took over a project that calculates the inbreeding-coefficient[1] on a platform for animal breeders. The product is used by breeding organization of endangered livestock (an Alpaca club in Ireland, a horse breeder in Belgium etc etc). My first reaction was WTF who decided on this technology. It was developed with some university professors focusing in veterinary geneology and so weren't aware that this isn't the right choice. When I asked them they were dead set on using this because apparently in their domain it is considered the go-to language for number-crunching. Idk if this is anecdotal or if there is a pattern but the feeling / takeaway I got was that some older academics would bring these things back because it's what they think is the right tool for the job. It was odd because most younger people I know who develop but don't consider themselves "developers" by trade would almost always resort to Python.
if the number crunching requirements are moderate (e.g. can be efficiently done in NumPy OR can be done <1min runtime in cPython interpreter and there are no real time requirements) it certainly is very questionable to go with Fortran. If the above isn't true, e.g. for some heavy physics calculations, Fortran is still a fine choice if you get the right people to maintain it. I'd choose it over C/C++ but would first have another look at Julia (esp. regarding its tooling maturity).
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took over a project that calculates the inbreeding-coefficient[1] on a platform for animal breeders. The product is used by breeding organization of endangered livestock (an Alpaca club in Ireland, a horse breeder in Belgium etc etc). My first reaction was WTF who decided on this technology. It was developed with some university professors focusing in veterinary geneology and so weren't aware that this isn't the right choice. When I asked them they were dead set on using this because apparently in their domain it is considered the go-to language for number-crunching. Idk if this is anecdotal or if there is a pattern but the feeling / takeaway I got was that some older academics would bring these things back because it's what they think is the right tool for the job. It was odd because most younger people I know who develop but don't consider themselves "developers" by trade would almost always resort to Python.
[1] https://en.wikipedia.org/wiki/Coefficient_of_inbreeding
if the number crunching requirements are moderate (e.g. can be efficiently done in NumPy OR can be done <1min runtime in cPython interpreter and there are no real time requirements) it certainly is very questionable to go with Fortran. If the above isn't true, e.g. for some heavy physics calculations, Fortran is still a fine choice if you get the right people to maintain it. I'd choose it over C/C++ but would first have another look at Julia (esp. regarding its tooling maturity).