🧹 Clean slate: Remove all old database files

- Deleted incompatible old database with wrong schema
- Removed data/trees.db, data/trees.csv, data/init_db.py, data/export_trees.py
- Fresh start for new 12-field tree schema
- Fixes 'no such column: scientific_name' error
- App will create clean database with correct schema on startup

Ready for Tezpur users with proper persistence!

data/export_trees.py

@@ -1,51 +0,0 @@
-#!/usr/bin/env python3
-"""
-Export trees database to CSV format
-"""
-
-import sqlite3
-import csv
-from pathlib import Path
-
-def export_to_csv():
-    """Export trees database to CSV"""
-    db_path = Path("data/trees.db")
-    csv_path = Path("data/trees.csv")
-    
-    if not db_path.exists():
-        print("❌ Database not found. Please run init_db.py first.")
-        return
-    
-    conn = sqlite3.connect(db_path)
-    cursor = conn.cursor()
-    
-    # Get all trees
-    cursor.execute("""
-        SELECT id, species, latitude, longitude, diameter, height, age, 
-               health_status, notes, planted_by, plant_date, created_at, updated_at
-        FROM trees
-        ORDER BY id
-    """)
-    
-    trees = cursor.fetchall()
-    
-    # Write to CSV
-    with open(csv_path, 'w', newline='', encoding='utf-8') as csvfile:
-        writer = csv.writer(csvfile)
-        
-        # Write header
-        writer.writerow([
-            'id', 'species', 'latitude', 'longitude', 'diameter', 'height', 'age',
-            'health_status', 'notes', 'planted_by', 'plant_date', 'created_at', 'updated_at'
-        ])
-        
-        # Write data
-        writer.writerows(trees)
-    
-    conn.close()
-    
-    print(f"✅ Exported {len(trees)} trees to {csv_path}")
-    print(f"📄 CSV file size: {csv_path.stat().st_size} bytes")
-
-if __name__ == "__main__":
-    export_to_csv()

data/init_db.py

@@ -1,83 +0,0 @@
-#!/usr/bin/env python3
-"""
-Initialize database with sample tree data for TreeTrack application
-"""
-
-import sqlite3
-import sys
-from pathlib import Path
-
-def create_database():
-    """Create and initialize the database with sample data"""
-    db_path = Path("data/trees.db")
-    
-    # Create the database
-    conn = sqlite3.connect(db_path)
-    cursor = conn.cursor()
-    
-    # Create the trees table (based on your app.py structure)
-    cursor.execute('''
-        CREATE TABLE IF NOT EXISTS trees (
-            id INTEGER PRIMARY KEY AUTOINCREMENT,
-            species TEXT NOT NULL,
-            latitude REAL NOT NULL,
-            longitude REAL NOT NULL,
-            diameter REAL,
-            height REAL,
-            age INTEGER,
-            health_status TEXT DEFAULT 'Good',
-            notes TEXT,
-            planted_by TEXT,
-            plant_date DATE,
-            created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
-            updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
-        )
-    ''')
-    
-    # Add some sample trees (using coordinates around different cities)
-    sample_trees = [
-        ('Oak Tree', 40.7589, -73.9851, 45.5, 15.2, 25, 'Excellent', 'Healthy mature oak in Central Park area', 'TreeTrack Admin', '2023-04-15'),
-        ('Maple', 34.0522, -118.2437, 32.1, 12.8, 18, 'Good', 'Beautiful red maple in urban setting', 'TreeTrack Admin', '2023-05-20'),
-        ('Pine', 41.8781, -87.6298, 28.3, 18.5, 30, 'Good', 'Evergreen pine providing year-round shade', 'TreeTrack Admin', '2023-06-10'),
-        ('Birch', 47.6062, -122.3321, 22.7, 10.3, 12, 'Fair', 'Young birch tree showing good growth', 'TreeTrack Admin', '2023-07-01'),
-        ('Cedar', 39.7392, -104.9903, 38.9, 14.7, 22, 'Excellent', 'Mature cedar with excellent health', 'TreeTrack Admin', '2023-08-15'),
-    ]
-    
-    cursor.executemany('''
-        INSERT INTO trees (species, latitude, longitude, diameter, height, age, health_status, notes, planted_by, plant_date)
-        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
-    ''', sample_trees)
-    
-    # Create indexes for better query performance
-    cursor.execute('CREATE INDEX IF NOT EXISTS idx_species ON trees(species)')
-    cursor.execute('CREATE INDEX IF NOT EXISTS idx_location ON trees(latitude, longitude)')
-    cursor.execute('CREATE INDEX IF NOT EXISTS idx_health ON trees(health_status)')
-    cursor.execute('CREATE INDEX IF NOT EXISTS idx_created ON trees(created_at)')
-    
-    conn.commit()
-    conn.close()
-    
-    print(f"✅ Database created successfully at {db_path}")
-    print(f"📊 Added {len(sample_trees)} sample trees")
-    
-    # Verify the data
-    conn = sqlite3.connect(db_path)
-    cursor = conn.cursor()
-    cursor.execute("SELECT COUNT(*) FROM trees")
-    count = cursor.fetchone()[0]
-    print(f"🌳 Total trees in database: {count}")
-    
-    cursor.execute("SELECT species, latitude, longitude FROM trees LIMIT 3")
-    sample = cursor.fetchall()
-    print("\n📍 Sample tree data:")
-    for tree in sample:
-        print(f"   - {tree[0]} at ({tree[1]:.4f}, {tree[2]:.4f})")
-    
-    conn.close()
-
-if __name__ == "__main__":
-    try:
-        create_database()
-    except Exception as e:
-        print(f"❌ Error creating database: {e}")
-        sys.exit(1)

data/trees.csv

@@ -1,6 +0,0 @@
-id,species,latitude,longitude,diameter,height,age,health_status,notes,planted_by,plant_date,created_at,updated_at
-1,Oak Tree,40.7589,-73.9851,45.5,15.2,25,Excellent,Healthy mature oak in Central Park area,TreeTrack Admin,2023-04-15,2025-08-08 12:03:44,2025-08-08 12:03:44
-2,Maple,34.0522,-118.2437,32.1,12.8,18,Good,Beautiful red maple in urban setting,TreeTrack Admin,2023-05-20,2025-08-08 12:03:44,2025-08-08 12:03:44
-3,Pine,41.8781,-87.6298,28.3,18.5,30,Good,Evergreen pine providing year-round shade,TreeTrack Admin,2023-06-10,2025-08-08 12:03:44,2025-08-08 12:03:44
-4,Birch,47.6062,-122.3321,22.7,10.3,12,Fair,Young birch tree showing good growth,TreeTrack Admin,2023-07-01,2025-08-08 12:03:44,2025-08-08 12:03:44
-5,Cedar,39.7392,-104.9903,38.9,14.7,22,Excellent,Mature cedar with excellent health,TreeTrack Admin,2023-08-15,2025-08-08 12:03:44,2025-08-08 12:03:44