10000 Update readme.md · oxylabs/python-cache-tutorial@e2f61c2 · GitHub
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@@ -158,6 +158,7 @@ print('Time taken (memoized function using manual decorator):', time.time() - st
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```
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And here’s the output:
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![](images/output_normal_memoized.png)
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Notice the time difference between the two functions. Both take almost
@@ -231,6 +232,7 @@ print('Time taken (memoized function with LRU cache):', time.time() - start_time
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```
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This produced the following output:
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![](images/output_normal_lru.png)
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### Performance comparison
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As the number of requests to the functions increases, you can see a
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significant reduction in execution times using the caching strategy. The
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following comparison chart depicts these results:
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![](images/comparison-chart.png)
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The comparison results clearly show that using a caching strategy in

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