** “ The call stack ” And “ Threads ” Differences between **
The call stack ：
def a():
print('a() starts')
b()
d()
print('a() returns')
def b():
print('b() starts')
c()
print('b() returns')
def c():
print('c() starts')
print('c() returns')
def d():
print('d() starts')
print('d() returns')
a()
Thread code ：
import threading
import time
def worker():
print(threading.current_thread().getName(), 'Starting')
time.sleep(0.2)
print(threading.current_thread().getName(), 'Exiting')
def my_service():
print(threading.current_thread().getName(), 'Starting')
time.sleep(0.3)
print(threading.current_thread().getName(), 'Exiting')
t = threading.Thread(name='my_service', target=my_service)
w = threading.Thread(name='worker', target=worker)
w2 = threading.Thread(target=worker) # use default name
w.start()
w2.start()
t.start()
Thread running results ：
worker Starting
Thread-1 Starting
my_service Starting
worker Exiting
Thread-1 Exiting
my_service Exiting
Call stack run result ：
a() starts
b() starts
c() starts
c() returns
b() returns
d() starts
d() returns
a() returns
Understand the parallel process of threads and the running time of each thread , It is the foundation of learning to use threads ; Call the running process of the stack , yes python Basic operation mode of function call in , It is easier to understand local and global scopes .
