Lars
3ab5dae130
- Introduced the `viz_bundle` block type to the report profile schema, allowing for the inclusion of bundled visualizations in PDF reports. - Updated the `build_structured_report_pdf` function to handle `VizBundleBlock` and append its content to the report. - Enhanced the report catalog API to include details for the new `viz_bundle` block type. - Added configuration editors for various visualization bundles in the frontend settings page. - Updated tests to validate the new `viz_bundle` functionality and ensure proper handling of report profiles. - Bumped application version to reflect these enhancements.
92 lines
3.4 KiB
Python
92 lines
3.4 KiB
Python
"""Chart.js-ähnliche Payloads → PNG (Matplotlib). Von PDF- und Bundle-Rendering gemeinsam genutzt."""
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from __future__ import annotations
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import io
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from typing import Any
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import matplotlib
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matplotlib.use("Agg")
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import matplotlib.pyplot as plt
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def _color_to_rgb(hex_or_rgba: str) -> tuple[float, float, float]:
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s = (hex_or_rgba or "#333333").strip()
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if s.startswith("#") and len(s) >= 7:
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try:
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r = int(s[1:3], 16) / 255.0
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g = int(s[3:5], 16) / 255.0
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b = int(s[5:7], 16) / 255.0
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return (r, g, b)
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except ValueError:
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pass
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return (0.12, 0.62, 0.46)
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def chart_payload_to_png(payload: dict[str, Any], fig_width_in: float = 6.2, fig_height_in: float = 3.4) -> bytes:
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chart_type = payload.get("chart_type") or "line"
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data = payload.get("data") or {}
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labels = data.get("labels") or []
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datasets = data.get("datasets") or []
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fig, ax = plt.subplots(figsize=(fig_width_in, fig_height_in), dpi=120)
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ax.set_facecolor("#fafaf9")
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fig.patch.set_facecolor("#ffffff")
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if chart_type == "pie" and datasets:
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ds0 = datasets[0]
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values = ds0.get("data") or []
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colors = ds0.get("backgroundColor") or ["#1D9E75", "#378ADD", "#D85A30"]
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if labels and values and len(labels) == len(values):
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ax.pie(values, labels=labels, autopct="%1.0f%%", colors=colors[: len(values)], startangle=90)
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ax.axis("equal")
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else:
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ax.text(0.5, 0.5, "Keine Daten", ha="center", va="center", transform=ax.transAxes)
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elif chart_type in ("line", "bar", "scatter") and datasets:
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x = range(len(labels)) if labels else []
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for i, ds in enumerate(datasets):
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y = ds.get("data") or []
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if not y:
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continue
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lab = ds.get("label") or f"Serie {i + 1}"
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col = _color_to_rgb(str(ds.get("borderColor") or ds.get("backgroundColor") or "#1D9E75"))
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if chart_type == "bar":
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yv = y[: len(labels)] if labels else y
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bg = ds.get("backgroundColor")
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if isinstance(bg, list):
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cols = [_color_to_rgb(str(c)) for c in bg[: len(yv)]]
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else:
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cols = [_color_to_rgb(str(bg or "#1D9E75"))] * len(yv)
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ax.bar(list(range(len(yv))), yv, label=lab, color=cols[: len(yv)], alpha=0.88)
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else:
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ax.plot(
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list(x)[: len(y)],
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y,
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label=lab,
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color=col,
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linewidth=1.6,
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marker="o",
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markersize=2,
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)
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if labels and chart_type != "bar":
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step = max(1, len(labels) // 8)
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ax.set_xticks(list(x)[::step])
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ax.set_xticklabels([labels[j] for j in range(0, len(labels), step)], rotation=25, fontsize=7)
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elif labels and chart_type == "bar":
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ax.set_xticks(list(x))
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ax.set_xticklabels(labels, rotation=30, fontsize=7)
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ax.legend(loc="upper right", fontsize=7)
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ax.grid(True, alpha=0.25)
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ax.set_xmargin(0.02)
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else:
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ax.text(0.5, 0.5, "Diagrammtyp nicht unterstützt oder leer", ha="center", va="center", transform=ax.transAxes)
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fig.tight_layout()
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buf = io.BytesIO()
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fig.savefig(buf, format="png", bbox_inches="tight", facecolor=fig.get_facecolor())
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plt.close(fig)
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buf.seek(0)
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return buf.read()
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