_width=4,
+    line_color="#306998",
+    alpha=0.9,
+    legend_label="Daily Temperature",
+)
+
+# Add circle markers at data points for hover interaction
+p.scatter(
+    x="date",
+    y="temperature",
+    source=source,
+    size=10,
+    fill_color="#306998",
+    line_color="#FFD43B",
+    line_width=2,
+    alpha=0.8,
+)
+
+# Styling - Text sizes for large canvas
+p.title.text_font_size = "36pt"
+p.title.text_color = "#306998"
+p.xaxis.axis_label_text_font_size = "28pt"
+p.yaxis.axis_label_text_font_size = "28pt"
+p.xaxis.major_label_text_font_size = "22pt"
+p.yaxis.major_label_text_font_size = "22pt"
+
+# Axis styling
+p.xaxis.axis_line_width = 3
+p.yaxis.axis_line_width = 3
+p.xaxis.major_tick_line_width = 3
+p.yaxis.major_tick_line_width = 3
+
+# Grid styling - subtle
+p.xgrid.grid_line_color = "#000000"
+p.xgrid.grid_line_alpha = 0.2
+p.xgrid.grid_line_dash = "dashed"
+p.ygrid.grid_line_color = "#000000"
+p.ygrid.grid_line_alpha = 0.2
+p.ygrid.grid_line_dash = "dashed"
+
+# Legend styling
+p.legend.location = "top_left"
+p.legend.label_text_font_size = "22pt"
+p.legend.glyph_width = 50
+p.legend.glyph_height = 50
+p.legend.border_line_color = "#306998"
+p.legend.border_line_width = 2
+p.legend.background_fill_alpha = 0.8
+
+# Background
+p.background_fill_color = "#FAFAFA"
+p.border_fill_color = "#FFFFFF"
+
+# Toolbar styling
+p.toolbar.logo = None
+
+# Save as HTML for interactivity
+output_file("plot.html", title="Interactive Line Chart")
+save(p)
+
+# Save as PNG for static preview
+export_png(p, filename="plot.png")

plots/line-interactive/metadata/bokeh.yaml

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+library: bokeh
+specification_id: line-interactive
+created: '2025-12-30T17:50:19Z'
+updated: '2025-12-30T18:03:47Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20602452572
+issue: 0
+python_version: 3.13.11
+library_version: 3.8.1
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-interactive/bokeh/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-interactive/bokeh/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-interactive/bokeh/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent use of Bokeh interactive tools (WheelZoom, BoxZoom, PanTool, ResetTool)
+    with wheel zoom as default active scroll
+  - Well-configured HoverTool with vline mode and formatted date/temperature display
+  - Appropriate text sizing for 4800x2700 canvas with readable fonts throughout
+  - Realistic seasonal temperature data pattern demonstrating time series characteristics
+  - Clean code structure following KISS principles with proper ColumnDataSource usage
+  - Dual output (HTML for interactivity, PNG for preview) is best practice for Bokeh
+  weaknesses:
+  - Legend placement in top_left overlaps with data peaks in winter months - consider
+    top_right or outside placement
+  - Missing RangeSlider or RangeTool widget for quick time range navigation as specified
+    in requirements
+  - Marker size could be reduced to 6-8 with alpha 0.6 for 365 data points to reduce
+    visual clutter