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targets_basics.html
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targets_basics.html
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<h1 class="title toc-ignore">Pipelines com targets</h1>
<h4 class="author">Gabriel Nakamura</h4>
<h4 class="date">2023-08-17</h4>
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<div id="apresentação" class="section level1">
<h1>Apresentação</h1>
<p>Algumas análises são extremamente demoradas para rodar, mas um
trabalho reprodutível computacionamente requer que estas análises rodem
repetidamente, porém isso pode custar muitas horas, ou até mesmo dias
para rodar algumas rotinas. Uma solução para otimizar a sequência de
trabalho é o pacote <code>{targets}</code></p>
</div>
<div id="targets" class="section level1">
<h1><code>{targets}</code></h1>
<p>O pacote <code>{targets}</code> possibilita otimizar a sequência de
trabalho (pipeline) por organizar esta sequência e identificar ações na
pipeline que devem ou não devem ser realizadas.</p>
<div id="exemplo" class="section level2">
<h2>Exemplo</h2>
<p>Para ilustrar o uso do pacote targets vamos utilizar um exemplo
contido na própria <a
href="https://books.ropensci.org/targets/">documentação do
pacote</a>.</p>
<p>Neste exemplo vamos analisar a relação entre quantidade de ozônio e
temperatura em um conjunto de dados presentes no próprio R base chamado
<code>airquality</code>. Para tanto precisamos seguir uma sequência de
análise de dados, que, basicamente, consiste em:</p>
<ol style="list-style-type: decimal">
<li><p>Ler e manipular a tabela de dados</p></li>
<li><p>Rodar um modelo relacionando ozônio e temperatura</p></li>
<li><p>Gerar resultados gráficos (figuras) para o modelo
ajustado</p></li>
</ol>
<p>A base de dados pode ser lida da seguinte forma</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">data</span>(airquality)</span>
<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a>airquality</span></code></pre></div>
<p>Imagine que estes dados estão organizados em um diretório local
inicializado a partir de um .Rproject e ele apresenta a seguinte
estrutura:</p>
<ul>
<li><p>Uma pasta <code>data</code> contendo os dados</p></li>
<li><p>Uma pasta R contendo:</p>
<ul>
<li>script com a leitura e transformação dos dados</li>
<li>script com o modelo</li>
<li>script com funções para plotar os resultados do modelo ajustado</li>
</ul></li>
</ul>
<p>Esta seria uma pasta organizada, tal como vimos durante as aulas.
Porém, para que o pacote targets funciona precisamos transformar esta
estrutura de acordo com um pipeline targets, que por sua vez necessita
da seguinte estrutura:</p>
<p><img src="figs/dir_targets.png" width="682" style="display: block; margin: auto;" /></p>
<p>Neste diretório precisamos transformar a sequência apresentada
anteriormente em uma sequência de funções. Portanto os scripts na pasta
R serão transformados em funções que serão colocadas dentro da pasta R,
com o nome de <code>functions.R</code>, e que apresentará a seguinte
forma:</p>
<p><img src="figs/pipeline-target.png" width="647" style="display: block; margin: auto;" /></p>
<p>Veja que a mesma sequência de análise está agora representada como
funções, naquilo que chamamos de uma <em>pipeline function</em>. Este
formato é necessário pois apenas assim o targets irá funcionar.</p>
<p>Uma vez organizado assim, devemos utilizar uma função do pacote
targets para gerar um workflow do tipo target. Isso será feito da
seguinte maneira:</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>targets<span class="sc">::</span><span class="fu">use_targets</span>()</span></code></pre></div>
<p>Isso criará um documento na raiz do seu projeto denominado
<code>_targets.R</code>, como ilustrado na figura abaixo, que representa
um diretório que segue um workflow do targets</p>
<p><img src="figs/target_target-file.png" width="1274" style="display: block; margin: auto;" /></p>
<p>O documento criado informará a sequência do workflow de análise que o
pacote targets deve seguir. Após editar o documento para este exemplo
