import os
import csv
import json

def main():
    base_dir = "7-national-park-zoo"
    
    staff_path = os.path.join(base_dir, "zoo-operations/phase-1-discovery/clean_data/staff.csv")
    enc_path = os.path.join(base_dir, "zoo-operations/phase-1-discovery/clean_data/enclosure_metadata.csv")
    health_path = os.path.join(base_dir, "veterinary-care/phase-1-discovery/clean_data/health.csv")
    enrichment_path = os.path.join(base_dir, "nutrition-dietary/phase-1-discovery/clean_data/enrichment.csv")
    
    out_path = os.path.join(base_dir, "prtototype/operational_data.js")
    
    # 1. Parse Staff
    staff = []
    if os.path.exists(staff_path):
        with open(staff_path, 'r', encoding='utf-8') as f:
            reader = csv.DictReader(f)
            for row in reader:
                staff_id = row.get("STAFF_ID", "").strip()
                if staff_id:
                    staff.append({
                        "id": staff_id,
                        "name": row.get("STAFF_NAME", "").strip(),
                        "role": row.get("ROLE", "").strip(),
                        "dept": row.get("DEPARTMENT", "").strip(),
                        "training": row.get("TRAINING_LEVEL", "").strip()
                    })
                    
    # 2. Parse Enclosures (forward-fill empty IDs/names)
    enclosures = []
    current_enc = None
    if os.path.exists(enc_path):
        with open(enc_path, 'r', encoding='utf-8') as f:
            reader = csv.DictReader(f)
            for row in reader:
                enc_id = row.get("ENCLOSURE_ID", "").strip()
                enc_name = row.get("ENCLOSURE_NAME", "").strip()
                species = row.get("SPECIES_HOUSED", "").strip()
                
                if enc_id or enc_name:
                    current_enc = {
                        "id": enc_id if enc_id else "TEMP-" + str(len(enclosures)),
                        "name": enc_name if enc_name else "Unnamed Enclosure",
                        "type": row.get("ENCLOSURE_TYPE", "").strip(),
                        "area": row.get("AREA_M2", "").strip(),
                        "veg": row.get("VEGETATION_COVER_PCT", "").strip(),
                        "shade": row.get("SHADE_TYPE", "").strip(),
                        "water": row.get("WATER_FEATURE", "").strip(),
                        "orientation": row.get("EXHIBIT_ORIENTATION", "").strip(),
                        "notes": row.get("NOTES", "").strip(),
                        "species": [species] if species else []
                    }
                    enclosures.append(current_enc)
                else:
                    if current_enc and species:
                        current_enc["species"].append(species)
                        
    # 3. Parse Health Reports
    health_records = []
    total_cases = 0
    severity_counts = {"Routine": 0, "Needs follow-up": 0, "Urgent": 0}
    if os.path.exists(health_path):
        with open(health_path, 'r', encoding='utf-8') as f:
            reader = csv.DictReader(f)
            for row in reader:
                rec_id = row.get("RECORD_ID", "").strip()
                if not rec_id or rec_id == "RECORD_ID" or "RECORD_ID" in rec_id:
                    continue
                species = row.get("SPECIES", "").strip()
                notes = row.get("CLINICAL_NOTES", "").strip()
                treatment = row.get("TREATMENTS_GIVEN", "").strip()
                vet = row.get("VET_ID", "").strip()
                date = row.get("DATE", "").strip()
                
                if not notes and not treatment:
                    continue
                
                severity = "Routine"
                notes_lower = notes.lower()
                if any(x in notes_lower for x in ["urgent", "severe", "cancer", "fracture", "bleeding", "fip", "anemia"]):
                    severity = "Urgent"
                elif any(x in notes_lower for x in ["follow up", "chronic", "injury", "wound", "diarrhea", "coughing"]):
                    severity = "Needs follow-up"
                    
                severity_counts[severity] += 1
                total_cases += 1
                
                if len(health_records) < 50:
                    health_records.append({
                        "id": rec_id,
                        "date": date,
                        "species": species,
                        "notes": notes,
                        "treatment": treatment,
                        "vet": vet,
                        "severity": severity
                    })
                    
    # 4. Parse Enrichment Logs
    enrichment_logs = []
    activity_types = {}
    total_enrichments = 0
    if os.path.exists(enrichment_path):
        with open(enrichment_path, 'r', encoding='utf-8') as f:
            reader = csv.DictReader(f)
            for row in reader:
                log_id = row.get("LOG_ID", "").strip()
                if not log_id or log_id == "LOG_ID" or "LOG_ID" in log_id:
                    continue
                act_type = row.get("ACTIVITY_TYPE", "").strip()
                if act_type:
                    activity_types[act_type] = activity_types.get(act_type, 0) + 1
                
                total_enrichments += 1
                if len(enrichment_logs) < 50:
                    enrichment_logs.append({
                        "id": log_id,
                        "date": row.get("DATE", "").strip(),
                        "activity": act_type,
                        "species": row.get("ENCLOSURE_ID", "").strip(),
                        "item": row.get("ENRICHMENT_ITEM", "").strip(),
                        "notes": row.get("NOTES", "").strip()
                    })

    # Prepare output data
    ops_data = {
        "staff": staff,
        "enclosures": enclosures,
        "health": {
            "total_cases": total_cases,
            "severity_counts": severity_counts,
            "recent": health_records
        },
        "enrichment": {
            "total_logs": total_enrichments,
            "activity_counts": activity_types,
            "recent": enrichment_logs
        }
    }
    
    # Write JS file
    with open(out_path, 'w', encoding='utf-8') as f:
        f.write("// Auto-generated from Discovery CSV files\n")
        f.write("window.ZOO_OPERATIONS = ")
        json.dump(ops_data, f, ensure_ascii=False, indent=2)
        f.write(";\n")
        
    print(f"Operational data generated successfully. Saved to {out_path}")

if __name__ == "__main__":
    main()