[migrate]:[FL-21][防雷分析普通/同跳计算接入ATP执行链路]
Co-authored-by: multica-agent <github@multica.ai>
This commit is contained in:
chengkai3
@@ -89,7 +89,10 @@ class FlAnalysisJobCreateRequest(BaseModel):
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job_name: str | None = Field(default=None, min_length=1, max_length=255)
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job_type: FlAnalysisJobType = "normal"
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external_adapter: FlAnalysisAdapter = "placeholder"
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adapter_config_json: dict[str, Any] = Field(default_factory=dict)
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adapter_config_json: dict[str, Any] = Field(
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default_factory=dict,
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description="normal/tongtiao 任务在 external_adapter=atp/wine 时可传 model_id、version_id/version_no、result_file、parameter_bindings 等 ATP 执行配置。",
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)
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execution_options_json: dict[str, Any] = Field(
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default_factory=dict,
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description="normal/tongtiao 任务可传波形、闪络判据以及波头/波尾扫描参数；mitigation 任务可传 source_job_id、selected_tower_ids、non_construction。",
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@@ -0,0 +1,610 @@
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from __future__ import annotations
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import json
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import os
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import re
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import subprocess
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any
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from sqlalchemy.orm import Session
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from ..models.atp_model import AtpModel, AtpModelVersion
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from ..models.base import utcnow
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from ..models.fl_analysis import FlAnalysisJob, FlAnalysisTowerSnapshot
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from ..schemas.atp_model import AtpSimulationRunRequest
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from .atp_model_service import (
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_resolve_engine_workdir,
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_resolve_native_engine_executable,
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_resolve_target_version,
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_resolve_timeout,
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_resolve_wine_engine_executable,
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_safe_entry_filename,
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_truncate_output,
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get_model_by_id,
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)
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PLACEHOLDER_PATTERN = re.compile(r"{{\s*([^{}]+?)\s*}}")
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DEFAULT_JSON_MARKERS = ("FL_ANALYSIS_RESULT_BEGIN", "FL_ANALYSIS_RESULT_END")
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LEGACY_RESULT_KEY_MAP = {
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"反击耐雷水平": "counterstrike_withstand_ka",
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"反击跳闸率": "counterstrike_trip_rate",
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"绕击耐雷水平": "shielding_withstand_ka",
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"绕击跳闸率": "shielding_trip_rate",
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"雷击风险等级": "risk_grade",
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"风险等级": "risk_grade",
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"单相闪络相": "flashover_phase",
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"闪络相": "flashover_phase",
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"主导相组": "dominant_phase_set",
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"同跳跳闸率": "counterstrike_trip_rate",
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}
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NUMERIC_RESULT_KEYS = {
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"counterstrike_withstand_ka",
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"counterstrike_trip_rate",
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"shielding_withstand_ka",
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"shielding_trip_rate",
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"score",
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"risk_grade",
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}
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@dataclass(slots=True)
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class ResolvedExternalWaveformJob:
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adapter: str
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model: AtpModel
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version: AtpModelVersion
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timeout_seconds: int
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extra_args: list[str]
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environment: dict[str, str]
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contract: dict[str, Any]
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parameter_bindings: dict[str, Any]
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@dataclass(slots=True)
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class ExternalTowerExecutionResult:
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result_json: dict[str, Any]
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engine_command: str
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working_dir: str
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stdout_text: str | None
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stderr_text: str | None
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def resolve_external_waveform_job(
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db: Session,
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*,
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external_adapter: str,
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adapter_config_json: dict[str, Any],
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) -> ResolvedExternalWaveformJob:
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adapter = str(external_adapter or "").strip().lower()
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if adapter not in {"atp", "wine"}:
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raise RuntimeError(f"Unsupported external adapter: {external_adapter}")
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config = dict(adapter_config_json or {})
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model_id = str(config.get("model_id") or "").strip()
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if not model_id:
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raise RuntimeError("外部 ATP/Wine 任务缺少 adapter_config_json.model_id")
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model = get_model_by_id(db, model_id)
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if model is None:
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raise RuntimeError(f"指定的 ATP 模型不存在: {model_id}")
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version_id = str(config.get("version_id") or "").strip() or None
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version_no = _coerce_positive_int(config.get("version_no"))
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version = _resolve_target_version(
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db,
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model=model,
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payload=AtpSimulationRunRequest(version_id=version_id, version_no=version_no),
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)
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if not (version.atp_text or "").strip():
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raise RuntimeError(f"ATP 模型版本缺少可执行模板: {model.code} v{version.version_no}")
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manifest_contract = _read_object((version.artifact_manifest_json or {}).get("fl_analysis"))
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adapter_contract = {
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key: value
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for key, value in config.items()
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if key
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in {
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"result_file",
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"result_format",
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"result_labels",
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"result_json_pointer",
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"result_key_map",
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"stdout_json_markers",
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}
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}
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parameter_bindings = {
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**_read_object(manifest_contract.get("parameter_bindings")),
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**_read_object(config.get("parameter_bindings")),
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}
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contract = {
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**manifest_contract,
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**adapter_contract,
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}
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contract["parameter_bindings"] = parameter_bindings
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timeout_seconds = _resolve_timeout(_coerce_positive_int(config.get("timeout_seconds")))
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extra_args = [str(item).strip() for item in list(config.get("extra_args") or []) if str(item).strip()]
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environment = {
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str(key): str(value)
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for key, value in _read_object(config.get("environment")).items()
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if str(key).strip()
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}
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return ResolvedExternalWaveformJob(
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adapter=adapter,
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model=model,
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version=version,
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timeout_seconds=timeout_seconds,
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extra_args=extra_args,
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environment=environment,
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contract=contract,
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parameter_bindings=parameter_bindings,
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)
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def render_atp_template(
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template: str,
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*,
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context: dict[str, Any],
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parameter_bindings: dict[str, Any] | None = None,
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) -> str:
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bindings = parameter_bindings or {}
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def replace_placeholder(match: re.Match[str]) -> str:
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expression = match.group(1).strip()
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return _render_placeholder(expression, context=context, parameter_bindings=bindings)
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return PLACEHOLDER_PATTERN.sub(replace_placeholder, template)
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def execute_external_waveform_tower_analysis(
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resolved_job: ResolvedExternalWaveformJob,
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*,
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job: FlAnalysisJob,
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snapshot: FlAnalysisTowerSnapshot,
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execution_options: dict[str, Any],
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baseline_result: dict[str, Any],
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) -> ExternalTowerExecutionResult:
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context = _build_template_context(
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job=job,
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snapshot=snapshot,
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execution_options=execution_options,
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baseline_result=baseline_result,
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)
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rendered_text = render_atp_template(
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resolved_job.version.atp_text or "",
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context=context,
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parameter_bindings=resolved_job.parameter_bindings,
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)
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run_dir = _prepare_run_directory(job=job, snapshot=snapshot, resolved_job=resolved_job)
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input_path = run_dir / _safe_entry_filename(
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resolved_job.version.entry_file,
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model_code=resolved_job.model.code,
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version_no=resolved_job.version.version_no,
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)
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input_path.write_text(rendered_text, encoding="utf-8")
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command = _build_command(
