File: snapshotting.html

package info (click to toggle)
r-cran-testthat 3.2.3-1
links: PTS, VCS
area: main
in suites: forky, sid, trixie
size: 3,452 kB
sloc: cpp: 9,261; ansic: 37; sh: 14; makefile: 5
file content (714 lines) | stat: -rw-r--r-- 252,130 bytes
<!DOCTYPE html>

<html>

<head>

<meta charset="utf-8" />
<meta name="generator" content="pandoc" />
<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />

<meta name="viewport" content="width=device-width, initial-scale=1" />



<title>Snapshot tests</title>

<script>// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
// be compatible with the behavior of Pandoc < 2.8).
document.addEventListener('DOMContentLoaded', function(e) {
  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
  var i, h, a;
  for (i = 0; i < hs.length; i++) {
    h = hs[i];
    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
    a = h.attributes;
    while (a.length > 0) h.removeAttribute(a[0].name);
  }
});
</script>

<style type="text/css">
code{white-space: pre-wrap;}
span.smallcaps{font-variant: small-caps;}
span.underline{text-decoration: underline;}
div.column{display: inline-block; vertical-align: top; width: 50%;}
div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
ul.task-list{list-style: none;}
</style>



<style type="text/css">
code {
white-space: pre;
}
.sourceCode {
overflow: visible;
}
</style>
<style type="text/css" data-origin="pandoc">
pre > code.sourceCode { white-space: pre; position: relative; }
pre > code.sourceCode > span { line-height: 1.25; }
pre > code.sourceCode > span:empty { height: 1.2em; }
.sourceCode { overflow: visible; }
code.sourceCode > span { color: inherit; text-decoration: inherit; }
div.sourceCode { margin: 1em 0; }
pre.sourceCode { margin: 0; }
@media screen {
div.sourceCode { overflow: auto; }
}
@media print {
pre > code.sourceCode { white-space: pre-wrap; }
pre > code.sourceCode > span { display: inline-block; text-indent: -5em; padding-left: 5em; }
}
pre.numberSource code
{ counter-reset: source-line 0; }
pre.numberSource code > span
{ position: relative; left: -4em; counter-increment: source-line; }
pre.numberSource code > span > a:first-child::before
{ content: counter(source-line);
position: relative; left: -1em; text-align: right; vertical-align: baseline;
border: none; display: inline-block;
-webkit-touch-callout: none; -webkit-user-select: none;
-khtml-user-select: none; -moz-user-select: none;
-ms-user-select: none; user-select: none;
padding: 0 4px; width: 4em;
color: #aaaaaa;
}
pre.numberSource { margin-left: 3em; border-left: 1px solid #aaaaaa; padding-left: 4px; }
div.sourceCode
{ }
@media screen {
pre > code.sourceCode > span > a:first-child::before { text-decoration: underline; }
}
code span.al { color: #ff0000; font-weight: bold; } 
code span.an { color: #60a0b0; font-weight: bold; font-style: italic; } 
code span.at { color: #7d9029; } 
code span.bn { color: #40a070; } 
code span.bu { color: #008000; } 
code span.cf { color: #007020; font-weight: bold; } 
code span.ch { color: #4070a0; } 
code span.cn { color: #880000; } 
code span.co { color: #60a0b0; font-style: italic; } 
code span.cv { color: #60a0b0; font-weight: bold; font-style: italic; } 
code span.do { color: #ba2121; font-style: italic; } 
code span.dt { color: #902000; } 
code span.dv { color: #40a070; } 
code span.er { color: #ff0000; font-weight: bold; } 
code span.ex { } 
code span.fl { color: #40a070; } 
code span.fu { color: #06287e; } 
code span.im { color: #008000; font-weight: bold; } 
code span.in { color: #60a0b0; font-weight: bold; font-style: italic; } 
code span.kw { color: #007020; font-weight: bold; } 
code span.op { color: #666666; } 
code span.ot { color: #007020; } 
code span.pp { color: #bc7a00; } 
code span.sc { color: #4070a0; } 
code span.ss { color: #bb6688; } 
code span.st { color: #4070a0; } 
code span.va { color: #19177c; } 
code span.vs { color: #4070a0; } 
code span.wa { color: #60a0b0; font-weight: bold; font-style: italic; } 
</style>
<script>
// apply pandoc div.sourceCode style to pre.sourceCode instead
(function() {
  var sheets = document.styleSheets;
  for (var i = 0; i < sheets.length; i++) {
    if (sheets[i].ownerNode.dataset["origin"] !== "pandoc") continue;
    try { var rules = sheets[i].cssRules; } catch (e) { continue; }
    var j = 0;
    while (j < rules.length) {
      var rule = rules[j];
      // check if there is a div.sourceCode rule
      if (rule.type !== rule.STYLE_RULE || rule.selectorText !== "div.sourceCode") {
        j++;
        continue;
      }
      var style = rule.style.cssText;
      // check if color or background-color is set
      if (rule.style.color === '' && rule.style.backgroundColor === '') {
        j++;
        continue;
      }
      // replace div.sourceCode by a pre.sourceCode rule
      sheets[i].deleteRule(j);
      sheets[i].insertRule('pre.sourceCode{' + style + '}', j);
    }
  }
})();
</script>




