Implementation of Threads

In this chapter, we will learn how to implement threads in Python.
Python threads are sometimes called lightweight processes because threads occupy much less memory than processes. Threads allow performing multiple tasks at once. In Python, we have the following two modules that implement threads in a program −
<_thread>module
<_thread>module
<threading>module
<threading>module
The main difference between these two modules is that <_thread> module treats a thread as a function whereas, the <threading> module treats every thread as an object and implements it in an object oriented way. Moreover, the <_thread>module is effective in low level threading and has fewer capabilities than the <threading> module.
In the earlier version of Python, we had the <thread> module but it has been considered as "deprecated" for quite a long time. Users have been encouraged to use the <threading> module instead. Therefore, in Python 3 the module "thread" is not available anymore. It has been renamed to "<_thread>" for backwards incompatibilities in Python3.
To generate new thread with the help of the <_thread> module, we need to call the start_new_thread method of it. The working of this method can be understood with the help of following syntax −
_thread.start_new_thread ( function, args[, kwargs] )

Here −
args is a tuple of arguments
args is a tuple of arguments
kwargs is an optional dictionary of keyword arguments
kwargs is an optional dictionary of keyword arguments
If we want to call function without passing an argument then we need to use an empty tuple of arguments in args.
This method call returns immediately, the child thread starts, and calls function with the passed list, if any, of args. The thread terminates as and when the function returns.
Following is an example for generating new thread by using the <_thread> module. We are using the start_new_thread() method here.
import _thread
import time

def print_time( threadName, delay):
   count = 0
   while count < 5:
      time.sleep(delay)
      count += 1
      print ("%s: %s" % ( threadName, time.ctime(time.time()) ))

try:
   _thread.start_new_thread( print_time, ("Thread-1", 2, ) )
   _thread.start_new_thread( print_time, ("Thread-2", 4, ) )
except:
   print ("Error: unable to start thread")
while 1:
   pass
The following output will help us understand the generation of new threads bwith the help of the <_thread> module.
Thread-1: Mon Apr 23 10:03:33 2018
Thread-2: Mon Apr 23 10:03:35 2018
Thread-1: Mon Apr 23 10:03:35 2018
Thread-1: Mon Apr 23 10:03:37 2018
Thread-2: Mon Apr 23 10:03:39 2018
Thread-1: Mon Apr 23 10:03:39 2018
Thread-1: Mon Apr 23 10:03:41 2018
Thread-2: Mon Apr 23 10:03:43 2018
Thread-2: Mon Apr 23 10:03:47 2018
Thread-2: Mon Apr 23 10:03:51 2018

The <threading> module implements in an object oriented way and treats every thread as an object. Therefore, it provides much more powerful, high-level support for threads than the <_thread> module. This module is included with Python 2.4.
The <threading> module comprises all the methods of the <_thread> module but it provides additional methods as well. The additional methods are as follows −
threading.activeCount() − This method returns the number of thread objects that are active
threading.activeCount() − This method returns the number of thread objects that are active
threading.currentThread() − This method returns the number of thread objects in the caller's thread control.
threading.currentThread() − This method returns the number of thread objects in the caller's thread control.
threading.enumerate() − This method returns a list of all thread objects that are currently active.
threading.enumerate() − This method returns a list of all thread objects that are currently active.
For implementing threading, the <threading> module has the Thread class which provides the following methods −
run() − The run() method is the entry point for a thread.
run() − The run() method is the entry point for a thread.
start() − The start() method starts a thread by calling the run method.
start() − The start() method starts a thread by calling the run method.
join([time]) − The join() waits for threads to terminate.
join([time]) − The join() waits for threads to terminate.
isAlive() − The isAlive() method checks whether a thread is still executing.
isAlive() − The isAlive() method checks whether a thread is still executing.
getName() − The getName() method returns the name of a thread.
getName() − The getName() method returns the name of a thread.
setName() − The setName() method sets the name of a thread.
setName() − The setName() method sets the name of a thread.
In this section, we will learn how to create threads using the <threading> module. Follow these steps to create a new thread using the <threading> module −
Step 1 − In this step, we need to define a new subclass of the Thread class.
Step 1 − In this step, we need to define a new subclass of the Thread class.
Step 2 − Then for adding additional arguments, we need to override the __init__(self [,args]) method.
Step 2 − Then for adding additional arguments, we need to override the __init__(self [,args]) method.
Step 3 − In this step, we need to override the run(self [,args]) method to implement what the thread should do when started.
Step 3 − In this step, we need to override the run(self [,args]) method to implement what the thread should do when started.
Now, after creating the new Thread subclass, we can create an instance of it and then start a new thread by invoking the start(), which in turn calls the run() method.
Consider this example to learn how to generate a new thread by using the <threading> module.
import threading
import time
exitFlag = 0

class myThread (threading.Thread):
   def __init__(self, threadID, name, counter):
      threading.Thread.__init__(self)
      self.threadID = threadID
      self.name = name
      self.counter = counter
   def run(self):
      print ("Starting " + self.name)
      print_time(self.name, self.counter, 5)
      print ("Exiting " + self.name)
def print_time(threadName, delay, counter):
   while counter:
      if exitFlag:
         threadName.exit()
      time.sleep(delay)
      print ("%s: %s" % (threadName, time.ctime(time.time())))
      counter -= 1

thread1 = myThread(1, "Thread-1", 1)
thread2 = myThread(2, "Thread-2", 2)

