"""Session-based CDSL execution with atomic executor registry."""

from __future__ import annotations

from copy import deepcopy
from dataclasses import dataclass, field
import math
from pathlib import Path
from typing import Any, Callable, Protocol

from .build123d_adapter import Build123dGeometryAdapter
from .capabilities import CapabilityAnalyzer, pattern_transform_blocker, sketch_ids_required_by_contract
from .runtime_types import (
    AxisSpec, CapabilityResult, FeaturePlanNode, FeatureResult, HoleSpec, PlaneSpec, Vector3,
    RuntimeDiagnostic, SelectorResolution, TopologyRecord, TopologyRegistry,
    vector_add, vector_cross, vector_dot, vector_scale, vector_subtract, vector_unit,
)
from .sketch_solver import CORE_SHAPE_GENERATORS, resolve_required_sketches


ALL_ATOMIC_IDS = frozenset({
    "extrude_add_blind", "extrude_add_two_sided", "extrude_cut_blind",
    "revolve_add", "revolve_cut", "hole_blind", "hole_countersink",
    "hole_counterbore", "sphere_add", "reference_plane", "reference_axis",
    "hole_wizard", "fillet", "chamfer", "pattern_linear", "pattern_mirror",
})


class RuntimeExecutionError(RuntimeError):
    """A feature execution failure with serializable runtime evidence."""

    def __init__(self, diagnostic: RuntimeDiagnostic, selector_resolutions: list[dict[str, Any]]) -> None:
        super().__init__(diagnostic.message)
        self.diagnostic = diagnostic
        self.selector_resolutions = selector_resolutions


class FeatureExecutionError(RuntimeError):
    """An expected feature-level execution rejection with a stable code."""

    def __init__(self, code: str, message: str, **detail: Any) -> None:
        super().__init__(message)
        self.code = code
        self.detail = detail


class AtomicExecutor(Protocol):
    atomic_id: str

    def preflight(self, node: FeaturePlanNode, session: "ExecutionSession") -> CapabilityResult: ...
    def execute(self, node: FeaturePlanNode, session: "ExecutionSession") -> FeatureResult: ...


class GeometryAdapter(Protocol):
    """Kernel boundary consumed by the session runtime.

    Geometry values remain opaque here.  A future adapter may use a different
    B-rep kernel as long as it preserves these construction/query contracts.
    """

    def topology_records(self, body: Any, feature_id: str, body_id: str) -> list[TopologyRecord]: ...
    def body_geometry(self, body: Any) -> dict[str, Any]: ...
    def faces_for_sketch(self, sketch: dict[str, Any]) -> list[Any]: ...
    def extrude(self, face: Any, direction: Vector3) -> Any: ...
    def revolve(self, face: Any, angle_deg: float, axis: AxisSpec) -> Any: ...
    def fuse(self, body: Any | None, solid: Any) -> Any: ...
    def cut(self, body: Any, tool: Any) -> Any: ...
    def sphere(self, radius_mm: float, center_mm: Vector3) -> Any: ...
    def hole_tool(self, spec: HoleSpec, starts: list[Vector3], inward: Vector3, through_depth_mm: float) -> Any: ...
    def body_center(self, body: Any) -> Vector3: ...
    def body_span(self, body: Any, direction: Vector3) -> float: ...
    def vertex_coordinates(self, vertex: Any) -> Vector3: ...
    def profile_sample_points(self, face: Any) -> list[Any]: ...
    def uniform_intersection_distance(self, target: Any, faces: list[Any], direction: Vector3) -> float: ...
    def fillet(self, body: Any, radius_mm: float, edges: list[Any]) -> Any: ...
    def tangent_edges(self, body: Any, seeds: list[Any]) -> list[Any]: ...
    def chamfer(self, body: Any, distance_mm: float, distance_2_mm: float | None, edges: list[Any], face: Any | None = None) -> Any: ...
    def export(self, body: Any, path: str) -> None: ...


@dataclass
class ExecutionSession:
    sketches: dict[str, dict[str, Any]]
    nodes: dict[str, FeaturePlanNode]
    adapter: GeometryAdapter = field(default_factory=Build123dGeometryAdapter)
    topology: TopologyRegistry = field(default_factory=TopologyRegistry)
    body: Any | None = None
    body_id: str | None = None
    results: dict[str, FeatureResult] = field(default_factory=dict)
    replay_definitions: dict[str, FeaturePlanNode] = field(default_factory=dict)
    selector_resolutions: list[dict[str, Any]] = field(default_factory=list)
    active_feature_id: str = ""

    def register_body(self, feature_id: str, body: Any, *, replay_node: FeaturePlanNode | None = None) -> None:
        self.body = body
        self.body_id = f"body:{feature_id}"
        self.topology.replace_body_topology(feature_id, self.body_id, self.adapter.topology_records(body, feature_id, self.body_id))
        self.topology.register(TopologyRecord(
            record_id=self.body_id, kind="body", feature_id=feature_id, body_id=self.body_id,
            geometry=self.adapter.body_geometry(body), value=body, owner_feature_ids=(feature_id,),
        ))
        if replay_node is not None:
            self.replay_definitions[feature_id] = replay_node

    def resolve(self, selector: dict[str, Any]) -> SelectorResolution:
        resolution = self.topology.resolve(selector, active_body_id=self.body_id)
        evidence = resolution.as_dict()
        evidence["feature_id"] = self.active_feature_id
        self.selector_resolutions.append(evidence)
        return resolution

    def result(self, node: FeaturePlanNode, *, context: PlaneSpec | AxisSpec | None = None, diagnostics: list[RuntimeDiagnostic] | None = None) -> FeatureResult:
        result = FeatureResult(
            feature_id=node.feature_id, atomic_id=node.atomic_id, status="executed", body_id=self.body_id,
            context=context, replay_definition={"atomic_id": node.atomic_id, "params": deepcopy(node.params), "sketch_id": node.sketch_id},
            diagnostics=diagnostics or [],
        )
        self.results[node.feature_id] = result
        return result

    def replay_sources(self, source_feature_ids: list[Any]) -> list[FeaturePlanNode]:
        """Return selected source features in their original history order.

