import psycopg2
import csv
import pandas as pd

# Step 1: Parse the CSV data
df = pd.read_csv("/home/juni/문서/대옹_모니터링/%EB%8C%80%EC%9B%85%ED%95%98%EC%9D%B4%ED%85%8D-%EB%AA%A8%EB%8B%88%ED%84%B0%EB%A7%81-%EC%86%8C%ED%94%84%ED%8A%B8%EC%9B%A8%EC%96%B4/file/workHistory.csv")  # Truncated for brevity, paste the entire CSV data here.

df = df.iloc[:,1:]

db_config = {
    'dbname': 'welding',
    'user': 'postgres',
    'password': 'ts4430!@',
    'host': 'localhost',  # e.g., 'localhost'
    'port': '5432',  # e.g., '5432'
}

conn = psycopg2.connect(**db_config)
cursor = conn.cursor()

insert_sql = """
INSERT INTO Welding_Jobs (Welding_Job_Number, Mold_Name, Work_Start_Time, Defect_Status, Temperature, Relative_Humidity, Absolute_Humidity)
VALUES (%s, %s, %s, %s, %s, %s, %s)
"""
for index, row in df.iterrows():
    cursor.execute(insert_sql, (
        row['용접 작업번호'],
        row['금형 이름'],
        row['작업 시작 시간'],
        row['불량 여부'],
        row['기온'],
        row['상대습도'],
        row['절대습도']
    ))

conn.commit()
cursor.close()
conn.close()