View difference between Paste ID: aybPTd3b and n31cuE1q

 import psycopg
 from psycopg.rows import dict_row
 import datetime
 import csv
 import pandas
 
 ########################################################################################################################
 # database connection parameters
 
 dbname = ''
 user = ''
 host = 'mach3db.com'
 password = ''
 connection_string = f"dbname={dbname} user={user} host={host} password={password} sslmode=require"
 
 ########################################################################################################################
 # table and query
 
 table = ''
 
 query = f"""
 
             SELECT * FROM {table}
 
 """
 ########################################################################################################################
 
 
 def get_column_names():
     column_query = f"""
         SELECT *
         FROM {table}
         LIMIT 0
     """
 
     with psycopg.connect(connection_string) as conn:
         with conn.cursor() as cur:
             cur.execute(column_query)
             return [desc[0] for desc in cur.description]
 
 
 def time_to_fetch_and_output_csv(fetchall=False):
-    base_dir = 'C:\\Users\\shaughnessy software\\Downloads\\'
+    base_dir = ''
 
     date_string = datetime.datetime.now().strftime('%c').replace(':', '-')
     filename_string = f'mach3db-benchmarket-output-{date_string}.csv'
 
     output_filename = f'{base_dir}{filename_string}'
 
     with psycopg.connect(connection_string) as conn:
         with conn.cursor() as cur:
             with open(output_filename, 'w', newline='') as f:
                 writer = csv.writer(f)
 
                 writer.writerow(
                     get_column_names()
                 )
 
                 if fetchall:
                     start_time = datetime.datetime.now()
 
                     cur.execute(query)
 
                     writer.writerows(
                         cur.fetchall()
                     )
 
                     end_time = datetime.datetime.now()
 
                     time_taken = (end_time - start_time).total_seconds()
 
                     return time_taken
                 else:
                     start_time = datetime.datetime.now()
 
                     cur.execute(query)
 
                     row = cur.fetchone()
 
                     while row:
                         writer.writerow(row)
                         row = cur.fetchone()
 
                     end_time = datetime.datetime.now()
 
                     time_taken = (end_time - start_time).total_seconds()
 
                     return time_taken
 
 
 def time_to_fetch_and_return(as_dict=False, as_df=False):
     if as_dict:
         row_factory = dict_row
     else:
         row_factory = None
 
     with psycopg.connect(connection_string, row_factory=row_factory) as conn:
         with conn.cursor() as cur:
             start_time = datetime.datetime.now()
 
             cur.execute(query)
 
             results = cur.fetchall()
 
             end_time = datetime.datetime.now()
 
             time_taken = (end_time - start_time).total_seconds()
 
             if as_df:
                 if as_dict:
                     results = pandas.DataFrame(results)
                 else:
                     results = pandas.DataFrame(results, columns=get_column_names())
 
             return results, time_taken
 
 
 def time_to_fetch():
     with psycopg.connect(connection_string) as conn:
         with conn.cursor() as cur:
             start_time = datetime.datetime.now()
 
             cur.execute(query)
 
             end_time = datetime.datetime.now()
 
             time_taken = (end_time - start_time).total_seconds()
 
             return time_taken
 
 
 if __name__ == '__main__':
     ####################################################################################################################
 
     # test parameters
 
     MODE_CHOICES = 'query_only', 'return_results', 'output_csv'
 
     SELECTED_MODE = 'query_only'
 
     # return_results sub-parameters
     as_dict = False
     as_df = True
     rows_to_print = 5
     set_trace = True
 
     # output_csv sub-parameters
     fetch_all = False
 
     ####################################################################################################################
 
     if SELECTED_MODE == 'query_only':
         print(
             f'Query time taken in seconds: {time_to_fetch()}'
         )
     elif SELECTED_MODE == 'output_csv':
         print(
             f'Query time taken in seconds: {time_to_fetch_and_output_csv(fetchall=fetch_all)}'
         )
     elif SELECTED_MODE == 'return_results':
         results, time_taken_in_seconds = time_to_fetch_and_return(
             as_dict=as_dict,
             as_df=as_df
         )
 
         if as_df:
             print(
                 results.head(
                     rows_to_print
                 )
             )
         else:
             if not as_dict:
                 print(
                     get_column_names()
                 )
 
             for row_to_print in results[:rows_to_print]:
                 print(
                     row_to_print
                 )
 
         print(
             f'Query time taken in seconds: {time_taken_in_seconds}'
         )
 
         if set_trace:
             import pdb; pdb.set_trace()
     else:
         print(f'INVALID MODE SELECTED! CHOICES ARE: {MODE_CHOICES}')