我在模型管理器上有一个自定义方法,该方法允许我使用postgreSQL
来监听来自数据库修改的通知。此代码的简短版本如下所示:
def listen_for_notify(self):
import select
import psycopg2
import psycopg2.extensions
from django.conf import settings
db_data = settings.DATABASES['default']
listened = None
returned_empty = None
search_timeout = 15
conn = psycopg2.connect(dbname=db_data['NAME'], user=db_data['USER'], password=db_data['PASSWORD'], host=db_data['HOST'], port=db_data['PORT'])
conn.set_isolation_level(psycopg2.extensions.ISOLATION_LEVEL_AUTOCOMMIT)
curs = conn.cursor()
curs.execute("LISTEN default;")
timeout = timezone.now() + timezone.timedelta(0, search_timeout)
while timezone.now() < timeout:
time_diff = timeout - timezone.now()
if select.select([conn], [], [], float(time_diff.seconds)) == ([], [], []):
listened = False
timeout = timezone.now()
else:
conn.poll()
while conn.notifies:
notify = conn.notifies.pop(0)
if notify.payload == "notified":
listened = True
returned_empty = False
timeout = timezone.now()
if notify.payload == 'search request returned empty':
listened = True
returned_empty = True
timeout = timezone.now()
curs.close()
conn.close()
return listened, returned_empty
如果我只能使用django.db
而不是使用psycopg2库,那将非常好。像这样:
def listen_for_notify(self):
from django.db import connection as conn
listened = None
returned_empty = None
search_timeout = 15
with conn.cursor() as curs
timeout = timezone.now() + timezone.timedelta(0, search_timeout)
while timezone.now() < timeout:
time_diff = timeout - timezone.now()
if select.select([conn], [], [], float(time_diff.seconds)) == ([], [], []):
listened = False
timeout = timezone.now()
else:
conn.poll()
while conn.notifies:
notify = conn.notifies.pop(0)
if notify.payload == "notified":
listened = True
returned_empty = False
timeout = timezone.now()
if notify.payload == 'search request returned empty':
listened = True
returned_empty = True
timeout = timezone.now()
return listened, returned_empty
我使用django.db
尝试了上述解决方案,但由于django.db.connection
对象没有fileno()
方法而无法使用。
当前是否不支持此功能,或者我缺少某些功能?尽管django.db
只是实际psycopg2
库的包装。所以我想知道为什么我不能在其上使用fileno()
方法。