From
Larry Rix@21:1/5 to
All on Wed Aug 4 12:49:01 2021
Hi Bruce,
I counted wrong. It is in the Top 100 (e.g. Next 50 after the First 50).
The Next 50 Programming Languages
The following list of languages denotes #51 to #100. Since the differences are relatively small, the programming languages are only listed (in alphabetical order).
ActionScript, Alice, Arc, Awk, B4X, bc, BCPL, Bourne shell, CFML, CL (OS/400), Clipper, CLIPS, Common Lisp, Eiffel, Elixir, Elm, Forth, Fortress, Haskell, Icon, Inform, Io, J#, Korn shell, LiveCode, Maple, Modula-2, MQL4, MUMPS, NATURAL, NXT-G, Oberon,
OCaml, Occam, OpenEdge ABL, PL/I, PostScript, PowerShell, Pure Data, Q, REXX, Ring, RPG, Simulink, Smalltalk, Solidity, SPARK, Stata, Uniface, Xojo
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Therefore—if you see a library that ought to be there, then roll up your sleeves and start coding. Even a weak attempt is better than no attempt at all. If that library happens to be a C API, then talk with the Eiffel Team about WrapC and getting a
wrapper on it.
Emmanuel Stapf
Eiffel Software
Maybe, judging by the Python data science crowd, it would be best to leverage a bunch of C libraries out there.
However, the Eiffel documentation is just about the pits, for me at least, with the numbers of practical examples close to zero. OTOH, it's good on the theoretical aspects. But that's not what I need when I'm in a hurry. When it comes to using Eiffel
collections, it is even worse.
So, if you want people to com to Eiffel, write good introductory documentation.
The reason Python has attracted so many non-programmers (but physicists, statisticians, etc) is because they found the entry level easy (I heard this on a recent Lex Friedman podcast, forgot the guy's name). My take on Eiffel is that it's easy too, or
reasonably easy - but the documentation and examples are so thin, you know? And that's on you guys, not on users coming to the language to check it out.
-- Hank
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