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Sync only changed files between two folders in Python
This code compares two folders and copies only the new or modified files from source to destination, skipping unchanged ones by comparing SHA-256 hashes.
import hashlib
from pathlib import Path
import shutil
def file_hash(path: Path, chunk_size: int = 8192) -> str:
hasher = hashlib.sha256()
with path.open("rb") as f:
for chunk in iter(lambda: f.read(chunk_size), b""):
hasher.update(chunk)
return hasher.hexdigest()
def sync_files(src: s…Benchmark Disk Write Speed in Python with tempfile
Benchmark raw disk write performance by writing a temporary file in 1MB chunks and measuring throughput in MB/s.
import os
import tempfile
import time
def benchmark_write(size_mb=50):
size_bytes = size_mb * 1024 * 1024
chunk = b'x' * 1024 * 1024 # 1 MB chunk
with tempfile.NamedTemporaryFile(delete=True) as tmp:
start = time.perf_counter()
written = 0
while written < size_bytes:
…How to sync a fork with upstream in Python
Run git fetch and merge commands from Python with subprocess to sync a forked repository with upstream/main.
import subprocess
import sys
def sync_fork_with_upstream():
"""Simulate syncing a forked repo with upstream via git commands."""
# Mock git operations: pretend to fetch from upstream and merge into main
fetch_result = subprocess.run(
["git", "fetch", "upstream"],
capture_output=True, tex…How to Mock a Fast uv pip sync in Python
Simulate a fast uv pip sync by mocking file operations and subprocess calls to test dependency installation workflows.
import os
import shutil
import subprocess
import sys
import tempfile
from pathlib import Path
def uv_pip_sync_fast_install_mock(requirements_text: str) -> dict:
"""Simulate a fast uv pip sync by mocking file operations and subprocess calls."""
mock_dir = Path(tempfile.mkdtemp(prefix="uv_mock_"))
req_lines…How to Memoize Async Functions with lru_cache in Python
Cache async function results with functools.lru_cache to avoid repeated expensive awaits, cutting total execution from ~0.4s to ~0.2s in this example.
from functools import lru_cache
import asyncio
@lru_cache(maxsize=128)
async def fetch_data(user_id: int) -> str:
# Simulate expensive async operation
await asyncio.sleep(0.1)
return f"Data for user {user_id}"
async def main():
start = asyncio.get_event_loop().time()
# First calls (miss cach…How to Run an Async Main with asyncio.run in Python
Show the canonical entry point for an asyncio program: define an async main, then launch it with asyncio.run.
import asyncio
async def main():
print("Hello from async main")
await asyncio.sleep(0.1)
print("Done")
if __name__ == "__main__":
asyncio.run(main())How to Signal asyncio Workers to Stop with an Event in Python
Use an asyncio.Event to coordinate graceful shutdown of multiple concurrent worker tasks in Python.
import asyncio
import random
async def worker(name, stop_event):
while not stop_event.is_set():
await asyncio.sleep(random.uniform(0.1, 0.5))
print(f"Worker {name} processing...")
print(f"Worker {name} stopped.")
async def main():
stop_event = asyncio.Event()
workers = [asyncio.create…How to Test HTTPX Async Client Pool Reuse with Mocks in Python
Mock an httpx.AsyncClient to verify connection pool reuse by asserting GET calls share a single client instance across concurrent async requests.
import asyncio
import httpx
from unittest.mock import AsyncMock, patch, Mock
async def fetch_with_pool(client, url, n_reuses=3):
results = []
for i in range(n_reuses):
resp = await client.get(url)
results.append(resp.status_code)
await asyncio.sleep(0) # yield to loop to mimic real us…How to Use ThreadPoolExecutor in Python for Parallel Processing
Use ThreadPoolExecutor with executor.map to run a function over many inputs concurrently and collect ordered results.
def worker(item):
return item * item
if __name__ == "__main__":
from concurrent.futures import ThreadPoolExecutor
numbers = list(range(1, 11))
with ThreadPoolExecutor(max_workers=4) as executor:
results = list(executor.map(worker, numbers))
print("Input: ", numbers)
print("Results:", …How to Use threading.Lock to Synchronize a Counter in Python
Safely increment a shared counter across multiple threads using threading.Lock as a mutex to prevent race conditions.
import threading
counter = 0
lock = threading.Lock()
def increment():
global counter
for _ in range(100000):
with lock:
counter += 1
threads = [threading.Thread(target=increment) for _ in range(5)]
for t in threads:
t.start()
for t in threads:
t.join()
print(f"Final counter valu…How to Use uvloop Faster Event Loop
Install uvloop at startup to replace asyncio's default event loop with a faster libuv-based one, with a graceful fallback when it's unavailable.
