64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
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from __future__ import annotations
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from typing import Any
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from app.algorithem.employee_behavior_profile import build_review_suggestions
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from app.models.employee_behavior_profile import EmployeeBehaviorProfileSnapshot
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def build_profile_payloads(
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rows: list[EmployeeBehaviorProfileSnapshot],
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) -> list[dict[str, Any]]:
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return [
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{
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"profile_type": row.profile_type,
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"profile_label": row.profile_type,
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"score": row.profile_score,
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"level": row.profile_level,
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"metrics": row.metrics_json or {},
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"top_contributors": row.basis_codes_json or [],
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}
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for row in sorted(rows, key=lambda item: item.profile_type)
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]
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def build_latest_review_suggestions(
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*,
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rows: list[EmployeeBehaviorProfileSnapshot],
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expense_score: int,
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process_score: int,
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) -> list[dict[str, Any]]:
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expense_row = next((row for row in rows if row.profile_type == "expense"), None)
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metrics = expense_row.metrics_json if expense_row is not None else {}
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formula_suggestions = build_review_suggestions(
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expense_profile_score=expense_score,
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process_quality_score=process_score,
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requested_days=metrics.get("requested_days"),
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peer_days_p75=metrics.get("peer_days_p75"),
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peer_unit_amount_p75=metrics.get("peer_unit_amount_p75"),
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)
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merged = [*formula_suggestions, *_merge_review_suggestions(rows)]
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seen: set[str] = set()
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unique: list[dict[str, Any]] = []
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for item in merged:
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key = str(item.get("type") or item.get("message") or "").strip()
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if not key or key in seen:
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continue
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seen.add(key)
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unique.append(item)
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return unique[:5]
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def _merge_review_suggestions(
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rows: list[EmployeeBehaviorProfileSnapshot],
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) -> list[dict[str, Any]]:
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merged: list[dict[str, Any]] = []
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seen: set[str] = set()
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for row in rows:
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for suggestion in (row.metrics_json or {}).get("review_suggestions") or []:
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key = str(suggestion.get("type") or suggestion.get("message") or "")
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if key and key not in seen:
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seen.add(key)
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merged.append(suggestion)
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return merged[:5]
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