chengkai3
432 lines
16 KiB
Python
432 lines
16 KiB
Python
from __future__ import annotations
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from collections import Counter
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from datetime import datetime
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from html import escape
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from typing import Any, Mapping, Sequence
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_RISK_LEVEL_LABELS = {
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"high": "高风险",
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"medium": "中风险",
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"low": "低风险",
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}
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def build_report_filename(
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*,
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line_name: str | None,
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report_job_name: str | None,
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generated_at: datetime,
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) -> str:
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base_name = _sanitize_filename(report_job_name or line_name or "防雷分析")
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timestamp = generated_at.strftime("%Y%m%d%H%M%S")
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return f"{base_name}-防雷报告-{timestamp}.doc"
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def build_report_summary_payload(report_data: Mapping[str, Any]) -> dict[str, Any]:
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report = _read_mapping(report_data, "report")
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risk_rows = _read_rows(report_data, "risk_rows")
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selected_risk_rows = _read_rows(report_data, "selected_risk_rows")
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selected_mitigation_rows = _read_rows(report_data, "selected_mitigation_rows")
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selected_scenario_rows = _read_rows(report_data, "selected_scenario_rows")
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factor_counts: Counter[str] = Counter()
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cause_counts: Counter[str] = Counter()
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action_counts: Counter[str] = Counter()
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for row in selected_risk_rows:
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result_json = _read_mapping(row, "result_json")
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for detail in _read_sequence(result_json, "reason_details"):
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label = str(detail.get("label") or detail.get("code") or "-").strip()
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if not label:
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continue
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grade = _as_int(detail.get("grade"))
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triggered = bool(detail.get("triggered"))
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if triggered or (grade is not None and grade <= 2):
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factor_counts[label] += 1
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for item in _split_cn_list(result_json.get("cause_analysis")):
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cause_counts[item] += 1
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for row in selected_mitigation_rows:
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result_json = _read_mapping(row, "result_json")
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for action in _read_sequence(result_json, "mitigation_actions"):
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label = str(action.get("label") or action.get("code") or "-").strip()
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if label:
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action_counts[label] += 1
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generated_at = report.get("generated_at")
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filename = build_report_filename(
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line_name=_read_mapping(report_data, "line").get("name"),
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report_job_name=_as_optional_str(report.get("job_name")),
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generated_at=generated_at if isinstance(generated_at, datetime) else datetime.utcnow(),
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)
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return {
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"report_kind": "fl-analysis",
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"generated_at": generated_at.isoformat() if isinstance(generated_at, datetime) else None,
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"document_filename": filename,
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"source_job_id": _as_optional_str(report.get("source_job_id")),
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"source_job_type": _as_optional_str(report.get("source_job_type")),
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"source_job_name": _as_optional_str(report.get("source_job_name")),
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"risk_job_id": _as_optional_str(report.get("risk_job_id")),
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"risk_job_name": _as_optional_str(report.get("risk_job_name")),
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"mitigation_job_id": _as_optional_str(report.get("mitigation_job_id")),
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"mitigation_job_name": _as_optional_str(report.get("mitigation_job_name")),
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"scenario_job_id": _as_optional_str(report.get("scenario_job_id")),
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"scenario_job_name": _as_optional_str(report.get("scenario_job_name")),
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"selected_tower_count": len(selected_risk_rows),
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"report_row_count": len(selected_mitigation_rows),
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"scenario_row_count": len(selected_scenario_rows),
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"risk_counts": _count_risk_levels(risk_rows),
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"selected_risk_counts": _count_risk_levels(selected_risk_rows),
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"post_mitigation_risk_counts": _count_risk_levels(selected_mitigation_rows),
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"post_recalc_risk_counts": _count_risk_levels(selected_scenario_rows),
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"selected_factor_trigger_counts": dict(factor_counts.most_common()),
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"selected_cause_counts": dict(cause_counts.most_common()),
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"mitigation_action_counts": dict(action_counts.most_common()),
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"has_mitigation_data": bool(selected_mitigation_rows),
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"has_scenario_data": bool(selected_scenario_rows),
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}
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def build_report_document(report_data: Mapping[str, Any]) -> tuple[str, bytes]:
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line = _read_mapping(report_data, "line")
