nathan
479df6bd8a
- Move Identity/, Workday/, Intune/ to archive/ (superseded by nexus-mcp shards) - Move 'Local Setup.md' to archive/ (superseded by nexus-mcp/Local-Setup.md) - Add archive/README.md explaining migration and preserved content - Clean repository structure: only nexus-mcp, documentation, and .github remain active All legacy functionality migrated to nexus-mcp sharded architecture. Archived folders preserved for reference and historical context. Refs: SESSION_SNAPSHOT_2026-04-13.md
298 lines
9.9 KiB
Python
298 lines
9.9 KiB
Python
from typing import Any
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# Mock dataset with reporting-line relationships for manager checks (WIS-017 prep)
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MOCK_WORKERS: dict[str, dict[str, Any]] = {
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"EMP001": {
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"name": "Nathan",
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"legal_name": "Nathaniel Cole",
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"preferred_name": "Nathan",
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"ad_display_name": "Nathan Cole",
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"status": "Active",
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"ad_enabled": True,
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"dept": "IT",
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"workday_cost_center": "CC100-IT",
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"workday_title": "Systems Engineer",
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"ad_title": "Systems Engineer",
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"ad_department": "IT",
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"email": "nathan@example.com",
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"manager_id": "EMP010",
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},
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"EMP002": {
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"name": "Terminated User",
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"legal_name": "Taylor Brooks",
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"preferred_name": "Taylor",
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"ad_display_name": "Taylor Brooks",
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"status": "Terminated",
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"ad_enabled": True,
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"dept": "Sales",
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"workday_cost_center": "CC200-SALES",
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"workday_title": "Account Executive",
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"ad_title": "Account Executive",
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"ad_department": "Sales",
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"email": "user2@example.com",
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"manager_id": "EMP020",
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},
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"EMP003": {
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"name": "Alicia",
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"legal_name": "Alicia Gomez",
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"preferred_name": "Alicia",
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"ad_display_name": "Alicia Gomez",
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"status": "Active",
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"ad_enabled": True,
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"dept": "IT",
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"workday_cost_center": "CC100-IT",
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"workday_title": "Senior Systems Analyst",
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"ad_title": "Systems Analyst",
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"ad_department": "IT",
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"email": "alicia@example.com",
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"manager_id": "EMP010",
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},
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"EMP004": {
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"name": "Jordan",
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"legal_name": "Jordan Lee",
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"preferred_name": "Jordan",
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"ad_display_name": "Jordan Lee",
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"status": "Leave",
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"ad_enabled": True,
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"dept": "Finance",
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"workday_cost_center": "CC300-FIN",
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"workday_title": "Finance Analyst",
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"ad_title": "Finance Analyst",
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"ad_department": "Accounting",
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"email": "jordan@example.com",
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"manager_id": "EMP030",
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},
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"EMP010": {
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"name": "Priya Manager",
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"legal_name": "Priya Narayanan",
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"preferred_name": "Priya",
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"ad_display_name": "Priya Manager",
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"status": "Active",
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"ad_enabled": True,
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"dept": "IT",
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"workday_cost_center": "CC110-IT-MGMT",
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"workday_title": "IT Manager",
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"ad_title": "IT Manager",
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"ad_department": "IT",
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"email": "priya@example.com",
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"manager_id": "EMP100",
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},
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"EMP020": {
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"name": "Ramon Director",
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"legal_name": "Ramon Alvarez",
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"preferred_name": "Ramon",
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"ad_display_name": "Ramon Director",
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"status": "Active",
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"ad_enabled": True,
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"dept": "Sales",
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"workday_cost_center": "CC210-SALES-MGMT",
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"workday_title": "Sales Director",
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"ad_title": "Sales Director",
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"ad_department": "Sales",
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"email": "ramon@example.com",
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"manager_id": "EMP100",
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},
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"EMP030": {
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"name": "Morgan Lead",
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"legal_name": "Morgan Patel",
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"preferred_name": "Morgan",
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"ad_display_name": "Morgan Patel",
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"status": "Active",
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"ad_enabled": True,
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"dept": "Finance",
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"workday_cost_center": "CC310-FIN-MGMT",
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"workday_title": "Finance Lead",
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"ad_title": "Finance Lead",
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"ad_department": "Finance",
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"email": "morgan@example.com",
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"manager_id": "EMP100",
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},
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"EMP100": {
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"name": "Chief Exec",
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"legal_name": "Evelyn Carter",
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"preferred_name": "Evelyn",
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"ad_display_name": "Evelyn Carter",
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"status": "Active",
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"ad_enabled": True,
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"dept": "Executive",
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"workday_cost_center": "CC999-EXEC",
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"workday_title": "Chief Executive Officer",
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"ad_title": "Chief Executive Officer",
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"ad_department": "Executive",
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"email": "ceo@example.com",
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"manager_id": "",
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},
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# Intentional unresolved manager reference for mismatch test scenarios
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"EMP777": {
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"name": "Mismatch Case",
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"legal_name": "Alexandra Rivers",
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"preferred_name": "Alex",
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"ad_display_name": "Jordan Rivers",
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"status": "Active",
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"ad_enabled": True,
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"dept": "Operations",
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"workday_cost_center": "CC400-OPS",
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"workday_title": "Operations Specialist",
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"ad_title": "Operations Specialist",
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"ad_department": "Operations",
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"email": "mismatch@example.com",
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"manager_id": "EMP999",
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},
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}
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def scan_status_reconciliation_mismatches() -> dict[str, Any]:
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"""Detect workers terminated in Workday but still enabled in AD."""
