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If you haven’t read the previous ones, here’s the first part, the second and third part of the series.

In case you missed them, here’s the first part and second part of the series.

We are excited to announce our next Zyte Automatic Extraction API: Product Reviews API (Beta). Using this API, you can get access to product reviews in a structured format, without writing site-specific code.

Today we are delighted to launch a beta of our newest data extraction API: Zyte Automatic Extraction Vehicle API.

We’ve just released a new open-source Scrapy middleware which makes it easy to integrate Zyte Automatic Extraction into your existing Scrapy spider.

In the fourth post of this solution architecture series, we will share with you our step-by-step process for evaluating the technical feasibility of a web scraping project.

In this second post in our solution architecture series, we will share with you our step-by-step process for data extraction requirement gathering.

Up until now, your deployment process using Scrapy Cloud has probably been something like this: code and test your spiders locally, commit and push your changes to a GitHub repository, and finally deploy them to Scrapy Cloud using shub deploy.

Let's start with what is XPath? XPath is a powerful language that is often used for scraping the web. It allows you to select nodes or compute values from an XML or HTML document and is actually one of the languages that you can use to extract web data using Scrapy.

You can deploy, run, and maintain control over your Scrapy spiders in Scrapy Cloud, our production environment.