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Monitor thread activity with ease using threading.active_count() in Python!

# Python Threading: How to Use `threading.active_count()`

The `threading.active_count()` method in Python returns the number of alive Thread objects at the moment. The count returned is equal to the length of the list returned by `enumerate()`.

### Understanding `threading.active_count()`
– **`threading.current_thread()`**: Returns the current Thread object corresponding to the caller’s controlling thread. If the caller’s controlling thread was not created through the threading module, a limited dummy thread object is returned.
– **`threading.excepthook(args…)`**: Handles uncaught exceptions raised by `Thread.run()`. The attributes of the `args` argument are:
– `exc_type`: The type of exception. If it is `SystemExit`, the exception is silently ignored; otherwise, the exception is printed on `sys.stderr`.
– `exc_value`: The exception value, which can be `None`.
– `exc_traceback`: The exception traceback, which can be `None`.
– `thread`: The thread that raised the exception, which can be `None`.

### Additional Thread Methods:
– **`threading.get_ident()`**: Returns the ‘thread identifier’ of the current thread, which is a non-zero integer. This value is used as a magic cookie, for example, to index into a dictionary of thread-specific data. The thread identifier can be recycled when a thread ends and another is created.
– **`threading.get_native_id()`**: Returns the native integer thread ID assigned by the kernel to the current thread, which is a non-negative integer.
– **`threading.enumerate()`**: Returns a list of all threads currently running.
– **`threading.main_thread()`**: Returns the main thread object. Under normal conditions, the main thread is the thread where the Python interpreter was started.
– **`threading.settrace(func)`**: Sets a trace function for all threads started in the threading module. The `func` is passed to each thread via `sys.settrace()` before the `run()` method is called.
– **`threading.stack_size([size])`**: Returns the stack size used when creating a new thread.
– **`threading.TIMEOUT_MAX`**: The maximum value allowed for the `timeout` parameter of blocking functions like `Lock.acquire()`, `RLock.acquire()`, `Condition.wait()`, etc. Specifying a timeout greater than this value results in an `OverflowError`.

### Example Using `threading.active_count()`
import threading

def my_function():
print(“Hello, I’m running in a thread!”)

# Create a thread and start it
thread = threading.Thread(target=my_function)

### Conclusion
In this discussion, we have explored the usage of `threading.active_count()` in Python threading. This method provides valuable information about the current number of active Thread objects in a program. By understanding and utilizing this method effectively, developers can better manage and monitor the concurrent execution of threads in their Python applications.