multithreading can significantly improve the speed of computation on multiprocessor or multi-core systems because each processor or core handles separate thread concurrently multithreading allows program to remain responsive while one thread waits for inputand another runs gui at the same time this statement holds true for both multiprocessor or single processor systems all the threads of process have access to its global variables if global variable changes in one threadit is visible to other threads as well thread can also have its own local variables disadvantages of multithreadingon single processor systemmultithreading won' hit the speed of computation the performance may downgrade due to the overhead of managing threads synchronization is needed to prevent mutual exclusion while accessing shared resources it directly leads to more memory and cpu utilization multithreading increases the complexity of the programthus also making it difficult to debug it raises the possibility of potential deadlocks it may cause starvation when thread doesn' get regular access to shared resources the application would then fail to resume its work summary in this python multithreading tutorialyou'll get to see different methods to create threads and learn to implement synchronization for thread-safe operations each section of this post includes an example and the sample code to explain the concept step by step by the waymultithreading is core concept of software programming that almost all the high-level programming languages support bibliography