code: def main(params):
      user = params.user
      password = params.password
      host = params.host
      port = params.port
      db = params.db
      table_name = params.table_name
      url = params.url
  
      # the backup files are gzipped, and it's important to keep the correct extension
      # for pandas to be able to open the file
      if url.endswith(".csv.gz"):
          csv_name = "output.csv.gz"
      else:
          csv_name = "output.csv"
  
      os.system(f"wget {url} -O {csv_name}")
  
      engine = create_engine(
          f"postgresql://{user}:{password}@{host}:{port}/{db}"
      )
  
      df_iter = pd.read_csv(csv_name, iterator=True, chunksize=100000)
  
      df = next(df_iter)
  
      df.tpep_pickup_datetime = pd.to_datetime(df.tpep_pickup_datetime)
      df.tpep_dropoff_datetime = pd.to_datetime(
          df.tpep_dropoff_datetime
      )
  
      df.head(n=0).to_sql(
          name=table_name, con=engine, if_exists="replace"
      )
  
      df.to_sql(name=table_name, con=engine, if_exists="append")
  
      while True:
          try:
              t_start = time()
  
              df = next(df_iter)
  
              df.tpep_pickup_datetime = pd.to_datetime(
                  df.tpep_pickup_datetime
              )
              df.tpep_dropoff_datetime = pd.to_datetime(
                  df.tpep_dropoff_datetime
              )
  
              df.to_sql(name=table_name, con=engine, if_exists="append")
  
              t_end = time()
  
              print(
                  "inserted another chunk, took %.3f second"
                  % (t_end - t_start)
              )
  
          except StopIteration:
              print(
                  "Finished ingesting data into the postgres database"
              )
              break
  
imports: import os
  import argparse
  from time import time
  import pandas
  from sqlalchemy import create_engine
label_desc: Use image node_id 1 for calling a global function with example usage: main(params) without return types