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Concurrency & performance

asyncio, threading, multiprocessing, and profiling-friendly performance patterns.

3 matches

How to Parse JSON Files in Parallel with Python ThreadPoolExecutor

Load and transform JSON records from multiple files concurrently using ThreadPoolExecutor for faster I/O-bound parsing.

import time
from concurrent.futures import ThreadPoolExecutor
import json

def load_json_file(path):
    with open(path, 'r') as f:
        return json.load(f)

def transform_record(record):
    record['full_name'] = f"{record.pop('first_name', '')} {record.pop('last_name', '')}".strip()
    record['score'] = int(reco…

17 0 Open

Concurrency & performance medium

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.

asyncio executor concurrency

Python

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_…

14 0 Open

Concurrency & performance medium

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.

threads concurrency performance

Python

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."""
  …

13 0 Open

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