<style type="text/css">body {
background-color: #fff;
margin: 1em auto;
max-width: 700px;
overflow: visible;
padding-left: 2em;
padding-right: 2em;
font-family: "Open Sans", "Helvetica Neue", Helvetica, Arial, sans-serif;
font-size: 14px;
line-height: 1.35;
}
#TOC {
clear: both;
margin: 0 0 10px 10px;
padding: 4px;
width: 400px;
border: 1px solid #CCCCCC;
border-radius: 5px;
background-color: #f6f6f6;
font-size: 13px;
line-height: 1.3;
}
#TOC .toctitle {
font-weight: bold;
font-size: 15px;
margin-left: 5px;
}
#TOC ul {
padding-left: 40px;
margin-left: -1.5em;
margin-top: 5px;
margin-bottom: 5px;
}
#TOC ul ul {
margin-left: -2em;
}
#TOC li {
line-height: 16px;
}
table {
margin: 1em auto;
border-width: 1px;
border-color: #DDDDDD;
border-style: outset;
border-collapse: collapse;
}
table th {
border-width: 2px;
padding: 5px;
border-style: inset;
}
table td {
border-width: 1px;
border-style: inset;
line-height: 18px;
padding: 5px 5px;
}
table, table th, table td {
border-left-style: none;
border-right-style: none;
}
table thead, table tr.even {
background-color: #f7f7f7;
}
p {
margin: 0.5em 0;
}
blockquote {
background-color: #f6f6f6;
padding: 0.25em 0.75em;
}
hr {
border-style: solid;
border: none;
border-top: 1px solid #777;
margin: 28px 0;
}
dl {
margin-left: 0;
}
dl dd {
margin-bottom: 13px;
margin-left: 13px;
}
dl dt {
font-weight: bold;
}
ul {
margin-top: 0;
}
ul li {
list-style: circle outside;
}
ul ul {
margin-bottom: 0;
}
pre, code {
background-color: #f7f7f7;
border-radius: 3px;
color: #333;
white-space: pre-wrap; 
}
pre {
border-radius: 3px;
margin: 5px 0px 10px 0px;
padding: 10px;
}
pre:not([class]) {
background-color: #f7f7f7;
}
code {
font-family: Consolas, Monaco, 'Courier New', monospace;
font-size: 85%;
}
p > code, li > code {
padding: 2px 0px;
}
div.figure {
text-align: center;
}
img {
background-color: #FFFFFF;
padding: 2px;
border: 1px solid #DDDDDD;
border-radius: 3px;
border: 1px solid #CCCCCC;
margin: 0 5px;
}
h1 {
margin-top: 0;
font-size: 35px;
line-height: 40px;
}
h2 {
border-bottom: 4px solid #f7f7f7;
padding-top: 10px;
padding-bottom: 2px;
font-size: 145%;
}
h3 {
border-bottom: 2px solid #f7f7f7;
padding-top: 10px;
font-size: 120%;
}
h4 {
border-bottom: 1px solid #f7f7f7;
margin-left: 8px;
font-size: 105%;
}
h5, h6 {
border-bottom: 1px solid #ccc;
font-size: 105%;
}
a {
color: #0033dd;
text-decoration: none;
}
a:hover {
color: #6666ff; }
a:visited {
color: #800080; }
a:visited:hover {
color: #BB00BB; }
a[href^="http:"] {
text-decoration: underline; }
a[href^="https:"] {
text-decoration: underline; }

code > span.kw { color: #555; font-weight: bold; } 
code > span.dt { color: #902000; } 
code > span.dv { color: #40a070; } 
code > span.bn { color: #d14; } 
code > span.fl { color: #d14; } 
code > span.ch { color: #d14; } 
code > span.st { color: #d14; } 
code > span.co { color: #888888; font-style: italic; } 
code > span.ot { color: #007020; } 
code > span.al { color: #ff0000; font-weight: bold; } 
code > span.fu { color: #900; font-weight: bold; } 
code > span.er { color: #a61717; background-color: #e3d2d2; } 
</style>




