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> Research across many languages suggests that lines of code/developer/day are roughly constant, so Python development should average 2.4 times as fast as Java.

> Research across many languages suggests that lines of code/developer/day are roughly constant, so Python development should average 2.4 times as fast as Java. Some people, with more Java experience than me, claim that modern IDEs like IntelliJ make them as productive with Java as they would be with Python. Java's verbosity is "mechanical", and if your tools help you with that, it's hard for me to buy 2.4x productivity difference. You are also assuming that static typing has no effect on how many people can work together. In Python (which I use for prototyping and appreciate), one might often wonder "does this method take a class, an instance of a class, or the returned value as an argument", etc.

btilly 17y ago
Debates on relative productivity are endless. I used the only numbers I have available that are backed by actual quantitative data rather than opinion. I'd love to see more up to date numbers. However even if you assume that the difference is much smaller, say a factor of 1.2, then you can afford an extra 2.3 computers for every developer. Oddly enough in the various companies I know well with small teams of experienced scripting programmers I've never seen that high a ratio of webservers to developers, so even so switching to Java doesn't make sense. On the question how many people can work together, needing to talk about data types is such a small portion of what people talk about that I would be shocked if it changes where the cutoff is between where small teams break down, or where large teams become as productive as that peak. That said I fully agree that Java is designed to let large teams cooperate, and that's likely to matter when you have teams of 50+ programmers. However if the productivity difference really is a factor of 2.4, and we assume linear growth in productivity for large teams, then you'll actually need a team of 50 or so programmers in Java to match the team of 5-7 programmers working in a modern scripting language. Given that, if you're working in a Java team below that size you should seriously ask yourself whether having a team size that requires getting that many people working together is a self-inflicted problem.

btilly 17y ago

Debates on relative productivity are endless. I used the only numbers I have available that are backed by actual quantitative data rather than opinion. I'd love to see more up to date numbers. However even if you assume that the difference is much smaller, say a factor of 1.2, then you can afford an extra 2.3 computers for every developer. Oddly enough in the various companies I know well with small teams of experienced scripting programmers I've never seen that high a ratio of webservers to developers, so even so switching to Java doesn't make sense. On the question how many people can work together, needing to talk about data types is such a small portion of what people talk about that I would be shocked if it changes where the cutoff is between where small teams break down, or where large teams become as productive as that peak. That said I fully agree that Java is designed to let large teams cooperate, and that's likely to matter when you have teams of 50+ programmers. However if the productivity difference really is a factor of 2.4, and we assume linear growth in productivity for large teams, then you'll actually need a team of 50 or so programmers in Java to match the team of 5-7 programmers working in a modern scripting language. Given that, if you're working in a Java team below that size you should seriously ask yourself whether having a team size that requires getting that many people working together is a self-inflicted problem.