111 lines
3.4 KiB
Python
111 lines
3.4 KiB
Python
"""Read native PowerPoint chart display caches for slide-library analysis.
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The template-fill workflow edits chart data from explicit fill plans. This
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module only reads the data currently visible in a chart XML part, keeping
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workbook parsing out of the analyzer.
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"""
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from __future__ import annotations
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from typing import Any
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from xml.etree import ElementTree as ET
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from .ooxml import NS
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def empty_chart_data() -> dict[str, Any]:
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return {
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"chart_type": None,
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"category_count": 0,
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"series_count": 0,
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"categories": [],
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"series": [],
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}
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def _local_name(tag: str) -> str:
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return tag.rsplit("}", 1)[-1]
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def _chart_types_with_series(chart_root: ET.Element) -> list[ET.Element]:
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plot_area = chart_root.find(".//c:plotArea", NS)
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if plot_area is None:
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return []
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chart_types: list[ET.Element] = []
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for child in list(plot_area):
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if _local_name(child.tag).endswith("Chart") and child.findall("c:ser", NS):
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chart_types.append(child)
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return chart_types
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def _coerce_number(value: str) -> int | float | str:
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try:
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number = float(value)
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except ValueError:
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return value
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if number.is_integer():
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return int(number)
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return number
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def _cache_values(parent: ET.Element | None, *, numeric: bool = False) -> list[Any]:
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if parent is None:
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return []
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cache = parent.find(".//c:strCache", NS)
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if cache is None:
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cache = parent.find(".//c:numCache", NS)
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if cache is None:
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return []
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values: list[Any] = []
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for point in cache.findall("c:pt", NS):
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value = point.findtext("c:v", default="", namespaces=NS)
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values.append(_coerce_number(value) if numeric else value)
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return values
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def _series_name(series: ET.Element, fallback: str) -> str:
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tx = series.find("c:tx", NS)
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if tx is None:
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return fallback
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values = _cache_values(tx)
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if values:
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return str(values[0])
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direct = tx.findtext("c:v", default="", namespaces=NS)
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return direct or fallback
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def read_chart_data(chart_root: ET.Element) -> dict[str, Any]:
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"""Return a compact summary of chart type, categories, series, and values."""
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chart_types = _chart_types_with_series(chart_root)
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if not chart_types:
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return empty_chart_data()
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first_series = chart_types[0].find("c:ser", NS)
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categories = _cache_values(first_series.find("c:cat", NS)) if first_series is not None else []
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series_payload: list[dict[str, Any]] = []
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plot_types: list[str] = []
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for chart_type in chart_types:
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plot_name = _local_name(chart_type.tag)
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plot_types.append(plot_name)
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for series in chart_type.findall("c:ser", NS):
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index = len(series_payload) + 1
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series_categories = _cache_values(series.find("c:cat", NS))
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if not categories and series_categories:
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categories = series_categories
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series_payload.append(
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{
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"name": _series_name(series, f"系列{index}"),
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"values": _cache_values(series.find("c:val", NS), numeric=True),
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"chart_type": plot_name,
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}
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)
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return {
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"chart_type": plot_types[0] if len(set(plot_types)) == 1 else "comboChart",
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"plot_types": plot_types,
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"category_count": len(categories),
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"series_count": len(series_payload),
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"categories": categories,
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"series": series_payload,
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}
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