我想用 self 参数线程化一个函数
I want to thread a function with the self parameter
我想对这个函数进行线程化处理,但不知道在设置了 self 参数后如何进行线程化处理。任何人都知道我该怎么做。我会很感激
这是函数
def processinformation(self):
app = App.get_running_app()
session = requests.Session()
self.notif_stream = session.get("**********************************" + app.displayname + "/.json", stream=True)
for line in self.notif_stream.iter_lines():
if line:
print(json.loads(line))
newline = ast.literal_eval(line.decode('utf-8'))
for key, thevalue in newline.items():
for key, value in thevalue.items():
self.notif = session.get("**********************************" + app.displayname + "/" + key + "/" + "notification" + "/.json")
self.notificationslist.adapter.data.extend([value])
好的,我通常没有太多理由编写多线程 Python 程序,但这似乎可行:
#!/usr/bin/env python3
import threading
class MyTarget:
def mymethod(self, arg1, arg2):
print(f"MyTarget, {arg1} {arg2}")
if __name__ == '__main__':
my_target = MyTarget()
t = threading.Thread(target=my_target.mymethod, args=("X", "Y"))
t.start()
# NOTE: In any _real_ program, the main thread would do
# something else, concurrently with the new thread.
t.join()
我想对这个函数进行线程化处理,但不知道在设置了 self 参数后如何进行线程化处理。任何人都知道我该怎么做。我会很感激
这是函数
def processinformation(self):
app = App.get_running_app()
session = requests.Session()
self.notif_stream = session.get("**********************************" + app.displayname + "/.json", stream=True)
for line in self.notif_stream.iter_lines():
if line:
print(json.loads(line))
newline = ast.literal_eval(line.decode('utf-8'))
for key, thevalue in newline.items():
for key, value in thevalue.items():
self.notif = session.get("**********************************" + app.displayname + "/" + key + "/" + "notification" + "/.json")
self.notificationslist.adapter.data.extend([value])
好的,我通常没有太多理由编写多线程 Python 程序,但这似乎可行:
#!/usr/bin/env python3
import threading
class MyTarget:
def mymethod(self, arg1, arg2):
print(f"MyTarget, {arg1} {arg2}")
if __name__ == '__main__':
my_target = MyTarget()
t = threading.Thread(target=my_target.mymethod, args=("X", "Y"))
t.start()
# NOTE: In any _real_ program, the main thread would do
# something else, concurrently with the new thread.
t.join()