</head>

<body>




<h1 class="title toc-ignore">Snapshot tests</h1>



<p>The goal of a unit test is to record the expected output of a
function using code. This is a powerful technique because not only does
it ensure that code doesn’t change unexpectedly, it also expresses the
desired behaviour in a way that a human can understand.</p>
<p>However, it’s not always convenient to record the expected behaviour
with code. Some challenges include:</p>
<ul>
<li><p>Text output that includes many characters like quotes and
newlines that require special handling in a string.</p></li>
<li><p>Output that is large, making it painful to define the reference
output, and bloating the size of the test file and making it hard to
navigate.</p></li>
<li><p>Binary formats like plots or images, which are very difficult to
describe in code: i.e. the plot looks right, the error message is useful
to a human, the print method uses colour effectively.</p></li>
</ul>
<p>For these situations, testthat provides an alternative mechanism:
snapshot tests. Instead of using code to describe expected output,
snapshot tests (also known as <a href="https://ro-che.info/articles/2017-12-04-golden-tests">golden
tests</a>) record results in a separate human readable file. Snapshot
tests in testthat are inspired primarily by <a href="https://jestjs.io/docs/en/snapshot-testing">Jest</a>, thanks to a
number of very useful discussions with Joe Cheng.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="fu">library</span>(testthat)</span></code></pre></div>
<div id="basic-workflow" class="section level2">
<h2>Basic workflow</h2>
<p>We’ll illustrate the basic workflow with a simple function that
generates an HTML heading. It can optionally include an <code>id</code>
attribute, which allows you to construct a link directly to that
heading.</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a>bullets <span class="ot">&lt;-</span> <span class="cf">function</span>(text, <span class="at">id =</span> <span class="cn">NULL</span>) {</span>
<span id="cb2-2"><a href="#cb2-2" tabindex="-1"></a>  <span class="fu">paste0</span>(</span>
<span id="cb2-3"><a href="#cb2-3" tabindex="-1"></a>    <span class="st">&quot;&lt;ul&quot;</span>, <span class="cf">if</span> (<span class="sc">!</span><span class="fu">is.null</span>(id)) <span class="fu">paste0</span>(<span class="st">&quot; id=</span><span class="sc">\&quot;</span><span class="st">&quot;</span>, id, <span class="st">&quot;</span><span class="sc">\&quot;</span><span class="st">&quot;</span>), <span class="st">&quot;&gt;</span><span class="sc">\n</span><span class="st">&quot;</span>, </span>
<span id="cb2-4"><a href="#cb2-4" tabindex="-1"></a>    <span class="fu">paste0</span>(<span class="st">&quot;  &lt;li&gt;&quot;</span>, text, <span class="st">&quot;&lt;/li&gt;</span><span class="sc">\n</span><span class="st">&quot;</span>, <span class="at">collapse =</span> <span class="st">&quot;&quot;</span>),</span>
<span id="cb2-5"><a href="#cb2-5" tabindex="-1"></a>    <span class="st">&quot;&lt;/ul&gt;</span><span class="sc">\n</span><span class="st">&quot;</span></span>
<span id="cb2-6"><a href="#cb2-6" tabindex="-1"></a>  )</span>
<span id="cb2-7"><a href="#cb2-7" tabindex="-1"></a>}</span>
<span id="cb2-8"><a href="#cb2-8" tabindex="-1"></a><span class="fu">cat</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>, <span class="at">id =</span> <span class="st">&quot;x&quot;</span>))</span>
<span id="cb2-9"><a href="#cb2-9" tabindex="-1"></a><span class="co">#&gt; &lt;ul id=&quot;x&quot;&gt;</span></span>
<span id="cb2-10"><a href="#cb2-10" tabindex="-1"></a><span class="co">#&gt;   &lt;li&gt;a&lt;/li&gt;</span></span>
<span id="cb2-11"><a href="#cb2-11" tabindex="-1"></a><span class="co">#&gt; &lt;/ul&gt;</span></span></code></pre></div>
<p>Testing this simple function is relatively painful. To write the test
you have to carefully escape the newlines and quotes. And then when you
re-read the test in the future, all that escaping makes it hard to tell
exactly what it’s supposed to return.</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;bullets&quot;</span>, {</span>
<span id="cb3-2"><a href="#cb3-2" tabindex="-1"></a>  <span class="fu">expect_equal</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>), <span class="st">&quot;&lt;ul&gt;</span><span class="sc">\n</span><span class="st">  &lt;li&gt;a&lt;/li&gt;</span><span class="sc">\n</span><span class="st">&lt;/ul&gt;</span><span class="sc">\n</span><span class="st">&quot;</span>)</span>
<span id="cb3-3"><a href="#cb3-3" tabindex="-1"></a>  <span class="fu">expect_equal</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>, <span class="at">id =</span> <span class="st">&quot;x&quot;</span>), <span class="st">&quot;&lt;ul id=</span><span class="sc">\&quot;</span><span class="st">x</span><span class="sc">\&quot;</span><span class="st">&gt;</span><span class="sc">\n</span><span class="st">  &lt;li&gt;a&lt;/li&gt;</span><span class="sc">\n</span><span class="st">&lt;/ul&gt;</span><span class="sc">\n</span><span class="st">&quot;</span>)</span>
<span id="cb3-4"><a href="#cb3-4" tabindex="-1"></a>})</span>
<span id="cb3-5"><a href="#cb3-5" tabindex="-1"></a><span class="co">#&gt; Test passed 🥇</span></span></code></pre></div>
<p>This is a great place to use snapshot testing. To do this we make two
changes to our code:</p>
<ul>
<li><p>We use <code>expect_snapshot()</code> instead of
<code>expect_equal()</code></p></li>
<li><p>We wrap the call in <code>cat()</code> (to avoid <code>[1]</code>
in the output, like in my first interactive example).</p></li>
</ul>
<p>This yields the following test:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;bullets&quot;</span>, {</span>
