Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FKFStjEFzpGyLq5bMpWxTd
245 lines
7.8 KiB
Python
245 lines
7.8 KiB
Python
"""Pure, deterministic drawing-requirement preflight validation."""
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from __future__ import annotations
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import hashlib
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import json
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import math
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import re
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from dataclasses import dataclass, field
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from numbers import Real
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from typing import Any
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PID_INTENT_RE = re.compile(
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r"\b(p&id|pid|piping and instrumentation|process flow|instrument)\b", re.IGNORECASE
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)
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def intent_reads_as_pid(intent: str) -> bool:
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return bool(PID_INTENT_RE.search(str(intent or "")))
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def pid_plan_warnings(intent: str, layer_set_id: str) -> list[str]:
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if intent_reads_as_pid(intent) and str(layer_set_id).strip().lower() != "pid":
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return [
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f"intent reads as a P&ID but the layer set is '{layer_set_id}'; pass layer_set_id='pid'"
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]
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return []
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@dataclass(frozen=True)
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class PreflightQuestion:
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code: str
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field: str
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question: str
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choices: list[str] = field(default_factory=list)
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def to_dict(self) -> dict:
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return {
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"code": self.code,
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"field": self.field,
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"question": self.question,
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"choices": list(self.choices),
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}
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@dataclass(frozen=True)
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class PreflightConflict:
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code: str
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field: str
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values: list[Any]
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message: str
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def to_dict(self) -> dict:
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return {
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"code": self.code,
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"field": self.field,
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"values": list(self.values),
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"message": self.message,
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}
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@dataclass
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class PreflightResult:
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ready: bool
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normalized_spec: dict
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questions: list[PreflightQuestion]
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conflicts: list[PreflightConflict]
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assumptions: list[dict]
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spec_hash: str
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def to_dict(self) -> dict:
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return {
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"ready": self.ready,
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"normalized_spec": self.normalized_spec,
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"questions": [item.to_dict() for item in self.questions],
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"conflicts": [item.to_dict() for item in self.conflicts],
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"assumptions": list(self.assumptions),
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"spec_hash": self.spec_hash,
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}
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def _normalize(value: Any) -> Any:
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if isinstance(value, dict):
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return {str(key).strip(): _normalize(item) for key, item in sorted(value.items())}
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if isinstance(value, list):
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return [_normalize(item) for item in value]
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if isinstance(value, str):
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return value.strip()
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if isinstance(value, Real) and not isinstance(value, bool):
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return float(value)
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return value
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def _spec_hash(spec: dict) -> str:
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encoded = json.dumps(spec, ensure_ascii=False, sort_keys=True, separators=(",", ":"))
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return "sha256:" + hashlib.sha256(encoded.encode("utf-8")).hexdigest()
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def preflight_drawing(
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intent: str,
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requirements: dict | None = None,
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sheet_size: str = "A3",
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scale: float = 1.0,
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layer_set_id: str = "mech",
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view_count: int = 1,
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dim_style: str = "chain",
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*,
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allow_assumptions: bool = False,
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) -> PreflightResult:
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"""Normalize a drawing request and surface missing or conflicting facts."""
