# database.py (SmartHeal) — dataset ID hardcoded

import os
import json
import logging
from datetime import datetime
from typing import Optional, Dict, Any, List

import mysql.connector
from mysql.connector import Error
from PIL import Image

# ----------------------------- Hardcoded Dataset -----------------------------
DATASET_ID = "SmartHeal/wound-image-uploads"  # <— hardcoded as requested

# Optional HF dataset integration
_HF_AVAILABLE = False
try:
    from huggingface_hub import HfApi, HfFolder, create_repo
    _HF_AVAILABLE = True
except Exception:
    _HF_AVAILABLE = False


# ----------------------------- helpers -----------------------------
def _now():
    return datetime.now()

def _abs(p: str) -> str:
    try:
        return os.path.abspath(p)
    except Exception:
        return p

def _ensure_dir(path: str):
    os.makedirs(path, exist_ok=True)

def _file_url(path: str) -> str:
    """
    For local files, return /file=/abs/path (works in Gradio/Spaces).
    For remote (http/https), return as-is.
    """
    if not path:
        return ""
    s = str(path)
    if s.startswith("http://") or s.startswith("https://"):
        return s
    return f"/file={_abs(s)}"


# -------------------------- DatabaseManager --------------------------
class DatabaseManager:
    """
    Database operations manager for SmartHeal
    - Keeps patient_id (INT) consistent for questionnaire_responses / ai_analyses joins
    - Uses patients.uuid (CHAR 36) in wounds / wound_images where those tables store VARCHAR
    - Saves images locally OR to a hardcoded Hugging Face dataset and stores the URL
    """

    def __init__(self, mysql_config: Dict[str, Any], hf_token: Optional[str] = None):
        self.mysql_config = mysql_config

        # storage backend: hardcoded dataset id; token from arg or env
        self.dataset_id = DATASET_ID
        self.hf_token = hf_token or os.getenv("HUGGINGFACE_TOKEN") or os.getenv("HF_TOKEN")
        self.use_dataset = bool(self.dataset_id and self.hf_token and _HF_AVAILABLE)

        if self.use_dataset:
            logging.info(f"HF dataset storage enabled: {self.dataset_id}")
            try:
                HfFolder.save_token(self.hf_token)
                try:
                    create_repo(repo_id=self.dataset_id, repo_type="dataset", exist_ok=True, token=self.hf_token)
                except Exception:
                    pass
                self.hf_api = HfApi(token=self.hf_token)
            except Exception as e:
                logging.warning(f"Could not initialize HF dataset backend, falling back to local. Err: {e}")
                self.use_dataset = False
        else:
            logging.info("Using LOCAL storage (uploads/)")

        _ensure_dir("uploads")
        self.test_connection()
        self._ensure_default_questionnaire()

    # -------------------- low-level connection utils --------------------
    def test_connection(self):
        try:
            conn = self.get_connection()
            if conn:
                conn.close()
                logging.info("✅ Database connection successful")
            else:
                logging.error("❌ Database connection failed")
        except Exception as e:
            logging.error(f"Database connection test failed: {e}")

    def get_connection(self):
        try:
            return mysql.connector.connect(**self.mysql_config)
        except Error as e:
            logging.error(f"Error connecting to MySQL: {e}")
            return None

    def execute_query(self, query, params=None, fetch=False):
        conn = self.get_connection()
        if not conn:
            return None
        cur = None
        try:
            cur = conn.cursor(dictionary=True)
            cur.execute(query, params or ())
            if fetch:
                return cur.fetchall()
            conn.commit()
            return cur.rowcount
        except Error as e:
            logging.error(f"Error executing query: {e}\nSQL: {query}\nParams: {params}")
            if conn:
                conn.rollback()
            return None
        finally:
            if cur: cur.close()
            if conn and conn.is_connected(): conn.close()

    def execute_query_one(self, query, params=None):
        conn = self.get_connection()
        if not conn:
            return None
        cur = None
        try:
            cur = conn.cursor(dictionary=True)
            cur.execute(query, params or ())
            return cur.fetchone()
        except Error as e:
            logging.error(f"Error executing query: {e}\nSQL: {query}\nParams: {params}")
            return None
        finally:
            if cur: cur.close()
            if conn and conn.is_connected(): conn.close()