<span id="cb4-2"><a href="#cb4-2" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="fu">cat</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>)))</span>
<span id="cb4-3"><a href="#cb4-3" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="fu">cat</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>, <span class="st">&quot;b&quot;</span>)))</span>
<span id="cb4-4"><a href="#cb4-4" tabindex="-1"></a>})</span>
<span id="cb4-5"><a href="#cb4-5" tabindex="-1"></a><span class="co">#&gt; ── Warning: bullets ────────────────────────────────────────────────────────────</span></span>
<span id="cb4-6"><a href="#cb4-6" tabindex="-1"></a><span class="co">#&gt; Adding new snapshot:</span></span>
<span id="cb4-7"><a href="#cb4-7" tabindex="-1"></a><span class="co">#&gt; Code</span></span>
<span id="cb4-8"><a href="#cb4-8" tabindex="-1"></a><span class="co">#&gt;   cat(bullets(&quot;a&quot;))</span></span>
<span id="cb4-9"><a href="#cb4-9" tabindex="-1"></a><span class="co">#&gt; Output</span></span>
<span id="cb4-10"><a href="#cb4-10" tabindex="-1"></a><span class="co">#&gt;   &lt;ul&gt;</span></span>
<span id="cb4-11"><a href="#cb4-11" tabindex="-1"></a><span class="co">#&gt;     &lt;li&gt;a&lt;/li&gt;</span></span>
<span id="cb4-12"><a href="#cb4-12" tabindex="-1"></a><span class="co">#&gt;   &lt;/ul&gt;</span></span>
<span id="cb4-13"><a href="#cb4-13" tabindex="-1"></a><span class="co">#&gt; </span></span>
<span id="cb4-14"><a href="#cb4-14" tabindex="-1"></a><span class="co">#&gt; ── Warning: bullets ────────────────────────────────────────────────────────────</span></span>
<span id="cb4-15"><a href="#cb4-15" tabindex="-1"></a><span class="co">#&gt; Adding new snapshot:</span></span>
<span id="cb4-16"><a href="#cb4-16" tabindex="-1"></a><span class="co">#&gt; Code</span></span>
<span id="cb4-17"><a href="#cb4-17" tabindex="-1"></a><span class="co">#&gt;   cat(bullets(&quot;a&quot;, &quot;b&quot;))</span></span>
<span id="cb4-18"><a href="#cb4-18" tabindex="-1"></a><span class="co">#&gt; Output</span></span>
<span id="cb4-19"><a href="#cb4-19" tabindex="-1"></a><span class="co">#&gt;   &lt;ul id=&quot;b&quot;&gt;</span></span>
<span id="cb4-20"><a href="#cb4-20" tabindex="-1"></a><span class="co">#&gt;     &lt;li&gt;a&lt;/li&gt;</span></span>
<span id="cb4-21"><a href="#cb4-21" tabindex="-1"></a><span class="co">#&gt;   &lt;/ul&gt;</span></span></code></pre></div>
<p>When we run the test for the first time, it automatically generates
reference output, and prints it, so that you can visually confirm that
it’s correct. The output is automatically saved in
<code>_snaps/{name}.md</code>. The name of the snapshot matches your
test file name — e.g. if your test is <code>test-pizza.R</code> then
your snapshot will be saved in
<code>test/testthat/_snaps/pizza.md</code>. As the file name suggests,
this is a markdown file, which I’ll explain shortly.</p>
<p>If you run the test again, it’ll succeed:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;bullets&quot;</span>, {</span>
<span id="cb5-2"><a href="#cb5-2" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="fu">cat</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>)))</span>
<span id="cb5-3"><a href="#cb5-3" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="fu">cat</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>, <span class="st">&quot;b&quot;</span>)))</span>
<span id="cb5-4"><a href="#cb5-4" tabindex="-1"></a>})</span>
<span id="cb5-5"><a href="#cb5-5" tabindex="-1"></a><span class="co">#&gt; Test passed 🎊</span></span></code></pre></div>
<p>But if you change the underlying code, say to tweak the indenting,
the test will fail:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" tabindex="-1"></a>bullets <span class="ot">&lt;-</span> <span class="cf">function</span>(text, <span class="at">id =</span> <span class="cn">NULL</span>) {</span>
<span id="cb6-2"><a href="#cb6-2" tabindex="-1"></a>  <span class="fu">paste0</span>(</span>
<span id="cb6-3"><a href="#cb6-3" tabindex="-1"></a>    <span class="st">&quot;&lt;ul&quot;</span>, <span class="cf">if</span> (<span class="sc">!</span><span class="fu">is.null</span>(id)) <span class="fu">paste0</span>(<span class="st">&quot; id=</span><span class="sc">\&quot;</span><span class="st">&quot;</span>, id, <span class="st">&quot;</span><span class="sc">\&quot;</span><span class="st">&quot;</span>), <span class="st">&quot;&gt;</span><span class="sc">\n</span><span class="st">&quot;</span>, </span>
<span id="cb6-4"><a href="#cb6-4" tabindex="-1"></a>    <span class="fu">paste0</span>(<span class="st">&quot;&lt;li&gt;&quot;</span>, text, <span class="st">&quot;&lt;/li&gt;</span><span class="sc">\n</span><span class="st">&quot;</span>, <span class="at">collapse =</span> <span class="st">&quot;&quot;</span>),</span>
<span id="cb6-5"><a href="#cb6-5" tabindex="-1"></a>    <span class="st">&quot;&lt;/ul&gt;</span><span class="sc">\n</span><span class="st">&quot;</span></span>
<span id="cb6-6"><a href="#cb6-6" tabindex="-1"></a>  )</span>
<span id="cb6-7"><a href="#cb6-7" tabindex="-1"></a>}</span>
<span id="cb6-8"><a href="#cb6-8" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;bullets&quot;</span>, {</span>
<span id="cb6-9"><a href="#cb6-9" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="fu">cat</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>)))</span>
<span id="cb6-10"><a href="#cb6-10" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="fu">cat</span>(<span class="fu">bullets</span>(<span class="st">&quot;a&quot;</span>, <span class="st">&quot;b&quot;</span>)))</span>
<span id="cb6-11"><a href="#cb6-11" tabindex="-1"></a>})</span>