        A pattern's exported selection order is not an execution order.  In
        particular, a boolean cut may appear before its parent boss in the
        raw selection array.  The CDSL feature list is dependency-ordered by
        semantic validation, so it is the stable order for replay.
        """
        requested = {str(feature_id) for feature_id in source_feature_ids}
        sources = [
            feature
            for feature_id, feature in self.nodes.items()
            if feature_id in requested and feature_id in self.replay_definitions
        ]
        if len(sources) != len(requested):
            missing = sorted(requested - {source.feature_id for source in sources})
            raise ValueError(f"pattern source features have no replay definitions: {', '.join(missing)}")
        return sources


def _normal_from_sketch(sketch: dict[str, Any]) -> Vector3:
    return PlaneSpec.from_mapping(sketch.get("workplane") or {}).normal


def _extent_reference(node: FeaturePlanNode, condition: dict[str, Any] | None = None) -> dict[str, Any]:
    condition = condition or node.params.get("end_condition") or {}
    reference = condition.get("reference")
    if not isinstance(reference, dict):
        raise FeatureExecutionError(
            "missing_extent_reference",
            "This end condition requires a captured target selector",
            extent=condition.get("type"),
        )
    return reference


def _targeted_extent_vector(
    node: FeaturePlanNode,
    faces: list[Any],
    direction: Vector3,
    session: ExecutionSession,
    condition: str,
    *,
    end_condition: dict[str, Any] | None = None,
    offset_mm: float | None = None,
) -> Vector3:
    if session.body is None:
        raise FeatureExecutionError("missing_extent_body", "Selector-dependent extent requires an existing body", extent=condition)
    if condition == "through_next":
        target = session.body
    else:
        reference = _extent_reference(node, end_condition)
        resolution = session.resolve(reference)
        if resolution.status != "resolved" or resolution.record is None:
            raise ValueError(resolution.diagnostic.message if resolution.diagnostic else "extent target was not resolved")
        expected_kind = {"up_to_vertex": "vertex", "up_to_body": "body"}.get(condition, "face")
        if resolution.record.kind != expected_kind:
            raise FeatureExecutionError(
                "unsupported_extent_target",
                "The resolved target kind is incompatible with this end condition",
                extent=condition, expected_kind=expected_kind, actual_kind=resolution.record.kind,
            )
        target = resolution.record.value
    if condition == "up_to_vertex":
        target_point = session.adapter.vertex_coordinates(target)
        projections = [
            vector_dot(vector_subtract(target_point, point), direction)
            for face in faces
            for point in session.adapter.profile_sample_points(face)
        ]
        if not projections or min(projections) <= 1e-6:
            raise FeatureExecutionError("extent_target_not_in_direction", "The target vertex is not ahead of the profile", extent=condition)
        if max(projections) - min(projections) > 1e-5:
            raise FeatureExecutionError("non_uniform_extent_target", "The target vertex does not define one extrusion distance", extent=condition)
        distance = sum(projections) / len(projections)
    else:
        try:
            distance = session.adapter.uniform_intersection_distance(target, faces, direction)
        except ValueError as error:
            code = "non_uniform_extent_target" if "non-uniform" in str(error) else "extent_target_not_reached"
            raise FeatureExecutionError(code, str(error), extent=condition) from error
    if condition == "offset_from_surface":
        offset = abs(float(offset_mm if offset_mm is not None else node.params.get("distance_mm") or 0.0))
        distance -= offset
        if distance <= 1e-6:
            raise FeatureExecutionError(
                "invalid_extent_offset",
                "Offset distance reaches or passes the target surface",
                extent=condition, offset_mm=offset,
            )
    return vector_scale(direction, distance)


def _side_extent_vectors(
    node: FeaturePlanNode,
    faces: list[Any],
    direction: Vector3,
    session: ExecutionSession,
    *,
    end_condition: dict[str, Any],
    distance_mm: float,
) -> list[Vector3]:
    """Resolve one directional extent without borrowing the opposite side.