    # ---------------------- One-time ensures ----------------------
    def _ensure_default_questionnaire(self):
        """Ensure a 'Default Patient Assessment' row exists in questionnaires."""
        try:
            row = self.execute_query_one(
                "SELECT id FROM questionnaires WHERE name = %s LIMIT 1",
                ("Default Patient Assessment",)
            )
            if not row:
                self.execute_query(
                    "INSERT INTO questionnaires (name, description, created_at, updated_at) "
                    "VALUES (%s, %s, NOW(), NOW())",
                    ("Default Patient Assessment", "Standard patient wound assessment form")
                )
                logging.info("Created default questionnaire 'Default Patient Assessment'")
        except Exception as e:
            logging.error(f"Error ensuring default questionnaire: {e}")

    # ------------------------------ patients ------------------------------
    def _normalize_age(self, age_val: Any) -> Optional[int]:
        try:
            return int(age_val) if age_val not in [None, ""] else None
        except Exception:
            return None

    def get_patient_by_id(self, patient_id: int) -> Optional[Dict[str, Any]]:
        return self.execute_query_one(
            "SELECT id, uuid, name, age, gender FROM patients WHERE id = %s LIMIT 1",
            (patient_id,)
        )

    def get_patient_by_name_age_gender(self, name: str, age: Any, gender: str) -> Optional[Dict[str, Any]]:
        age_val = self._normalize_age(age)
        if age_val is None:
            return self.execute_query_one(
                "SELECT id, uuid, name, age, gender FROM patients "
                "WHERE name = %s AND age IS NULL AND gender = %s LIMIT 1",
                (name, gender),
            )
        return self.execute_query_one(
            "SELECT id, uuid, name, age, gender FROM patients "
            "WHERE name = %s AND age = %s AND gender = %s LIMIT 1",
            (name, age_val, gender),
        )

    def create_patient(self, data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
        conn = None
        cur = None
        try:
            conn = self.get_connection()
            if not conn: return None
            cur = conn.cursor()
            import uuid as _uuid
            p_uuid = str(_uuid.uuid4())
            cur.execute("""
                INSERT INTO patients (uuid, name, age, gender, illness, allergy, notes, created_at)
                VALUES (%s,%s,%s,%s,%s,%s,%s,%s)
            """, (
                p_uuid,
                data.get("patient_name"),
                self._normalize_age(data.get("patient_age")),
                data.get("patient_gender"),
                data.get("medical_history", ""),
                data.get("allergies", ""),
                data.get("additional_notes", ""),
                _now()
            ))
            conn.commit()
            return {"id": cur.lastrowid, "uuid": p_uuid}
        except Exception as e:
            if conn: conn.rollback()
            logging.error(f"create_patient error: {e}")
            return None
        finally:
            try:
                if cur: cur.close()
                if conn: conn.close()
            except Exception:
                pass

    def list_patients_for_practitioner(self, practitioner_id: int) -> List[Dict[str, Any]]:
        return self.execute_query("""
            SELECT
              p.id, p.uuid, p.name, p.age, p.gender,
              COUNT(qr.id) AS total_visits,
              MAX(qr.submitted_at) AS last_visit,
              MIN(qr.submitted_at) AS first_visit
            FROM questionnaire_responses qr
            JOIN patients p ON p.id = qr.patient_id
            WHERE qr.practitioner_id = %s
            GROUP BY p.id, p.uuid, p.name, p.age, p.gender
            ORDER BY last_visit DESC
        """, (practitioner_id,), fetch=True) or []

    # --------------------------- questionnaires/visits ---------------------------
    def _ensure_default_questionnaire_id(self, created_by_user_id: Optional[int] = None) -> int:
        row = self.execute_query_one(
            "SELECT id FROM questionnaires WHERE name = 'Default Patient Assessment' LIMIT 1"
        )
        if row:
            return int(row["id"])
        self.execute_query("""
            INSERT INTO questionnaires (name, description, created_by, created_at, updated_at)
            VALUES ('Default Patient Assessment', 'Standard patient wound assessment form', %s, NOW(), NOW())
        """, (created_by_user_id,))
        row = self.execute_query_one(
            "SELECT id FROM questionnaires WHERE name = 'Default Patient Assessment' ORDER BY id DESC LIMIT 1"
        )
        return int(row["id"]) if row else 1

    def save_questionnaire(self, questionnaire_data: Dict[str, Any], existing_patient_id: Optional[int] = None):
        """
        Create a visit (questionnaire_responses) for an existing or new patient.
        Returns: {'response_id', 'patient_id', 'patient_uuid'}
        """
        conn = None
        cur = None
        try:
            conn = self.get_connection()
            if not conn: return None
            cur = conn.cursor(dictionary=True)

