# Fun One Liners

**URL:** <https://discourse.julialang.org/t/fun-one-liners/28352>\
**Category:** General Usage\
**Created:** [September 3, 2019, 11:13pm UTC](https://discourse.julialang.org/t/fun-one-liners/28352 "2019-09-03T23:13:18Z")\
**Posts on this page:** 1\
**Showing post:** 20

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**Author:** ![Tamas\_Papp](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tamas_papp/32/25949_2.png) [@Tamas\_Papp](https://discourse.julialang.org/u/Tamas_Papp)\
**Post date:** [September 6, 2019, 5:55am UTC](https://discourse.julialang.org/t/fun-one-liners/28352/20 "2019-09-06T05:55:47Z")

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There was a discussion about the complex step method a while ago here:

> [@Complex step differentiation method explained](https://discourse.julialang.org/t/complex-step-differentiation-method-explained/14647):
>
> I wrote a brief post explaining the “complex step method” that was the first topic in Nick Higham’s JuliaCon 2018 talk. (Using Julia for demonstrations, of course !)

It _is_ a neat trick, but it only works for complex analytic functions, which essentially rules out all nontrivial _programs_. Moreover, it can just fail silently (without erroring), which is a debugging nightmare.

So I don’t think it is something one would use in practice in any language. Incidentally, if a language for scientific computing doesn’t allow a disciplined AD implementation in 2019, prospects for that language are quite grim.

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_[View the full topic](https://discourse.julialang.org/t/fun-one-liners/28352)._