如果你想把你所有的数据放在一个带列名的Pandas数据框架中:

cur.execute("select * from tablename")
datapoints = cur.fetchall()
cols = [desc[0] for desc in cur.description]
df = pd.DataFrame((datapoints) , columns=[cols])

摘自Mark Lutz的《Programming Python》:

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

如果你想从db查询中获得一个命名元组obj，你可以使用下面的代码片段:

from collections import namedtuple

def create_record(obj, fields):
    ''' given obj from db returns named tuple with fields mapped to values '''
    Record = namedtuple("Record", fields)
    mappings = dict(zip(fields, obj))
    return Record(**mappings)

cur.execute("Select * FROM people")
colnames = [desc[0] for desc in cur.description]
rows = cur.fetchall()
cur.close()
result = []
for row in rows:
    result.append(create_record(row, colnames))

这允许您访问记录值，如果他们是类属性，即。

记录。id、记录。other_table_column_name等等。

或者更短

from psycopg2.extras import NamedTupleCursor
with cursor(cursor_factory=NamedTupleCursor) as cur:
   cur.execute("Select * ...")
   return cur.fetchall()

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))

如果你想把你所有的数据放在一个带列名的Pandas数据框架中:

cur.execute("select * from tablename")
datapoints = cur.fetchall()
cols = [desc[0] for desc in cur.description]
df = pd.DataFrame((datapoints) , columns=[cols])

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