    ``extrude_add_two_sided`` calls this once for each independently captured
    termination.  The regular one-sided executor also uses it for all simple
    termination modes, keeping the geometry adapter interface uniform.
    """
    condition = str(end_condition.get("type") or "blind")
    distance = abs(float(distance_mm or 0.0))
    if condition == "blind":
        if distance <= 0:
            raise ValueError("blind extent requires distance_mm > 0")
        return [vector_scale(direction, distance)]
    if condition == "mid_plane":
        if distance <= 0:
            raise ValueError("mid_plane extent requires distance_mm > 0")
        return [vector_scale(direction, distance / 2), vector_scale(direction, -distance / 2)]
    if condition == "through_all":
        if session.body is None:
            if distance <= 0:
                raise ValueError("through_all on an initial feature has no body and no fallback distance")
            return [direction * distance]
        return [vector_scale(direction, max(session.adapter.body_span(session.body, direction), 1.0) + 2.0)]
    if condition in {"up_to_surface", "up_to_vertex", "offset_from_surface", "through_next", "up_to_body"}:
        return [
            _targeted_extent_vector(
                node, faces, direction, session, condition,
                end_condition=end_condition, offset_mm=distance,
            )
        ]
    raise ValueError(f"unsupported directional extent {condition!r}")


def _extent_vectors(
    node: FeaturePlanNode,
    faces: list[Any],
    sketch: dict[str, Any],
    session: ExecutionSession,
) -> list[Vector3]:
    params = node.params
    normal = vector_unit(_normal_from_sketch(sketch), field_name="sketch normal")
    if bool(params.get("reverse")):
        normal = vector_scale(normal, -1)
    end_condition = params.get("end_condition") or {"type": "blind"}
    condition = end_condition.get("type", "blind")
    distance = abs(float(params.get("distance_mm") or 0.0))
    if node.atomic_id == "extrude_add_two_sided":
        reverse_condition = params.get("reverse_end_condition") or {"type": "blind"}
        reverse_distance = abs(float(params.get("reverse_distance_mm") or 0.0))
        if reverse_distance <= 0:
            raise ValueError("two-sided extrusion requires reverse_distance_mm > 0")
        return [
            *_side_extent_vectors(
                node, faces, normal, session, end_condition=end_condition, distance_mm=distance,
            ),
            *_side_extent_vectors(
                node, faces, vector_scale(normal, -1), session,
                end_condition=reverse_condition, distance_mm=reverse_distance,
            ),
        ]
    if condition in {"through_all", "through_all_both", "through_all_and_blind"}:
        if session.body is None:
            # A first feature with through-all has no body to terminate
            # against.  The source must provide a usable blind component.
            if distance <= 0:
                raise ValueError("through_all on an initial feature has no body and no fallback distance")
            return [vector_scale(normal, distance)]
        span = max(session.adapter.body_span(session.body, normal), 1.0) + 2.0
        if condition == "through_all":
            return [vector_scale(normal, span)]
        if condition == "through_all_both":
            return [vector_scale(normal, span), vector_scale(normal, -span)]
        # Through-all-and-blind is represented by a through direction plus
        # its captured opposite blind direction when available.
        reverse_distance = abs(float(params.get("reverse_distance_mm") or 0.0))
        return [vector_scale(normal, span), vector_scale(normal, -(reverse_distance or span))]
    return _side_extent_vectors(
        node, faces, normal, session, end_condition=end_condition, distance_mm=distance,
    )


def _revolve_axis(node: FeaturePlanNode, session: ExecutionSession) -> AxisSpec:
    raw_axis = node.params.get("axis") or {}
    if raw_axis.get("origin_mm") is not None and raw_axis.get("direction") is not None:
        return AxisSpec.from_mapping(raw_axis)
    selector = raw_axis.get("selector") if isinstance(raw_axis, dict) else None
    if not isinstance(selector, dict):
        selector = next((item for item in node.selectors if item.get("kind") == "axis"), None)
    if not isinstance(selector, dict):
        raise FeatureExecutionError(
            "missing_revolve_axis",
            "Revolve requires an explicit axis or an owner-qualified reference-axis selector",
        )
    resolution = session.resolve(selector)
    if resolution.status != "resolved" or resolution.record is None:
        raise ValueError(resolution.diagnostic.message if resolution.diagnostic else "revolve axis was not resolved")
    if not isinstance(resolution.record.value, AxisSpec):
        raise FeatureExecutionError(
            "unsupported_revolve_axis", "The resolved context is not an axis", actual_kind=resolution.record.kind,
        )
    return resolution.record.value


def _shape_from_primary(node: FeaturePlanNode, session: ExecutionSession, *, sketch: dict[str, Any] | None = None) -> FeatureResult:
    # 主形状特征（拉伸 / 旋转）的统一入口：由草图生成实体并与当前主体做布尔合并或切除。
    
    # 1. 取草图：优先使用外部传入的 sketch_override（阵列/镜像等重放场景），
    #    否则按 sketch_id 从会话草图表中取原始草图。
    selected_sketch = sketch or session.sketches.get(str(node.sketch_id))
    if selected_sketch is None:
        raise ValueError("primary feature has no resolved sketch")
    # 2. 从草图解析闭合轮廓区域（faces），没有闭合区域就无法生成实体。
    faces = session.adapter.faces_for_sketch(selected_sketch)
    if not faces:
        raise ValueError("sketch does not create a closed profile region")
    # 3. 按特征类型生成子实体：
    if node.atomic_id.startswith("extrude_"):
        #   拉伸：先按终止条件（盲孔/贯穿/至面/双侧等）求出位移向量，
        #   再对每个面沿每个向量做拉伸，得到实体列表。
        vectors = _extent_vectors(node, faces, selected_sketch, session)
        solids = [session.adapter.extrude(face, vector) for face in faces for vector in vectors]
    else:
        #   旋转：解析旋转轴并校验旋转角，然后绕轴旋转每个面得到实体列表。
        axis = _revolve_axis(node, session)
        angle = float(node.params.get("angle_deg") or 0.0)
        if angle <= 0:
            raise ValueError("revolve requires angle_deg > 0")
        solids = [session.adapter.revolve(face, angle, axis) for face in faces]
    # 4. 将所有子实体做布尔并（fuse）合并为一个工具体（tool）。
    tool = None
    for solid in solids:
        tool = session.adapter.fuse(tool, solid)
    if tool is None:
        raise ValueError("primary feature produced no solid")
    # 5. 与当前主体做布尔操作：
    if "cut" in node.atomic_id:
        #   切除类特征：要求已有主体，从主体上减去工具体（cut）。
        if session.body is None:
            raise ValueError("cut feature has no body")
        body = session.adapter.cut(session.body, tool)
    else:
        #   添加类特征：将工具体并到当前主体上（fuse），首个特征时 body 为 None 也能直接成立。
        body = session.adapter.fuse(session.body, tool)
    # 6. 登记新主体（更新拓扑、记录重放定义），并返回该特征的结果对象。
    session.register_body(node.feature_id, body, replay_node=node)
    return session.result(node)


