The threading.stack_size function in Python’s threading module allows you to get or set the stack size used for new threads. This can be useful for controlling the memory usage of threads, especially in applications that create many threads or require large stacks for deep recursion.
The threading.setprofile function in Python’s threading module sets a profile function for all threads started from the calling thread. This is useful for profiling the execution of threads, allowing you to gather performance metrics and analyze the behavior of your multithreaded application.
The threading.settrace function in Python’s threading module sets a trace function for all threads started from the calling thread. This can be useful for debugging and profiling, as it allows you to track the execution of all threads.
The threading.get_native_id function in Python’s threading module returns the native thread identifier of the current thread. This identifier is an integer assigned by the operating system (OS) and can be useful for debugging and logging purposes.
The threading.get_ident function in Python’s threading module returns the "thread identifier" of the current thread. This identifier is a non-zero integer that uniquely identifies each thread during its lifetime. It can be useful for debugging and logging purposes.
The threading.main_thread function in Python’s threading module returns the main Thread object. This is useful for getting information about the main thread of the program, such as its name and status.
The threading.enumerate function in Python’s threading module returns a list of all Thread objects currently alive. This is useful for monitoring the state of your application’s threads and getting information about all active threads.
The threading.current_thread function in Python’s threading module returns the current Thread object corresponding to the caller’s thread of control. This is useful for getting information about the currently executing thread.
The threading.active_count function in Python’s threading module returns the number of Thread objects currently alive. This is useful for monitoring the state of your application’s threads, such as determining how many threads are running at a given moment.
The threading.local class in Python’s threading module provides a way to manage thread-local data. Each thread that accesses a threading.local instance will have its own independent value for the attributes stored in it. This is useful for storing data that should not be shared between threads.
The threading.Barrier class in Python’s threading module provides a way to synchronize a fixed number of threads. This is useful for scenarios where multiple threads need to wait for each other to reach a certain point before continuing execution.
The threading.Timer class in Python’s threading module provides a way to execute a function after a specified delay. This is useful for scheduling tasks to run after a certain period of time has elapsed.
The threading.BoundedSemaphore class in Python’s threading module is a subclass of threading.Semaphore that ensures the semaphore’s value does not exceed its initial value. This is useful for preventing programming errors where a semaphore might be released more times than it was acquired.
The threading.Semaphore class in Python’s threading module provides a way to manage a counter that is decremented each time a thread acquires the semaphore and incremented each time a thread releases it. This is useful for controlling access to a resource that has a limited capacity.
The threading.Event class in Python’s threading module provides a simple mechanism for signaling between threads. It allows one or more threads to wait until they are notified that an event has occurred.
The threading.Condition class in Python’s threading module provides a mechanism for threads to wait until they are notified. This is useful for scenarios where threads need to coordinate their actions and wait for certain conditions to be met before continuing execution.
The threading.RLock class in Python’s threading module provides a reentrant lock, which allows a thread to acquire the lock multiple times before releasing it. This is useful for more complex synchronization scenarios where a thread might need to re-acquire the lock it already holds.
The threading.Lock class in Python’s threading module provides a simple mechanism for mutual exclusion, allowing only one thread to access a resource at a time. This is useful for preventing race conditions in multithreaded programs.
The threading.Thread class in Python’s threading module allows you to create and manage threads. This is useful for concurrent execution of tasks, making it possible to run multiple operations simultaneously.