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feat(pygal): implement bullet-basic (#1042)
## Implementation: `bullet-basic` - pygal Implements the **pygal** version of `bullet-basic`. **File:** `plots/bullet-basic/implementations/pygal.py` **Parent Issue:** #999 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20257947709)* --------- 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>
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‎plots/bullet-basic/implementations/pygal.py‎

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"""
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bullet-basic: Basic Bullet Chart
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Library: pygal
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Pygal lacks a native bullet chart type. We use HorizontalStackedBar for qualitative
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ranges, then inject custom SVG elements for actual value bars and target markers.
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"""
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import cairosvg
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import pygal
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from pygal.style import Style
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# Data - Sales KPIs showing actual vs target with qualitative ranges
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metrics = [
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{"label": "Revenue", "actual": 275, "target": 250, "max": 300, "unit": "$K"},
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{"label": "Profit", "actual": 85, "target": 100, "max": 120, "unit": "$K"},
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{"label": "New Orders", "actual": 320, "target": 350, "max": 400, "unit": ""},
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{"label": "Customers", "actual": 1450, "target": 1400, "max": 1600, "unit": ""},
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{"label": "Satisfaction", "actual": 4.2, "target": 4.5, "max": 5.0, "unit": "/5"},
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]
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# Qualitative range thresholds as percentage of max
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POOR_PCT = 50
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SATISFACTORY_PCT = 75
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# Custom style for bullet chart with grayscale bands
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custom_style = Style(
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background="white",
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plot_background="white",
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foreground="#333333",
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foreground_strong="#333333",
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foreground_subtle="#666666",
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colors=(
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"#E0E0E0", # Poor range (lightest)
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"#B8B8B8", # Satisfactory range
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"#909090", # Good range (darkest)
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"#306998", # Actual value (Python blue)
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"#1a1a1a", # Target marker (black)
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),
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title_font_size=72,
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label_font_size=42,
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major_label_font_size=40,
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legend_font_size=36,
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value_font_size=32,
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tooltip_font_size=32,
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)
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# Create horizontal stacked bar chart for range bands
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chart = pygal.HorizontalStackedBar(
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width=4800,
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height=2700,
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title="bullet-basic · pygal · pyplots.ai",
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style=custom_style,
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show_legend=True,
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legend_at_bottom=True,
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legend_box_size=28,
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print_values=False,
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show_y_guides=False,
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show_x_guides=True,
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x_label_rotation=0,
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margin=80,
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spacing=40,
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x_title="Performance (% of Maximum)",
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range=(0, 100),
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)
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# Build labels and range data
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labels = []
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poor_vals = []
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satisfactory_vals = []
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good_vals = []
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actual_pcts = []
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target_pcts = []
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for m in metrics:
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actual_pct = (m["actual"] / m["max"]) * 100
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target_pct = (m["target"] / m["max"]) * 100
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labels.append(f"{m['label']} ({m['actual']}{m['unit']})")
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# Stacked segments for qualitative ranges
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poor_vals.append(POOR_PCT)
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satisfactory_vals.append(SATISFACTORY_PCT - POOR_PCT)
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good_vals.append(100 - SATISFACTORY_PCT)
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actual_pcts.append(actual_pct)
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target_pcts.append(target_pct)
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chart.x_labels = labels
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chart.add("Poor (0-50%)", poor_vals)
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chart.add("Satisfactory (50-75%)", satisfactory_vals)
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chart.add("Good (75-100%)", good_vals)
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# Render base chart to SVG, then inject actual bars and target markers
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svg_string = chart.render().decode("utf-8")
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# Pygal plot coordinates (from SVG analysis):
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# Plot area: transform="translate(624, 192)", width=4096, height=2104
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# Bars start at x=78.77 within plot (total from origin: 624 + 78.77 = 702.77)
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# X-axis 0 maps to ~78.77, 100 maps to ~4017.23 (range of ~3938.46 pixels)
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PLOT_OFFSET_X = 624
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PLOT_OFFSET_Y = 192
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BAR_START_X = 78.77 # Within plot coordinates
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X_SCALE = 39.3846 # pixels per percentage point (3938.46 / 100)
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# Row Y positions (from SVG: y values in <desc> tags) - relative to plot origin
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ROW_Y_CENTERS = [1861.23, 1456.62, 1052.0, 647.38, 242.77] # Revenue, Profit, Orders, Customers, Satisfaction
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# Build custom SVG elements for actual bars and target markers
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custom_elements = []
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for i, (actual_pct, target_pct) in enumerate(zip(actual_pcts, target_pcts, strict=True)):
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# Calculate positions in plot coordinates
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y_center = PLOT_OFFSET_Y + ROW_Y_CENTERS[i]
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x_start = PLOT_OFFSET_X + BAR_START_X
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# Actual value bar - narrower bar centered on row
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actual_width = actual_pct * X_SCALE
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bar_height = 100 # Thinner than the range bands
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custom_elements.append(
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f'<rect x="{x_start}" y="{y_center - bar_height / 2}" '
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f'width="{actual_width}" height="{bar_height}" fill="#306998"/>'
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)
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# Target marker - thin vertical line extending beyond the bar
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target_x = x_start + target_pct * X_SCALE
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marker_height = 180
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marker_width = 12
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custom_elements.append(
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f'<rect x="{target_x - marker_width / 2}" y="{y_center - marker_height / 2}" '
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f'width="{marker_width}" height="{marker_height}" fill="#1a1a1a"/>'
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)
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# Add legend entries for Actual and Target (positioned after existing legend items)
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legend_y = 2574 # Same line as existing legend
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legend_x_actual = 3200
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legend_x_target = 3700
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custom_elements.append(f'<rect x="{legend_x_actual}" y="{legend_y}" width="28" height="28" fill="#306998"/>')
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custom_elements.append(
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f'<text x="{legend_x_actual + 40}" y="{legend_y + 24}" '
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f'font-family="Consolas, monospace" font-size="36" fill="#333">Actual</text>'
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)
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custom_elements.append(f'<rect x="{legend_x_target}" y="{legend_y}" width="28" height="28" fill="#1a1a1a"/>')
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custom_elements.append(
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f'<text x="{legend_x_target + 40}" y="{legend_y + 24}" '
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f'font-family="Consolas, monospace" font-size="36" fill="#333">Target</text>'
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)
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# Inject custom elements before closing </svg>
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injection = "\n".join(custom_elements)
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svg_output = svg_string.replace("</svg>", f"{injection}\n</svg>")
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# Save SVG and PNG
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with open("plot.html", "w") as f:
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f.write(svg_output)
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cairosvg.svg2png(bytestring=svg_output.encode(), write_to="plot.png")

‎plots/bullet-basic/metadata/pygal.yaml‎

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# Per-library metadata for pygal implementation of bullet-basic
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# Auto-generated by impl-generate.yml
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library: pygal
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specification_id: bullet-basic
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# Preview URLs (filled by workflow)
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preview_url: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/pygal/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/pygal/plot_thumb.png
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preview_html: https://storage.googleapis.com/pyplots-images/plots/bullet-basic/pygal/plot.html
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current:
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version: 0
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generated_at: 2025-12-16T05:56:05Z
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generated_by: claude-opus-4-5-20251101
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workflow_run: 20257947709
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issue: 999
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quality_score: 91
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# Version info (filled by workflow)
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python_version: "3.13.11"
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library_version: "unknown"
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history: []

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