def _execute_reference_plane(node: FeaturePlanNode, session: ExecutionSession) -> FeatureResult:
    # 基准面特征（reference_plane）执行入口：从参数解析平面并登记为拓扑上下文。
    
    # 1. 从特征参数 plane 中解析出平面定义 PlaneSpec（原点到法向）。
    plane = PlaneSpec.from_mapping(node.params.get("plane") or {})
    # 2. 将该平面注册到拓扑上下文，供后续特征（如草图基准、参考轴）引用。
    session.topology.register_context(node.feature_id, plane)
    # 3. 返回结果对象，并将该平面作为上下文一并携带。
    return session.result(node, context=plane)


def _execute_reference_axis(node: FeaturePlanNode, session: ExecutionSession) -> FeatureResult:
    # 基准轴特征（reference_axis）执行入口：由参数直接定义轴，或由两个基准平面求交线得到轴。
    
    # 1. 尝试直接取参数：若同时给出原点 origin_mm 与方向 direction，则直接构造轴。
    params = node.params.get("axis") or {}
    if params.get("origin_mm") and params.get("direction"):
        axis = AxisSpec.from_mapping(params)
    else:
        # 2. 否则从特征选择器中筛选出已解析的基准平面。
        planes = [session.resolve(selector) for selector in node.selectors if selector.get("kind") == "plane"]
        resolved = [item.record.value for item in planes if item.status == "resolved" and isinstance(item.record.value, PlaneSpec)]
        # 3. 校验：轴需要两个非平行的平面，不足两个则报错。
        if len(resolved) < 2:
            raise ValueError("reference axis requires two uniquely resolved planes")
        # 4. 用两平面法线叉积求交线方向；若方向长度接近 0 说明两平面平行，无法成轴。
        first, second = resolved[0], resolved[1]
        n1, n2 = first.normal, second.normal
        direction = vector_cross(n1, n2)
        squared_length = vector_dot(direction, direction)
        if squared_length <= 1e-18:
            raise ValueError("reference planes are parallel and cannot define an axis")
        # 5. 求交线上的一点：两平面到各自原点的垂距参与线性组合，得到交线上的最近点。
        d1 = vector_dot(n1, first.origin_mm)
        d2 = vector_dot(n2, second.origin_mm)
        point = vector_scale(vector_add(vector_scale(vector_cross(n2, direction), d1), vector_scale(vector_cross(direction, n1), d2)), 1 / squared_length)
        # 6. 由该点与归一化的交线方向组合成基准轴 AxisSpec。
        axis = AxisSpec(origin_mm=point, direction=vector_unit(direction, field_name="reference axis"))
    # 7. 注册为拓扑上下文，并返回结果对象（携带该轴）。
    session.topology.register_context(node.feature_id, axis)
    return session.result(node, context=axis)


def _execute_sphere(node: FeaturePlanNode, session: ExecutionSession) -> FeatureResult:
    # 球体特征（sphere_add）执行入口：按球心与半径生成球体并并入当前主体。
    
    # 1. 解析参数：半径 radius_mm 与球心 center_mm。
    radius = float(node.params.get("radius_mm") or 0.0)
    center = node.params.get("center_mm") or []
    # 2. 校验：半径必须大于 0，球心必须是三维坐标。
    if radius <= 0 or len(center) != 3:
        raise ValueError("sphere_add requires radius_mm and a three-dimensional center_mm")
    # 3. 由适配器创建球体实体。
    solid = session.adapter.sphere(radius, (float(center[0]), float(center[1]), float(center[2])))
    # 4. 球体与当前主体做布尔并（fuse）后登记为新主体，并返回该特征的结果对象。
    session.register_body(node.feature_id, session.adapter.fuse(session.body, solid), replay_node=node)
    return session.result(node)


def _host_plane(resolution: SelectorResolution) -> PlaneSpec:
    if resolution.record is None:
        raise ValueError(resolution.diagnostic.message if resolution.diagnostic else "host face was not resolved")
    geometry = resolution.record.geometry
    return PlaneSpec.from_mapping({
        "origin_mm": geometry["center_mm"],
        "x_dir": [1, 0, 0] if abs(float(geometry["normal"][0])) < 0.9 else [0, 1, 0],
        "normal": geometry["normal"],
    })


