对于C#应用程序,我使用了一个backgroundqueue,在那里我可以排队' action' in。我希望在Python中也这样做。
背景队列应该排队'一个'行动'它包含对函数的调用(带或不带变量),并且应该在主程序继续执行自己的功能时继续执行任务。
我已经尝试过使用rq,但这似乎不起作用。我很乐意听到一些建议!
编辑: 这是关于的代码:
class DatabaseHandler:
def __init__(self):
try:
self.cnx = mysql.connector.connect(user='root', password='', host='127.0.0.1', database='mydb')
self.cnx.autocommit = True
self.loop = asyncio.get_event_loop()
except mysql.connector.Error as err:
if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:
print("Something is wrong with your user name or password")
elif err.errno == errorcode.ER_BAD_DB_ERROR:
print("Database does not exist")
else:
print(err)
self.get_new_entries(30.0)
async def get_new_entries(self, delay):
start_time = t.time()
while True:
current_time = datetime.datetime.now() - datetime.timedelta(seconds=delay)
current_time = current_time.strftime("%Y-%m-%d %H:%M:%S")
data = current_time
print(current_time)
await self.select_latest_entries(data)
print("###################")
t.sleep(delay - ((t.time() - start_time) % delay))
async def select_latest_entries(self, input_data):
query = """SELECT FILE_NAME FROM `added_files` WHERE CREATION_TIME > %s"""
cursor = self.cnx.cursor()
await cursor.execute(query, (input_data,))
async for file_name in cursor.fetchall():
file_name_string = ''.join(file_name)
self.loop.call_soon(None, self.handle_new_file_names, file_name_string)
cursor.close()
def handle_new_file_names(self, filename):
# self.loop.run_in_executor(None, NF.create_new_npy_files, filename)
# self.loop.run_in_executor(None, self.update_entry, filename)
create_new_npy_files(filename)
self.update_entry(filename)
def update_entry(self, filename):
print(filename)
query = """UPDATE `added_files` SET NPY_CREATED_AT=NOW(), DELETED=1 WHERE FILE_NAME=%s"""
update_cursor = self.cnx.cursor()
self.cnx.commit()
update_cursor.execute(query, (filename,))
update_cursor.close()
如果有意义的话,create_new_npy_files(filename)
是静态类的静态方法。这是一个非常耗时的功能(1-2秒)
答案 0 :(得分:3)
如果要执行的操作很短且无阻塞,您可以使用call_soon
:
loop = asyncio.get_event_loop()
loop.call_soon(action, args...)
如果操作可能需要更长时间或可能阻止,请使用run_in_executor
将它们提交到线程池:
loop = asyncio.get_event_loop()
future = loop.run_in_executor(None, action, args...)
# you can await the future, access its result once ready, etc.
请注意,上述两个代码段都假定您已在程序中使用asyncio
,具体取决于python-asyncio
标记。这意味着您的select_statement
将如下所示:
async def select_statement():
loop = asyncio.get_event_loop()
while True:
# requires an async-aware db module
await cursor.execute(query, (input_data,))
async for file_name in cursor.fetchall():
loop.call_soon(self.handle_new_file_names, file_name_string))
# or loop.run_in_executor(...)