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adapter=resolved_job.adapter,
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input_path=input_path,
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extra_args=resolved_job.extra_args,
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)
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env = os.environ.copy()
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env.update(resolved_job.environment)
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try:
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result = subprocess.run(
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command,
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cwd=str(run_dir),
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env=env,
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capture_output=True,
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text=True,
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encoding="utf-8",
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errors="replace",
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timeout=resolved_job.timeout_seconds,
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check=False,
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)
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except subprocess.TimeoutExpired as exc:
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raise RuntimeError(
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f"{snapshot.tower_no} 外部 ATP/Wine 执行超时（{resolved_job.timeout_seconds}s）"
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) from exc
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except OSError as exc:
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raise RuntimeError(f"{snapshot.tower_no} 外部 ATP/Wine 启动失败: {exc}") from exc
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stdout_text = _truncate_output(result.stdout)
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stderr_text = _truncate_output(result.stderr)
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if result.returncode != 0:
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raise RuntimeError(
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f"{snapshot.tower_no} 外部 ATP/Wine 执行失败，退出码 {result.returncode}"
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)
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parsed_payload = _read_external_result_payload(
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contract=resolved_job.contract,
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stdout_text=result.stdout,
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run_dir=run_dir,
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)
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merged_result = _merge_external_result(
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baseline_result=baseline_result,
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external_payload=parsed_payload,
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resolved_job=resolved_job,
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engine_command=" ".join(command),
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working_dir=str(run_dir),
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)
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return ExternalTowerExecutionResult(
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result_json=merged_result,
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engine_command=" ".join(command),
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working_dir=str(run_dir),
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stdout_text=stdout_text,
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stderr_text=stderr_text,
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)
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def _build_template_context(
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*,
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job: FlAnalysisJob,
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snapshot: FlAnalysisTowerSnapshot,
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execution_options: dict[str, Any],
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baseline_result: dict[str, Any],
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) -> dict[str, Any]:
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return {
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"job": {
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"id": job.id,
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"job_name": job.job_name,
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"job_type": job.job_type,
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"external_adapter": job.external_adapter,
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},
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"snapshot": {
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"id": snapshot.id,
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"seq_no": snapshot.seq_no,
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"tower_no": snapshot.tower_no,
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"tower_model": snapshot.tower_model,
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"tower_type": snapshot.tower_type,
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"longitude": snapshot.longitude,
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"latitude": snapshot.latitude,
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"altitude_m": snapshot.altitude_m,
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"terrain": snapshot.terrain,
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},
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"base_tower": snapshot.base_tower_json or {},
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"profile": snapshot.profile_json or {},
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"execution_options": execution_options,
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"workflow": baseline_result.get("workflow") or {},
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"baseline_result": baseline_result,
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}
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def _prepare_run_directory(
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*,
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job: FlAnalysisJob,
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snapshot: FlAnalysisTowerSnapshot,
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resolved_job: ResolvedExternalWaveformJob,
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) -> Path:
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base_dir = _resolve_engine_workdir() / "fl-analysis" / job.id / snapshot.id
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base_dir.mkdir(parents=True, exist_ok=True)
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return base_dir
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def _build_command(*, adapter: str, input_path: Path, extra_args: list[str]) -> list[str]:
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if adapter == "wine":
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wine_binary, engine_path, error = _resolve_wine_engine_executable()
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if error or not wine_binary or not engine_path:
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raise RuntimeError(error or "Wine ATP engine unavailable")
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return [wine_binary, engine_path, str(input_path), *extra_args]
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engine_path, error = _resolve_native_engine_executable()
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if error or not engine_path:
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raise RuntimeError(error or "Native ATP engine unavailable")
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return [engine_path, str(input_path), *extra_args]
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def _render_placeholder(
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expression: str,
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*,
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context: dict[str, Any],
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parameter_bindings: dict[str, Any],
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) -> str:
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if expression in parameter_bindings:
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return _render_bound_placeholder(parameter_bindings[expression], context=context, name=expression)
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path, spec, width, default, required = _parse_inline_expression(expression)
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value = _read_path(context, path)
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return _stringify_value(
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value,
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format_spec=spec,
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width=width,
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default=default,
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required=required,
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name=expression,
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)
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def _render_bound_placeholder(binding: Any, *, context: dict[str, Any], name: str) -> str:
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if isinstance(binding, str):
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path, spec, width, default, required = _parse_inline_expression(binding)
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value = _read_path(context, path)
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return _stringify_value(
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value,
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format_spec=spec,
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width=width,
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default=default,
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required=required,
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name=name,
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)
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mapping = _read_object(binding)
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path = str(mapping.get("path") or mapping.get("source") or "").strip()
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if not path:
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raise RuntimeError(f"ATP 模板绑定缺少 path/source: {name}")
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value = _read_path(context, path)
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return _stringify_value(
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value,
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format_spec=str(mapping.get("format") or "").strip() or None,
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width=_coerce_positive_int(mapping.get("width")),
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default=mapping.get("default"),
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required=bool(mapping.get("required", "default" not in mapping)),
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name=name,
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)
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def _parse_inline_expression(expression: str) -> tuple[str, str | None, int | None, Any, bool]:
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parts = [part.strip() for part in expression.split("|")]
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path = parts[0]
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spec = parts[1] if len(parts) > 1 and parts[1] else None
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width = _coerce_positive_int(parts[2]) if len(parts) > 2 and parts[2] else None
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if len(parts) > 3:
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return path, spec, width, parts[3], False
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return path, spec, width, None, True
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def _stringify_value(
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value: Any,
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*,
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format_spec: str | None,
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width: int | None,
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default: Any,
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required: bool,
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name: str,
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) -> str:
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if value is None:
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if required:
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raise RuntimeError(f"ATP 模板占位符缺少取值: {name}")
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text = "" if default is None else str(default)
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return text.rjust(width) if width else text
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text: str
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if format_spec:
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text = _format_value(value, format_spec)
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elif isinstance(value, bool):
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text = "1" if value else "0"
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else:
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text = str(value)
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return text.rjust(width) if width else text
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def _format_value(value: Any, format_spec: str) -> str:
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numeric_value = float(value)
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normalized_spec = format_spec.strip()
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if normalized_spec.startswith("F"):
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precision = abs(int(normalized_spec[1:] or "0"))
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text = f"{numeric_value:.{precision}f}"
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if precision > 0:
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text = text.rstrip("0").rstrip(".")
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elif "." not in text:
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text = f"{text}."