def _hole_starts(
    spec: HoleSpec,
    *,
    host_plane: PlaneSpec,
    positions_are_local: bool,
) -> list[Vector3]:
    starts: list[Vector3] = []
    for point in spec.positions_mm:
        if positions_are_local:
            start = vector_add(
                vector_add(
                    vector_add(host_plane.origin_mm, vector_scale(host_plane.x_dir, point[0])),
                    vector_scale(host_plane.y_dir, point[1]),
                ),
                vector_scale(host_plane.normal, point[2]),
            )
        else:
            start = point
        starts.append(start)
    return starts


def _execute_hole(node: FeaturePlanNode, session: ExecutionSession, *, wizard: bool = False) -> FeatureResult:
    # 孔特征（hole）执行入口：在指定宿主面上按孔规格生成切除工具，并从主体上减去。
    
    # 1. 校验：孔是切除操作，必须先有主体。
    if session.body is None:
        raise ValueError("hole feature has no body")
    # 2. 确定宿主面 host_face：
    host_selector = node.params.get("host_face")
    if isinstance(host_selector, dict) and isinstance(host_selector.get("frame"), dict):
        #   若直接带 frame（平面定义），则以该平面为宿主，孔位按局部坐标解释。
        host = PlaneSpec.from_mapping(host_selector["frame"])
        positions_are_local = True
    else:
        #   否则从特征选择器中取 face，解析出宿主平面，孔位按世界坐标解释。
        selectors = list(node.selectors)
        if isinstance(host_selector, dict):
            selectors.append(host_selector)
        selector = next((item for item in selectors if item.get("kind") == "face"), None)
        if selector is None:
            raise ValueError("hole requires host_face selector or frame")
        host = _host_plane(session.resolve(selector))
        positions_are_local = False
    # 3. 解析孔规格 HoleSpec（直径、深度、类型等，wizard 模式提供额外默认值）。
    spec = HoleSpec.from_feature(node.atomic_id, node.params, wizard=wizard)
    # 4. 确定孔轴向：默认沿宿主面法向，但需保证指向主体内部（按主体中心与面原点的相对位置取反）。
    normal = host.normal
    inward = normal if vector_dot(vector_subtract(session.adapter.body_center(session.body), host.origin_mm), normal) >= 0 else vector_scale(normal, -1)
    # 5. 生成孔切除工具：按孔规格、起始位置、内方向及“贯穿到主体底面”的深度构造工具实体。
    tool = session.adapter.hole_tool(
        spec,
        _hole_starts(spec, host_plane=host, positions_are_local=positions_are_local),
        inward,
        session.adapter.body_span(session.body, inward) + 2.0,
    )
    # 6. 从主体上减去工具实体，登记新主体并返回结果。
    session.register_body(node.feature_id, session.adapter.cut(session.body, tool), replay_node=node)
    return session.result(node)


def _selector_edges(node: FeaturePlanNode, session: ExecutionSession, *, tangent_propagation: bool = False) -> list[Any]:
    resolved: list[SelectorResolution] = [session.resolve(selector) for selector in node.selectors]
    failed = next((item for item in resolved if item.status != "resolved"), None)
    if failed:
        raise ValueError(failed.diagnostic.message if failed.diagnostic else "selector resolution failed")
    edges: list[Any] = []
    for item in resolved:
        if item.record.kind == "edge":
            edges.append(item.record.value)
        elif item.record.kind == "face":
            edges.extend(item.record.value.edges())
    if not edges:
        raise ValueError("selectors did not resolve any edges")
    return session.adapter.tangent_edges(session.body, edges) if tangent_propagation else edges


def _execute_fillet(node: FeaturePlanNode, session: ExecutionSession) -> FeatureResult:
    # 圆角特征（fillet）执行入口：对选中边按半径做圆角，平滑尖角与棱边。

    # 1. 校验：圆角作用于已有主体，必须先有主体。
    if session.body is None:
        raise ValueError("fillet has no body")
    # 2. 解析圆角半径并校验必须大于 0。
    radius = float(node.params.get("radius_mm") or 0)
    if radius <= 0:
        raise ValueError("fillet radius_mm must be > 0")
    # 3. 解析目标边（支持 tangent_propagation 相切传播），并执行圆角。
    body = session.adapter.fillet(
        session.body, radius, _selector_edges(node, session, tangent_propagation=bool(node.params.get("tangent_propagation"))),
    )
    # 4. 登记新主体并返回结果。
    session.register_body(node.feature_id, body, replay_node=node)
    return session.result(node)


def _execute_chamfer(node: FeaturePlanNode, session: ExecutionSession) -> FeatureResult:
    # 倒角特征（chamfer）执行入口：对选中边按距离做倒角（可带第二距离形成不对称倒角）。