ele ficará da seguinte forma</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="co"># _targets.R file</span></span>
<span id="cb3-2"><a href="#cb3-2" tabindex="-1"></a><span class="fu">library</span>(targets)</span>
<span id="cb3-3"><a href="#cb3-3" tabindex="-1"></a><span class="fu">source</span>(<span class="st">"R/functions.R"</span>)</span>
<span id="cb3-4"><a href="#cb3-4" tabindex="-1"></a><span class="fu">tar_option_set</span>(<span class="at">packages =</span> <span class="fu">c</span>(<span class="st">"readr"</span>, <span class="st">"dplyr"</span>, <span class="st">"ggplot2"</span>))</span>
<span id="cb3-5"><a href="#cb3-5" tabindex="-1"></a><span class="fu">list</span>(</span>
<span id="cb3-6"><a href="#cb3-6" tabindex="-1"></a> <span class="fu">tar_target</span>(file, <span class="st">"data.csv"</span>, <span class="at">format =</span> <span class="st">"file"</span>),</span>
<span id="cb3-7"><a href="#cb3-7" tabindex="-1"></a> <span class="fu">tar_target</span>(data, <span class="fu">get_data</span>(file)),</span>
<span id="cb3-8"><a href="#cb3-8" tabindex="-1"></a> <span class="fu">tar_target</span>(model, <span class="fu">fit_model</span>(data)),</span>
<span id="cb3-9"><a href="#cb3-9" tabindex="-1"></a> <span class="fu">tar_target</span>(plot, <span class="fu">plot_model</span>(model, data))</span>
<span id="cb3-10"><a href="#cb3-10" tabindex="-1"></a>)</span></code></pre></div>
<p>Neste exemplo o arquivo apresenta os seguintes componentes:</p>
<ul>
<li><p>As funções necessárias para rodar o workflow</p></li>
<li><p>os pacotes necessários</p></li>
<li><p>uma lista que indica a sequência que o workflow deve
obedecer</p></li>
</ul>
<p>Para rodar o workflow via targets usamos a seguinte função</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>targets<span class="sc">::</span><span class="fu">tar_make</span>()</span></code></pre></div>
<p>A sequência do workflow vai iniciar e o tempo decorrido vai aparecer
no console</p>
<p><img src="figs/target_run.png" width="663" style="display: block; margin: auto;" /></p>
<div id="visualizando-o-workflow" class="section level3">
<h3>Visualizando o workflow</h3>
<p>Uma das vantagens do target é que podemos visualizar a sequência do
workflow e se ele está atualizado ou não. Para isso usamos a seguinte
função</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>targets<span class="sc">::</span><span class="fu">tar_visnetwork</span>()</span></code></pre></div>
<p>Esta função vai produzir um gráfico como mostrado nesta figura</p>
<p><img src="figs/target_viz.png" width="1275" style="display: block; margin: auto;" /></p>
<p>Podemos também acessar o output do workflow</p>
<p><img src="figs/target_viz_2.png" width="1275" style="display: block; margin: auto;" /></p>
</div>
<div id="identificando-mudanças-no-workflow" class="section level3">
<h3>Identificando mudanças no workflow</h3>
<p>Uma das maiores potencialidades do targets é identificar de maneira
eficiente partes do workflow que precisam ser rodadas novamente após
realizarmos mudanças na nossa pipeline. Por exemplo, vamos supor que
modificamos apenas um parâmetro que afeta a estética do plot final dos
resultados do modelo. Não necessitamos rodar tudo de novo, apenas a
figura resultante do modelo. O targets identifica onde esta modificação
foi feita e aponta a parte do workflow que precisa ser rodado novamente.
Podemos identificar isso através da função <code>tar_viznetwork()</code>
que vai gerar a seguinte figura (dado a situação descrita acima)</p>
<p><img src="figs/target_mudanca.png" width="1276" style="display: block; margin: auto;" /></p>
<p>A identificação do local exato de mudança do workflow é possível
graças ao target, evitando que tenhamos que rodar todo o workflow do
início ao fim, prática que é chamada de <a
href="https://www.worldhistory.org/sisyphus/">loop Sisypheano</a></p>
<p><img src="figs/Sisyphus.jpeg" width="125" style="display: block; margin: auto;" /></p>
</div>
</div>
</div>
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