threading.Thread() is one of the standard libraries in Python, providing a way to perform asynchronous tasks in the background easily.
It can be used without installing any external libraries and is useful for implementing simple parallel processing.

Python threading.Thread structure

1. When to Use

  • When the task takes a long time but failure is not catastrophic
  • When you want to quickly respond to users on a web server and handle the remaining post-processing separately
  • When you want to implement lightweight asynchronous processing before introducing heavy systems like Celery or Redis

2. Criteria for Use

Situation Recommendation
When you want to respond quickly ✅ Suitable for use
When the task duration is short or moderate ✅ Suitable for use
When failure of the task is not critical ✅ Suitable for use
When stability and monitoring are important ❌ Recommended to use something like Celery
When database transactions need to be handled carefully ⚠️ Caution needed with ORM usage

3. Example of Use

import threading
import time

def background_task():
    print("Starting background task")
    time.sleep(3)
    print("Background task completed")

# Execute thread
thread = threading.Thread(target=background_task)
thread.start()

print("Main thread finished")

target=function_name: Specifies the function to execute
You can pass arguments with args=(arg1, arg2, ...)
The thread will only run when .start() is called

4. Notes for Use in Django

  • Django's ORM is not thread-safe, so be careful with DB transaction handling
  • Exceptions raised inside threads are not automatically caught → Always use try/except
  • If you need to use request-related information inside a thread, ensure its validity (e.g., request.user, etc.)
  • It is recommended to implement logging to detection of post-processing failures

5. Summary

Advantages Disadvantages
Convenience (no installation needed) No automatic retries/monitoring
Improved response speed Potential conflicts with ORM
Possibility of ultra-lightweight asynchronous processing Difficulty managing task failures

6. Jesse's Comment

threading.Thread() is an excellent way to perform asynchronous processing quickly without putting too much load on the server.
As a middle step before migrating to Celery, it can be a sufficiently powerful tool in practice.