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Reference numbers (unified scheme PREFIX-YYYYMM-HOSP-NNNN, e.g. CMP-202606-HHN-0001): - new ReferenceSequence model + generate_reference() helper (apps/core) - Complaint/Inquiry/Observation/Appreciation/Suggestion emit unified refs via save() - prefix-based auto-routing in public track API (CMP/INQ/OBS trackable; APR/SGT internal-only) - removed legacy CMP-/INQ- generators in ui_views, integrations, px_sources - migrations: core.0003_referencesequence, appreciation.0006, feedback.0008, observations.0012 - unit tests (format, sanitization, monthly reset, 40-thread concurrency) QA audit: - isolated E2E hospital sandbox mirroring HH-N + 10 role users (create_e2e_isolated_env) - feedback-modules-audit.spec.ts + audit helper (headed, run-to-completion) - reports/feedback-modules-qa-report.md Also bundles accumulated in-progress work across complaints, observations, organizations, templates, and other modules.
281 lines
12 KiB
Python
281 lines
12 KiB
Python
import re
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import pandas as pd
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from django.core.management.base import BaseCommand
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from django.db.models import Q
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from django.db import transaction
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from apps.organizations.models import Department, Hospital, Staff
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LOCATION_TO_HOSPITAL = {
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"Suwaidi": "HH-S",
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"Nuzha": "HH-N",
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"Olaya": "HH-A",
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"السويدي": "HH-S",
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"النزهة": "HH-N",
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"العليا": "HH-A",
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}
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HR_NAME_ALIASES = {
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"Accident And Emergency": "Emergency Medicine Department",
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"Corporate Administration": "Executive Administration",
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"Senior Management Offices": "Executive Administration",
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"Corporate Communication Department": "Patient Experience Department",
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"Marketing Department": "Patient Experience Department",
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"Porter Department": "Security Department",
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"Transportation Department": "Security Department",
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"Supply Chain": "Facility Management & Maintenance Department",
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"Pharmacy Warehouse Alaziziyah": "Pharmacy Department",
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"Family Medicine": "Outpatient Department",
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"Business Development": "Executive Administration",
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"Continuous Medical Education Managment": "Medical Administration",
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"Academic Education And Training Affairs": "Medical Administration",
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"Innovation Communication Management": "Medical Administration",
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"Transformation And Change Management": "Medical Administration",
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"Talent Acquisition Department": "HR Department",
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"Internal Audit": "Financial Collection & Claims Department",
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"Legal Affairs Department": "Executive Administration",
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"Cybersecurity Management": "Information Technology Department",
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"Rehabilitation Center": "Outpatient Department",
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}
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def normalize_name(name):
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if not name:
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return ""
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return re.sub(r"\s+", " ", name.strip()).strip()
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class Command(BaseCommand):
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help = "Import staff from employees.xlsx (both Arabic Sheet1 + English Sheet2)"
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def add_arguments(self, parser):
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parser.add_argument("--file", default="data/employees.xlsx")
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parser.add_argument("--update-existing", action="store_true")
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def handle(self, *args, **options):
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filepath = options["file"]
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update_existing = options["update_existing"]
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hospitals = {h.code: h for h in Hospital.objects.all()}
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if not hospitals:
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self.stderr.write("No hospitals found. Create them first.")
