263 lines
10 KiB
Python
263 lines
10 KiB
Python
"""apply_actions 里的 $query：把字段值写成 {"$query": "SELECT ..."}，提交时替换成上传数据的查询结果
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模型不用把查询结果逐行抄进动作，又慢又容易抄错；替换发生在 run_batch 之前，替换后照常做字段校验
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结果的形状按写入字段的定义：单个值的字段（指标卡的数值等）取一行一列的那个值，元素是数字、文字的数组
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（指标卡的趋势数据）取唯一一列；其余是对象数组，键是查询结果的列名，正好对应图表物料的 dataset.source，
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series 的 encode 按列名引用
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"""
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from dataclasses import dataclass
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from typing import Any
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from pydantic import JsonValue
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from app.actions.batch import BatchError
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from app.agent.data_tools import DataContext
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from app.config import settings
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from app.resources.material_fields import component_fields, find_material
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from app.schemas.actions import AddAction, AgentAction, UpdateAction
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from app.schemas.component_resource import ComponentCatalog
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from app.schemas.material_field import MaterialField
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from app.schemas.screen import Screen
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QUERY_KEY = "$query"
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# 图表物料的数据都在这里，series 的 encode 按它的列名引用；整个换成查询结果时数据就不再是示例数据
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SOURCE_PATH = "props.option.dataset.source"
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# 字段是这些类型时，$query 的结果取一行一列的值
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SCALAR_TYPES = {"string", "number", "integer", "boolean", "color", "enum"}
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# 数组元素是这些类型时，$query 的结果取唯一一列
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LIST_ITEM_TYPES = {"string", "number", "integer", "boolean", "color"}
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@dataclass(frozen=True)
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class EmbeddedQuery:
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"""一处替换：第几个动作、写到哪个字段、结果的列和行数，写进 apply_actions 的结果供模型核对
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写入单个值的字段时 value 是取到的值，模型据此核对数字、在回复里引用
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"""
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index: int
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node_id: str
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path: str
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columns: list[str]
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rows: int
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value: JsonValue = None
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Found = list[EmbeddedQuery]
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def fill_queries(
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actions: list[AgentAction],
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data: DataContext,
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catalog: ComponentCatalog | None = None,
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screen: Screen | None = None,
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) -> tuple[list[AgentAction], list[EmbeddedQuery]]:
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"""替换 add 的 node 和 update 的 value 里所有的 $query；查询失败抛 BatchError，整批不生效
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catalog 和 screen 用来查写入字段的定义，决定结果的形状；没有时都按对象数组
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"""
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# update 的目标可能是这一批前面新增的组件，类型按执行顺序记下
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types = {node.id: node.type for node in screen.nodes} if screen else {}
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filled: list[AgentAction] = []
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embedded: list[EmbeddedQuery] = []
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for index, action in enumerate(actions):
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found: Found = []
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try:
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if isinstance(action, AddAction):
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types[action.node.id] = action.node.type
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node = _fill(
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action.node.model_dump(mode="json", exclude_unset=True),
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_Target(
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data, _fields(catalog, action.node.type), index, action.node.id
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),
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"",
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found,
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)
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if found:
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fields = action.model_dump(mode="json", exclude_unset=True)
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fields["node"] = node
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action = AddAction.model_validate(fields)
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elif isinstance(action, UpdateAction):
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target = _Target(
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data,
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_fields(catalog, types.get(action.target_id)),
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index,
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action.target_id,
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)
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value = _fill(action.value, target, action.field_path, found)
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if found:
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action = action.model_copy(update={"value": value})
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except ValueError as error: # 含 QueryError
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raise BatchError(index, action, str(error)) from error
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embedded.extend(found)
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filled.append(action)
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return filled, embedded
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@dataclass(frozen=True)
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class _Target:
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"""一个动作的替换上下文：查询用的数据、组件的字段定义、动作序号和组件 ID"""
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data: DataContext
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fields: dict[str, MaterialField]
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index: int
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node_id: str
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def _fields(
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catalog: ComponentCatalog | None, node_type: str | None
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) -> dict[str, MaterialField]:
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"""组件类型的字段定义，按路径索引；没有目录或类型不认识时为空，结果按对象数组处理"""
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if catalog is None or node_type is None:
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return {}
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try:
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component = find_material(catalog, node_type)
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except ValueError: # 物料不存在，补全或执行时会报错
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return {}
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return {field.path: field for field in component_fields(catalog, component)}
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def _fill(value: JsonValue, target: _Target, path: str, found: Found) -> JsonValue:
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if isinstance(value, dict):
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if QUERY_KEY in value:
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return _query(value, target, path, found)
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return {
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key: _fill(item, target, _join(path, key), found)
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for key, item in value.items()
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}
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if isinstance(value, list):
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return [
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_fill(item, target, _join(path, position), found)
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for position, item in enumerate(value)
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]
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return value
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def _query(
