A thread of execution is the smallest unit of programming commands. In computer science, multithreaded applications allow for multiple threads to exist within the same process simultaneously, in order to implement concurrency and parallelism. Multithreading provides a variety of advantages, in execution time, responsiveness, and the efficiency of resource consumption.

The threading module in Python 3, which is commonly considered superior to the old thread module, provides an efficient, powerful, and high-level API to work with threads while implementing multithreaded applications in Python, including options to spawn new threads dynamically and synchronize threads through different locking mechanisms.

Queuing and priority queuing are important data structures in the field of computer science, and they are essential concepts in concurrent and parallel programming. They allow for multithreaded applications to efficiently execute and complete their threads in an accurate manner, ensuring that the shared resources are processed in a specific and dynamic order.

In the next chapter, we will discuss a more advanced function of Python, the with statement, and how it complements the use of multithreaded programming in Python.