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<h1 class="title toc-ignore">Gotchas</h1>
</div>
<p>Mistakes I have made. And made. And made again. <em>Expect this page to grow as I (re)discover more gotchas.</em></p>
<pre class="r"><code>library(purrr)</code></pre>
<div id="the-magrittr-dot-tension" class="section level3">
<h3>The <code>magrittr</code> dot tension</h3>
<p>The tidyverse takes its dot <code>.</code> pronoun from the <a href="https://github.com/smbache/magrittr#readme"><code>magrittr</code> package</a>. It means “the thing we are operating on” and is also known as the “argument placeholder”.</p>
<p>You don’t need the dot when you’re using pipe-friendly functions and the planets align for you:</p>
<pre class="r"><code>8 %>% log2()
#> [1] 3
## is same as
log2(8)
#> [1] 3</code></pre>
<p>But sometimes the thing you’re passing into the right-hand side (RHS) is not the first argument:</p>
<pre class="r"><code>2 %>% log(8)
#> [1] 0.3333333
## is not what I want and is not the same as
2 %>% log(8, .)
#> [1] 3
## or
2 %>% log(8, base = .)
#> [1] 3</code></pre>
<p>And sometimes you want to prevent the left-hand side from being used as the (invisible) first argument on the RHS. So you have to enclose RHS in curly braces:</p>
<pre class="r"><code>iris %>% {
c(rows = nrow(.), cols = ncol(.))
}
#> rows cols
#> 150 5</code></pre>
<p>One last thing … and this leads to the gotcha. The <code>.</code> can also be used to create a <em>unary function</em>:</p>
<pre class="r"><code>att <- . %>% toupper() %>% paste("ALL THE THINGS!")
"open source" %>% att()
#> [1] "OPEN SOURCE ALL THE THINGS!"
"butter" %>% att()
#> [1] "BUTTER ALL THE THINGS!"
"teach" %>% att()
#> [1] "TEACH ALL THE THINGS!"</code></pre>
<p>What is <code>att</code> anyway?</p>
<pre class="r"><code>att
#> Functional sequence with the following components:
#>
#> 1. toupper(.)
#> 2. paste(., "ALL THE THINGS!")
#>
#> Use 'functions' to extract the individual functions.</code></pre>
<p>It is a “functional sequence”.</p>
<p>It’s fairly easy to write code where you think <code>.</code> is a placeholder, but it generates a functional sequence.</p>
<p>Watch me.</p>
<pre class="r"><code>library(purrr)
library(tibble)
x <- list(list(int = 1L, chr = 'a'), list(int = 2L, chr = 'b'))
## YES GOOD WORKS
x %>% {
tibble(id = map_int(., "int"),
chr = map_chr(., "chr"))
}
#> # A tibble: 2 × 2
#> id chr
#> <int> <chr>
#> 1 1 a
#> 2 2 b
## NO BAD DOES NOT WORK
x %>% {
tibble(id = . %>% map_int("int"),
chr = . %>% map_chr("chr"))
}
#> Error: Each variable must be a 1d atomic vector or list.
#> Problem variables: 'id', 'chr'</code></pre>
<p>What went wrong?</p>
<p><code>. %>% map_int("int")</code> built a unary function, instead of passing <code>x</code> into <code>map_int()</code>. Do not start a pipeline with <code>.</code> unless you want a unary function.</p>
<p>What does this have to do with <code>purrr</code>?</p>
<p>If you’ve got a complicated object <code>x</code> (e.g., a deeply nested list from JSON), you might build a data frame with repeated calls to <code>map_*()</code> functions. Be careful where you put your dot <code>.</code>!</p>
</div>
<div id="purrr-is-strict-about-types" class="section level3">
<h3><code>purrr</code> is strict about types</h3>
<p><code>purrr</code>’s type checking is very strict, which is overhwhelmingly positive. But it will force you to be more aware of integer vs. double.</p>
<pre class="r"><code>set.seed(4561)
(x <- sample(1:5))
#> [1] 1 4 2 5 3
times_two <- function(x) x * 2
times_two(x)
#> [1] 2 8 4 10 6
x_list <- as.list(x)
## WTF?
x_list %>%
map_int(times_two)
#> Error: Can't coerce element 1 from a double to a integer</code></pre>
<p>Why can I suddenly not multiply these numbers by 2?</p>
<p>Because we’ve said to expect integers back and, though the elements of <code>x</code> are integer, the result of multiplying by the <em>double</em> 2 is <em>double</em>.</p>
<p>What can you do? Buckle down and make sure that integer stays integer, if that’s appropriate. Or loosen up and use <code>map_dbl()</code> instead.</p>
<pre class="r"><code>## GOOD, in the buckle down sense
times_two <- function(x) x * 2L
x_list %>%
map_int(times_two)
#> [1] 2 8 4 10 6
## GOOD, in the loosen up sense
times_two <- function(x) x * 2
x_list %>%
map_dbl(times_two)
#> [1] 2 8 4 10 6</code></pre>
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