            # Resolve patient
            if existing_patient_id:
                p = self.get_patient_by_id(existing_patient_id)
                if not p:
                    raise Exception("Existing patient id not found")
                patient_id = p["id"]
                patient_uuid = p["uuid"]
            else:
                found = self.get_patient_by_name_age_gender(
                    questionnaire_data.get("patient_name"),
                    questionnaire_data.get("patient_age"),
                    questionnaire_data.get("patient_gender"),
                )
                if found:
                    patient_id, patient_uuid = found["id"], found["uuid"]
                else:
                    created = self.create_patient(questionnaire_data)
                    if not created:
                        raise Exception("Failed to create patient")
                    patient_id, patient_uuid = created["id"], created["uuid"]

            qid = self._ensure_default_questionnaire_id(questionnaire_data.get("user_id"))

            response_data = {
                "patient_info": {
                    "name": questionnaire_data.get("patient_name"),
                    "age": questionnaire_data.get("patient_age"),
                    "gender": questionnaire_data.get("patient_gender"),
                },
                "wound_details": {
                    "location": questionnaire_data.get("wound_location"),
                    "duration": questionnaire_data.get("wound_duration"),
                    "pain_level": questionnaire_data.get("pain_level"),
                    "moisture_level": questionnaire_data.get("moisture_level"),
                    "infection_signs": questionnaire_data.get("infection_signs"),
                    "diabetic_status": questionnaire_data.get("diabetic_status"),
                },
                "medical_history": {
                    "previous_treatment": questionnaire_data.get("previous_treatment"),
                    "medical_history": questionnaire_data.get("medical_history"),
                    "medications": questionnaire_data.get("medications"),
                    "allergies": questionnaire_data.get("allergies"),
                    "additional_notes": questionnaire_data.get("additional_notes"),
                },
            }

            practitioner_id = questionnaire_data.get("user_id") or 1

            cur.execute("""
                INSERT INTO questionnaire_responses
                    (questionnaire_id, patient_id, practitioner_id, response_data, submitted_at)
                VALUES (%s,%s,%s,%s,%s)
            """, (
                qid, patient_id, practitioner_id, json.dumps(response_data), _now()
            ))
            conn.commit()
            response_id = cur.lastrowid
            logging.info(f"✅ Saved response ID {response_id}")
            return {"response_id": response_id, "patient_id": patient_id, "patient_uuid": patient_uuid}
        except Exception as e:
            if conn: conn.rollback()
            logging.error(f"save_questionnaire error: {e}")
            return None
        finally:
            try:
                if cur: cur.close()
                if conn: conn.close()
            except Exception:
                pass

    # ------------------------------- wounds -------------------------------
    def create_wound(self, patient_uuid: str, questionnaire_data: Dict[str, Any]) -> Optional[str]:
        """Create wound (returns wound_uuid). Stores patient_uuid in wounds.patient_id (VARCHAR)."""
        conn = None
        cur = None
        try:
            conn = self.get_connection()
            if not conn: return None
            cur = conn.cursor()
            import uuid as _uuid
            wound_uuid = str(_uuid.uuid4())
            cur.execute("""
                INSERT INTO wounds (uuid, patient_id, position, category, moisture, infection, notes, created_at)
                VALUES (%s,%s,%s,%s,%s,%s,%s,%s)
            """, (
                wound_uuid,
                patient_uuid,
                questionnaire_data.get("wound_location") or "",
                "Assessment",
                questionnaire_data.get("moisture_level") or "",
                questionnaire_data.get("infection_signs") or "",
                questionnaire_data.get("additional_notes") or "",
                _now()
            ))
            conn.commit()
            return wound_uuid
        except Exception as e:
            if conn: conn.rollback()
            logging.error(f"create_wound error: {e}")
            return None
        finally:
            try:
                if cur: cur.close()
                if conn: conn.close()
            except Exception:
                pass

