Concurrency: threads, processes, asyncio

import time
from concurrent.futures import ThreadPoolExecutor

def fetch(page):                 # stands in for an API call
    time.sleep(0.3)              # waiting on the network
    return f"page {page}: 100 rows"

start = time.perf_counter()
results = [fetch(p) for p in range(1, 6)]
print(f"one by one: {time.perf_counter() - start:.1f}s")

start = time.perf_counter()
with ThreadPoolExecutor(max_workers=5) as pool:
    results = list(pool.map(fetch, range(1, 6)))
print(f"5 threads:  {time.perf_counter() - start:.1f}s")
print(results[0], "...", results[-1])

one by one: 1.5s
5 threads:  0.3s
page 1: 100 rows ... page 5: 100 rows

import asyncio, time

async def fetch(page):
    await asyncio.sleep(0.3)      # non-blocking wait
    return page * 100

async def main():
    start = time.perf_counter()
    jobs = (fetch(p) for p in range(1, 6))
    rows = await asyncio.gather(*jobs)
    took = time.perf_counter() - start
    print(rows, f"{took:.1f}s")

asyncio.run(main())

[100, 200, 300, 400, 500] 0.3s

from concurrent.futures import ProcessPoolExecutor

def checksum(chunk):           # CPU-bound work
    return sum(x * x % 7 for x in chunk)

if __name__ == "__main__":     # needed for processes
    step = 200_000
    chunks = [range(i, i + step)
              for i in range(0, 800_000, step)]
    with ProcessPoolExecutor(max_workers=2) as pool:
        print(list(pool.map(checksum, chunks)))

[399999, 400002, 399996, 400002]