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return text
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if normalized_spec.startswith("E"):
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precision = abs(int(normalized_spec[1:] or "0"))
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return f"{numeric_value:.{precision}E}"
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return format(value, normalized_spec)
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def _read_external_result_payload(
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*,
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contract: dict[str, Any],
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stdout_text: str,
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run_dir: Path,
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) -> dict[str, Any]:
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result_file = str(contract.get("result_file") or "").strip()
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source_text: str
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if result_file:
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result_path = (run_dir / result_file).resolve(strict=False)
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if not result_path.is_relative_to(run_dir.resolve(strict=False)):
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raise RuntimeError(f"外部结果文件越界: {result_file}")
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if not result_path.exists():
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raise RuntimeError(f"外部 ATP/Wine 未生成结果文件: {result_file}")
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source_text = result_path.read_text(encoding="utf-8", errors="replace")
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else:
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source_text = stdout_text
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payload = _parse_external_payload(source_text, contract)
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pointer = str(contract.get("result_json_pointer") or "").strip()
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if pointer:
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pointed = _read_path({"payload": payload}, f"payload.{pointer}")
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if not isinstance(pointed, dict):
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raise RuntimeError(f"外部结果指针无效: {pointer}")
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payload = pointed
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if not isinstance(payload, dict):
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raise RuntimeError("外部 ATP/Wine 结果不是 JSON 对象")
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return _normalize_external_result_payload(payload, _read_object(contract.get("result_key_map")))
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def _parse_external_payload(source_text: str, contract: dict[str, Any]) -> dict[str, Any]:
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labels = [str(item).strip() for item in list(contract.get("result_labels") or []) if str(item).strip()]
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if labels:
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values = [item.strip() for item in re.split(r"[|\r\n]+", source_text) if item.strip()]
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return {
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label: _coerce_scalar(values[index]) if index < len(values) else None
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for index, label in enumerate(labels)
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}
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result_format = str(contract.get("result_format") or "").strip().lower()
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if result_format in {"key_value", "kv", "text"}:
|
||||
return _parse_key_value_text(source_text)
|
||||
|
||||
markers = contract.get("stdout_json_markers")
|
||||
if isinstance(markers, list) and len(markers) == 2:
|
||||
candidate = _extract_marked_json(source_text, str(markers[0]), str(markers[1]))
|
||||
if candidate is not None:
|
||||
return json.loads(candidate)
|
||||
|
||||
candidate = source_text.strip()
|
||||
if candidate.startswith("{") and candidate.endswith("}"):
|
||||
return json.loads(candidate)
|
||||
|
||||
marked_json = _extract_marked_json(source_text, *DEFAULT_JSON_MARKERS)
|
||||
if marked_json is not None:
|
||||
return json.loads(marked_json)
|
||||
|
||||
raise RuntimeError("外部 ATP/Wine 结果无法解析为 JSON")
|
||||
|
||||
|
||||
def _parse_key_value_text(source_text: str) -> dict[str, Any]:
|
||||
result: dict[str, Any] = {}
|
||||
for line in source_text.splitlines():
|
||||
text = line.strip()
|
||||
if not text:
|
||||
continue
|
||||
if "=" in text:
|
||||
key, value = text.split("=", 1)
|
||||
elif ":" in text:
|
||||
key, value = text.split(":", 1)
|
||||
else:
|
||||
continue
|
||||
result[key.strip()] = _coerce_scalar(value.strip())
|
||||
return result
|
||||
|
||||
|
||||
def _extract_marked_json(source_text: str, start_marker: str, end_marker: str) -> str | None:
|
||||
start_index = source_text.find(start_marker)
|
||||
if start_index < 0:
|
||||
return None
|
||||
start_index += len(start_marker)
|
||||
end_index = source_text.find(end_marker, start_index)
|
||||
if end_index < 0:
|
||||
return None
|
||||
return source_text[start_index:end_index].strip()
|
||||
|
||||
|
||||
def _normalize_external_result_payload(
|
||||
payload: dict[str, Any],
|
||||
result_key_map: dict[str, Any],
|
||||
) -> dict[str, Any]:
|
||||
normalized: dict[str, Any] = {}
|
||||
for raw_key, raw_value in payload.items():
|
||||
key = str(result_key_map.get(raw_key) or raw_key).strip()
|
||||
key = LEGACY_RESULT_KEY_MAP.get(key, key)
|
||||
value = raw_value
|
||||
if key in NUMERIC_RESULT_KEYS:
|
||||
value = _coerce_scalar(raw_value)
|
||||
normalized[key] = value
|
||||
|
||||
risk_level = normalized.get("risk_level")
|
||||
if isinstance(risk_level, (int, float)) and "risk_grade" not in normalized:
|
||||
normalized["risk_grade"] = int(risk_level)
|
||||
normalized["risk_level"] = _risk_level_from_grade(int(risk_level))
|
||||
if "risk_level" not in normalized and "risk_grade" in normalized:
|
||||
grade = _coerce_positive_int(normalized.get("risk_grade")) or 1
|
||||
normalized["risk_grade"] = grade
|
||||
normalized["risk_level"] = _risk_level_from_grade(grade)
|
||||
return normalized
