feat(bokeh): implement line-markers (#2635)

## Implementation: `line-markers` - bokeh

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

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

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20594557478)*

---------

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

Author: github-actions[bot]

plots/line-markers/implementations/bokeh.py

@@ -0,0 +1,86 @@
+""" pyplots.ai
+line-markers: Line Plot with Markers
+Library: bokeh 3.8.1 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+from bokeh.io import export_png, save
+from bokeh.models import ColumnDataSource, Legend
+from bokeh.plotting import figure
+
+
+# Data - Monthly temperature readings for three weather stations
+np.random.seed(42)
+months = np.arange(1, 13)
+month_labels = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
+
+# Temperature patterns for different stations (°C)
+base_temp = np.array([2, 4, 8, 12, 17, 21, 24, 23, 19, 13, 7, 3])
+station_a = base_temp + np.random.randn(12) * 1.5
+station_b = base_temp + 3 + np.random.randn(12) * 1.5  # Warmer station
+station_c = base_temp - 2 + np.random.randn(12) * 1.5  # Cooler station
+
+# Create ColumnDataSources
+source_a = ColumnDataSource(data={"x": months, "y": station_a})
+source_b = ColumnDataSource(data={"x": months, "y": station_b})
+source_c = ColumnDataSource(data={"x": months, "y": station_c})
+
+# Create figure
+p = figure(
+    width=4800,
+    height=2700,
+    title="line-markers · bokeh · pyplots.ai",
+    x_axis_label="Month",
+    y_axis_label="Temperature (°C)",
+)
+
+# Color palette
+color_a = "#306998"  # Python Blue
+color_b = "#FFD43B"  # Python Yellow
+color_c = "#E74C3C"  # Colorblind-safe red
+
+# Plot lines with markers - Station A (circles)
+line_a = p.line("x", "y", source=source_a, line_width=4, color=color_a, alpha=0.9)
+scatter_a = p.scatter("x", "y", source=source_a, size=20, color=color_a, marker="circle", alpha=0.9)
+
+# Station B (squares)
+line_b = p.line("x", "y", source=source_b, line_width=4, color=color_b, alpha=0.9)
+scatter_b = p.scatter("x", "y", source=source_b, size=20, color=color_b, marker="square", alpha=0.9)
+
+# Station C (triangles)
+line_c = p.line("x", "y", source=source_c, line_width=4, color=color_c, alpha=0.9)
+scatter_c = p.scatter("x", "y", source=source_c, size=20, color=color_c, marker="triangle", alpha=0.9)
+
+# Legend
+legend = Legend(
+    items=[("Station A", [line_a, scatter_a]), ("Station B", [line_b, scatter_b]), ("Station C", [line_c, scatter_c])],
+    location="top_left",
+)
+
+p.add_layout(legend)
+p.legend.label_text_font_size = "20pt"
+p.legend.glyph_height = 30
+p.legend.glyph_width = 30
+p.legend.spacing = 10
+p.legend.padding = 15
+p.legend.background_fill_alpha = 0.7
+
+# Style text for 4800x2700 canvas
+p.title.text_font_size = "28pt"
+p.xaxis.axis_label_text_font_size = "22pt"
+p.yaxis.axis_label_text_font_size = "22pt"
+p.xaxis.major_label_text_font_size = "18pt"
+p.yaxis.major_label_text_font_size = "18pt"
+
+# Custom x-axis tick labels for months
+p.xaxis.ticker = months
+p.xaxis.major_label_overrides = dict(zip(months, month_labels, strict=True))
+
+# Grid styling
+p.grid.grid_line_alpha = 0.3
+p.grid.grid_line_dash = "dashed"
+
+# Output
+export_png(p, filename="plot.png")
+save(p, filename="plot.html")

plots/line-markers/metadata/bokeh.yaml

@@ -0,0 +1,25 @@
+library: bokeh
+specification_id: line-markers
+created: '2025-12-30T10:40:49Z'
+updated: '2025-12-30T10:50:29Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20594557478
+issue: 0
+python_version: 3.13.11
+library_version: 3.8.1
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-markers/bokeh/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-markers/bokeh/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-markers/bokeh/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent use of different marker shapes (circle, square, triangle) for series
+    differentiation
+  - Clean implementation of monthly temperature data with realistic seasonal patterns
+  - Good color palette that is colorblind-accessible (blue, yellow, red)
+  - Properly sized text for the 4800x2700 canvas
+  - Both PNG and interactive HTML outputs generated
+  - Good use of ColumnDataSource for data management
+  weaknesses:
+  - Legend text and glyph sizes could be slightly larger for better visibility at
+    full canvas size