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value: dict[str, Any], target: _Target, path: str, found: Found
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) -> JsonValue:
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data = target.data
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sql = value[QUERY_KEY]
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if len(value) != 1 or not isinstance(sql, str):
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raise ValueError(
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f'{path} 的 $query 要写成 {{"$query": "SELECT ..."}}，对象里不能有其他键'
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)
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if not data.files:
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raise ValueError("会话里没有上传的数据文件，不能使用 $query")
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limit = settings.data_embed_max_rows
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result = data.query(sql, max_rows=limit)
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if result.truncated:
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raise ValueError(
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f"{path} 的 $query 结果超过 {limit} 行，组件放不下；在 SQL 里聚合、筛选或 LIMIT"
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)
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if duplicated := sorted(
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{name for name in result.columns if result.columns.count(name) > 1}
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):
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raise ValueError(
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f"{path} 的 $query 结果有重名的列 {'、'.join(duplicated)}，用 AS 起不同的别名"
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)
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shape = (
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f"{len(result.rows)} 行 {len(result.columns)} 列（{'、'.join(result.columns)}）"
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)
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field = target.fields.get(path)
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if field is not None and field.value_type in SCALAR_TYPES:
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if len(result.rows) != 1 or len(result.columns) != 1:
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raise ValueError(
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f"{path}（{field.label}）是单个值，$query 的结果要一行一列，实际 {shape}"
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)
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scalar = result.rows[0][0]
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found.append(
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EmbeddedQuery(target.index, target.node_id, path, result.columns, 1, scalar)
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)
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return scalar
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listed = (
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field is not None
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and field.value_type == "array"
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and field.item_type in LIST_ITEM_TYPES
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)
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if listed and len(result.columns) != 1:
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raise ValueError(
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f"{path}（{field.label}）是一组值，$query 的结果要只有一列，实际 {shape}；"
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"排序用的列不用选出来，写在 ORDER BY 里"
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)
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found.append(
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EmbeddedQuery(
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target.index, target.node_id, path, result.columns, len(result.rows)
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)
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)
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if listed:
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return [row[0] for row in result.rows]
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return [dict(zip(result.columns, row, strict=True)) for row in result.rows]
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def _join(path: str, key: str | int) -> str:
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return f"{path}.{key}" if path else str(key)
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def _binding(node) -> tuple[Any, Any]:
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option = node.props.get("option")
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if not isinstance(option, dict):
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return None, None
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return option.get("dataset"), option.get("series")
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def rebound_nodes(before: Screen, after: Screen) -> set[str]:
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"""这一批改过数据或映射（option.dataset、option.series）的组件，新增的也算
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只按前后状态比较，不看是哪种动作改的：$query、直接写数据、单独改 encode 都会让两者对不上；没动过的旧组件不核对
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"""
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old = {node.id: _binding(node) for node in before.nodes}
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return {
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node.id
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for node in after.nodes
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if node.id not in old or old[node.id] != _binding(node)
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}
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def encode_problems(screen: Screen, node_ids: set[str]) -> list[str]:
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"""指定组件的 series encode 引用的列必须在 dataset.source 里
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数据换了列名、或 encode 改成了不存在的列时图表是空的，前端也不报错，所以在这里拦下
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"""
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problems = []
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for node in screen.nodes:
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if node.id not in node_ids:
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continue
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option = node.props.get("option")
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if not isinstance(option, dict):
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continue
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dataset = option.get("dataset")
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source = dataset.get("source") if isinstance(dataset, dict) else None
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# 空结果或不是对象数组时无从核对
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if not (
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isinstance(source, list)
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and source
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and all(isinstance(row, dict) for row in source)
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):
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continue
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columns = list(dict.fromkeys(key for row in source for key in row))
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series = option.get("series")
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items = series if isinstance(series, list) else [series]
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wrong = []
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for position, item in enumerate(items):
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encode = item.get("encode") if isinstance(item, dict) else None
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if not isinstance(encode, dict):
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continue
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for key, names in encode.items():
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missing = [
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name
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for name in (names if isinstance(names, list) else [names])
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if isinstance(name, str) and name not in columns
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]
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if missing:
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wrong.append(
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f"props.option.series.{position}.encode.{key} 用了 {'、'.join(missing)}"
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)
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if wrong:
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problems.append(
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f"组件 {node.id}：{'；'.join(wrong)}，但 props.option.dataset.source 的列是 {'、'.join(columns)}；"
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"把 encode 改成 dataset.source 里的列名；数据来自 $query 时也可以在 SQL 里用 AS 起对应的别名"
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)
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return problems
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