    # 1. 校验：倒角作用于已有主体，必须先有主体。
    if session.body is None:
        raise ValueError("chamfer has no body")
    # 2. 解析主距离并校验必须大于 0。
    distance = float(node.params.get("distance_mm") or 0)
    if distance <= 0:
        raise ValueError("chamfer distance_mm must be > 0")
    # 3. 解析目标边（支持相切传播），执行倒角；distance_2_mm 提供时产生非对称倒角。
    body = session.adapter.chamfer(
        session.body, distance, node.params.get("distance_2_mm"),
        _selector_edges(node, session, tangent_propagation=bool(node.params.get("tangent_propagation"))),
    )
    # 4. 登记新主体并返回结果。
    session.register_body(node.feature_id, body, replay_node=node)
    return session.result(node)


def _translated_sketch(sketch: dict[str, Any], offset: Vector3) -> dict[str, Any]:
    output = deepcopy(sketch)
    components = offset
    workplane = output.get("workplane") or {}
    origin = workplane.get("origin_mm") or [0, 0, 0]
    workplane["origin_mm"] = [float(origin[index]) + components[index] for index in range(3)]
    output["workplane"] = workplane
    for key in ("contour_edges_mm", "contour_regions_mm"):
        def translate(value: Any) -> None:
            if isinstance(value, dict):
                for point_key in ("start_mm", "end_mm", "center_mm"):
                    if point_key in value:
                        value[point_key] = [float(value[point_key][index]) + components[index] for index in range(3)]
                for child in value.values():
                    translate(child)
            elif isinstance(value, list):
                for child in value:
                    translate(child)
        translate(output.get(key))
    return output


def _translated_node(node: FeaturePlanNode, instance_id: str, offset: Vector3) -> FeaturePlanNode:
    params = deepcopy(node.params)
    components = offset
    if isinstance(params.get("plane"), dict) and params["plane"].get("origin_mm"):
        params["plane"]["origin_mm"] = [float(params["plane"]["origin_mm"][index]) + components[index] for index in range(3)]
    host = params.get("host_face")
    host_frame = host.get("frame") if isinstance(host, dict) else None
    positions_are_local = isinstance(host_frame, dict) and all(
        host_frame.get(key) is not None for key in ("origin_mm", "x_dir", "normal")
    )
    if positions_are_local and host_frame.get("origin_mm"):
        host_frame["origin_mm"] = [float(host_frame["origin_mm"][index]) + components[index] for index in range(3)]
    if not positions_are_local:
        for position in params.get("positions") or []:
            if position.get("mm"):
                position["mm"] = [float(position["mm"][index]) + components[index] for index in range(3)]
    axis = params.get("axis") or {}
    if axis.get("origin_mm"):
        axis["origin_mm"] = [float(axis["origin_mm"][index]) + components[index] for index in range(3)]
    return FeaturePlanNode(instance_id, node.atomic_id, node.name, (), params, node.selectors, node.sketch_id, node.declared_status, node.source_feature)


def _execute_linear_pattern(node: FeaturePlanNode, session: ExecutionSession, execute: Callable[[FeaturePlanNode, ExecutionSession, dict[str, Any] | None], FeatureResult]) -> FeatureResult:
    # 线性阵列特征（pattern）执行入口：沿两个方向按数量与间距重放源特征形成阵列。
    
    # 1. 取源特征的 replay 定义（源特征按 feature_id 在会话中登记，供本阵列重放）。
    params = node.params
    sources = session.replay_sources(params.get("source_feature_ids") or [])
    if not sources:
        raise ValueError("pattern source features have no replay definitions")
    # 2. 解析两个方向的实例数量。
    count_1 = int(params.get("pattern_count_1") or 1)
    count_2 = int(params.get("pattern_count_2") or 1)
    # 3. 解析两个方向的步长向量（方向单位向量 × 间距），作为阵列位移基准。
    direction_1 = vector_scale(vector_unit(tuple(float(value) for value in (params.get("direction_1") or [1, 0, 0])), field_name="pattern direction_1"), float(params.get("spacing_1_mm") or 0))
    direction_2 = vector_scale(vector_unit(tuple(float(value) for value in (params.get("direction_2") or [0, 1, 0])), field_name="pattern direction_2"), float(params.get("spacing_2_mm") or 0))
    # 4. 双重循环生成每个阵列实例（跳过原点 0,0 处，那里是源特征本身）。
    for first in range(count_1):
        for second in range(count_2):
            if first == 0 and second == 0:
                continue
            #   计算当前实例相对源特征的偏移向量。
            offset = vector_add(vector_scale(direction_1, first), vector_scale(direction_2, second))
            for source in sources:
                #   逐个源特征克隆并按偏移平移后重放执行（草图也同步平移）。
                dependency = pattern_transform_blocker(source)
                if dependency:
                    raise ValueError(f"pattern source uses an unsupported {dependency}")
                cloned = _translated_node(source, f"{node.feature_id}.p{first}_{second}.{source.feature_id}", offset)
                sketch = session.sketches.get(str(source.sketch_id))
                execute(cloned, session, _translated_sketch(sketch, offset) if sketch else None)
    # 5. 记录本阵列的 replay 定义：后续阵列若选中本阵列，按定义递归重放，
    #    而非复制当前主体做近似。
    # A later pattern may select this pattern feature.  The definition is
    # replayed recursively, never approximated by copying the current body.
    session.replay_definitions[node.feature_id] = node
    return session.result(node)


def _reflect_point(point: list[float] | tuple[float, float, float], plane: PlaneSpec, *, vector: bool = False) -> list[float]:
    value = tuple(float(component) for component in point)
    offset = value if vector else vector_subtract(value, plane.origin_mm)
    mirrored = vector_subtract(value, vector_scale(plane.normal, 2 * vector_dot(offset, plane.normal)))
    return list(mirrored)


def _mirrored_sketch(sketch: dict[str, Any], plane: PlaneSpec) -> dict[str, Any]:
    output = deepcopy(sketch)
    workplane = output.get("workplane") or {}
    if workplane.get("origin_mm"):
        workplane["origin_mm"] = _reflect_point(workplane["origin_mm"], plane)
    for key in ("x_dir", "y_dir", "normal"):
        if workplane.get(key):
            workplane[key] = _reflect_point(workplane[key], plane, vector=True)
    output["workplane"] = workplane

