<story><title>Why Python keeps growing, explained</title><url>https://github.blog/2023-03-02-why-python-keeps-growing-explained/</url></story><parent_chain><item><author>dagw</author><text>Realistically something that takes 1 second in C++ will take 10 seconds (if you write efficient python and lean heavily on fast libraries) to 10 minutes in python. But the rest of your point stands</text></item><item><author>xaitv</author><text>There&amp;#x27;s also the argument that at a certain scale the time of a developer is simply more expensive than time on a server.&lt;p&gt;If I write something in C++ that does a task in 1 second and it takes me 2 days to write, and I write the same thing in Python that takes 2 seconds but I can write it in 1 day, the 1 day of extra dev time might just pay for throwing a more high performance server against it and calling it a day. And then I don&amp;#x27;t even take the fact that a lot of applications are mostly waiting for database queries into consideration, nor maintainability of the code and the fact that high performance servers get cheaper over time.&lt;p&gt;If you work at some big corp where this would mean thousands of high performance servers that&amp;#x27;s simply not worth it, but in small&amp;#x2F;medium sized companies it usually is.</text></item><item><author>pletnes</author><text>Python keeps growing in number of users because it’s easy to get started, has libraries to load basically any data, and to perform any task. It’s frequently the second best language but it’s the second best language for anything.&lt;p&gt;By the time a python programmer has «graduated» to learning a second language, exponential growth has created a bunch of new python programmers, most of which don’t consider themselves programmers.&lt;p&gt;There are more non-programmers in this world, and they don’t care - or know about - concurrency, memory efficiency, L2 cache misses due to pointer chasing. These people all use python. This seems to be a perspective missing from most hackernews discussions, where people work on high performance Big corp big data web scale systems.</text></item></parent_chain><comment><author>giantrobot</author><text>I spend most of my time waiting on IO, something like C++ isn&amp;#x27;t going to improve my performance much. If C++ takes 1ms to transform data and my Python code takes 10ms, it&amp;#x27;s not much of a win for me when I&amp;#x27;m waiting 100ms for IO.&lt;p&gt;With Python I can write and test on a Mac or Windows and easily deploy on Linux. I can iterate quickly and if I really need &amp;quot;performance&amp;quot; I can throw bigger or more VPSes at the problem with little extra cognitive load.&lt;p&gt;I do not have anywhere near the same flexibility and low cognitive load with C++. The better performance is &lt;i&gt;nice&lt;/i&gt; but for almost everything I do day to day completely unnecessary and not worth the effort. My case isn&amp;#x27;t all cases, C++ (or whatever compiled language you pick) will be a win for some people but not for me.</text></comment>
<story><title>Why Python keeps growing, explained</title><url>https://github.blog/2023-03-02-why-python-keeps-growing-explained/</url></story><parent_chain><item><author>dagw</author><text>Realistically something that takes 1 second in C++ will take 10 seconds (if you write efficient python and lean heavily on fast libraries) to 10 minutes in python. But the rest of your point stands</text></item><item><author>xaitv</author><text>There&amp;#x27;s also the argument that at a certain scale the time of a developer is simply more expensive than time on a server.&lt;p&gt;If I write something in C++ that does a task in 1 second and it takes me 2 days to write, and I write the same thing in Python that takes 2 seconds but I can write it in 1 day, the 1 day of extra dev time might just pay for throwing a more high performance server against it and calling it a day. And then I don&amp;#x27;t even take the fact that a lot of applications are mostly waiting for database queries into consideration, nor maintainability of the code and the fact that high performance servers get cheaper over time.&lt;p&gt;If you work at some big corp where this would mean thousands of high performance servers that&amp;#x27;s simply not worth it, but in small&amp;#x2F;medium sized companies it usually is.</text></item><item><author>pletnes</author><text>Python keeps growing in number of users because it’s easy to get started, has libraries to load basically any data, and to perform any task. It’s frequently the second best language but it’s the second best language for anything.&lt;p&gt;By the time a python programmer has «graduated» to learning a second language, exponential growth has created a bunch of new python programmers, most of which don’t consider themselves programmers.&lt;p&gt;There are more non-programmers in this world, and they don’t care - or know about - concurrency, memory efficiency, L2 cache misses due to pointer chasing. These people all use python. This seems to be a perspective missing from most hackernews discussions, where people work on high performance Big corp big data web scale systems.</text></item></parent_chain><comment><author>joenot443</author><text>Damn! Is the rule of thumb really a 10x performance hit between Python&amp;#x2F;C++? I don’t doubt you’re correct, I’m just thinking of all the unnecessary cycles I put my poor CPU through.</text></comment>