# Rust / Julia Comparison Post

**URL:** <https://discourse.julialang.org/t/rust-julia-comparison-post/75403>\
**Category:** Performance\
**Tags:** rust\
**Created:** [January 29, 2022, 1:45am UTC](https://discourse.julialang.org/t/rust-julia-comparison-post/75403 "2022-01-29T01:45:37Z")\
**Posts on this page:** 1\
**Showing post:** 55

<div class="post-metadata">

**Author:** ![dmbates](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/dmbates/32/44_2.png) [@dmbates](https://discourse.julialang.org/u/dmbates)\
**Post date:** [February 1, 2022, 10:53pm UTC](https://discourse.julialang.org/t/rust-julia-comparison-post/75403/55 "2022-02-01T22:53:03Z")

</div>

The algorithm can be simplified considerably if we use the fact that the constraints generated by a guess and a target word, which is the pattern of colors on the tiles, can be considered as a 5-digit base-3 number. For example

```nohighlight
function constraints(guess, actual)
    val = 0
    mult = 1
    for (g, a) in zip(guess, actual)
        val += (g == a ? 2 : (g ∈ actual ? 1 : 0)) * mult
        mult *= 3
    end
    return val
end

```

Then we just need to keep track of the number of words that generate each of these numbers between 0 and 242.

For a given initial guess we can update an integer vector `counts` of length 243 as

```nohighlight
function ccounts!(counts, guess, words)
    fill!(counts, 0)
    for actual in words
        counts[constraints(guess, actual) + 1] += 1
    end
    return counts
end

```

So, for example,

```nohighlight
julia> show(ccounts!(counts, SVector{5,UInt8}("raise"...), words))
[168, 103, 10, 92, 78, 4, 91, 26, 9, 107, 23, 4, 34, 18, 1, 14, 2, 6, 51, 28, 1, 12, 4, 0, 6, 4, 1, 80, 24, 1, 43, 21, 0, 20, 2, 1, 21, 4, 1, 7, 1, 0, 5, 0, 0, 29, 5, 0, 0, 0, 0, 1, 0, 0, 17, 13, 1, 22, 8, 1, 7, 2, 0, 6, 1, 0, 1, 0, 0, 0, 0, 0, 9, 5, 0, 1, 0, 0, 2, 0, 0, 121, 102, 20, 69, 34, 13, 20, 28, 4, 35, 26, 8, 3, 1, 0, 0, 0, 0, 15, 12, 1, 1, 0, 0, 0, 0, 0, 41, 18, 2, 12, 4, 0, 1, 2, 0, 4, 4, 3, 1, 0, 0, 0, 0, 0, 3, 1, 0, 0, 0, 0, 0, 0, 0, 9, 7, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 61, 40, 6, 41, 26, 0, 26, 4, 1, 25, 3, 2, 2, 1, 0, 0, 0, 0, 23, 17, 0, 5, 1, 0, 3, 0, 0, 17, 10, 0, 20, 5, 0, 9, 0, 0, 5, 0, 0, 1, 0, 0, 0, 0, 0, 15, 2, 0, 1, 0, 0, 0, 0, 0, 20, 8, 2, 8, 2, 0, 5, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1]

```

This means that there are 168 words that would generate all grey tiles if your initial guess is “raise”, 103 that would give you a yellow tile followed by 4 grey tiles, etc. Now here is the real subtle point - for a given initial guess a word matches a constraint pattern if and only if it generates that pattern. That is, the `counts` vector is also the size of the pool after the first guess. Thus the average size of the pool after the first guess of “raise” is

```nohighlight
julia> sum(abs2, counts)/sum(counts)
61.00086393088553

```

which corresponds to the earlier result.

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