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jayraj175coder · jayraj175coder · commit c3c8dedd8efd · 2024-06-01T12:23:37.000+05:30
diff --git a/contrib/advanced-python/MultiThreadingg.md b/contrib/advanced-python/MultiThreadingg.md
@@ -1,14 +1,16 @@
                                                   # MultiThreading in python
 >> Introduction
-       Multithreading in Python allows you to run multiple threads (smaller units of a process) simultaneously, enabling concurrent execution of tasks. This can be particularly useful for I/O-bound operations or when you need to perform multiple operations at the same time.
+           Multithreading in Python allows you to run multiple threads (smaller units of a process) simultaneously, enabling concurrent execution of 
+      tasks. This can be particularly useful for I/O-bound operations or when you need to perform multiple operations at the same time.
 
 >> Why Use Multithreading?
    1.Improved performance: Allows multiple tasks to run concurrently, which can lead to more efficient utilization of resources.
    2.Responsive applications: Keeps your applications responsive, especially during long-running operations.
    3.Better resource utilization: Makes better use of system resources, especially in I/O-bound applications.
 
   - Threading Module
-    Python's threading module provides a way to create and manage threads. It includes the Thread class, which represents an individual thread of execution.
+     Python's threading module provides a way to create and manage threads. It includes the Thread class, which represents an individual thread of 
+     execution.
 
  **Creating a Thread**
      To create a new thread, you can instantiate the Thread class and provide a target function to be executed by the thread.
@@ -30,7 +32,8 @@ thread.start()
 thread.join()
 
  - Synchronizing Threads
-     When multiple threads access shared resources, synchronization is necessary to avoid data corruption. The threading module provides synchronization primitives like Lock, RLock, Semaphore, and Condition.
+        When multiple threads access shared resources, synchronization is necessary to avoid data corruption. The threading module provides 
+      synchronization primitives like Lock, RLock, Semaphore, and Condition.
 
   - Example using Lock
 
@@ -55,7 +58,8 @@ for thread in threads:
     thread.join()
 
  - Thread Communication
-   Threads can communicate using shared variables, but this requires careful synchronization. Another approach is to use thread-safe data structures like Queue from the queue module.
+     Threads can communicate using shared variables, but this requires careful synchronization. Another approach is to use thread-safe data 
+      structures like Queue from the queue module.
 
  ** Example using Queue
 
@@ -109,9 +113,11 @@ Let's create a more comprehensive example to demonstrate multithreading in a rea
     thread.join()
 
      >> Common Pitfalls
-       1.Global Interpreter Lock (GIL): Python's GIL can limit the performance benefits of threading for CPU-bound tasks. Consider using multiprocessing for such tasks.
-       2.Race conditions: Ensure proper synchronization to avoid race conditions when accessing shared resources.
-Deadlocks: Be cautious of deadlocks when using multiple locks.
+        1.Global Interpreter Lock (GIL): Python's GIL can limit the performance benefits of threading for CPU-bound tasks. Consider using 
+         multiprocessing for such tasks.
+        2.Race conditions: Ensure proper synchronization to avoid race conditions when accessing shared resources.
+         Deadlocks: Be cautious of deadlocks when using multiple locks.
 
   >> Conclusion
-    Multithreading in Python is a powerful tool for concurrent execution, especially for I/O-bound tasks. By understanding and correctly implementing threading, you can significantly improve the performance and responsiveness of your applications.
+       Multithreading in Python is a powerful tool for concurrent execution, especially for I/O-bound tasks. By understanding and correctly 
+      implementing threading, you can significantly improve the performance and responsiveness of your applications.
