93eb41a9f7
Release 0.58.0 includes the Earth high-precision boundary PMTiles/MVT pipeline, standardized Earth boundary source collectors, China POV boundary configuration templates, and removal of the legacy low-precision GeoJSON fallback. It also adds Earth news target-location queueing/archive support, fixes datasource task status visibility, documents the Earth surface depth-spacing rules that prevent far-zoom z-fighting snow/black blocks, and updates bilingual operations/developer docs.
188 lines
7.3 KiB
Python
188 lines
7.3 KiB
Python
"""Registry of target schemas supported by mapped custom data sources."""
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from __future__ import annotations
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from dataclasses import dataclass
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from datetime import datetime
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from typing import Any
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from pydantic import BaseModel, Field, ValidationError, field_validator
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class VesselAISRecord(BaseModel):
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mmsi: int = Field(ge=100000000, le=999999999)
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lat: float = Field(ge=-90, le=90)
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lon: float = Field(ge=-180, le=180)
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sog: float | None = None
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cog: float | None = Field(default=None, ge=0, le=360)
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heading: int | None = Field(default=None, ge=0, le=511)
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nav_status: int | None = None
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name: str | None = None
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callsign: str | None = None
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vessel_type: str | int | None = None
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vessel_type_name: str | None = None
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received_at: datetime | None = None
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class GeoPointRecord(BaseModel):
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lat: float = Field(ge=-90, le=90)
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lon: float = Field(ge=-180, le=180)
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name: str | None = None
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type: str | None = None
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source_id: str | None = None
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observed_at: datetime | None = None
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metadata: dict[str, Any] = Field(default_factory=dict)
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class GenericRecord(BaseModel):
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data: dict[str, Any] = Field(default_factory=dict)
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source_id: str | None = None
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observed_at: datetime | None = None
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@field_validator("data")
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@classmethod
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def require_payload(cls, value: dict[str, Any]) -> dict[str, Any]:
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if not value:
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raise ValueError("generic_records requires a non-empty data object")
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return value
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class EarthBoundarySourceRecord(BaseModel):
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source_id: str | None = None
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source_kind: str = Field(pattern="^(admin0-boundaries|coastline|claim-lines)$")
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name: str | None = None
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geometry: dict[str, Any] | None = None
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properties: dict[str, Any] = Field(default_factory=dict)
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artifact_path: str | None = None
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sha256: str | None = None
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feature_count: int | None = Field(default=None, ge=0)
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license: str | None = None
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@dataclass(frozen=True)
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class TargetField:
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name: str
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type: str
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required: bool = False
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description: str = ""
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example: Any = None
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def to_dict(self) -> dict[str, Any]:
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return {
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"name": self.name,
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"type": self.type,
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"required": self.required,
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"description": self.description,
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"example": self.example,
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}
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@dataclass(frozen=True)
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class TargetSchema:
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key: str
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label: str
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description: str
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fields: tuple[TargetField, ...]
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model: type[BaseModel]
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destination: str
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def to_dict(self) -> dict[str, Any]:
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return {
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"key": self.key,
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"label": self.label,
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"description": self.description,
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"destination": self.destination,
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"fields": [field.to_dict() for field in self.fields],
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}
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def validate_record(self, record: dict[str, Any]) -> tuple[dict[str, Any] | None, list[str]]:
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try:
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return self.model.model_validate(record).model_dump(mode="json"), []
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except ValidationError as exc:
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return None, [
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".".join(str(part) for part in error["loc"]) + f": {error['msg']}"
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for error in exc.errors()
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]
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TARGET_SCHEMAS: dict[str, TargetSchema] = {
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"vessel_ais": TargetSchema(
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key="vessel_ais",
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label="船舶 AIS",
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description="船只位置、航速、航向、MMSI 等 AIS 数据。",
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destination="vessel_position",
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model=VesselAISRecord,
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fields=(
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TargetField("mmsi", "integer", True, "MMSI 九位船舶标识", 257123000),
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TargetField("lat", "float", True, "纬度", 59.91),
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TargetField("lon", "float", True, "经度", 10.75),
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TargetField("sog", "float", False, "对地航速，单位节", 12.4),
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TargetField("cog", "float", False, "对地航向，0-360 度", 184.5),
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TargetField("heading", "integer", False, "船首向，0-511", 186),
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TargetField("nav_status", "integer", False, "导航状态码", 0),
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TargetField("name", "string", False, "船名", "OSLO EXPRESS"),
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TargetField("callsign", "string", False, "呼号", "LAAB"),
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TargetField("vessel_type", "string", False, "船型代码", 70),
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TargetField("vessel_type_name", "string", False, "船型名称", "Cargo"),
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TargetField("received_at", "datetime", False, "数据接收时间", "2026-04-28T00:00:00Z"),
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),
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),
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"geo_points": TargetSchema(
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key="geo_points",
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label="通用地理点",
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description="带经纬度的通用实体或事件点位。",
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destination="generic_geo_points",
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model=GeoPointRecord,
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fields=(
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TargetField("lat", "float", True, "纬度", 1.3),
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TargetField("lon", "float", True, "经度", 103.8),
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TargetField("name", "string", False, "点位名称", "Singapore"),
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TargetField("type", "string", False, "点位类型", "datacenter"),
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TargetField("source_id", "string", False, "来源侧 ID", "sg-1"),
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TargetField("observed_at", "datetime", False, "观测时间", "2026-04-28T00:00:00Z"),
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TargetField("metadata", "object", False, "扩展字段", {"provider": "example"}),
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),
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),
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"generic_records": TargetSchema(
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key="generic_records",
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label="通用结构化记录",
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description="未知结构数据沉淀，不直接进入 Earth 图层。",
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destination="collected_data",
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model=GenericRecord,
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fields=(
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TargetField("data", "object", True, "结构化记录主体", {"raw": "value"}),
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TargetField("source_id", "string", False, "来源侧 ID", "record-1"),
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TargetField("observed_at", "datetime", False, "观测时间", "2026-04-28T00:00:00Z"),
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),
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),
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"earth_boundary_source": TargetSchema(
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key="earth_boundary_source",
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label="Earth 边界矢量源",
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description="Admin-0 国界、海岸线、主张线等 Earth 边界源数据 artifact。",
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destination="collected_data",
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model=EarthBoundarySourceRecord,
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fields=(
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TargetField("source_id", "string", False, "来源侧 ID", "feature-1"),
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TargetField("source_kind", "string", True, "边界源类型", "admin0-boundaries"),
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TargetField("name", "string", False, "记录名称", "China"),
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TargetField("geometry", "object", False, "GeoJSON geometry", {"type": "Polygon", "coordinates": []}),
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TargetField("properties", "object", False, "GeoJSON properties", {"ISO_A3": "CHN"}),
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TargetField("artifact_path", "string", False, "完整源数据本地 artifact 路径", "data/earth-boundary-sources/earth_admin0_boundaries/abc.geojson"),
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TargetField("sha256", "string", False, "源数据 artifact SHA-256", "abc123"),
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TargetField("feature_count", "integer", False, "源数据 feature 数", 1),
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TargetField("license", "string", False, "源数据许可", "ODbL"),
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),
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),
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}
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def list_target_schemas() -> list[dict[str, Any]]:
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return [schema.to_dict() for schema in TARGET_SCHEMAS.values()]
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def get_target_schema(key: str) -> TargetSchema:
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try:
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return TARGET_SCHEMAS[key]
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except KeyError as exc:
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raise ValueError(f"Unsupported target schema: {key}") from exc
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