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req = _normalize(dict(requirements or {}))
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assumptions: list[dict] = []
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if allow_assumptions and not req.get("units"):
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req["units"] = "mm"
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assumptions.append({"field": "units", "value": "mm", "reason": "default"})
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if allow_assumptions and not req.get("tolerance_policy"):
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req["tolerance_policy"] = "general"
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assumptions.append({"field": "tolerance_policy", "value": "general", "reason": "default"})
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if isinstance(req.get("units"), str):
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req["units"] = req["units"].lower()
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if isinstance(req.get("part_type"), str):
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req["part_type"] = req["part_type"].lower()
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questions: list[PreflightQuestion] = []
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required = (
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("units", "MISSING_UNITS", "What drawing units should be used?", ["mm", "inch"]),
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(
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"part_type",
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"MISSING_PART_TYPE",
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"What kind of part or drawing is being produced?",
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[],
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),
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("dimensions", "MISSING_DIMENSIONS", "What are the main production dimensions?", []),
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(
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"tolerance_policy",
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"MISSING_TOLERANCE_POLICY",
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"Which tolerance policy should apply?",
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["ISO 2768-m", "explicit", "none"],
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),
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)
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for field_name, code, question, choices in required:
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value = req.get(field_name)
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if value is None or value == "" or value == {} or value == []:
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questions.append(PreflightQuestion(code, field_name, question, choices))
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conflicts: list[PreflightConflict] = []
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seen_constraints: dict[str, Any] = {}
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for constraint in req.get("constraints", []) or []:
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if not isinstance(constraint, dict):
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continue
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field_name = str(constraint.get("field", "")).strip()
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if not field_name or "value" not in constraint:
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continue
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value = _normalize(constraint["value"])
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if field_name in seen_constraints and seen_constraints[field_name] != value:
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conflicts.append(
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PreflightConflict(
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"CONFLICTING_REQUIREMENT",
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field_name,
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[seen_constraints[field_name], value],
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f"Conflicting values were supplied for {field_name}.",
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)
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)
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else:
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seen_constraints[field_name] = value
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normalized_sheet = str(sheet_size).strip().upper()
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normalized_layer_set = str(layer_set_id).strip().lower()
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normalized_dim_style = str(dim_style).strip().lower()
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try:
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normalized_scale = float(scale)
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except (TypeError, ValueError):
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normalized_scale = float("nan")
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try:
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normalized_view_count = int(view_count)
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except (TypeError, ValueError):
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normalized_view_count = 0
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parameter_rules = (
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(
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normalized_sheet in {"A4", "A3", "A2", "A1", "A0"},
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"INVALID_SHEET_SIZE",
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"sheet_size",
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sheet_size,
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"sheet_size must be one of A4, A3, A2, A1, A0.",
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),
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(
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math.isfinite(normalized_scale) and normalized_scale > 0,
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"INVALID_SCALE",
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"scale",
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scale,
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"scale must be a finite number greater than zero.",
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),
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(
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1 <= normalized_view_count <= 20,
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"INVALID_VIEW_COUNT",
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"view_count",
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view_count,
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"view_count must be between 1 and 20.",
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),
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(
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normalized_dim_style in {"chain", "baseline", "ordinate", "mixed"},
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"INVALID_DIM_STYLE",
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"dim_style",
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dim_style,
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"dim_style must be chain, baseline, ordinate, or mixed.",
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),
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(
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normalized_layer_set in {"iso13567", "mech", "pid"},
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"INVALID_LAYER_SET",
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"layer_set_id",
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layer_set_id,
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"layer_set_id must be iso13567, mech, or pid.",
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),
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)
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for valid, code, field_name, value, message in parameter_rules:
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if not valid:
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conflicts.append(PreflightConflict(code, field_name, [value], message))
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for message in pid_plan_warnings(intent, normalized_layer_set):
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conflicts.append(
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PreflightConflict(
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"LAYER_SET_INTENT_MISMATCH", "layer_set_id", [layer_set_id, "pid"], message
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)
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)
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normalized_spec = {
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"intent": str(intent).strip(),
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"requirements": req,
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"sheet_size": normalized_sheet,
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"scale": normalized_scale if math.isfinite(normalized_scale) else str(scale).strip(),
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"layer_set_id": normalized_layer_set,
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"view_count": normalized_view_count,
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"dim_style": normalized_dim_style,
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}
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return PreflightResult(
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ready=not questions and not conflicts,
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normalized_spec=normalized_spec,
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questions=questions,
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conflicts=conflicts,
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assumptions=assumptions,
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spec_hash=_spec_hash(normalized_spec),
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)
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