68 lines
1.8 KiB
Python
68 lines
1.8 KiB
Python
import requests
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from time import time
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from threading import Thread
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# This example shows how downloading multiple images from the
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# internet can be sped up using multiple threads. We are just
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# getting JSON responses and recording the time taken in each
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# example
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# Images are being download from the pexels.com API
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from pexels_api_key import API_KEY
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api_url = 'https://api.pexels.com/v1/search?query='
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queries = ['people', 'cars', 'landscpapes', 'pets',
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'tech', 'food', 'books', 'sports', 'games', 'plants']
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def download_images(query):
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full_url = f'{api_url}{query}'
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headers = {'Authorization': API_KEY}
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requests.get(full_url, data=None, headers=headers)
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# Sequential Example
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def record_seq_time():
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t0 = time()
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print('\nDownloading images sequentially')
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for query in queries:
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download_images(query=query)
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t1 = time()
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print('Download complete')
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return f'{t1-t0:.2f}s'
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# Threaded example - no need to wait for a response before sending the next request
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def record_con_time():
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t0 = time()
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threads = []
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print('\nDownloading images using multiple threads')
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for query in queries:
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thread = Thread(target=download_images, args=(query,))
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threads.append(thread)
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thread.start()
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for thread in threads:
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thread.join()
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t1 = time()
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print('Download complete')
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return f'{t1-t0:.2f}'
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def main():
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seq_time = record_seq_time()
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con_time = record_con_time()
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print('\n=======================================================')
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print(f'Sequential download completed in {seq_time}')
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print(f'Multi-threaded download completed in {con_time}') # this is significantly faster
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print('=======================================================')
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if __name__ == '__main__':
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main()
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