thread1.start()
thread2.start()
thread1.join()
thread2.join()
print ("Exiting Main Thread")
Starting Thread-1
Starting Thread-2
Now, consider the following output −
Thread-1: Mon Apr 23 10:52:09 2018
Thread-1: Mon Apr 23 10:52:10 2018
Thread-2: Mon Apr 23 10:52:10 2018
Thread-1: Mon Apr 23 10:52:11 2018
Thread-1: Mon Apr 23 10:52:12 2018
Thread-2: Mon Apr 23 10:52:12 2018
Thread-1: Mon Apr 23 10:52:13 2018
Exiting Thread-1
Thread-2: Mon Apr 23 10:52:14 2018
Thread-2: Mon Apr 23 10:52:16 2018
Thread-2: Mon Apr 23 10:52:18 2018
Exiting Thread-2
Exiting Main Thread

There are five thread states - new, runnable, running, waiting and dead. Among these five Of these five, we will majorly focus on three states - running, waiting and dead. A thread gets its resources in the running state, waits for the resources in the waiting state; the final release of the resource, if executing and acquired is in the dead state.
The following Python program with the help of start(), sleep() and join() methods will show how a thread entered in running, waiting and dead state respectively.
Step 1 − Import the necessary modules, <threading> and <time>
import threading
import time
Step 2 − Define a function, which will be called while creating a thread.
def thread_states():
   print("Thread entered in running state")
Step 3 − We are using the sleep() method of time module to make our thread waiting for say 2 seconds.
time.sleep(2)
Step 4 − Now, we are creating a thread named T1, which takes the argument of the function defined above.
T1 = threading.Thread(target=thread_states)
Step 5 − Now, with the help of the start() function we can start our thread. It will produce the message, which has been set by us while defining the function.
T1.start()
Thread entered in running state
Step 6 − Now, at last we can kill the thread with the join() method after it finishes its execution.
T1.join()
In python, we can start a new thread by different ways but the easiest one among them is to define it as a single function. After defining the function, we can pass this as the target for a new threading.Thread object and so on. Execute the following Python code to understand how the function works −
import threading
import time
import random
def Thread_execution(i):
   print("Execution of Thread {} started\n".format(i))
   sleepTime = random.randint(1,4)
   time.sleep(sleepTime)
   print("Execution of Thread {} finished".format(i))
for i in range(4):
   thread = threading.Thread(target=Thread_execution, args=(i,))
   thread.start()
   print("Active Threads:" , threading.enumerate())
Execution of Thread 0 started
Active Threads:
   [<_MainThread(MainThread, started 6040)>,
      <HistorySavingThread(IPythonHistorySavingThread, started 5968)>,
      <Thread(Thread-3576, started 3932)>]

Execution of Thread 1 started
Active Threads:
   [<_MainThread(MainThread, started 6040)>,
      <HistorySavingThread(IPythonHistorySavingThread, started 5968)>,
      <Thread(Thread-3576, started 3932)>,
      <Thread(Thread-3577, started 3080)>]

Execution of Thread 2 started
Active Threads:
   [<_MainThread(MainThread, started 6040)>,
      <HistorySavingThread(IPythonHistorySavingThread, started 5968)>,
      <Thread(Thread-3576, started 3932)>,
      <Thread(Thread-3577, started 3080)>,
      <Thread(Thread-3578, started 2268)>]

Execution of Thread 3 started
Active Threads:
   [<_MainThread(MainThread, started 6040)>,
      <HistorySavingThread(IPythonHistorySavingThread, started 5968)>,
      <Thread(Thread-3576, started 3932)>,
      <Thread(Thread-3577, started 3080)>,
      <Thread(Thread-3578, started 2268)>,
      <Thread(Thread-3579, started 4520)>]
Execution of Thread 0 finished
Execution of Thread 1 finished
Execution of Thread 2 finished
Execution of Thread 3 finished

Before implementing the daemon threads in Python, we need to know about daemon threads and their usage. In terms of computing, daemon is a background process that handles the requests for various services such as data sending, file transfers, etc. It would be dormant if it is not required any more. The same task can be done with the help of non-daemon threads also. However, in this case, the main thread has to keep track of the non-daemon threads manually. On the other hand, if we are using daemon threads then the main thread can completely forget about this and it will be killed when main thread exits. Another important point about daemon threads is that we can opt to use them only for non-essential tasks that would not affect us if it does not complete or gets killed in between. Following is the implementation of daemon threads in python −
import threading
import time

def nondaemonThread():
   print("starting my thread")
   time.sleep(8)
   print("ending my thread")
def daemonThread():
   while True:
   print("Hello")
   time.sleep(2)
if __name__ == '__main__':
   nondaemonThread = threading.Thread(target = nondaemonThread)
   daemonThread = threading.Thread(target = daemonThread)
   daemonThread.setDaemon(True)
   daemonThread.start()
   nondaemonThread.start()
In the above code, there are two functions namely >nondaemonThread() and >daemonThread(). The first function prints its state and sleeps after 8 seconds while the the deamonThread() function prints Hello after every 2 seconds indefinitely. We can understand the difference between nondaemon and daemon threads with the help of following output −
Hello

starting my thread
Hello
Hello
Hello
Hello
ending my thread
Hello
Hello
Hello
Hello
Hello


    57 Lectures 
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 Denis Tishkov
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