<span id="cb6-12"><a href="#cb6-12" tabindex="-1"></a><span class="co">#&gt; ── Failure: bullets ────────────────────────────────────────────────────────────</span></span>
<span id="cb6-13"><a href="#cb6-13" tabindex="-1"></a><span class="co">#&gt; Snapshot of code has changed:</span></span>
<span id="cb6-14"><a href="#cb6-14" tabindex="-1"></a><span class="co">#&gt;     old                 | new                    </span></span>
<span id="cb6-15"><a href="#cb6-15" tabindex="-1"></a><span class="co">#&gt; [2]   cat(bullets(&quot;a&quot;)) |   cat(bullets(&quot;a&quot;)) [2]</span></span>
<span id="cb6-16"><a href="#cb6-16" tabindex="-1"></a><span class="co">#&gt; [3] Output              | Output              [3]</span></span>
<span id="cb6-17"><a href="#cb6-17" tabindex="-1"></a><span class="co">#&gt; [4]   &lt;ul&gt;              |   &lt;ul&gt;              [4]</span></span>
<span id="cb6-18"><a href="#cb6-18" tabindex="-1"></a><span class="co">#&gt; [5]     &lt;li&gt;a&lt;/li&gt;      -   &lt;li&gt;a&lt;/li&gt;        [5]</span></span>
<span id="cb6-19"><a href="#cb6-19" tabindex="-1"></a><span class="co">#&gt; [6]   &lt;/ul&gt;             |   &lt;/ul&gt;             [6]</span></span>
<span id="cb6-20"><a href="#cb6-20" tabindex="-1"></a><span class="co">#&gt; </span></span>
<span id="cb6-21"><a href="#cb6-21" tabindex="-1"></a><span class="co">#&gt; * Run `testthat::snapshot_accept(&#39;snapshotting.Rmd&#39;)` to accept the change.</span></span>
<span id="cb6-22"><a href="#cb6-22" tabindex="-1"></a><span class="co">#&gt; * Run `testthat::snapshot_review(&#39;snapshotting.Rmd&#39;)` to interactively review the change.</span></span>
<span id="cb6-23"><a href="#cb6-23" tabindex="-1"></a><span class="co">#&gt; </span></span>
<span id="cb6-24"><a href="#cb6-24" tabindex="-1"></a><span class="co">#&gt; ── Failure: bullets ────────────────────────────────────────────────────────────</span></span>
<span id="cb6-25"><a href="#cb6-25" tabindex="-1"></a><span class="co">#&gt; Snapshot of code has changed:</span></span>
<span id="cb6-26"><a href="#cb6-26" tabindex="-1"></a><span class="co">#&gt;     old                      | new                         </span></span>
<span id="cb6-27"><a href="#cb6-27" tabindex="-1"></a><span class="co">#&gt; [2]   cat(bullets(&quot;a&quot;, &quot;b&quot;)) |   cat(bullets(&quot;a&quot;, &quot;b&quot;)) [2]</span></span>
<span id="cb6-28"><a href="#cb6-28" tabindex="-1"></a><span class="co">#&gt; [3] Output                   | Output                   [3]</span></span>
<span id="cb6-29"><a href="#cb6-29" tabindex="-1"></a><span class="co">#&gt; [4]   &lt;ul id=&quot;b&quot;&gt;            |   &lt;ul id=&quot;b&quot;&gt;            [4]</span></span>
<span id="cb6-30"><a href="#cb6-30" tabindex="-1"></a><span class="co">#&gt; [5]     &lt;li&gt;a&lt;/li&gt;           -   &lt;li&gt;a&lt;/li&gt;             [5]</span></span>
<span id="cb6-31"><a href="#cb6-31" tabindex="-1"></a><span class="co">#&gt; [6]   &lt;/ul&gt;                  |   &lt;/ul&gt;                  [6]</span></span>
<span id="cb6-32"><a href="#cb6-32" tabindex="-1"></a><span class="co">#&gt; </span></span>
<span id="cb6-33"><a href="#cb6-33" tabindex="-1"></a><span class="co">#&gt; * Run `testthat::snapshot_accept(&#39;snapshotting.Rmd&#39;)` to accept the change.</span></span>
<span id="cb6-34"><a href="#cb6-34" tabindex="-1"></a><span class="co">#&gt; * Run `testthat::snapshot_review(&#39;snapshotting.Rmd&#39;)` to interactively review the change.</span></span>
<span id="cb6-35"><a href="#cb6-35" tabindex="-1"></a><span class="co">#&gt; Error:</span></span>
<span id="cb6-36"><a href="#cb6-36" tabindex="-1"></a><span class="co">#&gt; ! Test failed</span></span></code></pre></div>
<p>If this is a deliberate change, you can follow the advice in the
message and update the snapshots for that file by running
<code>snapshot_accept(&quot;pizza&quot;)</code>; otherwise you can fix the bug and
your tests will pass once more. (You can also accept snapshot for all
files with <code>snapshot_accept()</code>).</p>
<div id="snapshot-format" class="section level3">
<h3>Snapshot format</h3>
<p>Snapshots are recorded using a subset of markdown. You might wonder
why we use markdown? It’s important that snapshots be readable by
humans, because humans have to look at it during code reviews. Reviewers
often don’t run your code but still want to understand the changes.</p>
<p>Here’s the snapshot file generated by the test above:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode md"><code class="sourceCode markdown"><span id="cb7-1"><a href="#cb7-1" tabindex="-1"></a><span class="fu"># bullets</span></span>
<span id="cb7-2"><a href="#cb7-2" tabindex="-1"></a></span>
<span id="cb7-3"><a href="#cb7-3" tabindex="-1"></a><span class="in">    &lt;ul&gt;</span></span>
<span id="cb7-4"><a href="#cb7-4" tabindex="-1"></a><span class="in">      &lt;li&gt;a&lt;/li&gt;</span></span>
<span id="cb7-5"><a href="#cb7-5" tabindex="-1"></a><span class="in">    &lt;/ul&gt;</span></span>
<span id="cb7-6"><a href="#cb7-6" tabindex="-1"></a>  </span>
<span id="cb7-7"><a href="#cb7-7" tabindex="-1"></a>---</span>
<span id="cb7-8"><a href="#cb7-8" tabindex="-1"></a></span>
<span id="cb7-9"><a href="#cb7-9" tabindex="-1"></a><span class="in">    &lt;ul id=&quot;x&quot;&gt;</span></span>
<span id="cb7-10"><a href="#cb7-10" tabindex="-1"></a><span class="in">      &lt;li&gt;a&lt;/li&gt;</span></span>
<span id="cb7-11"><a href="#cb7-11" tabindex="-1"></a><span class="in">    &lt;/ul&gt;</span></span></code></pre></div>
<p>Each test starts with <code># {test name}</code>, a level 1 heading.
Within a test, each snapshot expectation is indented by four spaces,