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report = _read_mapping(report_data, "report")
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risk_rows = _read_rows(report_data, "risk_rows")
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selected_risk_rows = _read_rows(report_data, "selected_risk_rows")
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selected_mitigation_rows = _read_rows(report_data, "selected_mitigation_rows")
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selected_scenario_rows = _read_rows(report_data, "selected_scenario_rows")
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summary = build_report_summary_payload(report_data)
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generated_at = report.get("generated_at")
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if isinstance(generated_at, datetime):
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generated_at_text = generated_at.strftime("%Y-%m-%d %H:%M:%S")
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else:
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generated_at_text = "-"
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source_job_type = _format_job_type(_as_optional_str(report.get("source_job_type")))
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source_job_name = _as_optional_str(report.get("source_job_name")) or "-"
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mitigation_job_name = _as_optional_str(report.get("mitigation_job_name")) or "未关联措施任务"
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scenario_job_name = _as_optional_str(report.get("scenario_job_name")) or "未关联复算任务"
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scenario_base_job_type = _format_job_type(_as_optional_str(report.get("scenario_base_job_type")))
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if scenario_base_job_type == "-":
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scenario_base_job_type = "原计算任务"
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factor_rows = [
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[label, str(count)]
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for label, count in summary["selected_factor_trigger_counts"].items()
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] or [["未命中重点风险因子", "0"]]
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cause_rows = [
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[label, str(count)]
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for label, count in summary["selected_cause_counts"].items()
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] or [["未提取到高风险原因", "0"]]
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risk_table_rows = []
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for row in selected_risk_rows:
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result_json = _read_mapping(row, "result_json")
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risk_table_rows.append(
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[
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_display(row.get("tower_no")),
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_format_risk_level(row.get("risk_level")),
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_display(result_json.get("score")),
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_display(result_json.get("cause_analysis")),
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_display(result_json.get("mitigation_recommendation")),
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]
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)
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mitigation_table_rows = []
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for row in selected_mitigation_rows:
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result_json = _read_mapping(row, "result_json")
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mitigation_table_rows.append(
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[
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_display(row.get("tower_no")),
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_format_risk_level(result_json.get("current_risk_level")),
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_format_risk_level(result_json.get("expected_risk_level") or row.get("risk_level")),
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_join_action_summaries(result_json),
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_display(result_json.get("recommendation_result")),
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]
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)
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scenario_table_rows = []
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for row in selected_scenario_rows:
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result_json = _read_mapping(row, "result_json")
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scenario_table_rows.append(
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[
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_display(row.get("tower_no")),
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_format_number(result_json.get("counterstrike_withstand_ka")),
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_format_number(result_json.get("counterstrike_trip_rate")),
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_format_number(result_json.get("shielding_withstand_ka")),
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_format_number(result_json.get("shielding_trip_rate")),
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_format_total_trip_rate(result_json),
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_format_risk_level(row.get("risk_level")),
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]
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)
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html = f"""<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8" />
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<title>{escape(summary["document_filename"])}</title>
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<style>
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body {{
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font-family: "SimSun", "Noto Serif CJK SC", serif;
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font-size: 12pt;
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line-height: 1.65;
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color: #222;
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margin: 28px 36px;
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}}
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h1, h2, h3 {{
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color: #0f2742;
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margin: 0 0 12px;
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}}
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h1 {{
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font-size: 22pt;
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text-align: center;
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margin-top: 24px;
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}}
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h2 {{
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font-size: 16pt;
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margin-top: 28px;
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border-bottom: 1px solid #c8d3df;
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padding-bottom: 4px;
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}}
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h3 {{
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font-size: 13pt;
