我也曾经面临过类似的问题。我用一个简单的技巧来解决这个问题。 假设您在一个列表中有这样的列名

col_name = ['a', 'b', 'c']

然后你就可以跟着做了

for row in cursor.fetchone():
    print zip(col_name, row)

你可以做的另一件事是创建一个游标，你可以通过它们的名字引用你的列(这是一个需要，导致我在第一个地方到这个页面):

import psycopg2
from psycopg2.extras import RealDictCursor

ps_conn = psycopg2.connect(...)
ps_cursor = psql_conn.cursor(cursor_factory=RealDictCursor)

ps_cursor.execute('select 1 as col_a, 2 as col_b')
my_record = ps_cursor.fetchone()
print (my_record['col_a'],my_record['col_b'])

>> 1, 2

执行SQL查询后，编写2.7中编写的python脚本

total_fields = len(cursor.description)    
fields_names = [i[0] for i in cursor.description   
    Print fields_names

要在单独的查询中获得列名，可以查询information_schema。表列。

#!/usr/bin/env python3

import psycopg2

if __name__ == '__main__':
  DSN = 'host=YOUR_DATABASE_HOST port=YOUR_DATABASE_PORT dbname=YOUR_DATABASE_NAME user=YOUR_DATABASE_USER'

  column_names = []

  with psycopg2.connect(DSN) as connection:
      with connection.cursor() as cursor:
          cursor.execute("select column_name from information_schema.columns where table_schema = 'YOUR_SCHEMA_NAME' and table_name='YOUR_TABLE_NAME'")
          column_names = [row[0] for row in cursor]

  print("Column names: {}\n".format(column_names))

要在相同的查询中获取列名作为数据行，您可以使用游标的description字段:

#!/usr/bin/env python3

import psycopg2

if __name__ == '__main__':
  DSN = 'host=YOUR_DATABASE_HOST port=YOUR_DATABASE_PORT dbname=YOUR_DATABASE_NAME user=YOUR_DATABASE_USER'

  column_names = []
  data_rows = []

  with psycopg2.connect(DSN) as connection:
    with connection.cursor() as cursor:
      cursor.execute("select field1, field2, fieldn from table1")
      column_names = [desc[0] for desc in cursor.description]
      for row in cursor:
        data_rows.append(row)

  print("Column names: {}\n".format(column_names))

摘自Mark Lutz的《Programming Python》:

curs.execute("Select * FROM people LIMIT 0")
colnames = [desc[0] for desc in curs.description]

如果你想获得一个已经关联列标头的pandas数据帧，试试这个:

import psycopg2, pandas

con=psycopg2.connect(
    dbname=DBNAME, 
    host=HOST, 
    port=PORT, 
    user=USER, 
    password=PASSWORD
)

sql = """
select * from x
"""

d = pandas.read_sql_query(sql,con)

con.close()

print(type(d))

print(pandas.DataFrame.head(d))