Pinscope open-source core

Agentic schematic validation: datasheet extraction via Claude Console Skills, netlist/BOM design graph, per-IC direct datasheet review with page citations, capacitor derating, Next.js report UI. Extracted from the Pinscope cloud codebase. Auth and billing live in the private gateway repo behind stable seams (billing_hook.py, adapter files listed in CLAUDE.md).
2026-07-16 21:29:45 -07:00
commit 6672d2be57
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+"""Build a BOM summary table from the design graph. No AI — pure collation."""
+
+from __future__ import annotations
+
+from backend.pinscopex.models import ComponentType, DesignGraph
+from backend.pinscopex.utils import natural_sort_key
+
+
+def build_bom_summary(
+    graph: DesignGraph,
+    datasheet_mpns: set[str] | None = None,
+    descriptions: dict[str, str] | None = None,
+) -> list[dict]:
+    """Group components by MPN and collate BOM summary rows.
+
+    ``descriptions`` is an optional ``{mpn: description}`` map (e.g. from
+    extracted ``package_info.description``). When supplied, IC rows get a
+    ``description`` field — used by the frontend to show what the chip does
+    in place of the empty Specs cell.
+
+    Returns a list of dicts, each with:
+      mpn, designators, value, category, specs, description
+    """
+    # Group components by MPN (or by value+type if no MPN)
+    by_key: dict[str, list] = {}
+    for comp in graph.components.values():
+        key = comp.mpn if comp.mpn else f"__no_mpn__{comp.value}__{comp.component_type}"
+        by_key.setdefault(key, []).append(comp)
+
+    rows = []
+    for comps in by_key.values():
+        first = comps[0]
+        designators = sorted(
+            [c.reference for c in comps], key=natural_sort_key
+        )
+
+        # Extract display-friendly specs
+        specs_dict = None
+        if first.specs:
+            if hasattr(first.specs, "values"):
+                # SimpleComponentSpecs — flatten the values dict
+                raw = {k: v for k, v in first.specs.values.items() if v is not None}
+            else:
+                raw = first.specs.model_dump(exclude={"specs_type"})
+                # Drop None values and internal numeric fields
+                raw = {
+                    k: v for k, v in raw.items()
+                    if v is not None and k not in ("value_ohms", "value_farads", "value_henries")
+                }
+            specs_dict = raw if raw else None
+
+        has_ds = bool(
+            first.mpn
+            and datasheet_mpns is not None
+            and first.mpn in datasheet_mpns
+        )
+
+        description = None
+        if (
+            descriptions is not None
+            and first.mpn
+            and first.component_type == ComponentType.IC
+        ):
+            description = descriptions.get(first.mpn)
+
+        rows.append({
+            "mpn": first.mpn,
+            "designators": designators,
+            "value": first.value,
+            "category": first.component_subtype,
+            "specs": specs_dict,
+            "description": description,
+            "has_datasheet": has_ds,
+        })
+
+    # Sort: ICs first, then passives, then others; within each by category then MPN
+    def sort_key(row: dict) -> tuple:
+        cat = row["category"] or ""
+        if cat.startswith("ic"):
+            group = 0
+        elif cat.startswith("passive"):
+            group = 1
+        else:
+            group = 2
+        return (group, cat, row["mpn"] or "")
+
+    rows.sort(key=sort_key)
+    return rows