Python Program on Lock in Multithreading using Class & Object

Embarking on the next phase of Python practicality, we delve into the third part of our exploration of multithreading, emphasizing locks implemented through class and object structures. As we unveil the intricacies of thread synchronization, our goal is to provide a straightforward understanding of how incorporating classes and objects enhances the management of concurrent processes in Python.

Throughout this exploration, we’ll unravel practical examples and applications, shedding light on the seamless coordination achieved by merging locks with class and object structures.

Topic Explanation:

In the context of multithreading, effective synchronization is paramount to avoid conflicts and ensure orderly execution. Employing locks within class and object structures offers a structured approach to thread coordination. By encapsulating threads and lock mechanisms within custom classes, this method enhances code organization and readability, simplifying the complexities of managing shared resources in a multithreaded environment.

Furthermore, as we delve into practical examples, the utilization of classes and objects in conjunction with locks becomes a powerful tool for creating well-behaved multithreaded applications. The object-oriented nature of this approach allows for modular code design, making it easier to comprehend and maintain. By promoting a systematic and object-centric synchronization mechanism, this technique facilitates seamless coordination among threads, fostering a more efficient and reliable concurrent programming experience.

Prerequisites

• Basic understanding of Python programming.
• Familiarity with multithreading concepts in Python.
• Knowledge of shared resources and potential issues in concurrent programming.
• Understanding the concept of thread synchronization.
• Awareness of the role of locks in preventing conflicts among threads.

Code With Comments:

# Importing necessary libraries
from threading import *
import time

# Defining a class named Table
class Table:
    def __init__(self):
        # Initializing a Lock instance within the class constructor
        self.l = Lock()

    # Method to print the multiplication table
    def printtable(self, n):
        # Acquiring the lock to ensure exclusive access to shared resources
        self.l.acquire()
        for i in range(1, 11):
            # Printing the product of the number and the iteration
            print(n * i)
            # Introducing a delay to simulate a real-world scenario
            time.sleep(1)
        # Releasing the lock after completing the task
        self.l.release()

# Creating an instance of the Table class
T = Table()

# Creating threads with the printtable method and different arguments
T1 = Thread(target=T.printtable, args=(5,), name="First")
T2 = Thread(target=T.printtable, args=(9,), name="Second")

# Starting the threads
T1.start()
T2.start()

Output:
5 10 15 20 25 30 35 40 45 50 9 18 27 36 45 54 63 72 81 90

Code Explanation:

Importing Libraries:

• from threading import *: Importing the Thread class and other threading-related functions from the threading module.

Defining Table Class:

• class Table: …: Defining a class named Table to encapsulate the functionality.

Initializing Lock in Constructor:

• self.l = Lock(): Initializing a Lock instance within the class constructor to manage thread synchronization.

Method printtable:

• def printtable(self, n): …: Method to print the multiplication table with a lock to ensure thread safety.

Acquiring Lock:

• self.l.acquire(): Acquiring the lock before entering the critical section to prevent concurrent access to shared resources.

Printing Table:

• print(n * i): Printing the product of the number and the iteration.

Introducing Delay:

• time.sleep(1): Introducing a 1-second delay to simulate a scenario where threads perform tasks with varying durations.

Releasing Lock:

• self.l.release(): Releasing the lock after completing the critical section.

Creating an Instance of Table:

• T = Table(): Creating an instance of the Table class.

Creating Threads:

• T1 = Thread(target=T.printtable, args=(5,), name=”First”): Creating threads with the printtable method and different arguments.

Starting Threads:

• T1.start(): Starting the threads to execute the specified functions concurrently.

Conclusion:

Wrapping up our journey into thread synchronization with locks, employing class and object structures in Python’s multithreading environment unveils a strategic and object-oriented methodology. In exploring practical examples and applications, we’ve witnessed firsthand how this method facilitates smooth coordination among threads, showcasing the versatility and effectiveness of integrating locks with class and object structures. Comments. As we conclude this phase of our Python journey, the strategic use of locks was the most important to use the resource efficiently.

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