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copied!<p>I don't see how a binary search could be at all faster than straight in order iteration, and in most cases, it would end up being slower. Given <code>n</code> is the length of the list, if you are searching for the last good url of the first good batch, only the case where <code>urls[n/2]-1</code> is your target would take the same number of searches as just brute force iteration; all others would take more. If you are looking for the last good url in the entire list, the only search target that would take the same number of searches compared to a reversed order iteration would be <code>urls[n/2]-1</code>. Binary search is only faster when your dataset is ordered. For an unordered dataset, sampling the middle of the set tells you nothing about being able to exclude values to either side of it, so you still have to process the entire sequence before you can tell anything.</p> <p>I suspect what you may really be wanting here is a way to sample your dataset at intervals so that you can run fewer requests before finding your target, which isn't quite the same as a binary search. Binary search relies on the fact that sampling a point in your sequence provides information on being able to exclude either one side or the other of the sequence from subsequent searches based upon a binary condition. What you have is a system where if a sample fails the test, you can exclude one side, but if it passes the test, it tells you nothing about what you can assume about any other values in the list. That doesn't really work for a binary search.</p>

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