Initial GeoIntel V1 foundation
This commit is contained in:
Codex
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from __future__ import annotations
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import json
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import re
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import uuid
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from html import escape
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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 app.core.errors import AppError
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from app.models import AnalysisRun, Dataset, Export, Project, QualityCheck
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from app.schemas.export import ExportContentResponse, ExportCreateResponse, ExportListResponse, ExportRead
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from app.services.dataset_service import DatasetService
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from app.services.detection_service import DetectionService
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from app.services.segmentation_service import SegmentationService
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from app.services.storage_service import StorageService
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class ExportService:
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@staticmethod
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def export_dataset_geojson(db: Session, dataset_id: uuid.UUID, name: str | None = None) -> ExportCreateResponse:
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dataset = db.get(Dataset, dataset_id)
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if not dataset:
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raise AppError(code="DATASET_NOT_FOUND", message="Dataset not found", status_code=404)
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if dataset.dataset_type not in DatasetService.VECTOR_TYPES:
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raise AppError(
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code="INVALID_DATASET_TYPE",
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message="GeoJSON dataset export requires a vector dataset",
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details={"dataset_type": dataset.dataset_type},
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status_code=400,
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)
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feature_collection = DatasetService.get_dataset_geojson(db, dataset_id)
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filename = ExportService._filename(name, f"{dataset.id}.geojson", ".geojson")
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export_path = StorageService.dataset_export_path(str(dataset.project_id), str(dataset.id), filename)
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metadata = {
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"source": "dataset",
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"dataset_id": str(dataset.id),
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"project_id": str(dataset.project_id),
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"dataset_type": dataset.dataset_type,
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"feature_count": len(feature_collection.get("features", [])),
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}
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export = ExportService._write_json_export(
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db,
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project_id=dataset.project_id,
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analysis_run_id=None,
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export_type="dataset_geojson",
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storage_path=export_path,
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content=feature_collection,
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metadata=metadata,
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)
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return ExportService._create_response(export)
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@staticmethod
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def export_detection_run_geojson(db: Session, analysis_run_id: uuid.UUID, name: str | None = None) -> ExportCreateResponse:
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run = db.get(AnalysisRun, analysis_run_id)
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if not run or run.analysis_type != "detection":
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raise AppError(code="DETECTION_RUN_NOT_FOUND", message="Detection run not found", status_code=404)
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feature_collection = DetectionService.detections_to_geojson(db, analysis_run_id=analysis_run_id)
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filename = ExportService._filename(name, f"{run.id}-detections.geojson", ".geojson")
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export_path = StorageService.dataset_export_path(str(run.project_id), str(run.dataset_id or run.id), filename)
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metadata = {
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"source": "detection_run",
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"analysis_run_id": str(run.id),
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"project_id": str(run.project_id),
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"dataset_id": str(run.dataset_id) if run.dataset_id else None,
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"feature_count": len(feature_collection.get("features", [])),
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}
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export = ExportService._write_json_export(
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db,
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project_id=run.project_id,
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analysis_run_id=run.id,
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export_type="detection_geojson",
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storage_path=export_path,
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content=feature_collection,
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metadata=metadata,
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)
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return ExportService._create_response(export)
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@staticmethod
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def export_segmentation_run_geojson(db: Session, analysis_run_id: uuid.UUID, name: str | None = None) -> ExportCreateResponse:
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run = db.get(AnalysisRun, analysis_run_id)
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if not run or run.analysis_type != "segmentation":
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raise AppError(code="SEGMENTATION_RUN_NOT_FOUND", message="Segmentation run not found", status_code=404)
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feature_collection = SegmentationService.segmentations_to_geojson(db, analysis_run_id=analysis_run_id)
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filename = ExportService._filename(name, f"{run.id}-segmentations.geojson", ".geojson")
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export_path = StorageService.dataset_export_path(str(run.project_id), str(run.dataset_id or run.id), filename)
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metadata = {
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"source": "segmentation_run",
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"analysis_run_id": str(run.id),
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"project_id": str(run.project_id),
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"dataset_id": str(run.dataset_id) if run.dataset_id else None,
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"feature_count": len(feature_collection.get("features", [])),
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}
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export = ExportService._write_json_export(
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db,
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project_id=run.project_id,
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analysis_run_id=run.id,
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export_type="segmentation_geojson",
