If you run a company, then you might make better choices (or at least allow for proper discovery of what approach to take to building a large system). But ther

If you run a company, then you might make better choices (or at least allow for proper discovery of what approach to take to building a large system). But there seems to be an accepted rule that "if you're doing data science, you are a Python shop". And if you are trying to pitch a data science company to investors, they know Python for data science. New companies start all the time using a technology because "that's what you use", without knowing why or why not. In fact, (and not that I idolize him, which I really do not), Paul Graham's http://www.paulgraham.com/avg.html http://www.paulgraham.com/avg.html essay talks about this. Most companies follow whatever is the accepted practice for doing things. It may "work", but it definitely may not be optimal. And the companies that choose a different path based on more consideration or more awareness may have an easier time. I mean after all, there was a time when everyone wrote C (because C was so much better than COBOL or whatever). And believe it or not, there was a time when it was impossible to convince a company to try Java. Or as the old saying went, "nobody got fired for buying IBM". After all, it was the safe path. Substitute Oracle, or C, or C++, or Java, or Python, or PHP, or Windows (there was a time when people didn't trust Linux and couldn't imagine why you would ever try to run your business software on Linux machines). Your reasoning makes sense, but in practice in the software world, it is not as well planned or thought out as you might expect.