I work for a mobile games company as a data scientist. I use Ruby for data wrangling and some sorts of analysis, Python for more specific things (essentially scikit-learn) and bash scripts for gluing everything together.
- Lua is tiny. As someone accostumed to Python and Ruby, it is shocking to see such a small standard library. For example, this is the manual – there are only 158 Lua functions listed there.
- The syntax is incredibly simple. Take a look at these diagrams; if you understand the Extended Backus-Naur Form, you can read Lua’s syntax quite easily. For comparison, Ruby’s syntax is complex enough that there are lots (and lots and lots) of small corner cases that I probably never heard about, even after years using it. Ah! And Ruby’s parse.y has 11.3k lines.
- Lua was built with embedding in mind; it is used for interface customization in World of Warcraft, for example.
- It is a Brazilian programming language! :-) Lua was created in 1993 in Rio de Janeiro, according to Wikipedia.
Random number generators
After finding so many interesting features about the language, I wrote some random number generators:
-- Some RNGs for getting to play with Lua.
-- Carlos Agarie <email@example.com>
-- Public domain.
-- N(mean; std^2).
function gauss(mean, std)
if std <= 0.0 then error("standard deviation must be positive!") end
u1 = math.random()
u2 = math.random()
r = math.sqrt(-2.0 * math.log(u1))
theta = 2.0 * math.pi * u2
return mean + std * r * math.sin(theta)
-- This distribution models the time between events in a Poisson process.
if mean <= 0.0 then error("mean must be positive!") end
return -mean * math.log(math.random())
-- This is a non-exponential type of distribution, one without a mean value.
function cauchy(median, scale)
if scale <= 0.0 then error("scale must be positive!") end
return median + scale * math.tan(math.pi * (math.random() - 0.5))
I decided to write RNGs after reading John D. Cook’s post about RNGs in Julia. :)