In this chapter, we provided a high-level analysis of concurrent programs in Python, via scheduling, testing, and debugging. Scheduling can be done in Python via the APScheduler module, which provides powerful and flexible functionalities to specify how scheduled jobs should be executed later on in the future. Furthermore, the module allows scheduled jobs to be distributed and executed across different threads and processes, offering a concurrency improvement in testing speed.
Concurrency also introduces complex problems in terms of testing and debugging, resulting from simultaneous and parallel interactions between the agents in a program. However, these problems can be approached effectively, with methodical solutions and the appropriate tools.
This topic marks the end of our journey through Mastering Concurrency in Python. Throughout this book, we have considered and...