i.e. as code, and are separated by <code>---</code>, a horizontal
rule.</p>
</div>
<div id="interactive-usage" class="section level3">
<h3>Interactive usage</h3>
<p>Because the snapshot output uses the name of the current test file
and the current test, snapshot expectations don’t really work when run
interactively at the console. Since they can’t automatically find the
reference output, they instead just print the current value for manual
inspection.</p>
</div>
</div>
<div id="other-types-of-output" class="section level2">
<h2>Other types of output</h2>
<p>So far we’ve focussed on snapshot tests for output printed to the
console. But <code>expect_snapshot()</code> also captures messages,
errors, and warnings<a href="#fn1" class="footnote-ref" id="fnref1"><sup>1</sup></a>. The following function generates a some
output, a message, and a warning:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" tabindex="-1"></a>f <span class="ot">&lt;-</span> <span class="cf">function</span>() {</span>
<span id="cb8-2"><a href="#cb8-2" tabindex="-1"></a>  <span class="fu">print</span>(<span class="st">&quot;Hello&quot;</span>)</span>
<span id="cb8-3"><a href="#cb8-3" tabindex="-1"></a>  <span class="fu">message</span>(<span class="st">&quot;Hi!&quot;</span>)</span>
<span id="cb8-4"><a href="#cb8-4" tabindex="-1"></a>  <span class="fu">warning</span>(<span class="st">&quot;How are you?&quot;</span>)</span>
<span id="cb8-5"><a href="#cb8-5" tabindex="-1"></a>}</span></code></pre></div>
<p>And <code>expect_snapshot()</code> captures them all:</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;f() makes lots of noise&quot;</span>, {</span>
<span id="cb9-2"><a href="#cb9-2" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="fu">f</span>())</span>
<span id="cb9-3"><a href="#cb9-3" tabindex="-1"></a>})</span>
<span id="cb9-4"><a href="#cb9-4" tabindex="-1"></a><span class="co">#&gt; ── Warning: f() makes lots of noise ────────────────────────────────────────────</span></span>
<span id="cb9-5"><a href="#cb9-5" tabindex="-1"></a><span class="co">#&gt; Adding new snapshot:</span></span>
<span id="cb9-6"><a href="#cb9-6" tabindex="-1"></a><span class="co">#&gt; Code</span></span>
<span id="cb9-7"><a href="#cb9-7" tabindex="-1"></a><span class="co">#&gt;   f()</span></span>
<span id="cb9-8"><a href="#cb9-8" tabindex="-1"></a><span class="co">#&gt; Output</span></span>
<span id="cb9-9"><a href="#cb9-9" tabindex="-1"></a><span class="co">#&gt;   [1] &quot;Hello&quot;</span></span>
<span id="cb9-10"><a href="#cb9-10" tabindex="-1"></a><span class="co">#&gt; Message</span></span>
<span id="cb9-11"><a href="#cb9-11" tabindex="-1"></a><span class="co">#&gt;   Hi!</span></span>
<span id="cb9-12"><a href="#cb9-12" tabindex="-1"></a><span class="co">#&gt; Condition</span></span>
<span id="cb9-13"><a href="#cb9-13" tabindex="-1"></a><span class="co">#&gt;   Warning in `f()`:</span></span>
<span id="cb9-14"><a href="#cb9-14" tabindex="-1"></a><span class="co">#&gt;   How are you?</span></span></code></pre></div>
<p>Capturing errors is <em>slightly</em> more difficult because
<code>expect_snapshot()</code> will fail when there’s an error:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;you can&#39;t add a number and a letter&quot;</span>, {</span>
<span id="cb10-2"><a href="#cb10-2" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="dv">1</span> <span class="sc">+</span> <span class="st">&quot;a&quot;</span>)</span>
<span id="cb10-3"><a href="#cb10-3" tabindex="-1"></a>})</span>
<span id="cb10-4"><a href="#cb10-4" tabindex="-1"></a><span class="co">#&gt; ── Error: you can&#39;t add a number and a letter ──────────────────────────────────</span></span>
<span id="cb10-5"><a href="#cb10-5" tabindex="-1"></a><span class="co">#&gt; Error in `1 + &quot;a&quot;`: non-numeric argument to binary operator</span></span>
<span id="cb10-6"><a href="#cb10-6" tabindex="-1"></a><span class="co">#&gt; Backtrace:</span></span>
<span id="cb10-7"><a href="#cb10-7" tabindex="-1"></a><span class="co">#&gt;     ▆</span></span>
<span id="cb10-8"><a href="#cb10-8" tabindex="-1"></a><span class="co">#&gt;  1. └─testthat::expect_snapshot(1 + &quot;a&quot;)</span></span>
<span id="cb10-9"><a href="#cb10-9" tabindex="-1"></a><span class="co">#&gt;  2.   └─rlang::cnd_signal(state$error)</span></span>
<span id="cb10-10"><a href="#cb10-10" tabindex="-1"></a><span class="co">#&gt; Error:</span></span>
<span id="cb10-11"><a href="#cb10-11" tabindex="-1"></a><span class="co">#&gt; ! Test failed</span></span></code></pre></div>
<p>This is a safety valve that ensures that you don’t accidentally write
broken code. To deliberately snapshot an error, you’ll have to
specifically request it with <code>error = TRUE</code>:</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;you can&#39;t add a number and a letter&quot;</span>, {</span>
<span id="cb11-2"><a href="#cb11-2" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="dv">1</span> <span class="sc">+</span> <span class="st">&quot;a&quot;</span>, <span class="at">error =</span> <span class="cn">TRUE</span>)</span>
<span id="cb11-3"><a href="#cb11-3" tabindex="-1"></a>})</span>
<span id="cb11-4"><a href="#cb11-4" tabindex="-1"></a><span class="co">#&gt; ── Warning: you can&#39;t add a number and a letter ────────────────────────────────</span></span>
<span id="cb11-5"><a href="#cb11-5" tabindex="-1"></a><span class="co">#&gt; Adding new snapshot:</span></span>
<span id="cb11-6"><a href="#cb11-6" tabindex="-1"></a><span class="co">#&gt; Code</span></span>
<span id="cb11-7"><a href="#cb11-7" tabindex="-1"></a><span class="co">#&gt;   1 + &quot;a&quot;</span></span>
