import os
import pandas as pd
import time
from sqlalchemy import create_engine, Column, String, Integer, Float, DateTime, inspect, MetaData
from sqlalchemy.orm import declarative_base
from sqlalchemy.exc import SQLAlchemyError


DATABASE_URL = os.environ.get('DATABASE_URL')
engine = create_engine(DATABASE_URL)


def get_df_from_csv(csv_file_path):
    df = pd.read_csv(csv_file_path)
    return df

def get_schema_from_df(df):
    schema = pd.io.json.build_table_schema(df)
    return schema

def create_table_from_schema(table_name, schema):
    Base = declarative_base()
    
    inspector = inspect(engine)
    metadata = MetaData()
    metadata.reflect(bind=engine)

    # Check if table already exists
    if table_name in inspector.get_table_names():
        existing_columns = {column['name']: column['type'] for column in inspector.get_columns(table_name)}
        new_columns = {field['name']: field['type'] for field in schema['fields']}
        
        if existing_columns == new_columns:
            print(f"Table '{table_name}' with the same schema already exists. Skipping creation.")
            return
        else:
            print(f"Table '{table_name}' exists but has a different schema. Creating a new table with a timestamp suffix.")
            table_name = f"{table_name}_{int(time.time())}"

    class DynamicTable(Base):
        __tablename__ = table_name
        
        id = Column(Integer, primary_key=True)
        
        for column in schema['fields']:
            if column['name'] != 'id':
                if column['type'] == 'integer':
                    locals()[column['name']] = Column(Integer)
                elif column['type'] == 'number':
                    locals()[column['name']] = Column(Float)
                elif column['type'] == 'datetime':
                    locals()[column['name']] = Column(DateTime)
                else:
                    locals()[column['name']] = Column(String)
    
    try:
        Base.metadata.create_all(engine)
        print(f"Table '{table_name}' created successfully.")
    except SQLAlchemyError as e:
        print(f"Error creating table: {str(e)}")


def save_data_to_table(table_name, df):
    try:
        df.to_sql(table_name, engine)
    except SQLAlchemyError as e:
        print(f"Error saving data to table: {str(e)}")
    


if __name__ == "__main__":
    filename = 'data.csv'
    df = get_df_from_csv(filename)
    schema = get_schema_from_df(df)    
    table_name = filename.split('.')[0]
    
    create_table_from_schema(table_name, schema)
    save_data_to_table(table_name, df)