record and compare time to make 10 API requests

single_thread_vs_multi_thread/main.py

@@ -0,0 +1,67 @@
+import requests
+from time import time
+from threading import Thread
+
+# This example shows how downloading multiple images from the
+# internet can be sped up using multiple threads. We are just
+# getting JSON responses and recording the time taken in each
+# example
+
+# Images are being download from the pexels.com API
+
+from pexels_api_key import API_KEY
+
+
+api_url = 'https://api.pexels.com/v1/search?query='
+queries = ['people', 'cars', 'landscpapes', 'pets',
+           'tech', 'food', 'books', 'sports', 'games', 'plants']
+
+
+def download_images(query):
+    full_url = f'{api_url}{query}'
+    headers = {'Authorization': API_KEY}
+    requests.get(full_url, data=None, headers=headers)
+
+
+# Sequential Example
+
+def record_seq_time():
+    t0 = time()
+    print('\nDownloading images sequentially')
+    for query in queries:
+        download_images(query=query)
+    t1 = time()
+    print('Download complete')
+    return f'{t1-t0:.2f}s'
+
+
+# Threaded example - no need to wait for a response before sending the next request
+
+
+def record_con_time():
+    t0 = time()
+    threads = []
+    print('\nDownloading images using multiple threads')
+    for query in queries:
+        thread = Thread(target=download_images, args=(query,))
+        threads.append(thread)
+        thread.start()
+    for thread in threads:
+        thread.join()
+    t1 = time()
+    print('Download complete')
+    return f'{t1-t0:.2f}'
+
+
+
+def main():
+    seq_time = record_seq_time()
+    con_time = record_con_time()
+    print('\n=======================================================')
+    print(f'Sequential download completed in {seq_time}')
+    print(f'Multi-threaded download completed in {con_time}')  # this is significantly faster 
+    print('=======================================================')
+
+
+if __name__ == '__main__':
+    main()