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        <h2 class="heading-6 logo">katydid</h2>
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  <div class="section-3">
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      <h1 class="heading-17">What is Katydid?</h1>
      <div class="div-block-3 benchmarks">
        <p>Katydid is a validation language based on regular expressions, but extended to be able to match deeply nested structures. It was built to filter through petabytes of serialized protocol buffers, but it can also filter through xml and json. </p>
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      <a href="https://katydid.github.io/play/" class="link-block-3 w-inline-block"><img src="images/code-min.png" loading="lazy" sizes="100vw" width="1154" alt="" srcset="images/code-min-p-500.png 500w, images/code-min-p-800.png 800w, images/code-min-p-1080.png 1080w, images/code-min-p-1600.png 1600w, images/code-min.png 2308w" class="image-28"></a>
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      <h1 class="heading-23">Katydid is Fast</h1>
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        <h2 class="heading-18">matches up to millions of records per second</h2>
        <div class="par-div">
          <p>Katydid can match up to millions of protocol buffers on a single core. To achieve this speed, no memory allocation is done after initialization, except for the ongoing memoization, which becomes less and less the more matching is done.</p>
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        <h2 class="heading-19">filters faster the more records it matches</h2>
        <div class="par-div">
          <p>Katydid matches faster and faster the more records or serialized messages are passed to it, as it memoizes paths that have been seen before, which speeds up matching, while using the same validator.</p>
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      <div class="tick-h2 first">
        <div class="tick"><img src="images/block-tick.svg" loading="lazy" data-w-id="70c05ecd-e288-afe6-d268-5e580e6b7f84" style="opacity:0" alt="A graph showing: the more times the algorithm is run, the faster it becomes." class="tick-animation one"></div>
        <h2 class="heading-20">matches deeply nested and recursive structures</h2>
        <div class="par-div">
          <p>It is also extendible to match any structure with an implemented parser. The current implementation is in Go, but we are also working towards a Haskell implementation and proofs of correctness in <a href="https://leanprover.github.io/" target="_blank" class="inline-link">LeanProver</a>.</p>
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      <h1 class="heading-21">Benchmarks</h1>
      <div class="div-block-3 benchmarks">
        <p>Below is a graph of how the matching speeds up after matching 10, 100 and then a 1000 randomly initialized protocol buffers and also the ultimate speed which is achieved by memoizing all possibilities, given the filter: <br>‍<br><span class="inline-code">.Addresses:_:[Number:456, Street: &quot;TheStreet&quot;]</span><br>‍</p>
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      </div>
      <div class="graph-vertical-div">
        <h1 class="graph-heading">Memoized vs Compiled Benchmarks</h1>
        <a href="#" class="graph-link-block w-inline-block"><img src="images/graph-vertical-min.png" loading="lazy" sizes="(max-width: 479px) 100vw, 411px" width="411" alt="" srcset="images/graph-vertical-min-p-500.png 500w, images/graph-vertical-min.png 822w" class="image-25"></a>
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      <h1 class="heading-22">Katydid is Extendable</h1>
      <div class="div-block-3 benchmarks">
        <p>Katydid also makes it easy to add another format. While regular expressions are used as validators only for strings and RelaxNG, DTD and XSchema are validation languages only for XML. Katydid can validate any serialized data that has an implemented parser.</p>
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      <p class="cta-text">Get a taste of Katydid in our Playground or take a Guided Tour.</p>
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      <div class="text-block-23">© Copyright Walter Schulze</div>
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