|
||||
|
||||
|
||||
def _merge_external_result(
|
||||
*,
|
||||
baseline_result: dict[str, Any],
|
||||
external_payload: dict[str, Any],
|
||||
resolved_job: ResolvedExternalWaveformJob,
|
||||
engine_command: str,
|
||||
working_dir: str,
|
||||
) -> dict[str, Any]:
|
||||
merged = dict(baseline_result)
|
||||
workflow = {
|
||||
**_read_object(baseline_result.get("workflow")),
|
||||
**_read_object(external_payload.get("workflow")),
|
||||
}
|
||||
if workflow:
|
||||
merged["workflow"] = workflow
|
||||
for key, value in external_payload.items():
|
||||
if key == "workflow" and isinstance(value, dict):
|
||||
continue
|
||||
merged[key] = value
|
||||
|
||||
if merged.get("selected_case") is None and baseline_result.get("selected_case") is not None:
|
||||
merged["selected_case"] = baseline_result.get("selected_case")
|
||||
if merged.get("summary_text") is None and baseline_result.get("summary_text") is not None:
|
||||
merged["summary_text"] = baseline_result.get("summary_text")
|
||||
if merged.get("cause_analysis") is None and baseline_result.get("cause_analysis") is not None:
|
||||
merged["cause_analysis"] = baseline_result.get("cause_analysis")
|
||||
if merged.get("mitigation_recommendation") is None and baseline_result.get("mitigation_recommendation") is not None:
|
||||
merged["mitigation_recommendation"] = baseline_result.get("mitigation_recommendation")
|
||||
|
||||
external_execution = {
|
||||
"adapter_status": "executed",
|
||||
"adapter": resolved_job.adapter,
|
||||
"model_id": resolved_job.model.id,
|
||||
"model_code": resolved_job.model.code,
|
||||
"model_name": resolved_job.model.name,
|
||||
"version_id": resolved_job.version.id,
|
||||
"version_no": resolved_job.version.version_no,
|
||||
"engine_command": engine_command,
|
||||
"working_dir": working_dir,
|
||||
"executed_at": utcnow().isoformat(),
|
||||
}
|
||||
merged["external_execution"] = external_execution
|
||||
merged["external_result_json"] = external_payload
|
||||
return merged
|
||||
|
||||
|
||||
def _read_path(context: dict[str, Any], path: str) -> Any:
|
||||
current: Any = context
|
||||
for segment in [item for item in path.split(".") if item]:
|
||||
if isinstance(current, dict):
|
||||
current = current.get(segment)
|
||||
continue
|
||||
if isinstance(current, list) and segment.isdigit():
|
||||
index = int(segment)
|
||||
if 0 <= index < len(current):
|
||||
current = current[index]
|
||||
continue
|
||||
return None
|
||||
return current
|
||||
|
||||
|
||||
def _read_object(value: Any) -> dict[str, Any]:
|
||||
if isinstance(value, dict):
|
||||
return {str(key): item for key, item in value.items()}
|
||||
return {}
|
||||
|
||||
|
||||
def _coerce_positive_int(value: Any) -> int | None:
|
||||
try:
|
||||
parsed = int(value)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
return parsed if parsed > 0 else None
|
||||
|
||||
|
||||
def _coerce_scalar(value: Any) -> Any:
|
||||
if isinstance(value, (int, float, bool)) or value is None:
|
||||
return value
|
||||
|
||||
text = str(value).strip()
|
||||
if not text:
|
||||
return text
|
||||
lowered = text.lower()
|
||||
if lowered in {"true", "false"}:
|
||||
return lowered == "true"
|
||||
try:
|
||||
if any(char in text for char in {".", "e", "E"}):
|
||||
return float(text)
|
||||
return int(text)
|
||||
except ValueError:
|
||||
return text
|
||||
|
||||
|
||||
def _risk_level_from_grade(grade: int) -> str:
|
||||
if grade >= 3:
|
||||
return "high"
|
||||
if grade == 2:
|
||||
return "medium"
|
||||
return "low"
|
||||
@@ -27,6 +27,8 @@ from ..schemas.fl_analysis import (
|
||||
FlAnalysisTowerResultListResponse,
|
||||
FlAnalysisTowerResultSummary,
|
||||
)
|
||||
from .atp_model_service import _truncate_output
|
||||
from .fl_analysis_external import execute_external_waveform_tower_analysis, resolve_external_waveform_job
|
||||
from .fl_analysis_report import build_report_document, build_report_summary_payload
|
||||
from .fl_analysis_rules import (
|
||||
grade_mitigation_snapshot_payload,
|
||||
@@ -180,6 +182,21 @@ def create_job(
|
||||
)
|
||||
or 0
|
||||
)
|
||||
if payload.job_type in {"normal", "tongtiao"}:
|
||||
if payload.external_adapter in {"atp", "wine"}:
|
||||
try:
|
||||
resolve_external_waveform_job(
|
||||
db,
|
||||
external_adapter=payload.external_adapter,
|
||||
adapter_config_json=payload.adapter_config_json or {},
|
||||
)
|
||||
except RuntimeError as exc:
|
||||
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(exc)) from exc
|
||||
elif payload.external_adapter != "placeholder":
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_400_BAD_REQUEST,
|
||||
detail="普通计算和同跳计算仅支持 placeholder/atp/wine 适配器",
|
||||
)
|
||||
if total_tower_count <= 0:
|
||||
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="当前线路没有可分析的杆塔数据")
|
||||
|
||||
@@ -362,6 +379,20 @@ def execute_job(job_id: str) -> None:
|
||||
result_count = 0
|
||||
summary = _new_result_summary()
|
||||
tower_map = {tower.id: tower for tower in towers}
|
||||
external_job = None
|
||||
stdout_chunks: list[str] = []
|
||||
stderr_chunks: list[str] = []
|
||||
if job.job_type in {"normal", "tongtiao"} and job.external_adapter in {"atp", "wine"}:
|
||||
external_job = resolve_external_waveform_job(
|
||||
db,
|
||||
external_adapter=job.external_adapter,
|
||||
adapter_config_json=job.adapter_config_json or {},
|
||||
)
|
||||
summary["external_model_id"] = external_job.model.id
|
||||
summary["external_model_code"] = external_job.model.code
|
||||
summary["external_model_name"] = external_job.model.name
|
||||
summary["external_version_id"] = external_job.version.id
|
||||
summary["external_version_no"] = external_job.version.version_no
|
||||
for snapshot in snapshots:
|
||||
payload = {
|
||||
"base_tower_json": snapshot.base_tower_json or {},
|
||||
@@ -376,9 +407,43 @@ def execute_job(job_id: str) -> None:
|
||||
non_construction=bool(execution_options.get("non_construction")),
|
||||
)
|
||||
elif job.job_type == "normal":
|
||||
graded = grade_normal_snapshot_payload(payload, execution_options=execution_options)
|
||||
baseline_result = grade_normal_snapshot_payload(payload, execution_options=execution_options)
|
||||
if external_job is not None:
|
||||
execution = execute_external_waveform_tower_analysis(
|
||||
external_job,
|
||||
job=job,
|
||||
snapshot=snapshot,
|
||||
execution_options=execution_options,
|
||||
baseline_result=baseline_result,
|
||||
)
|
||||
graded = execution.result_json
|
||||
run.engine_command = run.engine_command or execution.engine_command
|
||||