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storage_path=export_path,
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content=feature_collection,
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metadata=metadata,
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)
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return ExportService._create_response(export)
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@staticmethod
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def export_project_metadata(db: Session, project_id: uuid.UUID, name: str | None = None) -> ExportCreateResponse:
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project = db.get(Project, project_id)
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if not project:
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raise AppError(code="PROJECT_NOT_FOUND", message="Project not found", status_code=404)
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content = ExportService._project_summary(db, project)
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filename = ExportService._filename(name, f"{project.id}-metadata.json", ".json")
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export_path = StorageService.dataset_export_path(str(project.id), "project", filename)
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metadata = {
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"source": "project_metadata",
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"project_id": str(project.id),
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"dataset_count": len(content["datasets"]),
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"quality_check_count": len(content["quality_checks"]),
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"export_count": len(content["exports"]),
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}
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export = ExportService._write_json_export(
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db,
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project_id=project.id,
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analysis_run_id=None,
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export_type="project_metadata_json",
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storage_path=export_path,
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content=content,
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metadata=metadata,
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)
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return ExportService._create_response(export)
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@staticmethod
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def export_project_report(db: Session, project_id: uuid.UUID, name: str | None = None) -> ExportCreateResponse:
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project = db.get(Project, project_id)
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if not project:
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raise AppError(code="PROJECT_NOT_FOUND", message="Project not found", status_code=404)
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summary = ExportService._project_summary(db, project)
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html = ExportService._render_project_report_html(summary)
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filename = ExportService._filename(name, f"{project.id}-report.html", ".html")
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export_path = StorageService.dataset_export_path(str(project.id), "project", filename)
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metadata = {
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"source": "project_report",
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"project_id": str(project.id),
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"dataset_count": len(summary["datasets"]),
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"quality_check_count": len(summary["quality_checks"]),
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"export_count": len(summary["exports"]),
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"format": "html",
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}
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export = ExportService._write_text_export(
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db,
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project_id=project.id,
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analysis_run_id=None,
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export_type="project_report_html",
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storage_path=export_path,
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content=html,
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metadata=metadata,
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)
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return ExportService._create_response(export)
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@staticmethod
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def list_project_exports(db: Session, project_id: uuid.UUID, limit: int = 50, offset: int = 0) -> ExportListResponse:
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if not db.get(Project, project_id):
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raise AppError(code="PROJECT_NOT_FOUND", message="Project not found", status_code=404)
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query = db.query(Export).filter(Export.project_id == project_id).order_by(Export.created_at.desc())
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rows = query.offset(offset).limit(limit).all()
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total = query.count()
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return ExportListResponse(
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items=[ExportRead.model_validate(row) for row in rows],
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total=total,
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limit=limit,
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offset=offset,
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)
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@staticmethod
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def get_export(db: Session, export_id: uuid.UUID) -> ExportRead:
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export = db.get(Export, export_id)
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if not export:
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raise AppError(code="EXPORT_NOT_FOUND", message="Export not found", status_code=404)
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return ExportRead.model_validate(export)
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@staticmethod
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def get_export_content(db: Session, export_id: uuid.UUID) -> ExportContentResponse:
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export = db.get(Export, export_id)
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if not export:
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raise AppError(code="EXPORT_NOT_FOUND", message="Export not found", status_code=404)
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path = ExportService.get_export_download_path(db, export_id)
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try:
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content = json.loads(path.read_text(encoding="utf-8"))
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except json.JSONDecodeError as exc:
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raise AppError(code="EXPORT_CONTENT_INVALID", message="Export artifact is not valid JSON", status_code=422) from exc
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return ExportContentResponse(export_id=export.id, export_type=export.export_type, content=content)
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@staticmethod
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def get_export_download_path(db: Session, export_id: uuid.UUID) -> Path:
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export = db.get(Export, export_id)
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if not export:
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raise AppError(code="EXPORT_NOT_FOUND", message="Export not found", status_code=404)
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path = Path(export.storage_path)
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if not path.exists() or not path.is_file():