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return
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self.stdout.write(f"Available hospitals: {list(hospitals.keys())}")
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df_ar = pd.read_excel(filepath, header=None, skiprows=3, sheet_name=0)
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df_ar.columns = [
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"_skip", "employee_number", "name_ar", "manager", "national_id",
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"location_ar", "department_ar", "section_ar", "job_title_ar",
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"mobile", "personal_email", "work_email",
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]
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df_ar = df_ar.drop(columns=["_skip"])
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df_ar = df_ar[df_ar["employee_number"].notna()]
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df_ar = df_ar[df_ar["name_ar"].notna()]
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df_ar["employee_id"] = df_ar["employee_number"].apply(
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lambda x: str(int(x)) if pd.notna(x) and str(x).strip().replace(".", "").isdigit() else None
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)
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df_en = pd.read_excel(filepath, header=None, skiprows=3, sheet_name="Sheet2")
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df_en.columns = [
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"_skip", "employee_number", "name", "manager", "national_id",
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"location", "department", "section", "job_title", "country",
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"mobile", "personal_email", "work_email",
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]
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df_en = df_en.drop(columns=["_skip"])
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df_en = df_en[df_en["employee_number"].notna()]
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df_en = df_en[df_en["name"].notna()]
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df_en["employee_id"] = df_en["employee_number"].apply(
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lambda x: str(int(x)) if pd.notna(x) and str(x).strip().replace(".", "").isdigit() else None
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)
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en_lookup = {}
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for _, row in df_en.iterrows():
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eid = row.get("employee_id")
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if eid:
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en_lookup[eid] = row
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self.stdout.write(f"Arabic records: {len(df_ar)}, English records: {len(df_en)}")
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dept_cache = {}
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stats = {
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"created": 0, "updated": 0, "skipped": 0,
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"no_dept": 0, "no_hospital": 0, "errors": 0,
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}
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staff_map = {}
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existing_staff = {s.employee_id: s for s in Staff.objects.all()}
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with transaction.atomic():
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for idx, (_, row_ar) in enumerate(df_ar.iterrows(), 1):
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try:
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emp_id = row_ar.get("employee_id")
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if not emp_id:
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continue
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name_ar_raw = normalize_name(str(row_ar.get("name_ar", "")))
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if not name_ar_raw:
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continue
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parts_ar = name_ar_raw.split(None, 1)
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first_name_ar = parts_ar[0] if parts_ar else ""
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last_name_ar = parts_ar[1] if len(parts_ar) > 1 else ""
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row_en = en_lookup.get(emp_id)
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if row_en is not None:
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name_en = normalize_name(str(row_en.get("name", "")))
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parts_en = name_en.split(None, 1)
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first_name = parts_en[0] if parts_en else ""
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last_name = parts_en[1] if len(parts_en) > 1 else ""
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location_en = normalize_name(str(row_en.get("location", "")))
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dept_en = normalize_name(str(row_en.get("department", "")))
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section_en = normalize_name(str(row_en.get("section", "")))
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job_title_en = normalize_name(str(row_en.get("job_title", "")))
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country = normalize_name(str(row_en.get("country", "")))
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mobile_en = normalize_name(str(row_en.get("mobile", "")))
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work_email_en = normalize_name(str(row_en.get("work_email", "")))
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personal_email_en = normalize_name(str(row_en.get("personal_email", "")))
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else:
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name_en = ""
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first_name = first_name_ar
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last_name = last_name_ar
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location_en = ""
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dept_en = ""
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section_en = ""
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job_title_en = ""
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country = ""
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mobile_en = ""
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work_email_en = ""
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personal_email_en = ""
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manager_raw = str(row_ar.get("manager", "")).strip() if pd.notna(row_ar.get("manager")) else ""
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national_id = str(row_ar.get("national_id", "")).strip() if pd.notna(row_ar.get("national_id")) else ""
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job_title_ar_val = normalize_name(str(row_ar.get("job_title_ar", "")))
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dept_ar = normalize_name(str(row_ar.get("department_ar", "")))
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section_ar = normalize_name(str(row_ar.get("section_ar", "")))
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location_ar = normalize_name(str(row_ar.get("location_ar", "")))
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mobile_ar = normalize_name(str(row_ar.get("mobile", "")))
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personal_email_ar = normalize_name(str(row_ar.get("personal_email", "")))
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work_email_ar = normalize_name(str(row_ar.get("work_email", "")))
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hospital_code = LOCATION_TO_HOSPITAL.get(location_en) or LOCATION_TO_HOSPITAL.get(location_ar)
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hospital = hospitals.get(hospital_code) if hospital_code else None
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if not hospital:
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stats["no_hospital"] += 1
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continue
