4 ms·

It's got the fastest development speed of the main stream languages. It's got a huge technical advantage.

crabbone 4y ago
This is just false (spoken from a perspective of infra / system / automation person, being in the field for many years). But, this is very typical of religious people: to claim anything that suites their agenda w/o even trying to verify their claims, not even being bothered by whether the claim even makes sense. First of all, there's no such thing as a "development speed of a language", just like there isn't a development speed of ice-cream. It's just kind of a Jabberwocky: it feels like it's in English, but it doesn't really mean anything. Development speed differs by the kind of project (eg. Web site vs filesystem), quality requirements, size of the team working on the project, expertise of the team working on the project... Needless to say that there are areas where Python is entirely not applicable, so, the development speed wouldn't even be a factor. But, even in areas where it's commonly used there are often languages that will compete for this metric, and there are certainly teams using other languages that will beat teams using Python. But, overall, Python projects tend to be easy to start and hard to develop further and to refine. Python projects tend to fare worse in large teams. Python also doesn't attract high-caliber programmers, while also is often the first language a programmer learns, so it tends to be populated by mediocre-bad programmers (similar problem used to exist in Java before it was replaced by Python in intro to CS courses). Finally, a huge portion of development speed rests on company's infrastructure: how quickly and reliably can developers test their code plays a tremendous role in productivity. Ironically, Python tooling is so bad that sometimes it's faster to compile a C++ program of equivalent size than to install a bunch of Python packages implementing the same thing (god forbid you are using Anaconda, because that can take hours and days in the worst case to install a handful of packages).

This is just false (spoken from a perspective of infra / system / automation person, being in the field for many years). But, this is very typical of religious people: to claim anything that suites their agenda w/o even trying to verify their claims, not even being bothered by whether the claim even makes sense. First of all, there's no such thing as a "development speed of a language", just like there isn't a development speed of ice-cream. It's just kind of a Jabberwocky: it feels like it's in English, but it doesn't really mean anything. Development speed differs by the kind of project (eg. Web site vs filesystem), quality requirements, size of the team working on the project, expertise of the team working on the project... Needless to say that there are areas where Python is entirely not applicable, so, the development speed wouldn't even be a factor. But, even in areas where it's commonly used there are often languages that will compete for this metric, and there are certainly teams using other languages that will beat teams using Python. But, overall, Python projects tend to be easy to start and hard to develop further and to refine. Python projects tend to fare worse in large teams. Python also doesn't attract high-caliber programmers, while also is often the first language a programmer learns, so it tends to be populated by mediocre-bad programmers (similar problem used to exist in Java before it was replaced by Python in intro to CS courses). Finally, a huge portion of development speed rests on company's infrastructure: how quickly and reliably can developers test their code plays a tremendous role in productivity. Ironically, Python tooling is so bad that sometimes it's faster to compile a C++ program of equivalent size than to install a bunch of Python packages implementing the same thing (god forbid you are using Anaconda, because that can take hours and days in the worst case to install a handful of packages).