Downloading a large file in parts using multiple parallel threads

I have a use case, where a large remote file needs to be downloaded in parts, by using multiple threads. Each thread must run simultaneously (in parallel), grabbing a specific part of the file. The expectation is to combine the parts into a single (original) file, once all parts were successfully downloaded.

Perhaps using the requests library could do the job, but then I am not sure how I would multithread this into a solution that combines the chunks together.

url = 'https://url.com/file.iso'
headers = {"Range": "bytes=0-1000000"}  # first megabyte
r = get(url, headers=headers)

I was also thinking of using curl where Python would orchestrate the downloads, but I am not sure that's the correct way to go. It just seems to be too complex and swaying away from the vanilla Python solution. Something like this:

curl --range 200000000-399999999 -o file.iso.part2

Can someone explain how you'd go about something like this? Or post a code example of something that works in Python 3? I usually find the Python-related answers quite easily, but the solution to this problem seems to be eluding me.

Here is a version using Python 3 with Asyncio, it's just an example, it can be improved, but you should be able to get everything you need.

• get_size: Send an HEAD request to get the size of the file
• download_range: Download a single chunk
• download: Download all the chunks and merge them

import asyncio
import concurrent.futures
import functools
import requests
import os


# WARNING:
# Here I'm pointing to a publicly available sample video.
# If you are planning on running this code, make sure the
# video is still available as it might change location or get deleted.
# If necessary, replace it with a URL you know is working.
URL = 'https://download.samplelib.com/mp4/sample-30s.mp4'
OUTPUT = 'video.mp4'


async def get_size(url):
    response = requests.head(url)
    size = int(response.headers['Content-Length'])
    return size


def download_range(url, start, end, output):
    headers = {'Range': f'bytes={start}-{end}'}
    response = requests.get(url, headers=headers)

    with open(output, 'wb') as f:
        for part in response.iter_content(1024):
            f.write(part)


async def download(run, loop, url, output, chunk_size=1000000):
    file_size = await get_size(url)
    chunks = range(0, file_size, chunk_size)

    tasks = [
        run(
            download_range,
            url,
            start,
            start + chunk_size - 1,
            f'{output}.part{i}',
        )
        for i, start in enumerate(chunks)
    ]

    await asyncio.wait(tasks)

    with open(output, 'wb') as o:
        for i in range(len(chunks)):
            chunk_path = f'{output}.part{i}'

            with open(chunk_path, 'rb') as s:
                o.write(s.read())

            os.remove(chunk_path)


if __name__ == '__main__':
    executor = concurrent.futures.ThreadPoolExecutor(max_workers=3)
    loop = asyncio.new_event_loop()
    run = functools.partial(loop.run_in_executor, executor)

    asyncio.set_event_loop(loop)

    try:
        loop.run_until_complete(
            download(run, loop, URL, OUTPUT)
        )
    finally:
        loop.close()