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raise AppError(
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code="EXPORT_CONTENT_NOT_FOUND",
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message="Export artifact is missing from storage",
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details={"storage_path": export.storage_path},
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status_code=404,
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)
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return path
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@staticmethod
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def _write_json_export(
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db: Session,
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*,
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project_id: uuid.UUID,
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analysis_run_id: uuid.UUID | None,
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export_type: str,
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storage_path: str,
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content: dict[str, Any],
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metadata: dict[str, Any],
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) -> Export:
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path = Path(storage_path)
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text(json.dumps(content, ensure_ascii=False, indent=2), encoding="utf-8")
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return ExportService._persist_export(
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db,
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project_id=project_id,
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analysis_run_id=analysis_run_id,
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export_type=export_type,
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storage_path=str(path),
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metadata=metadata,
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)
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@staticmethod
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def _write_text_export(
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db: Session,
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*,
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project_id: uuid.UUID,
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analysis_run_id: uuid.UUID | None,
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export_type: str,
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storage_path: str,
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content: str,
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metadata: dict[str, Any],
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) -> Export:
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path = Path(storage_path)
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text(content, encoding="utf-8")
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return ExportService._persist_export(
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db,
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project_id=project_id,
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analysis_run_id=analysis_run_id,
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export_type=export_type,
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storage_path=str(path),
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metadata=metadata,
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)
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@staticmethod
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def _persist_export(
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db: Session,
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*,
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project_id: uuid.UUID,
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analysis_run_id: uuid.UUID | None,
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export_type: str,
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storage_path: str,
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metadata: dict[str, Any],
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) -> Export:
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export = Export(
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id=uuid.uuid4(),
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project_id=project_id,
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analysis_run_id=analysis_run_id,
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export_type=export_type,
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storage_path=storage_path,
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metadata_json=metadata,
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)
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db.add(export)
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db.commit()
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db.refresh(export)
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return export
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@staticmethod
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def _project_summary(db: Session, project: Project) -> dict[str, Any]:
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datasets = db.query(Dataset).filter(Dataset.project_id == project.id).order_by(Dataset.created_at.desc()).all()
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quality_checks = (
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db.query(QualityCheck)
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.filter(QualityCheck.project_id == project.id)
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.order_by(QualityCheck.created_at.desc())
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.all()
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)
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exports = db.query(Export).filter(Export.project_id == project.id).order_by(Export.created_at.desc()).all()
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return {
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"project": {
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"id": str(project.id),
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"name": project.name,
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"description": project.description,
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"region": project.region,
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"status": project.status,
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},
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"datasets": [
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{
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"id": str(dataset.id),
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"name": dataset.name,
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"dataset_type": dataset.dataset_type,
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"dataset_role": dataset.dataset_role,
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"source_name": dataset.source_name,
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"reference_layer_name": dataset.reference_layer_name,
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"status": dataset.status,
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"crs": dataset.crs,
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"bounds_json": dataset.bounds_json,
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"feature_count": (dataset.metadata_json or {}).get("feature_count"),
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}
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for dataset in datasets
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],
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"quality_checks": [
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{
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"id": str(check.id),
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"analysis_run_id": str(check.analysis_run_id) if check.analysis_run_id else None,
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"candidate_dataset_id": str(check.candidate_dataset_id) if check.candidate_dataset_id else None,
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"reference_dataset_id": str(check.reference_dataset_id),
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"check_type": check.check_type,
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"status": check.status,
