Respostas:
De "Programming Python", de Mark Lutz:
curs.execute("Select * FROM people LIMIT 0")
colnames = [desc[0] for desc in curs.description]
information_schema
.
curs.execute("Select userId FROM people") colnames = [desc[0] for desc in curs.description] assert colnames == ['userid']
Outra coisa que você pode fazer é criar um cursor com o qual você poderá referenciar suas colunas por seus nomes (essa é uma necessidade que me levou a esta página em primeiro lugar):
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
Para obter os nomes das colunas em uma consulta separada , você pode consultar a tabela information_schema.columns.
#!/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))
Para obter nomes de colunas na mesma consulta que as linhas de dados , você pode usar o campo de descrição do cursor:
#!/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))
Se você deseja ter um objeto de tupla nomeado na consulta db, pode usar o seguinte trecho:
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))
Isso permite que você acesse valores de registro como se fossem propriedades de classe, ou seja,
record.id, record.other_table_column_name etc.
ou ainda mais curto
from psycopg2.extras import NamedTupleCursor
with cursor(cursor_factory=NamedTupleCursor) as cur:
cur.execute("Select * ...")
return cur.fetchall()
Após executar a consulta SQL, escreva o seguinte script python escrito em 2.7
total_fields = len(cursor.description)
fields_names = [i[0] for i in cursor.description
Print fields_names
Notei que você deve usar cursor.fetchone()
após a consulta para obter a lista de colunas em cursor.description
(ou seja, em [desc[0] for desc in curs.description]
)
Eu também costumava enfrentar problemas semelhantes. Eu uso um truque simples para resolver isso. Suponha que você tenha nomes de colunas em uma lista como
col_name = ['a', 'b', 'c']
Então você pode fazer o seguinte
for row in cursor.fetchone():
print zip(col_name, row)
# You can use this function
def getColumns(cursorDescription):
columnList = []
for tupla in cursorDescription:
columnList.append(tupla[0])
return columnList
#!/usr/bin/python
import psycopg2
#note that we have to import the Psycopg2 extras library!
import psycopg2.extras
import sys
def main():
conn_string = "host='localhost' dbname='my_database' user='postgres' password='secret'"
# print the connection string we will use to connect
print "Connecting to database\n ->%s" % (conn_string)
# get a connection, if a connect cannot be made an exception will be raised here
conn = psycopg2.connect(conn_string)
# conn.cursor will return a cursor object, you can use this query to perform queries
# note that in this example we pass a cursor_factory argument that will
# dictionary cursor so COLUMNS will be returned as a dictionary so we
# can access columns by their name instead of index.
cursor = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)
# tell postgres to use more work memory
work_mem = 2048
# by passing a tuple as the 2nd argument to the execution function our
# %s string variable will get replaced with the order of variables in
# the list. In this case there is only 1 variable.
# Note that in python you specify a tuple with one item in it by placing
# a comma after the first variable and surrounding it in parentheses.
cursor.execute('SET work_mem TO %s', (work_mem,))
# Then we get the work memory we just set -> we know we only want the
# first ROW so we call fetchone.
# then we use bracket access to get the FIRST value.
# Note that even though we've returned the columns by name we can still
# access columns by numeric index as well - which is really nice.
cursor.execute('SHOW work_mem')
# Call fetchone - which will fetch the first row returned from the
# database.
memory = cursor.fetchone()
# access the column by numeric index:
# even though we enabled columns by name I'm showing you this to
# show that you can still access columns by index and iterate over them.
print "Value: ", memory[0]
# print the entire row
print "Row: ", memory
if __name__ == "__main__":
main()
curs.execute("SELECT * FROM people LIMIT 0")