Get the latest
pets news and features.
from us.

Scrapy – Managing Web Scraping Projects

Scrapy is a free, high-level Python web scraping framework that uses spiders to define how a website should be scraped. It is a fast, reliable, and flexible platform for scraping large volumes of data.

It can be used in all types of projects. From small, single-page websites to massive, multi-page scraping jobs. Its simplicity means that it’s easy to learn and easy to use.

Managing Web Scraping Projects

Before starting a scraping project, it’s important to understand the target website  and how it operates. The first thing to check is whether the website is static or generated by JavaScript. This is because it can affect the way a Scrapy crawler extracts structured data.

If the site is JavaScript, you’ll need to disable it before starting a crawl. This can be done by visiting the developer toolbox and clicking F12 on the network tab. Then type Disable JavaScript, and press Enter to reload the page.

The second thing to look at is the page source code. This will show you the XPath queries that are used to search the pages of the site. Using these XPath queries, you can create a spider that will scrape the pages of your target site.

For example, you might want to scrape all the faculty members at UCSB who have a psychology degree. So you’d write XPath queries to search for these names and emails on each of the detail pages that are linked from the faculty page on the UCSB psychology department website.

When you have written a few XPath queries, you’ll need to test them against the detail pages of your target website. It’s a good idea to create a project that has just a few of these pages and run it repeatedly until you get consistent results.

Another thing to consider is how you’ll store the scraped data once it’s collected. Usually it’s best to store the raw data in a file, so you can quickly access it. There are various options for this, including storing the scraped data in the database or using a file storage service like Amazon S3.

Performing Advanced Scraping Operations

When scraping large amounts of data, you may need to perform advanced scraping operations. This can involve downloading all the pages of a site at once, or simply extracting a single article from a news site and storing it. Depending on the resources of your computer, these operations can be quite expensive.

Using a web scraping library to perform these functions is a popular option. Some of these libraries are open-source, and some are commercial.

Some of these libraries provide a range of features that allow you to do things like set up a server to manage your scrapers. Others give you functionality to automate the scraping process, such as task distribution and scheduling.

Other features include proxy management, browser emulation, and scaleability. Some of these libraries are built into Scrapy, but many are third-party extensions.

Proxies for scraping:

If you need to run a scraper on a remote server then it’s essential to set up a proxy. This is especially important when scraping from a public website. A proxy will help prevent your scraper from being blocked or banned. Some of the popular solutions are the Tor project and paid services like ProxyMesh.