In concurrent applications, inspecting active thread names aids debugging and system observability. Python’s built-in threading module provides utilities to enumerate and identify threads.

The threading.enumerate() function returns a list of all currently alive Thread objects. Each thread object exposes a name attribute that can be accessed directly:

import threading

def list_active_thread_names():
    return [t.name for t in threading.enumerate()]

# Example usage
for thread_name in list_active_thread_names():
    print(thread_name)

When spawning new threads, assigning meaningful names improves traceability. This is done via the name parameter in the Thread constructor:

import threading

def task():
    current = threading.current_thread()
    print(f"Executing in thread: {current.name}")

worker = threading.Thread(target=task, name="DataProcessor")
worker.start()
worker.join()

Adopting clear and distinct naming conventions—such as including role or purpose in the name—enhances log readability and simplifies runtime diagnostics. While Python allows duplicate thread names, using unique identifiers per thread is recommended for clarity in complex systems.