Concurrency & performance
asyncio, threading, multiprocessing, and profiling-friendly performance patterns.
How to Use a Weakref Cache to Avoid Memory Leaks in Python
This code demonstrates building a value cache with weakref.WeakValueDictionary so objects can be garbage collected when no longer referenced, preventing memory leaks.
import weakref
import gc
class ExpensiveObject:
def __init__(self, name):
self.name = name
def __repr__(self):
return f"ExpensiveObject('{self.name}')"
class ObjectCache:
def __init__(self):
self._cache = weakref.WeakValueDictionary()
def get_or_create(self, name):
…How to Use threading.local for Per-Thread Data in Python
Use threading.local to keep thread-specific data — each thread gets its own copy of the attribute, so values don't leak between threads.
import threading
import time
local_storage = threading.local()
def worker(name):
local_storage.name = name
time.sleep(0.1)
print(f"Thread {threading.current_thread().name}: {local_storage.name}")
if __name__ == "__main__":
threads = []
for i in range(3):
t = threading.Thread(target=worke…Browse by section
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Concurrency & performance — Python code examples
What you will find here
This page collects concurrency & performance snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.