import asyncio
try:
import uvloop
uvloop.install()
USING_UVLOOP = True
except ImportError:
USING_UVLOOP = False
async def fetch_data(index):
await asyncio.sleep(0.01)
return f"data-{index}"
async def main():
tasks = [fetch_data(i) for i in range(10)]
results = await asyncio.gather(*…How to Wait for the First Future to Complete in Python
Use concurrent.futures.wait with FIRST_COMPLETED to pause until any task finishes and inspect the remaining pending futures.
import concurrent.futures
import time
def task(name, delay):
time.sleep(delay)
return f"{name} done"
if __name__ == "__main__":
with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
futures = [
executor.submit(task, "task1", 2),
executor.submit(task, "ta…How to set a timeout with asyncio.wait_for in Python
Use asyncio.wait_for to bound an async function with a timeout, catching TimeoutError when it exceeds the limit.
import asyncio
async def slow_task():
await asyncio.sleep(3)
return "finished"
async def main():
try:
result = await asyncio.wait_for(slow_task(), timeout=1)
print(result)
except asyncio.TimeoutError:
print("Task timed out")
if __name__ == "__main__":
asyncio.run(main())Run Background Tasks with asyncio.create_task in Python
Create background tasks in an asyncio event loop with asyncio.create_task and run them concurrently using asyncio.gather.
import asyncio
import time
async def background_worker(name, duration):
"""Simulates a long-running background task."""
print(f"{name} started at t={time.monotonic():.1f}")
await asyncio.sleep(duration)
print(f"{name} finished at t={time.monotonic():.1f}")
async def main():
print(f"Main starting …Synchronize Threads with a Barrier in Python
Demonstrates using threading.Barrier to synchronize multiple threads at phase boundaries, ensuring all workers wait for each other before proceeding.
import threading
import time
from random import randint
def worker(barrier, worker_id):
for phase in range(3):
time.sleep(randint(1, 3))
print(f"Worker {worker_id} finished phase {phase} at {time.time():.2f}")
barrier.wait()
print(f"Worker {worker_id}: all phases complete")
if __name_…Thread-Safe Producer Consumer Queue in Python
A producer-consumer pattern using thread-safe queue.Queue with two threads, demonstrating safe communication and synchronized task completion.
import queue
import threading
import time
import random
def producer(q, item_count):
for i in range(item_count):
item = random.randint(1, 100)
q.put(item)
print(f"Producer added: {item}")
time.sleep(0.1)
def consumer(q):
while True:
try:
item = q.get(time…asyncio sleep cooperative scheduling demo in Python
This demo shows how asyncio.sleep yields control between concurrent tasks, letting multiple workers interleave their ticks.
import asyncio
async def worker(name, delay):
for i in range(3):
print(f"{name}: tick {i}")
await asyncio.sleep(delay)
return f"{name} done"
async def main():
tasks = [
asyncio.create_task(worker("A", 0.1)),
asyncio.create_task(worker("B", 0.2)),
asyncio.create_tas…How to Build a WebSocket Echo Server in Python with asyncio
Create a simple WebSocket echo server using the websockets library and asyncio to handle concurrent connections.
import asyncio
import websockets
async def echo(websocket):
async for message in websocket:
await websocket.send(f"Echo: {message}")
async def main():
async with websockets.serve(echo, "localhost", 8765):
print("WebSocket server started on ws://localhost:8765")
await asyncio.Future() …How to Poll an Operation Status Endpoint in Python
Mock a polling endpoint in Python that simulates checking an async operation's status until it completes or times out.
import time
import random
def poll_status(url: str, timeout: float = 5.0) -> dict:
"""Mock a polling endpoint that eventually returns a completed status."""
start = time.time()
while time.time() - start < timeout:
# Simulate delayed response
time.sleep(0.2)
# 80% chance to report …How to Compose Parallel API Calls in Python with asyncio.gather
Compose multiple mock API responses in parallel using asyncio.gather with per-service simulated latency.
import asyncio
import random
import time
async def mock_api(name: str, delay: float) -> dict:
await asyncio.sleep(delay)
return {"service": name, "value": random.randint(1, 100)}
async def fetch_all():
services = {
"users": mock_api("users", 0.2),
"orders": mock_api("orders", 0.3),
…How to Optimize SQLite Database Performance in Python
A Python helper that creates an index, enables WAL mode, and tunes synchronous settings to optimize SQLite database performance.
import sqlite3
DATABASE_PATH = "beginners.db"
UNOPTIMIZED_TABLE_SCHEMA = """
CREATE TABLE IF NOT EXISTS users (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
email TEXT NOT NULL
)
"""
def optimize_database(db_path: str = DATABASE_PATH) -> dict:
with sqlite3.connect(db_path) as connection:
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