115 lines
4.1 KiB
Python
115 lines
4.1 KiB
Python
"""Assemble the scope-centric fit guide.
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Builds the data for the top-level ``/scopes`` page: one row per augmented part
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of part type "Scope", one column per non-Scope part type, where each cell lists
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the parts of that type that fit the row's scope.
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"""
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.crud import augmented_part as augmented_part_crud
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from app.crud import fit as fit_crud
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from app.crud import part_type as part_type_crud
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from app.crud import scope_info as scope_info_crud
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from app.models.fit import FitLabel
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SCOPE_TYPE_NAME = "Scope"
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# "exact" outranks "possible" when the same part fits a scope via several fits.
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_LABEL_RANK = {FitLabel.EXACT.value: 2, FitLabel.POSSIBLE.value: 1}
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async def build(db: AsyncSession) -> dict:
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"""Return the context for ``scopes.html``.
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Shape::
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{
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"column_types": [PartType, ...], # non-Scope, ordered by name
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"rows": [
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{
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"scope": AugmentedPart,
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"info": ScopeInfo | None,
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"cells": {part_type_id: [{"part": AugmentedPart, "label": str}]},
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},
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...,
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],
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}
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"""
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part_types = await part_type_crud.list_all(db, limit=1000)
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scope_type = next(
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(pt for pt in part_types if pt.name == SCOPE_TYPE_NAME), None
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)
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column_types = [
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pt for pt in part_types if scope_type is None or pt.id != scope_type.id
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]
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if scope_type is None:
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return {"column_types": column_types, "rows": []}
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scopes = await augmented_part_crud.list_by_part_type(db, scope_type.id)
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scope_ids = {s.id for s in scopes}
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if not scope_ids:
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return {"column_types": column_types, "rows": []}
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fits = await fit_crud.list_for_parts(
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db, list(scope_ids), exclude_label=FitLabel.NONE
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)
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# Resolve the "other" (non-scope) part on each fit in a single batched query.
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other_ids: set[int] = set()
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for fit in fits:
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scope_id, other_id = _scope_and_other(fit, scope_ids)
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if scope_id is not None and other_id not in scope_ids:
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other_ids.add(other_id)
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other_parts = {
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p.id: p for p in await augmented_part_crud.get_many(db, list(other_ids))
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}
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infos = {
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info.augmented_part_id: info
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for info in await scope_info_crud.list_by_augmented_parts(db, list(scope_ids))
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}
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# cell_map[scope_id][type_id][other_part_id] -> {"part", "label"}, dedup'd so a
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# part appears once per cell, keeping its strongest fit label.
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cell_map: dict[int, dict[int, dict[int, dict]]] = {
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sid: {} for sid in scope_ids
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}
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for fit in fits:
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scope_id, other_id = _scope_and_other(fit, scope_ids)
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if scope_id is None:
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continue
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other = other_parts.get(other_id)
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if other is None or other.part_type_id == scope_type.id:
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continue # scope-to-scope fits have no column
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by_type = cell_map[scope_id].setdefault(other.part_type_id, {})
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existing = by_type.get(other.id)
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label = fit.label.value
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if existing is None or _LABEL_RANK[label] > _LABEL_RANK[existing["label"]]:
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by_type[other.id] = {"part": other, "label": label}
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rows = []
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for scope in scopes:
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cells = {
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type_id: sorted(
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entries.values(), key=lambda e: e["part"].description.lower()
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)
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for type_id, entries in cell_map[scope.id].items()
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}
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rows.append(
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{"scope": scope, "info": infos.get(scope.id), "cells": cells}
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)
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return {"column_types": column_types, "rows": rows}
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def _scope_and_other(fit, scope_ids: set[int]) -> tuple[int | None, int]:
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"""Return (scope_part_id, other_part_id) for a fit, or (None, _) if neither
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side is a scope. When both sides are scopes, side A is treated as the scope."""
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if fit.augmented_part_a_id in scope_ids:
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return fit.augmented_part_a_id, fit.augmented_part_b_id
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if fit.augmented_part_b_id in scope_ids:
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return fit.augmented_part_b_id, fit.augmented_part_a_id
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return None, fit.augmented_part_b_id
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