我将如何在 python 中创建一个 (async/threaded/task) 背景队列?
How would I go and create an (async/threaded/task) backgroundqueue in python?
对于 C# 应用程序,我使用了一个后台队列,我可以在其中排队 'actions'。我希望在 Python 中做同样的事情。
后台队列应该 'enqueue' 一个 'action' 包含对函数的调用(有或没有变量)并且应该在主程序继续执行其自己的功能时继续执行任务。
我已经尝试过使用 rq,但似乎不起作用。我很想听听一些建议!
编辑:
这段代码是关于:
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()
create_new_npy_files(filename)
是来自静态 class 的静态方法,如果这有意义的话。这是一个非常耗时的函数(1-2 秒)
如果要执行的动作很短non-blocking,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的时间或可能会阻塞,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,以上两个片段都假设您已经在程序中使用了 asyncio
,基于 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(...)
对于 C# 应用程序,我使用了一个后台队列,我可以在其中排队 'actions'。我希望在 Python 中做同样的事情。
后台队列应该 'enqueue' 一个 'action' 包含对函数的调用(有或没有变量)并且应该在主程序继续执行其自己的功能时继续执行任务。
我已经尝试过使用 rq,但似乎不起作用。我很想听听一些建议!
编辑: 这段代码是关于:
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()
create_new_npy_files(filename)
是来自静态 class 的静态方法,如果这有意义的话。这是一个非常耗时的函数(1-2 秒)
如果要执行的动作很短non-blocking,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的时间或可能会阻塞,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,以上两个片段都假设您已经在程序中使用了 asyncio
,基于 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(...)