Dynamic class names are becoming increasingly common in modern web landscape which can be a tough challenge in web scraping. Let's take a look at this dynamic class example and how can we parse it:
<div class="pdd fg-black">
<h2>Product Details</h2>
<div class="fqv b1">
<div class="fz g1">Price</div>
<div class="g2 cvx">22.55</div>
</div>
</div>
Usually, we'd see some human-like class names that we can rely on using CSS Selectors, however in this case the class names look non-sensical which means these classes are most likely dynamic. Dynamic classes can change at any moment which would break our scraper.
The best way to deal with this issue is to use text-based XPath parsing. In our example above to select the price we can find HTML elements by text and relative relationship. See this interactive example:
In this example, we select an element that has the text of Price and then select the first following sibling for the price value. With this approach even if the class names will change our parser will continue to extract data successfully!
For more on text-based parsing see:
In this short intro we'll be taking a look at web microformats. What are microformats and how can we take advantage in web scraping? We'll do a quick overview and some examples in Python using extrcut library.
JSONPath is a path expression language for JSON. It is used to query data from JSON datasets and it is similar to XPath query language for XML documents. Parsing HTML
Introduction to JMESPath - JSON query language which is used in web scraping to parse JSON datasets for scrape data.
