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Comment by anamax | Hacker News Reader

> The use of the algorithm is mostly orthogonal to the language being used.

I don't find that to be true. I use more sophisticated algorithms in "higher level" languages because I can implement them in about the same time it takes me to implement less sophisticated algorithms in "lower level" languages.

> Personally, I often do an initial write of a program first in Python and rewrite in C/C++ if necessary. Usually, the first unoptimized C++ implementation is 10-100x faster than an optimized Python implementation.

Yes, but the c/c++ rewrite gets to take advantage of what you learned in the python AND you only do the c rewrite when you need the speed and are willing to pay the time penalty to get it. (There's some extra cost to the c version otherwise you'd always do c and never do python.)

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I use more sophisticated algorithms in "higher level" languages because I can implement them in about the same time it takes me to implement less sophisticated algorithms in "lower level" languages.

These are factors not related directly to the language, but level of understanding, time, and money. An experienced C++ programmer can probably implement the 'better' algorithm equally quick in C++.

There's some extra cost to the c version otherwise you'd always do c and never do python.

Not necessarily. In an existing project in a non-C language, the C implementation will require you to write and maintain a binding as well. That could be a good reason to use Python/Ruby/Prolog/whatever by default, unless it's not fast enough.

> These are factors not related directly to the language, but level of understanding, time, and money. An experienced C++ programmer can probably implement the 'better' algorithm equally quick in C++.

There are programmer performance factors directly related to language differences.

The mainstream example is efficiency of DSLs. Try writing a complex regexp in a standard regexp DSL that originates from Perl and in plain C/C++.

The less known example is writing complex business logic in Clojure vs Java. The very fact that Clojure version lets you examine much more business logic in one screen without scrolling puts much less pressure on programmer's concentration and memory.

Thus the very ability to write complex business logic without lots of bugs in tight time constraints depends on a language.

> An experienced C++ programmer can probably implement the 'better' algorithm equally quick in C++.

While there are programmers who can implement a given algorithm faster in C++ than Python, I suspect that they're the exception (among folks who know both).

> In an existing project in a non-C language, the C implementation will require you to write and maintain a binding as well.

If there's no c penalty, other languages wouldn't have been used as often for said existing projects to begin with.

My view is that each language has both strengths and weaknesses, so different languages are better suited to different tasks depending on factors like available personnel, existing sw, ease of implementation (to reach an acceptable level of performance).

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