<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>JulianWasTaken</author><text>Can I tangentially point out without much connection to this benchmark more than any of the others recently, that one of the great things about PyPy is that if you have a thing and you run it on PyPy, you can usually pop in the IRC channel and often get even &lt;i&gt;more&lt;/i&gt; tips on how to tune it to be even faster?&lt;p&gt;There are the simple tips like &quot;write everything in Python where possible, don&apos;t use C extensions&quot; like the OP noticed, but even after you&apos;ve made the decision on using PyPy there are often specific performance characteristics of the PyPy implementation that can be really helpful to keep in mind, and it&apos;s a great resource to try and take advantage of (human interaction with PyPy developers like fijal who care about making things fast).</text><parent_chain></parent_chain></comment><story><title>Wikipedia processing. PyPy vs CPython benchmark</title><url>http://rz.scale-it.pl/2013/02/18/wikipedia_processing._PyPy_vs_CPython_benchmark.html</url><text>What PyPy can do for Wikipedia processing tasks? Speedup!</text></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>tworats</author><text>Great to see real world use cases, and very encouraging to see PyPy performing so well. I&apos;ll definitely be trying it on my future compute-intensive projects.</text><parent_chain></parent_chain></comment><story><title>Wikipedia processing. PyPy vs CPython benchmark</title><url>http://rz.scale-it.pl/2013/02/18/wikipedia_processing._PyPy_vs_CPython_benchmark.html</url><text>What PyPy can do for Wikipedia processing tasks? Speedup!</text></story>