Concurrency & performance
asyncio, threading, multiprocessing, and profiling-friendly performance patterns.
How to Mock anyio.run Backends (asyncio vs trio) in Python
Demonstrates how to mock anyio.run to verify backend selection (asyncio or trio) without actually running the event loop.
import anyio
from unittest.mock import Mock, patch
async def fetch_data():
await anyio.sleep(0.1)
return {"data": 42}
def run_with_backend(backend: str):
async def main():
result = await fetch_data()
print(f"[{backend}] Result: {result}")
anyio.run(main, backend=backend)
if __nam…
How to Run Blocking Code in an Executor with asyncio in Python
This code runs blocking functions concurrently without stalling the event loop by offloading them to thread pool executors via asyncio.
import asyncio
import time
def blocking_task(name: str, duration: float) -> str:
"""Simulate a blocking operation."""
time.sleep(duration)
return f"Finished {name} after {duration}s"
async def main() -> None:
loop = asyncio.get_running_loop()
results = await asyncio.gather(
loop.run_in_…
How to Speed Up Downloads with ThreadPoolExecutor in Python
Compare sequential and thread-pool download loops to measure real speedup when I/O s bound.
import time
import threading
from concurrent.futures import ThreadPoolExecutor
def download_file(file_id):
"""Simulate fetching a file by sleeping briefly."""
time.sleep(0.2) # pretend network latency
return f"file_{file_id}"
def sequential_downloads(num_files):
"""Process files one at a time."""
…
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Concurrency & performance — Python code examples
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