In a large real-world application, the modules and functions have to go through a lot of input and output-based tasks like reading or updating databases, communication with different micro-services, and request-response with clients or peers. These tasks may take a significant amount of time to complete.
The time taken in serving a request and responding to the client is called latency and programmers need to reduce latency as much as possible. This leads to the need for parallel processing where our application is able to execute some function or method with different parameters for different clients. We can achieve that using threading. A thread can execute a function in parallel with other threads. Each thread shares the same code, data, and files while they have their own stack and registers.
In Python, we can create and run threads using the threading module. This module in python provides powerful and high-level support for threads.
- Import the libraries. We will use threading module to create and run thread. To observe the output, we will create some delay using time module.
import threading import time
- Define a sample function that we will use to run on different threads. In this example lets make a function that prints the squares of numbers in the given list.
# A sample function to print squares def print_squares(thread_name, numbers): for number in numbers: print(thread_name, number**2) # Produce some delay to see the output # syntax: time.sleep(<time in seconds : float>) time.sleep(1)
- Now create 2 or more threads using the threading.Thread class. The syntax of creating a thread is given below:
Syntax: thread_object = threading.Thread(target=<function name>, args=<tuple of arguments you want to pass>)
# Creating 3 threads that execute the same function with different parameters thread1 = threading.Thread( target=print_squares, args=("thread1", [1, 2, 3, 4, 5])) thread2 = threading.Thread( target=print_squares, args=("thread2", [6, 7, 8, 9, 10])) thread3 = threading.Thread( target=print_squares, args=("thread3", [11, 12, 13, 14, 15]))
- Now we need to start the execution. The Thread class has a start() method that transit the thread in running mode. The threads will run until they are not completed.
# Start the threads thread1.start() thread2.start() thread3.start()
- We can block the program execution while all the threads are not completed using join() method of the Thread class.
# Join the threads before moving further thread1.join() thread2.join() thread3.join()
Below is the full code:
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