我注意到你必须在查询后使用cursor.fetchone()来获取cursor.description中的列列表(即在[desc[0] for desc in curs.description])

我注意到你必须在查询后使用cursor.fetchone()来获取cursor.description中的列列表(即在[desc[0] for desc in curs.description])

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))

 # You can use this function
 def getColumns(cursorDescription):
     columnList = []
     for tupla in cursorDescription:
         columnList.append(tupla[0])
     return columnList 

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))