    # --------------------------- image storage ---------------------------
    def _read_image_size(self, image_path: str):
        try:
            with Image.open(image_path) as im:
                return im.size  # (w, h)
        except Exception:
            return (None, None)

    def _copy_to_uploads(self, src_path: str, suffix: str) -> str:
        ext = os.path.splitext(src_path)[1] or ".jpg"
        base = f"wound_{datetime.utcnow().strftime('%Y%m%d_%H%M%S_%f')}_{suffix}{ext}"
        dst = os.path.join("uploads", base)
        try:
            with open(src_path, "rb") as r, open(dst, "wb") as w:
                w.write(r.read())
            return dst
        except Exception:
            return src_path

    def _hf_upload_and_url(self, local_path: str, subdir: str) -> Optional[str]:
        """Upload a file to the (hardcoded) HF dataset and return a public resolve URL."""
        if not self.use_dataset:
            return None
        try:
            # destination path in repo (datasets use 'main' branch)
            day = datetime.utcnow().strftime("%Y/%m/%d")
            fname = os.path.basename(local_path)
            repo_path = f"{subdir}/{day}/{fname}"
            self.hf_api.upload_file(
                path_or_fileobj=local_path,
                path_in_repo=repo_path,
                repo_id=self.dataset_id,
                repo_type="dataset",
                commit_message=f"Add {repo_path}"
            )
            return f"https://huggingface.co/datasets/{self.dataset_id}/resolve/main/{repo_path}"
        except Exception as e:
            logging.error(f"HF upload failed: {e}")
            return None

    def _insert_wound_image_row(self, conn, cur, patient_uuid: str, wound_uuid: Optional[str], image_path_or_url: str) -> Optional[int]:
        """Insert one row in wound_images; width/height detected for local files only."""
        width, height = (None, None)
        if not (image_path_or_url.startswith("http://") or image_path_or_url.startswith("https://")):
            width, height = self._read_image_size(image_path_or_url)

        import uuid as _uuid
        img_uuid = str(_uuid.uuid4())
        cur.execute("""
            INSERT INTO wound_images (uuid, patient_id, wound_id, image, width, height, created_at)
            VALUES (%s,%s,%s,%s,%s,%s,%s)
        """, (
            img_uuid,
            patient_uuid,
            wound_uuid,
            image_path_or_url,
            int(width) if width else None,
            int(height) if height else None,
            _now()
        ))
        conn.commit()
        return cur.lastrowid

    def save_wound_images_bundle(
        self,
        patient_uuid: str,
        original_path: str,
        analysis_result: Dict[str, Any],
        wound_uuid: Optional[str] = None
    ) -> Dict[str, Any]:
        """
        Save original + detection + segmentation images to wound_images.
        Stores **HF dataset URLs** when configured, else local paths.
        Returns display URLs for UI.
        """
        out = {
            "original_id": None, "original_url": None,
            "detection_id": None, "detection_url": None,
            "segmentation_id": None, "segmentation_url": None
        }

        conn = self.get_connection()
        if not conn: return out
        cur = conn.cursor()

        try:
            # Ensure wound row exists if not provided (minimal)
            if not wound_uuid:
                import uuid as _uuid
                wound_uuid = str(_uuid.uuid4())
                cur.execute("""
                    INSERT INTO wounds (uuid, patient_id, category, notes, created_at)
                    VALUES (%s,%s,%s,%s,%s)
                """, (wound_uuid, patient_uuid, "Assessment", "", _now()))
                conn.commit()

            # 1) Original
            local_orig = self._copy_to_uploads(original_path, "original")
            url_orig = self._hf_upload_and_url(local_orig, subdir="original") if self.use_dataset else None
            store_orig = url_orig or local_orig
            img_id = self._insert_wound_image_row(conn, cur, patient_uuid, wound_uuid, store_orig)
            out["original_id"] = img_id
            out["original_url"] = _file_url(store_orig)

