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I’m a bit biased as someone who switched from Python to Julia for my physics research (I.e. I’m biased to believe I made a good choice and others should follow

I’m a bit biased as someone who switched from Python to Julia for my physics research (I.e. I’m biased to believe I made a good choice and others should follow my decision making), but I think any extra effort you spend in the beginning to get it working in Julia will pay big dividends. In the scientific world, Julia’s package ecosystem is already more developed than Python in some fields (Differential equations being one, but there are others), so you may not find that limiting you. Furthermore, for the reasons laid out in the article, Julia is highly composable and empirically, has a far greater ratio of code re-use than Python. I believe you’ll see greater bang for your buck in Julia because code you write is more likely to be re-used, especially in scientific domains.

ablekh 7y ago
Your blazingly fast and thoughtful comment is much appreciated. Let's see what others have to say ... :-) One clarification that I would like to make (which IMO diminishes your second point's potential value) is that the B2B SaaS platform that I plan to build would stay away from implementing a myriad of domain-specific scientific methods and algorithms (though I plan to provide a valuable core) and rather would enable users to integrate their own implementations (through a plug-in architecture). Thus, Julia's package ecosystem seems to be a factor of somewhat lesser importance.