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"score": check.score,
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}
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for check in quality_checks
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],
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"exports": [
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{
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"id": str(export.id),
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"analysis_run_id": str(export.analysis_run_id) if export.analysis_run_id else None,
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"export_type": export.export_type,
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"storage_path": export.storage_path,
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"metadata_json": export.metadata_json,
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"created_at": export.created_at.isoformat() if export.created_at else None,
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}
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for export in exports
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],
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}
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@staticmethod
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def _render_project_report_html(summary: dict[str, Any]) -> str:
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project = summary["project"]
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datasets = summary["datasets"]
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quality_checks = summary["quality_checks"]
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exports = summary["exports"]
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dataset_rows = "\n".join(
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"<tr>"
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f"<td>{escape(str(item['name']))}</td>"
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f"<td>{escape(str(item['dataset_type']))}</td>"
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f"<td>{escape(str(item['dataset_role']))}</td>"
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f"<td>{escape(str(item['status']))}</td>"
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f"<td>{escape(str(item['feature_count'] if item['feature_count'] is not None else 'n/a'))}</td>"
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"</tr>"
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for item in datasets
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)
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quality_rows = "\n".join(
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"<tr>"
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f"<td>{escape(str(item['check_type']))}</td>"
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f"<td>{escape(str(item['status']))}</td>"
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f"<td>{escape(str(item['score'] if item['score'] is not None else 'n/a'))}</td>"
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f"<td>{escape(str(item['reference_dataset_id']))}</td>"
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"</tr>"
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for item in quality_checks
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)
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export_rows = "\n".join(
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"<tr>"
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f"<td>{escape(str(item['export_type']))}</td>"
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f"<td>{escape(str(item['storage_path']))}</td>"
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f"<td>{escape(str(item['created_at'] or 'n/a'))}</td>"
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"</tr>"
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for item in exports
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)
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return f"""<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8" />
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<title>GeoIntel Project Report - {escape(str(project["name"]))}</title>
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<style>
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body {{ font-family: Arial, sans-serif; color: #0f172a; margin: 2rem; }}
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h1, h2 {{ margin-bottom: 0.4rem; }}
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table {{ width: 100%; border-collapse: collapse; margin: 1rem 0 2rem; }}
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th, td {{ border: 1px solid #cbd5e1; padding: 0.5rem; text-align: left; }}
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th {{ background: #e2e8f0; }}
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.muted {{ color: #475569; }}
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</style>
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</head>
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<body>
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<h1>{escape(str(project["name"]))}</h1>
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<p class="muted">GeoIntel project report artifact</p>
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<p>Region: {escape(str(project["region"]))}</p>
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<p>Status: {escape(str(project["status"]))}</p>
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<p>Description: {escape(str(project["description"] or "n/a"))}</p>
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<h2>Datasets ({len(datasets)})</h2>
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<table>
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<thead><tr><th>Name</th><th>Type</th><th>Role</th><th>Status</th><th>Features</th></tr></thead>
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<tbody>{dataset_rows or '<tr><td colspan="5">No datasets</td></tr>'}</tbody>
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</table>
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<h2>QA/QC Results ({len(quality_checks)})</h2>
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<table>
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<thead><tr><th>Check</th><th>Status</th><th>Score</th><th>Reference dataset</th></tr></thead>
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<tbody>{quality_rows or '<tr><td colspan="4">No QA/QC results</td></tr>'}</tbody>
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</table>
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<h2>Export History ({len(exports)})</h2>
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<table>
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<thead><tr><th>Type</th><th>Storage path</th><th>Created</th></tr></thead>
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<tbody>{export_rows or '<tr><td colspan="3">No exports</td></tr>'}</tbody>
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</table>
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</body>
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</html>
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"""
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@staticmethod
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def _create_response(export: Export) -> ExportCreateResponse:
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return ExportCreateResponse(
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export_id=export.id,
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path=export.storage_path,
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status="ready",
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export_type=export.export_type,
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metadata_json=export.metadata_json,
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)
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@staticmethod
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def _filename(name: str | None, fallback: str, suffix: str) -> str:
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raw_name = name or fallback
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cleaned = re.sub(r"[^A-Za-z0-9_.-]+", "_", raw_name).strip("._")
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if not cleaned:
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cleaned = fallback
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if not cleaned.lower().endswith(suffix):
|
||||
cleaned = f"{cleaned}{suffix}"
|
||||
return cleaned
|
||||
Reference in New Issue
Block a user