            # 2) Detection / Segmentation from analysis_result
            va = (analysis_result or {}).get("visual_analysis", {}) or {}
            det = va.get("detection_image_path")
            seg = va.get("segmentation_image_path")

            if det and os.path.exists(det):
                local_det = self._copy_to_uploads(det, "detect")
                url_det = self._hf_upload_and_url(local_det, subdir="detect") if self.use_dataset else None
                store_det = url_det or local_det
                did = self._insert_wound_image_row(conn, cur, patient_uuid, wound_uuid, store_det)
                out["detection_id"] = did
                out["detection_url"] = _file_url(store_det)

            if seg and os.path.exists(seg):
                local_seg = self._copy_to_uploads(seg, "segment")
                url_seg = self._hf_upload_and_url(local_seg, subdir="segment") if self.use_dataset else None
                store_seg = url_seg or local_seg
                sid = self._insert_wound_image_row(conn, cur, patient_uuid, wound_uuid, store_seg)
                out["segmentation_id"] = sid
                out["segmentation_url"] = _file_url(store_seg)

            return out
        except Exception as e:
            logging.error(f"save_wound_images_bundle error: {e}", exc_info=True)
            try:
                conn.rollback()
            except Exception:
                pass
            return out
        finally:
            try:
                cur.close()
                conn.close()
            except Exception:
                pass

    # For older callers that only save one image
    def save_wound_image(self, patient_id: int, image) -> Optional[Dict[str, Any]]:
        """
        Back-compat single-image save:
        - If `image` is a PIL.Image -> we write to uploads and (optionally) the dataset.
        - If `image` is a filepath -> we copy + (optionally) upload.
        Stores patients.uuid into wound_images.patient_id (VARCHAR).
        """
        try:
            # Normalize to a temporary local path first
            _ensure_dir("uploads")
            image_uid = os.urandom(8).hex()
            tmp_local = os.path.join("uploads", f"wound_{image_uid}_tmp.jpg")

            if hasattr(image, "save"):
                image.save(tmp_local, format="JPEG", quality=95)
            elif isinstance(image, str) and os.path.exists(image):
                with Image.open(image) as pil:
                    pil = pil.convert("RGB")
                    pil.save(tmp_local, format="JPEG", quality=95)
            else:
                logging.error("Invalid image object/path")
                return None

            # Resolve patients.uuid
            conn = self.get_connection()
            if not conn: return None
            cur = conn.cursor()

            cur2 = conn.cursor(dictionary=True)
            cur2.execute("SELECT uuid FROM patients WHERE id = %s LIMIT 1", (patient_id,))
            row = cur2.fetchone()
            cur2.close()
            if not row:
                logging.error("Patient id not found while saving image")
                conn.close()
                return None
            patient_uuid = row["uuid"]

            # Push to uploads/dataset with final name
            local_path = self._copy_to_uploads(tmp_local, "original")
            url = self._hf_upload_and_url(local_path, subdir="original") if self.use_dataset else None
            path_or_url = url or local_path

            width, height = self._read_image_size(local_path)
            import uuid as _uuid
            img_uuid = str(_uuid.uuid4())
            cur.execute("""
                INSERT INTO wound_images (uuid, patient_id, image, width, height, created_at)
                VALUES (%s,%s,%s,%s,%s,%s)
            """, (
                img_uuid,
                patient_uuid,
                path_or_url,
                int(width) if width else None,
                int(height) if height else None,
                _now()
            ))
            conn.commit()
            image_db_id = cur.lastrowid
            cur.close()
            conn.close()

            return {
                "id": image_db_id,
                "filename": os.path.basename(local_path),
                "path": path_or_url,
                "url": _file_url(path_or_url),
            }
        except Exception as e:
            logging.error(f"Image save error: {e}", exc_info=True)
            return None

    # ------------------------------- analyses -------------------------------
    def save_analysis(self, questionnaire_id: int, image_id: Optional[int], analysis_data: Dict[str, Any]) -> Optional[int]:
        conn = None
        cur = None
        try:
            conn = self.get_connection()
            if not conn: return None
            cur = conn.cursor()
            cur.execute("""
                INSERT INTO ai_analyses (
                    questionnaire_id, image_id, analysis_data, summary, recommendations,
                    risk_score, risk_level, processing_time, model_version, created_at
                ) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
            """, (
                questionnaire_id,
                image_id,
                json.dumps(analysis_data) if analysis_data else None,
                (analysis_data or {}).get("summary", ""),
                (analysis_data or {}).get("recommendations", ""),
                int((analysis_data or {}).get("risk_score", 0) or 0),
                (analysis_data or {}).get("risk_level", "Unknown"),
                float((analysis_data or {}).get("processing_time", 0.0) or 0.0),
                (analysis_data or {}).get("model_version", "v1.0"),
                _now()
            ))
            conn.commit()
            return cur.lastrowid
        except Exception as e:
            if conn: conn.rollback()
            logging.error(f"save_analysis error: {e}")
            return None
        finally:
            try:
                if cur: cur.close()
                if conn: conn.close()
            except Exception:
                pass

