Multithreading in Python: Concurrent Execution for Improved Performance

By default, a computer program executes the instructions in a sequential manner, from start to the end. Multithreading refers to the mechanism of dividing the main task in more than one sub-tasks and executing them in an overlapping manner. This makes the execution faster as compared to single thread.

The operating system is capable of handling multiple processes concurrently. It allocates a separate memory space to each process, so that one process cannot access or write anything other's space. A thread on the other hand can be thought of as a light-weight sub-process in a single program. Threads of a single program share the memory space allocated to it.

Multiple threads within a process share the same data space with the main thread and can therefore share information or communicate with each other more easily than if they were separate processes.

As they are light-weight, do not require much memory overhead; they are cheaper than processes.

A process always starts with a single thread (main thread). As and when required, a new thread can be started and sub task is delegated to it. Now the two threads are working in an overlapping manner. When the task assigned to the secondary thread is over, it merges with the main thread.

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