Thread Synchronization Basics
In multithreaded programs, multiple threads often need to access and modify shared data. If two or more threads try to change a shared variable at the same time, you can encounter a race condition. A race condition happens when the outcome of a program depends on the unpredictable timing of threads, which can lead to incorrect or inconsistent results. For example, if two threads both increment a shared counter without coordination, both might read the same value before either writes back, causing one increment to be lost. To prevent this, you need a way to synchronize threads so that only one thread can access the critical section of code at a time.
Python provides synchronization primitives like the Lock from the threading module. A lock ensures that only one thread can enter a critical section at any given moment. When a thread acquires a lock, other threads trying to acquire it will wait until it is released. This prevents simultaneous access to shared resources and eliminates race conditions.
123456789101112131415161718192021import threading counter = 0 lock = threading.Lock() def increment(): global counter for _ in range(100000): with lock: counter += 1 threads = [] for _ in range(2): t = threading.Thread(target=increment) threads.append(t) t.start() for t in threads: t.join() print("Final counter value:", counter)
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In multithreaded programs, multiple threads often need to access and modify shared data. If two or more threads try to change a shared variable at the same time, you can encounter a race condition. A race condition happens when the outcome of a program depends on the unpredictable timing of threads, which can lead to incorrect or inconsistent results. For example, if two threads both increment a shared counter without coordination, both might read the same value before either writes back, causing one increment to be lost. To prevent this, you need a way to synchronize threads so that only one thread can access the critical section of code at a time.
Python provides synchronization primitives like the Lock from the threading module. A lock ensures that only one thread can enter a critical section at any given moment. When a thread acquires a lock, other threads trying to acquire it will wait until it is released. This prevents simultaneous access to shared resources and eliminates race conditions.
123456789101112131415161718192021import threading counter = 0 lock = threading.Lock() def increment(): global counter for _ in range(100000): with lock: counter += 1 threads = [] for _ in range(2): t = threading.Thread(target=increment) threads.append(t) t.start() for t in threads: t.join() print("Final counter value:", counter)
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