Learn Creating and Managing Processes | Working with Processes


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import multiprocessing
import time

def worker():
    print("Process started")
    time.sleep(2)
    print("Process finished")

if __name__ == "__main__":
    process = multiprocessing.Process(target=worker)
    process.start()
    print("Main process continues")
    process.join()
    print("Main process waited for worker to finish")

The code sample above shows how to create and manage a process using Python's multiprocessing module.

Steps to Launch a Process

Define a function: Write a function, such as worker, containing the code to run in a separate process;
Create a Process object: Pass the target function to multiprocessing.Process;
Start the process: Call start() to launch the new process. It runs concurrently with the main process;
Main process continues: The main process can execute its own code while the child process runs;
Wait for completion: Call join() to make the main process wait until the child process finishes.

Understanding the Process Lifecycle

A process is created, started, runs independently, and then terminates when its target function completes.

Key Differences: Processes vs. Threads

Processes:
- Have their own memory space and resources;
- Do not share state directly with other processes;
- Require special mechanisms for communication, such as multiprocessing.Queue or Pipe;
- Are more robust for CPU-bound tasks and can use multiple CPU cores.
Threads:
- Share the same memory space within a process;
- Can access shared data easily, but this increases the risk of race conditions and data corruption;
- Are often used for I/O-bound tasks within the same memory space.

Tip: Use processes for tasks that need true parallelism and isolation. Use threads for tasks that need lightweight concurrency and easy data sharing.

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Section 3. Chapter 1

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              1234567891011121314
            
import multiprocessing
import time

def worker():
    print("Process started")
    time.sleep(2)
    print("Process finished")

if __name__ == "__main__":
    process = multiprocessing.Process(target=worker)
    process.start()
    print("Main process continues")
    process.join()
    print("Main process waited for worker to finish")