<span id="cb11-8"><a href="#cb11-8" tabindex="-1"></a><span class="co">#&gt; Condition</span></span>
<span id="cb11-9"><a href="#cb11-9" tabindex="-1"></a><span class="co">#&gt;   Error in `1 + &quot;a&quot;`:</span></span>
<span id="cb11-10"><a href="#cb11-10" tabindex="-1"></a><span class="co">#&gt;   ! non-numeric argument to binary operator</span></span></code></pre></div>
<p>When the code gets longer, I like to put <code>error = TRUE</code> up
front so it’s a little more obvious:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;you can&#39;t add weird things&quot;</span>, {</span>
<span id="cb12-2"><a href="#cb12-2" tabindex="-1"></a>  <span class="fu">expect_snapshot</span>(<span class="at">error =</span> <span class="cn">TRUE</span>, {</span>
<span id="cb12-3"><a href="#cb12-3" tabindex="-1"></a>    <span class="dv">1</span> <span class="sc">+</span> <span class="st">&quot;a&quot;</span></span>
<span id="cb12-4"><a href="#cb12-4" tabindex="-1"></a>    mtcars <span class="sc">+</span> iris</span>
<span id="cb12-5"><a href="#cb12-5" tabindex="-1"></a>    mean <span class="sc">+</span> sum</span>
<span id="cb12-6"><a href="#cb12-6" tabindex="-1"></a>  })</span>
<span id="cb12-7"><a href="#cb12-7" tabindex="-1"></a>})</span>
<span id="cb12-8"><a href="#cb12-8" tabindex="-1"></a><span class="co">#&gt; ── Warning: you can&#39;t add weird things ─────────────────────────────────────────</span></span>
<span id="cb12-9"><a href="#cb12-9" tabindex="-1"></a><span class="co">#&gt; Adding new snapshot:</span></span>
<span id="cb12-10"><a href="#cb12-10" tabindex="-1"></a><span class="co">#&gt; Code</span></span>
<span id="cb12-11"><a href="#cb12-11" tabindex="-1"></a><span class="co">#&gt;   1 + &quot;a&quot;</span></span>
<span id="cb12-12"><a href="#cb12-12" tabindex="-1"></a><span class="co">#&gt; Condition</span></span>
<span id="cb12-13"><a href="#cb12-13" tabindex="-1"></a><span class="co">#&gt;   Error in `1 + &quot;a&quot;`:</span></span>
<span id="cb12-14"><a href="#cb12-14" tabindex="-1"></a><span class="co">#&gt;   ! non-numeric argument to binary operator</span></span>
<span id="cb12-15"><a href="#cb12-15" tabindex="-1"></a><span class="co">#&gt; Code</span></span>
<span id="cb12-16"><a href="#cb12-16" tabindex="-1"></a><span class="co">#&gt;   mtcars + iris</span></span>
<span id="cb12-17"><a href="#cb12-17" tabindex="-1"></a><span class="co">#&gt; Condition</span></span>
<span id="cb12-18"><a href="#cb12-18" tabindex="-1"></a><span class="co">#&gt;   Error in `Ops.data.frame()`:</span></span>
<span id="cb12-19"><a href="#cb12-19" tabindex="-1"></a><span class="co">#&gt;   ! &#39;+&#39; only defined for equally-sized data frames</span></span>
<span id="cb12-20"><a href="#cb12-20" tabindex="-1"></a><span class="co">#&gt; Code</span></span>
<span id="cb12-21"><a href="#cb12-21" tabindex="-1"></a><span class="co">#&gt;   mean + sum</span></span>
<span id="cb12-22"><a href="#cb12-22" tabindex="-1"></a><span class="co">#&gt; Condition</span></span>
<span id="cb12-23"><a href="#cb12-23" tabindex="-1"></a><span class="co">#&gt;   Error in `mean + sum`:</span></span>
<span id="cb12-24"><a href="#cb12-24" tabindex="-1"></a><span class="co">#&gt;   ! non-numeric argument to binary operator</span></span></code></pre></div>
</div>
<div id="snapshotting-values" class="section level2">
<h2>Snapshotting values</h2>
<p><code>expect_snapshot()</code> is the most used snapshot function
because it records everything: the code you run, printed output,
messages, warnings, and errors. If you care about the return value
rather than any side-effects, you may might to use
<code>expect_snapshot_value()</code> instead. It offers a number of
serialisation approaches that provide a tradeoff between accuracy and
human readability.</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1" tabindex="-1"></a><span class="fu">test_that</span>(<span class="st">&quot;can snapshot a simple list&quot;</span>, {</span>
<span id="cb13-2"><a href="#cb13-2" tabindex="-1"></a>  x <span class="ot">&lt;-</span> <span class="fu">list</span>(<span class="at">a =</span> <span class="fu">list</span>(<span class="dv">1</span>, <span class="dv">5</span>, <span class="dv">10</span>), <span class="at">b =</span> <span class="fu">list</span>(<span class="st">&quot;elephant&quot;</span>, <span class="st">&quot;banana&quot;</span>))</span>
<span id="cb13-3"><a href="#cb13-3" tabindex="-1"></a>  <span class="fu">expect_snapshot_value</span>(x)</span>
<span id="cb13-4"><a href="#cb13-4" tabindex="-1"></a>})</span>
<span id="cb13-5"><a href="#cb13-5" tabindex="-1"></a><span class="co">#&gt; ── Warning: can snapshot a simple list ─────────────────────────────────────────</span></span>
<span id="cb13-6"><a href="#cb13-6" tabindex="-1"></a><span class="co">#&gt; Adding new snapshot:</span></span>
<span id="cb13-7"><a href="#cb13-7" tabindex="-1"></a><span class="co">#&gt; {</span></span>
<span id="cb13-8"><a href="#cb13-8" tabindex="-1"></a><span class="co">#&gt;   &quot;a&quot;: [</span></span>
<span id="cb13-9"><a href="#cb13-9" tabindex="-1"></a><span class="co">#&gt;     1,</span></span>
<span id="cb13-10"><a href="#cb13-10" tabindex="-1"></a><span class="co">#&gt;     5,</span></span>
<span id="cb13-11"><a href="#cb13-11" tabindex="-1"></a><span class="co">#&gt;     10</span></span>
<span id="cb13-12"><a href="#cb13-12" tabindex="-1"></a><span class="co">#&gt;   ],</span></span>
<span id="cb13-13"><a href="#cb13-13" tabindex="-1"></a><span class="co">#&gt;   &quot;b&quot;: [</span></span>
<span id="cb13-14"><a href="#cb13-14" tabindex="-1"></a><span class="co">#&gt;     &quot;elephant&quot;,</span></span>
<span id="cb13-15"><a href="#cb13-15" tabindex="-1"></a><span class="co">#&gt;     &quot;banana&quot;</span></span>