run.working_dir = run.working_dir or execution.working_dir
|
||||
if execution.stdout_text:
|
||||
stdout_chunks.append(f"[{snapshot.tower_no}] {execution.stdout_text}")
|
||||
if execution.stderr_text:
|
||||
stderr_chunks.append(f"[{snapshot.tower_no}] {execution.stderr_text}")
|
||||
else:
|
||||
graded = baseline_result
|
||||
elif job.job_type == "tongtiao":
|
||||
graded = grade_tongtiao_snapshot_payload(payload, execution_options=execution_options)
|
||||
baseline_result = grade_tongtiao_snapshot_payload(payload, execution_options=execution_options)
|
||||
if external_job is not None:
|
||||
execution = execute_external_waveform_tower_analysis(
|
||||
external_job,
|
||||
job=job,
|
||||
snapshot=snapshot,
|
||||
execution_options=execution_options,
|
||||
baseline_result=baseline_result,
|
||||
)
|
||||
graded = execution.result_json
|
||||
run.engine_command = run.engine_command or execution.engine_command
|
||||
run.working_dir = run.working_dir or execution.working_dir
|
||||
if execution.stdout_text:
|
||||
stdout_chunks.append(f"[{snapshot.tower_no}] {execution.stdout_text}")
|
||||
if execution.stderr_text:
|
||||
stderr_chunks.append(f"[{snapshot.tower_no}] {execution.stderr_text}")
|
||||
else:
|
||||
graded = baseline_result
|
||||
else:
|
||||
graded = grade_snapshot_payload(payload)
|
||||
db.add(
|
||||
@@ -415,6 +480,12 @@ def execute_job(job_id: str) -> None:
|
||||
summary["non_construction"] = bool(execution_options.get("non_construction"))
|
||||
elif job.job_type in {"normal", "tongtiao"}:
|
||||
summary["workflow"] = _workflow_summary_from_execution_options(execution_options)
|
||||
if external_job is not None:
|
||||
summary["external_engine_adapter"] = job.external_adapter
|
||||
if stdout_chunks:
|
||||
run.stdout_text = _truncate_output("\n\n".join(stdout_chunks))
|
||||
if stderr_chunks:
|
||||
run.stderr_text = _truncate_output("\n\n".join(stderr_chunks))
|
||||
db.commit()
|
||||
|
||||
_finish_rule_based_run(
|
||||
@@ -423,6 +494,7 @@ def execute_job(job_id: str) -> None:
|
||||
run_id=run.id,
|
||||
started_perf=started_perf,
|
||||
summary=summary,
|
||||
adapter_status="executed" if external_job is not None else "computed",
|
||||
)
|
||||
|
||||
except Exception as exc:
|
||||
@@ -448,6 +520,7 @@ def _finish_rule_based_run(
|
||||
run_id: str,
|
||||
started_perf: float,
|
||||
summary: dict[str, Any],
|
||||
adapter_status: str = "computed",
|
||||
) -> None:
|
||||
job = get_job_by_id(db, job_id)
|
||||
run = db.execute(select(FlAnalysisRun).where(FlAnalysisRun.id == run_id)).scalar_one_or_none()
|
||||
@@ -467,7 +540,7 @@ def _finish_rule_based_run(
|
||||
job.error_message = None
|
||||
job.result_summary_json = {
|
||||
**summary,
|
||||
"adapter_status": "computed",
|
||||
"adapter_status": adapter_status,
|
||||
"external_adapter": job.external_adapter,
|
||||
}
|
||||
job.finished_at = now
|
||||
@@ -1236,6 +1309,14 @@ def _as_int(value: Any) -> int | None:
|
||||
return None
|
||||
|
||||
|
||||
def _as_float(value: Any) -> float | None:
|
||||
try:
|
||||
parsed = float(value)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
return parsed
|
||||
|
||||
|
||||
def _placeholder_message_for_adapter(adapter: str) -> str:
|
||||
if adapter == "wine":
|
||||
return "Wine 外部程序适配器已预留，真实执行链路尚未接入"
|
||||
|
||||
@@ -0,0 +1,203 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from types import SimpleNamespace
|
||||
|
||||
from sqlalchemy import create_engine, select
|
||||
from sqlalchemy.orm import Session, sessionmaker
|
||||
|
||||
from app.core.database import Base
|
||||
from app.models.atp_model import AtpModel, AtpModelVersion, AtpSimulationRun
|
||||
from app.models.fl_analysis import FlAnalysisJob, FlAnalysisRun, FlAnalysisTowerResult, FlAnalysisTowerSnapshot
|
||||
from app.models.line import Line
|
||||
from app.models.line_tower import LineTower
|
||||
from app.models.tower_profile import TowerProfile
|
||||
from app.schemas.fl_analysis import FlAnalysisJobCreateRequest
|
||||
from app.services import fl_analysis_external, fl_analysis_service
|
||||
|
||||
|
||||
def _build_sessionmaker():
|
||||
engine = create_engine("sqlite+pysqlite:///:memory:")
|
||||
Base.metadata.create_all(
|
||||
bind=engine,
|
||||
tables=[
|
||||
Line.__table__,
|
||||
LineTower.__table__,
|
||||
TowerProfile.__table__,
|
||||
FlAnalysisJob.__table__,
|
||||
FlAnalysisRun.__table__,
|
||||
FlAnalysisTowerSnapshot.__table__,
|
||||
FlAnalysisTowerResult.__table__,
|
||||
AtpModel.__table__,
|
||||
AtpModelVersion.__table__,
|
||||
AtpSimulationRun.__table__,
|
||||
],
|
||||
)
|
||||
return sessionmaker(bind=engine, autocommit=False, autoflush=False, expire_on_commit=False)
|
||||
|
||||
|
||||
def test_render_atp_template_supports_binding_formats_and_defaults() -> None:
|
||||
rendered = fl_analysis_external.render_atp_template(
|
||||
"R={{GROUND_RES}}\nHEAD={{profile.current_head_time_us|F1|6|2.6}}\nNAME={{snapshot.tower_no}}",
|
||||
context={
|
||||
"snapshot": {"tower_no": "N-01"},
|
||||
"base_tower": {"ground_resistance_ohm": 12.34},
|
||||
"profile": {},
|
||||
},
|
||||
parameter_bindings={
|
||||
"GROUND_RES": {
|
||||
"path": "base_tower.ground_resistance_ohm",
|
||||
"format": "F1",
|
||||
"width": 6,
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
assert "R= 12.3" in rendered
|
||||
assert "HEAD= 2.6" in rendered
|
||||
assert "NAME=N-01" in rendered
|
||||
|
||||
|
||||
def test_execute_job_runs_external_adapter_and_backfills_results(monkeypatch, tmp_path) -> None:
|
||||
testing_session = _build_sessionmaker()
|
||||
session: Session = testing_session()
|
||||
try:
|
||||
monkeypatch.setattr(fl_analysis_service, "SessionLocal", testing_session)
|
||||
monkeypatch.setattr(fl_analysis_service, "_publish_change", lambda *args, **kwargs: None)
|
||||
monkeypatch.setattr(fl_analysis_external, "_resolve_engine_workdir", lambda: tmp_path)
|
||||
monkeypatch.setattr(fl_analysis_external, "_resolve_native_engine_executable", lambda: ("/bin/sh", None))
|
||||
|
||||
line = Line(code="L-001", name="示例线路", voltage_kv=220, lightning_param_json={})
|
||||
session.add(line)
|
||||
session.flush()
|
||||
|
||||
tower = LineTower(
|
||||
line_id=line.id,
|
||||
seq_no=1,
|
||||
tower_no="N1",
|
||||
tower_model="220-TEST-ZX",
|
||||
tower_type="直线",
|
||||
altitude_m=1680.0,
|
||||
ground_resistance_ohm=12.0,
|
||||
lightning_density=3.2,
|
||||
span_large_m=260.0,
|
||||
slope_1=3.0,
|
||||
slope_2=1.5,
|
||||
circuit_geometry_json={
|
||||
"I": {
|
||||
"phase_spacing_m": {"upper": 9.0, "middle": 4.5, "lower": 8.5},
|
||||