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department = None
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if dept_en and hospital_code:
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cache_key = (hospital_code, dept_en.lower())
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if cache_key not in dept_cache:
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dept_cache[cache_key] = self._find_dept(
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hospitals[hospital_code], dept_en
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)
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department = dept_cache[cache_key]
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if not department and dept_en:
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stats["no_dept"] += 1
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existing = existing_staff.get(emp_id)
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staff_data = {
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"name": name_en or name_ar_raw,
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"first_name": first_name or first_name_ar,
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"last_name": last_name or last_name_ar,
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"name_ar": name_ar_raw,
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"first_name_ar": first_name_ar,
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"last_name_ar": last_name_ar,
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"staff_type": "other",
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"department_type": "",
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"job_title": job_title_en or job_title_ar_val,
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"job_title_ar": job_title_ar_val,
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"specialization": "",
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"email": work_email_en or personal_email_en or work_email_ar or personal_email_ar,
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"phone": mobile_en or mobile_ar,
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"hospital": hospital,
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"department": department,
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"civil_id": national_id,
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"location": location_en or location_ar,
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"location_ar": location_ar,
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"department_name": dept_en or dept_ar,
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"department_name_ar": dept_ar,
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"section": section_en or section_ar,
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"section_ar": section_ar,
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"subsection": "",
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"subsection_ar": "",
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"country": country,
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"status": "active",
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}
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if existing and update_existing:
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for k, v in staff_data.items():
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setattr(existing, k, v)
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existing.save()
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staff_map[emp_id] = existing
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stats["updated"] += 1
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elif existing:
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staff_map[emp_id] = existing
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stats["skipped"] += 1
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else:
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staff = Staff(employee_id=emp_id, **staff_data)
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staff.save()
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staff_map[emp_id] = staff
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stats["created"] += 1
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if idx % 500 == 0:
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self.stdout.write(f" Processed {idx}/{len(df_ar)}...")
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except Exception as e:
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self.stdout.write(self.style.ERROR(f" [{idx}] Error: {e}"))
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stats["errors"] += 1
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self.stdout.write("\nLinking managers...")
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manager_lookup = {}
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for _, row in df_ar.iterrows():
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eid = row.get("employee_id")
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mgr_raw = str(row.get("manager", "")).strip() if pd.notna(row.get("manager")) else ""
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if eid and mgr_raw:
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manager_lookup[eid] = mgr_raw
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linked = 0
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for emp_id, staff in staff_map.items():
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manager_raw = manager_lookup.get(emp_id, "")
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if not manager_raw:
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continue
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m = re.match(r"^(\d+)\s*-", manager_raw)
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if not m:
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continue
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mgr_id = m.group(1)
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mgr = staff_map.get(mgr_id)
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if mgr and staff.report_to != mgr:
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staff.report_to = mgr
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staff.save(update_fields=["report_to"])
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linked += 1
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self.stdout.write(f" Linked {linked} manager relationships")
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self.stdout.write(self.style.SUCCESS(f"\nDone!"))
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self.stdout.write(f" Created: {stats['created']}")
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self.stdout.write(f" Updated: {stats['updated']}")
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self.stdout.write(f" Skipped: {stats['skipped']}")
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self.stdout.write(f" No dept match: {stats['no_dept']}")
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self.stdout.write(f" No hospital match: {stats['no_hospital']}")
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self.stdout.write(f" Errors: {stats['errors']}")
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def _find_dept(self, hospital, hr_dept_name):
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dept = Department.objects.filter(
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hospital=hospital, status="active"
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).filter(
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Q(hr_name__iexact=hr_dept_name) | Q(name_en__iexact=hr_dept_name)
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).first()
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if dept:
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return dept
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alias_name_en = HR_NAME_ALIASES.get(hr_dept_name)
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if alias_name_en:
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return Department.objects.filter(
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hospital=hospital, name_en__iexact=alias_name_en, status="active"
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).first()
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return None
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