import mysql.connector
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime

# Database connection
try:
    cloud_conn = mysql.connector.connect(
        host='106.227.91.181',
        database='huaerdames_cloud',
        port=3306,
        user='root',
        password='cuixing@HuaerdaMySQL'
    )

    # Query to get net_weight by month
    query = """
    SELECT 
        DATE_FORMAT(create_time, '%Y-%m') as month,
        SUM(net_weight) as total_weight
    FROM wms_ingredients_log
    WHERE is_deleted = 0
        AND net_weight IS NOT NULL
        AND create_time IS NOT NULL
    GROUP BY DATE_FORMAT(create_time, '%Y-%m')
    ORDER BY month
    """

    # Execute query and load data into DataFrame
    df = pd.read_sql(query, cloud_conn)

    # Close database connection
    cloud_conn.close()

    # Convert month to datetime for better plotting
    df['month'] = pd.to_datetime(df['month'])

    # Create the plot
    plt.figure(figsize=(12, 6))
    plt.plot(df['month'], df['total_weight'], marker='o')
    
    # Customize the plot
    plt.title('Monthly Net Weight Statistics', fontsize=14)
    plt.xlabel('Month', fontsize=12)
    plt.ylabel('Total Net Weight', fontsize=12)
    plt.grid(True)
    
    # Rotate x-axis labels for better readability
    plt.xticks(rotation=45)
    
    # Adjust layout to prevent label cutoff
    plt.tight_layout()

    # Save the plot
    plt.savefig('monthly_weight_plot.png')
    
    # Show the plot
    plt.show()

except mysql.connector.Error as err:
    print(f"Database error: {err}")
except Exception as e:
    print(f"Error: {e}")