"phase_height_m": {"upper": 29.0, "middle": 31.0, "lower": 25.0},
|
||||
},
|
||||
"lightning_wire": {
|
||||
"left_mid_distance_m": 9.0,
|
||||
"right_mid_distance_m": 9.0,
|
||||
"height_m": 41.0,
|
||||
},
|
||||
"insulator_length_mm": 4200.0,
|
||||
},
|
||||
lightning_result_json={},
|
||||
)
|
||||
session.add(tower)
|
||||
session.flush()
|
||||
|
||||
session.add(
|
||||
TowerProfile(
|
||||
tower_id=tower.id,
|
||||
structure_kind="直线",
|
||||
arrester_a="是",
|
||||
arrester_b="否",
|
||||
arrester_c="是",
|
||||
shield_wire_height_m=41.0,
|
||||
insulator_length_m=4200.0,
|
||||
current_type="Heidler",
|
||||
current_head_time_us=2.6,
|
||||
current_tail_time_us=50.0,
|
||||
)
|
||||
)
|
||||
|
||||
model = AtpModel(code="fl-normal-model", name="普通计算ATP模型", source_type="atp", status="enabled")
|
||||
session.add(model)
|
||||
session.flush()
|
||||
|
||||
session.add(
|
||||
AtpModelVersion(
|
||||
model_id=model.id,
|
||||
version_no=1,
|
||||
status="released",
|
||||
entry_file="runner.sh",
|
||||
artifact_manifest_json={
|
||||
"fl_analysis": {
|
||||
"result_file": "result.json",
|
||||
"parameter_bindings": {
|
||||
"GROUND_RES": {
|
||||
"path": "base_tower.ground_resistance_ohm",
|
||||
"format": "F1",
|
||||
}
|
||||
},
|
||||
}
|
||||
},
|
||||
atp_text="""#!/bin/sh
|
||||
cat > result.json <<'JSON'
|
||||
{"counterstrike_withstand_ka": {{GROUND_RES}}, "risk_grade": 3, "score": 91, "summary_text": "ATP执行完成"}
|
||||
JSON
|
||||
""",
|
||||
content_hash="normal-v1",
|
||||
)
|
||||
)
|
||||
session.commit()
|
||||
|
||||
created = fl_analysis_service.create_job(
|
||||
session,
|
||||
FlAnalysisJobCreateRequest(
|
||||
line_id=line.id,
|
||||
job_name="普通计算-ATP",
|
||||
job_type="normal",
|
||||
external_adapter="atp",
|
||||
adapter_config_json={"model_id": model.id},
|
||||
execution_options_json={
|
||||
"current_waveform": "double_slope",
|
||||
"flashover_method": "intersection",
|
||||
"altitude_correction": "formula1",
|
||||
"induced_voltage_formula": "formula2",
|
||||
"head_time_min_us": 2.4,
|
||||
"head_time_max_us": 2.6,
|
||||
"head_time_step_us": 0.2,
|
||||
"tail_time_min_us": 45.0,
|
||||
"tail_time_max_us": 50.0,
|
||||
"tail_time_step_us": 5.0,
|
||||
},
|
||||
),
|
||||
actor=SimpleNamespace(id="tester"),
|
||||
)
|
||||
session.close()
|
||||
|
||||
fl_analysis_service.execute_job(created.job.id)
|
||||
|
||||
verify_session: Session = testing_session()
|
||||
try:
|
||||
saved_job = fl_analysis_service.get_job_by_id(verify_session, created.job.id)
|
||||
assert saved_job is not None
|
||||
assert saved_job.status == "success"
|
||||
assert saved_job.result_summary_json["adapter_status"] == "executed"
|
||||
assert saved_job.result_summary_json["external_model_code"] == "fl-normal-model"
|
||||
assert saved_job.result_summary_json["external_version_no"] == 1
|
||||
|
||||
result_row = verify_session.execute(
|
||||
select(FlAnalysisTowerResult).where(FlAnalysisTowerResult.job_id == created.job.id)
|
||||
).scalar_one()
|
||||
assert result_row.risk_level == "high"
|
||||
assert result_row.summary_text == "ATP执行完成"
|
||||
assert result_row.result_json["counterstrike_withstand_ka"] == 12.0
|
||||
assert result_row.result_json["external_execution"]["adapter"] == "atp"
|
||||
assert result_row.result_json["external_execution"]["model_code"] == "fl-normal-model"
|
||||
|
||||
saved_run = verify_session.execute(
|
||||
select(FlAnalysisRun).where(FlAnalysisRun.job_id == created.job.id)
|
||||
).scalar_one()
|
||||
assert saved_run.status == "success"
|
||||
assert saved_run.runner_kind == "atp"
|
||||
assert saved_run.engine_command is not None
|
||||
assert saved_run.working_dir is not None
|
||||
finally:
|
||||
verify_session.close()
|
||||
finally:
|
||||
session.close()
|
||||
@@ -26,6 +26,11 @@ import { useAuth } from "@/components/auth-provider";
|
||||
import { Card } from "@/components/ui-antd";
|
||||
import { readApiError } from "@/lib/api";
|
||||
import type {
|
||||
AtpEngineStatusResponse,
|
||||
AtpModelListResponse,
|
||||
AtpModelSummary,
|
||||
AtpModelVersionListResponse,
|
||||
AtpModelVersionSummary,
|
||||
FlAnalysisJobDetail,
|
||||
FlAnalysisJobListResponse,
|
||||
FlAnalysisJobSummary,
|
||||
@@ -39,6 +44,9 @@ type CreateJobFormValues = {
|
||||
job_name: string;
|
||||
line_id: string;
|
||||
job_type: "normal" | "tongtiao" | "risk";
|
||||
external_adapter: "placeholder" | "wine" | "atp";
|
||||
atp_model_id: string;
|
||||
atp_version_id: string;
|
||||
current_waveform: "heidler" | "double_slope" | "double_exponential";
|
||||
flashover_method: "guideline" | "intersection" | "leader_development";
|
||||
altitude_correction: "none" | "formula1" | "formula2";
|
||||
@@ -138,6 +146,9 @@ const CREATE_JOB_DEFAULTS: CreateJobFormValues = {
|
||||
job_name: "",
|
||||
line_id: "",
|
||||
job_type: "normal",
|
||||
external_adapter: "placeholder",
|
||||
atp_model_id: "",
|
||||
atp_version_id: "",
|
||||
current_waveform: "heidler",
|
||||
flashover_method: "intersection",
|
||||
altitude_correction: "none",
|
||||
@@ -194,6 +205,14 @@ function formatInducedVoltageFormula(value: string | null | undefined): string {
|
||||
return value || "-";
|
||||
}
|
||||
|
||||
function formatExternalAdapter(value: string | null | undefined): string {
|
||||
if (value === "wine") return "Wine / ATP";
|
||||
if (value === "atp") return "原生 ATP";
|
||||
if (value === "placeholder") return "规则近似";
|
||||
if (value === "custom") return "自定义";
|
||||
return value || "-";
|
||||
}
|
||||
|
||||
function riskColor(value: string | null | undefined): string {
|
||||
if (value === "high") return "red";
|
||||
if (value === "medium") return "orange";
|
||||
@@ -367,9 +386,12 @@ export default function AdminFlAnalysisPage() {
|
||||
const [messageApi, contextHolder] = message.useMessage();
|
||||
const selectedLineId = Form.useWatch("line_id", createJobForm);
|
||||
const selectedCreateJobType = Form.useWatch("job_type", createJobForm) ?? CREATE_JOB_DEFAULTS.job_type;
|
||||
const selectedExternalAdapter = Form.useWatch("external_adapter", createJobForm) ?? CREATE_JOB_DEFAULTS.external_adapter;
|
||||
const selectedAtpModelId = Form.useWatch("atp_model_id", createJobForm) ?? "";
|
||||
|
||||
const canRead = hasPermission("line.read") || hasPermission("line.manage");
|
||||
const canManage = hasPermission("line.manage") || hasPermission("tower.manage");
|
||||
const canReadAtp = hasPermission("atp.read") || hasPermission("atp.run") || hasPermission("atp.manage");
|
||||
|
||||
const linesQuery = useQuery({
|
||||
queryKey: ["/api/v1/lines"],
|
||||