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mismatches: list[dict[str, Any]] = []
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total_scanned = 0
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for employee_id, details in MOCK_WORKERS.items():
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total_scanned += 1
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workday_status = details.get("status")
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ad_enabled = bool(details.get("ad_enabled", False))
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if workday_status == "Terminated" and ad_enabled:
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mismatches.append(
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{
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"employee_id": employee_id,
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"employee_name": details["name"],
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"workday_status": workday_status,
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"ad_enabled": ad_enabled,
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"mismatch_type": "terminated_but_enabled",
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"severity": "high",
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}
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)
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return {
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"scan_summary": {
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"total_records_checked": total_scanned,
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"mismatches_found": len(mismatches),
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"status": "action_required" if mismatches else "clean",
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},
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"mismatches": mismatches,
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}
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def scan_job_title_mismatches() -> dict[str, Any]:
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"""Detect workers whose Workday title differs from their AD title."""
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mismatches: list[dict[str, Any]] = []
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total_scanned = 0
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for employee_id, details in MOCK_WORKERS.items():
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total_scanned += 1
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workday_title = details.get("workday_title", "")
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ad_title = details.get("ad_title", "")
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if workday_title and ad_title and workday_title != ad_title:
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mismatches.append(
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{
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"employee_id": employee_id,
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"employee_name": details["name"],
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"workday_title": workday_title,
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"ad_title": ad_title,
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"mismatch_type": "job_title_mismatch",
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"severity": "medium",
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}
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)
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return {
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"scan_summary": {
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"total_records_checked": total_scanned,
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"mismatches_found": len(mismatches),
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"status": "action_required" if mismatches else "clean",
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},
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"mismatches": mismatches,
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}
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def scan_department_drift() -> dict[str, Any]:
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"""Detect workers whose Workday department context differs from AD department."""
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mismatches: list[dict[str, Any]] = []
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total_scanned = 0
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for employee_id, details in MOCK_WORKERS.items():
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total_scanned += 1
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workday_department = details.get("dept", "")
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workday_cost_center = details.get("workday_cost_center", "")
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ad_department = details.get("ad_department", "")
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if workday_department and ad_department and workday_department != ad_department:
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mismatches.append(
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{
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"employee_id": employee_id,
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"employee_name": details["name"],
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"workday_department": workday_department,
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"workday_cost_center": workday_cost_center,
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"ad_department": ad_department,
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"mismatch_type": "department_drift",
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"severity": "medium",
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}
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)
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return {
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"scan_summary": {
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"total_records_checked": total_scanned,
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"mismatches_found": len(mismatches),
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"status": "action_required" if mismatches else "clean",
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},
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"mismatches": mismatches,
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}
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def _normalize_name_tokens(value: str) -> list[str]:
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return [token for token in value.lower().replace(".", " ").split() if token]
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def scan_name_variance() -> dict[str, Any]:
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"""Detect AD display names that do not align to legal or preferred Workday names."""
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mismatches: list[dict[str, Any]] = []
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total_scanned = 0
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for employee_id, details in MOCK_WORKERS.items():
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total_scanned += 1
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legal_name = details.get("legal_name", "")
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preferred_name = details.get("preferred_name", "")
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ad_display_name = details.get("ad_display_name", "")
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if not legal_name or not ad_display_name:
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continue
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legal_tokens = _normalize_name_tokens(legal_name)
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preferred_tokens = _normalize_name_tokens(preferred_name)
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display_tokens = _normalize_name_tokens(ad_display_name)
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if not legal_tokens or not display_tokens:
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continue
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legal_first = legal_tokens[0]
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legal_last = legal_tokens[-1]
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preferred_first = preferred_tokens[0] if preferred_tokens else ""
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display_first = display_tokens[0]
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display_last = display_tokens[-1]
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first_name_aligned = display_first in {legal_first, preferred_first}
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last_name_aligned = display_last == legal_last
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if first_name_aligned and last_name_aligned:
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continue
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mismatches.append(
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{
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"employee_id": employee_id,
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"employee_name": details["name"],
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"workday_legal_name": legal_name,
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"workday_preferred_name": preferred_name,
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"ad_display_name": ad_display_name,
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"mismatch_type": "name_variance_requires_review",
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"severity": "low",
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}
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)
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return {
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"scan_summary": {
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"total_records_checked": total_scanned,
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"mismatches_found": len(mismatches),
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"status": "action_required" if mismatches else "clean",
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},
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"mismatches": mismatches,
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} |