    # A reflection reverses handedness.  ``PlaneSpec`` reconstructs its local
    # y direction as normal x x, so keeping the reflected normal means that
    # local y is the inverse of the reflected source y.  Profiles represented
    # as local circles (rather than already-transformed contour edges) must
    # therefore invert v to remain at their actual reflected world position.
    def mirror_local_coordinates(value: Any) -> None:
        if isinstance(value, dict):
            for point_key in ("center", "start", "end"):
                point = value.get(point_key)
                if isinstance(point, list) and len(point) == 2:
                    value[point_key] = [float(point[0]), -float(point[1])]
            for child in value.values():
                mirror_local_coordinates(child)
        elif isinstance(value, list):
            for child in value:
                mirror_local_coordinates(child)

    mirror_local_coordinates(output.get("entities"))
    # This is not consumed after sketch resolution, but retaining the same
    # local semantics makes an overridden sketch safe to inspect or replay.
    mirror_local_coordinates(output.get("profile"))

    def mirror(value: Any) -> None:
        if isinstance(value, dict):
            for point_key in ("start_mm", "end_mm", "center_mm"):
                if point_key in value:
                    value[point_key] = _reflect_point(value[point_key], plane)
            if value.get("normal"):
                value["normal"] = _reflect_point(value["normal"], plane, vector=True)
            for child in value.values():
                mirror(child)
        elif isinstance(value, list):
            for child in value:
                mirror(child)
    mirror(output.get("contour_edges_mm"))
    mirror(output.get("contour_regions_mm"))
    return output


def _mirrored_node(node: FeaturePlanNode, instance_id: str, plane: PlaneSpec) -> FeaturePlanNode:
    params = deepcopy(node.params)
    if isinstance(params.get("plane"), dict):
        for key in ("origin_mm", "x_dir", "y_dir", "normal"):
            if params["plane"].get(key):
                params["plane"][key] = _reflect_point(params["plane"][key], plane, vector=key != "origin_mm")
    host = params.get("host_face")
    host_frame = host.get("frame") if isinstance(host, dict) else None
    positions_are_local = isinstance(host_frame, dict) and all(
        host_frame.get(key) is not None for key in ("origin_mm", "x_dir", "normal")
    )
    if positions_are_local:
        for key in ("origin_mm", "x_dir", "y_dir", "normal"):
            if host_frame.get(key):
                host_frame[key] = _reflect_point(host_frame[key], plane, vector=key != "origin_mm")
        # See _mirrored_sketch: the canonical reflected plane reverses local
        # y, so local hole coordinates must do the same.
        for position in params.get("positions") or []:
            point = position.get("mm")
            if isinstance(point, list) and len(point) == 3:
                position["mm"] = [float(point[0]), -float(point[1]), float(point[2])]
    else:
        for position in params.get("positions") or []:
            if position.get("mm"):
                position["mm"] = _reflect_point(position["mm"], plane)
    axis = params.get("axis") or {}
    if axis.get("origin_mm"):
        axis["origin_mm"] = _reflect_point(axis["origin_mm"], plane)
    if axis.get("direction"):
        axis["direction"] = _reflect_point(axis["direction"], plane, vector=True)
    return FeaturePlanNode(instance_id, node.atomic_id, node.name, (), params, node.selectors, node.sketch_id, node.declared_status, node.source_feature)


def _execute_mirror_pattern(node: FeaturePlanNode, session: ExecutionSession) -> FeatureResult:
    mirror = node.params.get("mirror_plane") or {}
    resolution = session.resolve(mirror)
    if resolution.status != "resolved" or not isinstance(resolution.record.value, PlaneSpec):
        raise ValueError(resolution.diagnostic.message if resolution.diagnostic else "mirror plane was not resolved")
    sources = session.replay_sources(node.params.get("source_feature_ids") or [])
    if not sources:
        raise ValueError("mirror pattern source features have no replay definitions")
    for source in sources:
        dependency = pattern_transform_blocker(source)
        if dependency:
            raise ValueError(f"mirror pattern source uses an unsupported {dependency}")
        cloned = _mirrored_node(source, f"{node.feature_id}.m.{source.feature_id}", resolution.record.value)
        sketch = session.sketches.get(str(source.sketch_id))
        _execute_node(cloned, session, _mirrored_sketch(sketch, resolution.record.value) if sketch else None)
    session.replay_definitions[node.feature_id] = node
    return session.result(node)


def _execute_node(node: FeaturePlanNode, session: ExecutionSession, sketch_override: dict[str, Any] | None = None) -> FeatureResult:
    executor = EXECUTORS.get(node.atomic_id)
    if executor is None:
        raise ValueError(f"No executor registered for {node.atomic_id!r}")
    previous_feature_id = session.active_feature_id
    session.active_feature_id = node.feature_id
    try:
        return executor(node, session, sketch_override)
    finally:
        session.active_feature_id = previous_feature_id