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margin-top: 18px;
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}}
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p {{
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margin: 8px 0;
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text-indent: 2em;
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}}
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.meta {{
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margin: 20px auto 0;
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width: 100%;
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border-collapse: collapse;
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}}
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.meta td {{
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border: 1px solid #cad5df;
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padding: 8px 10px;
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vertical-align: top;
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}}
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table.data {{
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width: 100%;
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border-collapse: collapse;
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margin: 12px 0 18px;
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table-layout: fixed;
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}}
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table.data th,
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table.data td {{
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border: 1px solid #cad5df;
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padding: 8px 10px;
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vertical-align: top;
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word-break: break-word;
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}}
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table.data th {{
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background: #edf3f8;
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font-weight: 700;
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}}
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.muted {{
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color: #5f6c7b;
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text-indent: 0;
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}}
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</style>
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</head>
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<body>
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<h1>{escape(_display(report.get("job_name") or line.get("name") or "防雷报告"))}</h1>
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<table class="meta">
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<tr>
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<td><strong>线路名称</strong><br />{escape(_display(line.get("name")))}</td>
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<td><strong>线路编码</strong><br />{escape(_display(line.get("code")))}</td>
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<td><strong>电压等级</strong><br />{escape(_display(line.get("voltage_kv")))} kV</td>
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</tr>
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<tr>
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<td><strong>生成时间</strong><br />{escape(generated_at_text)}</td>
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<td><strong>报告来源</strong><br />{escape(source_job_type)} / {escape(source_job_name)}</td>
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<td><strong>关联任务</strong><br />措施：{escape(mitigation_job_name)}<br />复算：{escape(scenario_job_name)}</td>
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</tr>
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</table>
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<h2>一、线路概况</h2>
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<p>本报告基于线路既有防雷分析任务结果生成，复用了源端“先形成任务结果，再按杆塔勾选纳入报告范围”的工作流。当前线路共纳入 {len(selected_risk_rows)} 座重点杆塔进行报告输出，原始风险评估覆盖 {len(risk_rows)} 座杆塔。</p>
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<h2>二、重点风险因子概览</h2>
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<p>针对纳入报告的重点杆塔，统计其已触发或达到重点阈值的风险因子，用于快速识别本线路防雷薄弱项。</p>
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{_render_table(["风险因子", "命中杆塔数"], factor_rows)}
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<h3>高风险原因分布</h3>
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{_render_table(["原因", "出现次数"], cause_rows)}
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<h2>三、雷害风险评估结果</h2>
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<p>线路整体风险分布为：高风险 {summary["risk_counts"]["high"]} 座，中风险 {summary["risk_counts"]["medium"]} 座，低风险 {summary["risk_counts"]["low"]} 座。纳入报告的重点杆塔中，高风险 {summary["selected_risk_counts"]["high"]} 座，中风险 {summary["selected_risk_counts"]["medium"]} 座。</p>
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{_render_table(["杆塔号", "风险等级", "得分", "高风险原因", "措施建议"], risk_table_rows or [["-", "-", "-", "当前任务暂无重点杆塔结果", "-"]])}
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<h2>四、差异化防雷措施与预期效果</h2>
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<p>若已存在关联的措施推荐任务，则下表展示当前风险、建议后风险以及推荐动作；若尚未生成措施任务，则报告保留风险原因与通用治理建议。</p>
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{_render_table(["杆塔号", "当前风险", "建议后风险", "改造动作", "措施结论"], mitigation_table_rows or [["-", "-", "-", "当前未关联成功的措施推荐任务", "-"]])}
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<h3>表14 采取措施后的计算结果表</h3>
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<p>若已生成与措施任务关联的加装避雷器复算任务，则下表按 {escape(scenario_base_job_type)} 口径展示补装避雷器后的耐雷水平、跳闸率与风险等级；若未生成复算任务，则此表保留为空。</p>
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{_render_table(["杆塔号", "反击耐雷水平(kA)", "反击跳闸率", "绕击耐雷水平(kA)", "绕击跳闸率", "总雷击跳闸率", "风险等级"], scenario_table_rows or [["-", "-", "-", "-", "-", "-", "当前未关联成功的加装避雷器复算任务"]])}
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<p class="muted">说明：本报告为可直接下载的 Word 兼容文档，内容按风险评估结果和已关联的措施推荐结果动态生成。</p>
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</body>
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</html>
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"""
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return summary["document_filename"], html.encode("utf-8")
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def _sanitize_filename(value: str) -> str:
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cleaned = "".join("-" if char in '<>:"/\\|?*' else char for char in value).strip()
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return cleaned[:80] or "防雷分析"
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def _count_risk_levels(rows: Sequence[Mapping[str, Any]]) -> dict[str, int]:
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counts = {"high": 0, "medium": 0, "low": 0}
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for row in rows:
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risk_level = _normalize_risk_level(row.get("risk_level"))
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if risk_level in counts:
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counts[risk_level] += 1
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return counts
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def _format_job_type(value: str | None) -> str:
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if value == "risk":
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return "风险评估任务"
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if value == "mitigation":
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return "措施推荐任务"