@@ -395,6 +417,43 @@ export default function AdminFlAnalysisPage() {
|
||||
},
|
||||
});
|
||||
|
||||
const engineQuery = useQuery({
|
||||
queryKey: ["/api/v1/atp/models/engine/status"],
|
||||
enabled: !!user && canReadAtp,
|
||||
queryFn: async () => {
|
||||
const response = await fetchWithAuth("/api/v1/atp/models/engine/status");
|
||||
if (!response.ok) {
|
||||
throw new Error(await readApiError(response));
|
||||
}
|
||||
return (await response.json()) as AtpEngineStatusResponse;
|
||||
},
|
||||
staleTime: 30_000,
|
||||
});
|
||||
|
||||
const atpModelsQuery = useQuery({
|
||||
queryKey: ["/api/v1/atp/models", "enabled"],
|
||||
enabled: !!user && canReadAtp,
|
||||
queryFn: async () => {
|
||||
const response = await fetchWithAuth("/api/v1/atp/models?status=enabled");
|
||||
if (!response.ok) {
|
||||
throw new Error(await readApiError(response));
|
||||
}
|
||||
return (await response.json()) as AtpModelListResponse;
|
||||
},
|
||||
});
|
||||
|
||||
const atpVersionsQuery = useQuery({
|
||||
queryKey: ["/api/v1/atp/models/versions", selectedAtpModelId],
|
||||
enabled: !!user && canReadAtp && !!selectedAtpModelId,
|
||||
queryFn: async () => {
|
||||
const response = await fetchWithAuth(`/api/v1/atp/models/${selectedAtpModelId}/versions?limit=200&offset=0`);
|
||||
if (!response.ok) {
|
||||
throw new Error(await readApiError(response));
|
||||
}
|
||||
return (await response.json()) as AtpModelVersionListResponse;
|
||||
},
|
||||
});
|
||||
|
||||
const selectedJob = useMemo(() => {
|
||||
if (!selectedJobId) {
|
||||
return jobsQuery.data?.items[0] ?? null;
|
||||
@@ -439,6 +498,12 @@ export default function AdminFlAnalysisPage() {
|
||||
return rows.filter((item) => item.risk_level !== "low");
|
||||
}, [selectedJob?.job_type, towerResultsQuery.data?.items]);
|
||||
|
||||
const atpModels = useMemo(() => atpModelsQuery.data?.items ?? [], [atpModelsQuery.data]);
|
||||
const selectedAtpModel = useMemo(
|
||||
() => atpModels.find((item) => item.id === selectedAtpModelId) ?? null,
|
||||
[atpModels, selectedAtpModelId],
|
||||
);
|
||||
|
||||
useEffect(() => {
|
||||
const firstLine = linesQuery.data?.items[0];
|
||||
if (firstLine && !createJobForm.getFieldValue("line_id")) {
|
||||
@@ -446,6 +511,37 @@ export default function AdminFlAnalysisPage() {
|
||||
}
|
||||
}, [createJobForm, linesQuery.data?.items]);
|
||||
|
||||
useEffect(() => {
|
||||
if (!["normal", "tongtiao"].includes(selectedCreateJobType)) {
|
||||
return;
|
||||
}
|
||||
if (!["atp", "wine"].includes(selectedExternalAdapter)) {
|
||||
return;
|
||||
}
|
||||
if (!atpModels.length || createJobForm.getFieldValue("atp_model_id")) {
|
||||
return;
|
||||
}
|
||||
createJobForm.setFieldValue("atp_model_id", atpModels[0].id);
|
||||
}, [atpModels, createJobForm, selectedCreateJobType, selectedExternalAdapter]);
|
||||
|
||||
useEffect(() => {
|
||||
if (!["atp", "wine"].includes(selectedExternalAdapter)) {
|
||||
return;
|
||||
}
|
||||
const versions = atpVersionsQuery.data?.items ?? [];
|
||||
if (!versions.length) {
|
||||
return;
|
||||
}
|
||||
const currentVersionId = createJobForm.getFieldValue("atp_version_id");
|
||||
if (currentVersionId && versions.some((item) => item.id === currentVersionId)) {
|
||||
return;
|
||||
}
|
||||
const preferredVersion =
|
||||
versions.find((item) => item.version_no === selectedAtpModel?.active_version_no)
|
||||
?? versions[0];
|
||||
createJobForm.setFieldValue("atp_version_id", preferredVersion.id);
|
||||
}, [atpVersionsQuery.data?.items, createJobForm, selectedAtpModel?.active_version_no, selectedExternalAdapter]);
|
||||
|
||||
async function invalidateFlAnalysisQueries(): Promise<void> {
|
||||
await queryClient.invalidateQueries({
|
||||
predicate: (query) =>
|
||||
@@ -506,7 +602,9 @@ export default function AdminFlAnalysisPage() {
|
||||
line_id: values.line_id,
|
||||
job_name: values.job_name.trim() || null,
|
||||
job_type: values.job_type,
|
||||
external_adapter: "placeholder",
|
||||
external_adapter: values.job_type === "normal" || values.job_type === "tongtiao"
|
||||
? values.external_adapter
|
||||
: "placeholder",
|
||||
};
|
||||
if (values.job_type === "normal" || values.job_type === "tongtiao") {
|
||||
payload.execution_options_json = {
|
||||
@@ -521,6 +619,12 @@ export default function AdminFlAnalysisPage() {
|
||||
tail_time_max_us: values.tail_time_max_us,
|
||||
tail_time_step_us: values.tail_time_step_us,
|
||||
};
|
||||
if (values.external_adapter !== "placeholder") {
|
||||
payload.adapter_config_json = {
|
||||
model_id: values.atp_model_id,
|
||||
version_id: values.atp_version_id || undefined,
|
||||
};
|
||||
}
|
||||
}
|
||||
return payload;
|
||||
}
|
||||
@@ -960,6 +1064,30 @@ export default function AdminFlAnalysisPage() {
|
||||
const selectedLine = useMemo(() => {
|
||||
return linesQuery.data?.items.find((item) => item.id === selectedLineId) ?? null;
|
||||
}, [linesQuery.data?.items, selectedLineId]);
|
||||
const externalAdapterActive = selectedExternalAdapter === "atp" || selectedExternalAdapter === "wine";
|
||||
const engineMode = engineQuery.data?.mode;
|
||||
const adapterOptions = [
|
||||
{
|
||||
value: "placeholder",
|
||||
label: "规则近似(占位)",
|
||||
disabled: false,
|
||||
},
|
||||
{
|
||||
value: "atp",
|
||||
label: "原生 ATP",
|
||||
disabled: !canReadAtp || engineMode === "wine" || engineQuery.data?.available === false,
|
||||
},
|
||||
{
|
||||
value: "wine",
|
||||
label: "Wine / ATP",
|
||||
disabled: !canReadAtp || engineMode === "native" || engineQuery.data?.available === false,
|
||||
},
|
||||
] as const;
|
||||
const workflowExecutionMessage = externalAdapterActive
|
||||
? engineQuery.data?.available
|
||||
? `当前将通过 ${formatExternalAdapter(selectedExternalAdapter)} 链路执行 ATP 模型，并把外部结果回填到任务明细。`
|
||||
: `当前已选择 ${formatExternalAdapter(selectedExternalAdapter)}，但 ATP 引擎不可用：${engineQuery.data?.error || "请先检查执行器配置" }`
|
||||
: `当前按 ${formatJobType(selectedCreateJobType)} 口径生成规则近似版结果；切换到 ATP/Wine 适配器后会走真实外部执行链路。`;
|
||||
|
||||
if (!initializing && !user) {
|
||||
return <Alert type="warning" showIcon message="请先登录后查看防雷分析结果。" />;
|
||||
@@ -981,6 +1109,10 @@ export default function AdminFlAnalysisPage() {
|
||||
const selectedJobExecutionOptions = readObject(selectedJobDetail?.execution_options_json);
|
||||
const selectedJobSummary = readObject(selectedJobDetail?.result_summary_json);
|
||||
const selectedJobWorkflow = readObject(selectedJobDetail?.result_summary_json).workflow as WorkflowSummary | undefined;
|
||||
const selectedJobExternalModelCode = readOptionalString(selectedJobSummary, "external_model_code");
