Python Download Image From URL Efficiently

I have a list of image URL that are stored in a Pandas Dataframe. I want to download all of these images and store them localy.

The code I use to do so is :

import os
import requests

def load(df, output_folder):        
    print("Ready to load "+str(len(df.index))+" images.")
    for i,row in df.iterrows():
        print("Image "+str(i))
        save_image_from_url(row["image_url"], os.path.join(output_folder, row["image_name"]))

''' From a given URL, download the image and store it at the given path'''
def save_image_from_url(url, output_path):
    image = requests.get(url)

    with open(output_path, 'wb') as f:
        f.write(image.content)

The problem is that the process is very slow (from 0.5 seconds to 4 seconds per images). Is there a way to do it faster ?

The obvious way is to parallelize the downloads, you have a clear example in the docs

For your case, try this aproach:

import concurrent.futures
import os
import requests


def save_image_from_url(url, output_folder):
    image = requests.get(url.image_url)
    output_path = os.path.join(
        output_folder, url.image_name
    )
    with open(output_path, "wb") as f:
        f.write(image.content)

def load(df, output_folder):    
    with concurrent.futures.ThreadPoolExecutor(
        max_workers=5
    ) as executor:
        future_to_url = {
            executor.submit(save_image_from_url, url, output_folder): url
            for _, url in df.iterrows()
        }
        for future in concurrent.futures.as_completed(
            future_to_url
        ):
            url = future_to_url[future]
            try:
                future.result()
            except Exception as exc:
                print(
                    "%r generated an exception: %s" % (url, exc)
                )