    def save_analysis_result(self, questionnaire_response_id: int, analysis_result: Dict[str, Any]):
        """
        Compatibility wrapper used by some callers (without image_id).
        Stores under the questionnaire template linked to the response.
        """
        try:
            row = self.execute_query_one(
                "SELECT questionnaire_id FROM questionnaire_responses WHERE id = %s LIMIT 1",
                (questionnaire_response_id,)
            )
            if not row:
                logging.error("No questionnaire_response found for analysis_result save")
                return None
            questionnaire_id = row["questionnaire_id"]

            return self.save_analysis(
                questionnaire_id=questionnaire_id,
                image_id=None,
                analysis_data=analysis_result or {}
            )
        except Exception as e:
            logging.error(f"Error saving analysis result: {e}")
            return None

    # ------------------------------- queries for UI -------------------------------
    def get_user_history_rows(self, user_id: int) -> List[Dict[str, Any]]:
        """
        Latest 20 visits across patients; joins ai_analyses.image_id -> wound_images to pull display image.
        """
        return self.execute_query("""
            SELECT
                qr.id AS response_id,
                qr.submitted_at AS visit_date,
                p.id AS patient_id,
                p.uuid AS patient_uuid,
                p.name AS patient_name,
                p.age AS patient_age,
                p.gender AS patient_gender,
                a.summary,
                a.recommendations,
                a.risk_score,
                a.risk_level,
                a.analysis_data,
                wi.image AS image_url
            FROM questionnaire_responses qr
            JOIN patients p ON p.id = qr.patient_id
            LEFT JOIN ai_analyses a ON a.questionnaire_id = qr.id
            LEFT JOIN wound_images wi ON wi.id = a.image_id
            WHERE qr.practitioner_id = %s
            ORDER BY qr.submitted_at DESC
            LIMIT 20
        """, (user_id,), fetch=True) or []

    def get_patient_progression_rows(self, user_id: int, patient_id: int) -> List[Dict[str, Any]]:
        """
        Chronological visits for a given patient (INT id).
        """
        return self.execute_query("""
            SELECT
                qr.id AS response_id,
                qr.submitted_at AS visit_date,
                p.id AS patient_id,
                p.uuid AS patient_uuid,
                p.name AS patient_name,
                p.age AS patient_age,
                p.gender AS patient_gender,
                a.summary,
                a.recommendations,
                a.risk_score,
                a.risk_level,
                a.analysis_data,
                wi.image AS image_url
            FROM questionnaire_responses qr
            JOIN patients p ON p.id = qr.patient_id
            LEFT JOIN ai_analyses a ON a.questionnaire_id = qr.id
            LEFT JOIN wound_images wi ON wi.id = a.image_id
            WHERE qr.practitioner_id = %s AND p.id = %s
            ORDER BY qr.submitted_at ASC
        """, (user_id, patient_id), fetch=True) or []

    # ----------------------------- organizations -----------------------------
    def get_organizations(self):
        try:
            rows = self.execute_query(
                "SELECT id, name as org_name, location FROM organizations ORDER BY name",
                fetch=True
            )
            return rows or [{'id': 1, 'org_name': 'Default Hospital', 'location': 'Default Location'}]
        except Exception as e:
            logging.error(f"Error getting organizations: {e}")
            return [{'id': 1, 'org_name': 'Default Hospital', 'location': 'Default Location'}]

    def create_organization(self, org_data: Dict[str, Any]):
        try:
            res = self.execute_query("""
                INSERT INTO organizations (name, email, phone, country_code, department, location, created_at)
                VALUES (%s,%s,%s,%s,%s,%s,%s)
            """, (
                org_data.get('org_name', ''),
                org_data.get('email', ''),
                org_data.get('phone', ''),
                org_data.get('country_code', ''),
                org_data.get('department', ''),
                org_data.get('location', ''),
                _now()
            ))
            if res:
                row = self.execute_query_one(
                    "SELECT id FROM organizations WHERE name = %s ORDER BY created_at DESC LIMIT 1",
                    (org_data.get('org_name', ''),)
                )
                return row['id'] if row else None
            return None
        except Exception as e:
            logging.error(f"Error creating organization: {e}")
            return None