<span id="cb13-16"><a href="#cb13-16" tabindex="-1"></a><span class="co">#&gt;   ]</span></span>
<span id="cb13-17"><a href="#cb13-17" tabindex="-1"></a><span class="co">#&gt; }</span></span></code></pre></div>
</div>
<div id="whole-file-snapshotting" class="section level2">
<h2>Whole file snapshotting</h2>
<p><code>expect_snapshot()</code>,
<code>expect_snapshot_output()</code>,
<code>expect_snapshot_error()</code>, and
<code>expect_snapshot_value()</code> use one snapshot file per test
file. But that doesn’t work for all file types — for example, what
happens if you want to snapshot an image?
<code>expect_snapshot_file()</code> provides an alternative workflow
that generates one snapshot per expectation, rather than one file per
test. Assuming you’re in <code>test-burger.R</code> then the snapshot
created by
<code>expect_snapshot_file(code_that_returns_path_to_file(), &quot;toppings.png&quot;)</code>
would be saved in
<code>tests/testthat/_snaps/burger/toppings.png</code>. If a future
change in the code creates a different file it will be saved in
<code>tests/testthat/_snaps/burger/toppings.new.png</code>.</p>
<p>Unlike <code>expect_snapshot()</code> and friends,
<code>expect_snapshot_file()</code> can’t provide an automatic diff when
the test fails. Instead you’ll need to call
<code>snapshot_review()</code>. This launches a Shiny app that allows
you to visually review each change and approve it if it’s
deliberate:</p>
<p><img role="img" aria-label="Screenshot of the Shiny app for reviewing snapshot changes to images. It shows the changes to a png file of a plot created in a snapshot test. There is a button to accept the changed snapshot, or to skip it." src="data:image/png;base64,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" alt="Screenshot of the Shiny app for reviewing snapshot changes to images. It shows the changes to a png file of a plot created in a snapshot test. There is a button to accept the changed snapshot, or to skip it." width="600" /></p>
<p><img role="img" aria-label="Screenshot of the Shiny app for reviewing snapshot changes to text files. It shows the changes to a .R file created in a snapshot test, where a line has been removed. There is a button to accept the changed snapshot, or to skip it." src="data:image/png;base64,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" alt="Screenshot of the Shiny app for reviewing snapshot changes to text files. It shows the changes to a .R file created in a snapshot test, where a line has been removed. There is a button to accept the changed snapshot, or to skip it." width="600" /></p>
<p>The display varies based on the file type (currently text files,
common image files, and csv files are supported).</p>
<p>Sometimes the failure occurs in a non-interactive environment where
you can’t run <code>snapshot_review()</code>, e.g. in
<code>R CMD check</code>. In this case, the easiest fix is to retrieve
the <code>.new</code> file, copy it into the appropriate directory, then
run <code>snapshot_review()</code> locally. If your code was run on a CI
platform, you’ll need to start by downloading the run “artifact”, which
contains the check folder.</p>
<p>In most cases, we don’t expect you to use
<code>expect_snapshot_file()</code> directly. Instead, you’ll use it via
a wrapper that does its best to gracefully skip tests when differences
in platform or package versions make it unlikely to generate perfectly
reproducible output.</p>
</div>
<div id="previous-work" class="section level2">
<h2>Previous work</h2>
<p>This is not the first time that testthat has attempted to provide
snapshot testing (although it’s the first time I knew what other
languages called them). This section describes some of the previous
attempts and why we believe the new approach is better.</p>
<ul>
<li><p><code>verify_output()</code> has three main drawbacks:</p>
<ul>
<li><p>You have to supply a path where the output will be saved. This
seems like a small issue, but thinking of a good name, and managing the
difference between interactive and test-time paths introduces a
surprising amount of friction.</p></li>
<li><p>It always overwrites the previous result; automatically assuming
that the changes are correct. That means you have to use it with git and
it’s easy to accidentally accept unwanted changes.</p></li>
<li><p>It’s relatively coarse grained, which means tests that use it
tend to keep growing and growing.</p></li>
</ul></li>
<li><p><code>expect_known_output()</code> is finer grained version of
<code>verify_output()</code> that captures output from a single
function. The requirement to produce a path for each individual
expectation makes it even more painful to use.</p></li>
<li><p><code>expect_known_value()</code> and
<code>expect_known_hash()</code> have all the disadvantages of
<code>expect_known_output()</code>, but also produce binary output
meaning that you can’t easily review test differences in pull
requests.</p></li>
</ul>
</div>
<div class="footnotes footnotes-end-of-document">
<hr />
<ol>
<li id="fn1"><p>We no longer recommend
<code>expect_snapshot_output()</code>,
<code>expect_snapshot_warning()</code>, or
<code>expect_snapshot_error()</code>. Just use
<code>expect_snapshot()</code>.<a href="#fnref1" class="footnote-back">↩︎</a></p></li>
</ol>
</div>



<!-- code folding -->


<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
  (function () {
    var script = document.createElement("script");
    script.type = "text/javascript";
    script.src  = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML";
    document.getElementsByTagName("head")[0].appendChild(script);
  })();
</script>

</body>
</html>