|
||||
const selectedJobExternalModelName = readOptionalString(selectedJobSummary, "external_model_name");
|
||||
const selectedJobExternalVersionNo = readOptionalNumber(selectedJobSummary, "external_version_no");
|
||||
const detailExternalExecution = readObject(detailResultObject.external_execution);
|
||||
const sourceJobId = readOptionalString(selectedJobExecutionOptions, "source_job_id");
|
||||
const canCreateMitigation = selectedJob?.job_type === "risk";
|
||||
const canCreateReport = selectedJob?.job_type === "risk" || selectedJob?.job_type === "mitigation";
|
||||
@@ -1000,7 +1132,7 @@ export default function AdminFlAnalysisPage() {
|
||||
防雷分析与改造
|
||||
</Typography.Title>
|
||||
<Typography.Text type="secondary">
|
||||
支持源端“普通计算 / 同跳计算 / 风险评估 / 措施推荐 / 报告生成”工作流。普通计算和同跳计算当前为规则近似版，ATP/Wine 外部链路仍保留为后续接入点；报告任务可基于风险或措施结果直接导出 Word 兼容文档。
|
||||
支持源端“普通计算 / 同跳计算 / 风险评估 / 措施推荐 / 报告生成”工作流。普通计算和同跳计算可按 ATP/Wine 外部链路执行，也可退回规则近似版；报告任务可基于风险或措施结果直接导出 Word 兼容文档。
|
||||
</Typography.Text>
|
||||
</div>
|
||||
|
||||
@@ -1017,7 +1149,7 @@ export default function AdminFlAnalysisPage() {
|
||||
createJobMutation.mutate(values);
|
||||
}}
|
||||
>
|
||||
<div className="grid gap-3 md:grid-cols-4">
|
||||
<div className="grid gap-3 md:grid-cols-2 xl:grid-cols-5">
|
||||
<Form.Item
|
||||
name="line_id"
|
||||
label="线路"
|
||||
@@ -1043,6 +1175,15 @@ export default function AdminFlAnalysisPage() {
|
||||
]}
|
||||
/>
|
||||
</Form.Item>
|
||||
{selectedCreateJobType === "normal" || selectedCreateJobType === "tongtiao" ? (
|
||||
<Form.Item
|
||||
name="external_adapter"
|
||||
label="执行适配器"
|
||||
rules={[{ required: true, message: "请选择执行适配器" }]}
|
||||
>
|
||||
<Select options={adapterOptions.map((item) => ({ ...item }))} />
|
||||
</Form.Item>
|
||||
) : null}
|
||||
<Form.Item name="job_name" label="任务名">
|
||||
<Input
|
||||
placeholder={selectedLine
|
||||
@@ -1060,10 +1201,60 @@ export default function AdminFlAnalysisPage() {
|
||||
{selectedCreateJobType === "normal" || selectedCreateJobType === "tongtiao" ? (
|
||||
<>
|
||||
<Alert
|
||||
type="info"
|
||||
type={externalAdapterActive && engineQuery.data?.available === false ? "warning" : "info"}
|
||||
showIcon
|
||||
message={`当前按${formatJobType(selectedCreateJobType)}口径生成波头/波尾扫描结果，并在最不利点输出结果。`}
|
||||
message={workflowExecutionMessage}
|
||||
/>
|
||||
{atpModelsQuery.error && externalAdapterActive ? (
|
||||
<Alert
|
||||
type="error"
|
||||
showIcon
|
||||
message={atpModelsQuery.error instanceof Error ? atpModelsQuery.error.message : "ATP 模型列表加载失败"}
|
||||
/>
|
||||
) : null}
|
||||
{externalAdapterActive ? (
|
||||
<div className="grid gap-3 md:grid-cols-2 xl:grid-cols-4">
|
||||
<Form.Item
|
||||
name="atp_model_id"
|
||||
label="ATP模型"
|
||||
rules={[{ required: true, message: "请选择 ATP 模型" }]}
|
||||
>
|
||||
<Select
|
||||
showSearch
|
||||
optionFilterProp="label"
|
||||
loading={atpModelsQuery.isLoading}
|
||||
placeholder="选择 ATP 模型"
|
||||
options={atpModels.map((item: AtpModelSummary) => ({
|
||||
value: item.id,
|
||||
label: `${item.name} / ${item.code}`,
|
||||
}))}
|
||||
/>
|
||||
</Form.Item>
|
||||
<Form.Item
|
||||
name="atp_version_id"
|
||||
label="模型版本"
|
||||
rules={[{ required: true, message: "请选择模型版本" }]}
|
||||
>
|
||||
<Select
|
||||
showSearch
|
||||
optionFilterProp="label"
|
||||
loading={atpVersionsQuery.isLoading}
|
||||
placeholder="选择模型版本"
|
||||
options={(atpVersionsQuery.data?.items ?? []).map((item: AtpModelVersionSummary) => ({
|
||||
value: item.id,
|
||||
label: `v${item.version_no}${item.version_tag ? ` / ${item.version_tag}` : ""}`,
|
||||
}))}
|
||||
/>
|
||||
</Form.Item>
|
||||
<Alert
|
||||
type="info"
|
||||
showIcon
|
||||
message={`执行模式：${engineQuery.data ? formatExternalAdapter(engineQuery.data.mode === "wine" ? "wine" : "atp") : "-"}`}
|
||||
description={selectedAtpModel ? `当前模型：${selectedAtpModel.name} / ${selectedAtpModel.code}` : "从 ATP 模型管理中选择已发布模板版本。"}
|
||||
className="md:col-span-2"
|
||||
/>
|
||||
</div>
|
||||
) : null}
|
||||
<div className="grid gap-3 md:grid-cols-4">
|
||||
<Form.Item name="current_waveform" label="雷电流波形">
|
||||
<Select
|
||||
@@ -1196,6 +1387,14 @@ export default function AdminFlAnalysisPage() {
|
||||
</>
|
||||
) : selectedJobDetail.job_type === "normal" || selectedJobDetail.job_type === "tongtiao" ? (
|
||||
<>
|
||||
<Descriptions.Item label="适配器">{formatExternalAdapter(selectedJobDetail.external_adapter)}</Descriptions.Item>
|
||||
<Descriptions.Item label="ATP模型">
|
||||
{selectedJobExternalModelName || selectedJobExternalModelCode || "-"}
|
||||
{selectedJobExternalModelName && selectedJobExternalModelCode ? ` / ${selectedJobExternalModelCode}` : ""}
|
||||
</Descriptions.Item>
|
||||
<Descriptions.Item label="模型版本">
|
||||
{typeof selectedJobExternalVersionNo === "number" ? `v${selectedJobExternalVersionNo}` : "-"}
|
||||
</Descriptions.Item>
|
||||
<Descriptions.Item label="平均得分">{String(selectedJobDetail.result_summary_json?.score_average ?? "-")}</Descriptions.Item>
|
||||
<Descriptions.Item label="平均扫描点">{String(readObject(selectedJobDetail.result_summary_json).scan_point_average ?? "-")}</Descriptions.Item>
|
||||
<Descriptions.Item label="雷电流波形">{formatCurrentWaveform(selectedJobWorkflow?.current_waveform)}</Descriptions.Item>
|
||||
@@ -1330,6 +1529,17 @@ export default function AdminFlAnalysisPage() {
|
||||
<Descriptions.Item label="感应电压公式">{formatInducedVoltageFormula(detailWorkflow.induced_voltage_formula)}</Descriptions.Item>
|
||||
<Descriptions.Item label="波头范围">{formatRangeSummary(detailWorkflow.head_time_range_us)}</Descriptions.Item>
|
||||
<Descriptions.Item label="波尾范围">{formatRangeSummary(detailWorkflow.tail_time_range_us)}</Descriptions.Item>
|
||||
<Descriptions.Item label="执行适配器">
|
||||
{formatExternalAdapter(readOptionalString(detailExternalExecution, "adapter"))}
|
||||
</Descriptions.Item>
|
||||
<Descriptions.Item label="ATP模型">
|
||||
{readOptionalString(detailExternalExecution, "model_name") || readOptionalString(detailExternalExecution, "model_code") || "-"}
|
||||
</Descriptions.Item>
|
||||
<Descriptions.Item label="模型版本">
|
||||
{typeof readOptionalNumber(detailExternalExecution, "version_no") === "number"
|
||||
? `v${readOptionalNumber(detailExternalExecution, "version_no")}`
|
||||
: "-"}
|
||||
</Descriptions.Item>
|
||||
{selectedJob?.job_type === "tongtiao" ? (
|
||||
<>
|
||||
<Descriptions.Item label="主导相组">{readOptionalString(detailResultObject, "dominant_phase_set") ?? "-"}</Descriptions.Item>
|
||||
|
||||
Reference in New Issue
Block a user