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if value == "normal":
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return "普通计算任务"
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if value == "tongtiao":
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return "同跳计算任务"
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if value == "scenario":
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return "加装避雷器复算任务"
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if value == "report":
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return "报告任务"
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return value or "-"
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def _format_risk_level(value: Any) -> str:
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normalized = _normalize_risk_level(value)
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if normalized is None:
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return _display(value)
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return _RISK_LEVEL_LABELS[normalized]
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def _normalize_risk_level(value: Any) -> str | None:
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if value is None:
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return None
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text = str(value).strip().lower()
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if not text:
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return None
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if text in {"high", "高", "高风险"}:
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return "high"
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if text in {"medium", "中", "中风险"}:
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return "medium"
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if text in {"low", "低", "低风险"}:
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return "low"
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return None
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def _join_action_summaries(result_json: Mapping[str, Any]) -> str:
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actions = []
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for action in _read_sequence(result_json, "mitigation_actions"):
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summary = str(action.get("summary") or action.get("label") or action.get("code") or "").strip()
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if summary:
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actions.append(summary)
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return "；".join(actions) if actions else "-"
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def _split_cn_list(value: Any) -> list[str]:
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if value is None:
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return []
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text = str(value).replace("\n", "；")
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items = []
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for separator in ("；", ";", "、", ",", "，"):
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if separator in text:
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text = text.replace(separator, "；")
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for item in text.split("；"):
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cleaned = item.strip()
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if cleaned:
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items.append(cleaned)
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return items
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def _render_table(headers: Sequence[str], rows: Sequence[Sequence[str]]) -> str:
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header_html = "".join(f"<th>{escape(str(item))}</th>" for item in headers)
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body_html = "".join(
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"<tr>" + "".join(f"<td>{escape(str(cell))}</td>" for cell in row) + "</tr>"
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for row in rows
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)
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return f'<table class="data"><thead><tr>{header_html}</tr></thead><tbody>{body_html}</tbody></table>'
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def _read_rows(payload: Mapping[str, Any], key: str) -> list[Mapping[str, Any]]:
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value = payload.get(key)
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if not isinstance(value, Sequence) or isinstance(value, (str, bytes, bytearray)):
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return []
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return [item for item in value if isinstance(item, Mapping)]
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def _read_mapping(payload: Mapping[str, Any], key: str) -> Mapping[str, Any]:
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value = payload.get(key)
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return value if isinstance(value, Mapping) else {}
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def _read_sequence(payload: Mapping[str, Any], key: str) -> list[Mapping[str, Any]]:
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value = payload.get(key)
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if not isinstance(value, Sequence) or isinstance(value, (str, bytes, bytearray)):
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return []
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return [item for item in value if isinstance(item, Mapping)]
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def _display(value: Any) -> str:
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if value is None:
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return "-"
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text = str(value).strip()
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return text or "-"
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def _format_number(value: Any) -> str:
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parsed = _as_optional_float(value)
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if parsed is None:
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return "-"
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return f"{parsed:.4f}".rstrip("0").rstrip(".")
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def _format_total_trip_rate(result_json: Mapping[str, Any]) -> str:
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counterstrike_value = _as_optional_float(result_json.get("counterstrike_trip_rate"))
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shielding_value = _as_optional_float(result_json.get("shielding_trip_rate"))
|
||
if counterstrike_value is None and shielding_value is None:
|
||
return "-"
|
||
return _format_number((counterstrike_value or 0.0) + (shielding_value or 0.0))
|
||
|
||
|
||
def _as_optional_str(value: Any) -> str | None:
|
||
if value is None:
|
||
return None
|
||
text = str(value).strip()
|
||
return text or None
|
||
|
||
|
||
def _as_optional_float(value: Any) -> float | None:
|
||
try:
|
||
return float(value)
|
||
except (TypeError, ValueError):
|
||
return None
|
||
|
||
|
||
def _as_int(value: Any) -> int | None:
|
||
if isinstance(value, bool):
|
||
return int(value)
|
||
if isinstance(value, int):
|
||
return value
|
||
if isinstance(value, float):
|
||
return int(value)
|
||
try:
|
||
return int(str(value).strip())
|
||
except (TypeError, ValueError):
|
||
return None
|