ExecutorFunction = Callable[[FeaturePlanNode, ExecutionSession, dict[str, Any] | None], FeatureResult]


def _primary_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    return _shape_from_primary(node, session, sketch=sketch)


def _reference_plane_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_reference_plane(node, session)


def _reference_axis_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_reference_axis(node, session)


def _sphere_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_sphere(node, session)


def _hole_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_hole(node, session)


def _hole_wizard_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_hole(node, session, wizard=True)


def _fillet_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_fillet(node, session)


def _chamfer_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_chamfer(node, session)


def _linear_pattern_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_linear_pattern(node, session, _execute_node)


def _mirror_pattern_executor(node: FeaturePlanNode, session: ExecutionSession, sketch: dict[str, Any] | None) -> FeatureResult:
    del sketch
    return _execute_mirror_pattern(node, session)


EXECUTORS: dict[str, ExecutorFunction] = {
    "reference_plane": _reference_plane_executor,
    "reference_axis": _reference_axis_executor,
    "sphere_add": _sphere_executor,
    "extrude_add_blind": _primary_executor,
    "extrude_add_two_sided": _primary_executor,
    "extrude_cut_blind": _primary_executor,
    "revolve_add": _primary_executor,
    "revolve_cut": _primary_executor,
    "hole_blind": _hole_executor,
    "hole_countersink": _hole_executor,
    "hole_counterbore": _hole_executor,
    "hole_wizard": _hole_wizard_executor,
    "fillet": _fillet_executor,
    "chamfer": _chamfer_executor,
    "pattern_linear": _linear_pattern_executor,
    "pattern_mirror": _mirror_pattern_executor,
}


def analyze_cdsl(cdsl: dict[str, Any]):
    """Resolve profiles and return the current runtime capability analysis."""
    sketch_errors: dict[str, str] = {}
    resolved = resolve_required_sketches(
        deepcopy(cdsl), sketch_ids_required_by_contract(cdsl), errors=sketch_errors,
    )
    analyzer = CapabilityAnalyzer(atomic_ids=EXECUTORS, profile_types=CORE_SHAPE_GENERATORS)
    return analyzer.analyze(resolved, sketch_errors=sketch_errors)


def rebuild_cdsl(cdsl: dict[str, Any], out_step: Path, *, strict: bool = True) -> dict[str, Any]:
    """Rebuild CDSL through session-scoped atomic executors only."""
    sketch_errors: dict[str, str] = {}
    resolved = resolve_required_sketches(
        deepcopy(cdsl), sketch_ids_required_by_contract(cdsl), errors=sketch_errors,
    )
    analysis = CapabilityAnalyzer(atomic_ids=EXECUTORS, profile_types=CORE_SHAPE_GENERATORS).analyze(
        resolved, sketch_errors=sketch_errors,
    )
    if strict and not analysis.runtime_eligible:
        first = next((result for result in analysis.feature_results if not result.executable), None)
        if first is None:
            raise ValueError(analysis.document_blockers[0].code)
        if any(blocker.code == "unknown_atomic" for blocker in first.blockers):
            raise ValueError(f"unsupported atomic_id: {first.atomic_id}")
        detail = "; ".join(blocker.code for blocker in first.blockers)
        raise ValueError(f"Feature {first.feature_id} is not runtime eligible: {detail}")
    session = ExecutionSession(
        sketches={str(sketch.get("id")): sketch for sketch in (resolved.get("geometry") or {}).get("sketches") or []},
        nodes={node.feature_id: node for node in analysis.plan},
    )
    diagnostics: list[RuntimeDiagnostic] = []
    for node, preflight in zip(analysis.plan, analysis.feature_results):
        if not preflight.executable:
            diagnostics.extend(preflight.blockers)
            if strict:
                break
            continue
        try:
            _execute_node(node, session)
        except Exception as error:
            failed_resolution = next(
                (item for item in reversed(session.selector_resolutions) if item["status"] != "resolved"), None,
            )
            diagnostic = (
                RuntimeDiagnostic(error.code, str(error), feature_id=node.feature_id, detail=error.detail)
                if isinstance(error, FeatureExecutionError)
                else
                RuntimeDiagnostic(
                    failed_resolution["diagnostic"]["code"], failed_resolution["diagnostic"]["message"],
                    feature_id=node.feature_id, detail=failed_resolution["diagnostic"].get("detail") or {},
                )
                if failed_resolution and failed_resolution.get("diagnostic")
                else RuntimeDiagnostic("execution_failed", str(error), feature_id=node.feature_id)
            )
            diagnostics.append(diagnostic)
            if strict:
                raise RuntimeExecutionError(diagnostic, list(session.selector_resolutions)) from error
    if session.body is None:
        raise ValueError("CDSL execution produced no body")
    out_step.parent.mkdir(parents=True, exist_ok=True)
    session.adapter.export(session.body, str(out_step))
    geometry = session.adapter.body_geometry(session.body)
    bbox = geometry["bbox_mm"]
    return {
        "engine": "cdsl_session_runtime",
        "out_step": str(out_step),
        "volume_mm3": float(geometry["volume_mm3"]),
        "bbox_mm": {"min": bbox[:3], "max": bbox[3:]},
        "feature_results": [result.as_dict() for result in session.results.values()],
        "runtime_diagnostics": [diagnostic.as_dict() for diagnostic in diagnostics],
        "topology_records": [record.public_dict() for record in session.topology.records()],
        "selector_resolution": session.selector_resolutions,
    }