Price intelligence with Python: Scrapy, SQL and Pandas

In this article I will guide you through a web scraping and data visualization project. We will extract e-commerce data from real e-commerce websites then try to get some insights out of it. The goal of this article is to show you how to get product pricing data from the web and what are some ways to analyze pricing data. We will also look at how price intelligence makes a real difference for...

The Web Data Extraction Summit 2019

The Web Data Extraction Summit was held last week, on 17th September, in Dublin, Ireland. This was the first-ever event dedicated to web scraping and data extraction. We had over 140 curious attendees, 16 great speakers from technical deep dives to business use cases, 12 amazing presentations, a customer panel discussion and unlimited Guinness.

News Data Extraction at Scale with AI powered AutoExtract

A huge portion of the internet is news. It’s a very important type of content because there are always things happening either in our local area or globally that we want to know about. The amount of news published everyday on different sites is ridiculous. Sometimes it’s good news and sometimes it’s bad news but one thing’s for sure: it’s humanly impossible to read all of it everyday.

Gain a Competitive Edge with Product Data

Product data - whether from e-commerce sites, auto listings or product reviews, offers a treasure trove of insights that can give your business an immense competitive edge in your market. Getting access to this data in a structured format can unleash new potential for not only business intelligence teams, but also their counterparts in marketing, sales, and management that rely on accurate...

Four Use Cases for Online Public Sentiment Data

The manual method of discovery for gauging online public sentiment towards a product, company, or industry is cursory at best, and at worst, may harm your business by providing incorrect or misleading insights.

The First-Ever Web Data Extraction Summit!

The range of use cases for web data extraction is rapidly increasing and with it the necessary investment. Plus the number of websites continues to grow rapidly and is expected to exceed 2 billion by 2020.

How to use proxies with Python Requests module

Sending HTTP requests in Python is not necessarily easy. We have built-in modules like urllib, urllib2 to deal with HTTP requests. Also, we have third-party tools like Requests. Many developers use Requests because it is high level and designed to make it extremely easy to send HTTP requests.

How to set up a custom proxy in Scrapy?

When scraping the web at a reasonable scale, you can come across a series of problems and challenges. You may want to access a website from a specific country/region. Or maybe you want to work around anti-bot solutions. Whatever the case, to overcome these obstacles you need to use and manage proxies. In this article, I'm going to cover how to set up a custom proxy inside your Scrapy spider in...

GDPR Update: Scraping Public Personal Data

One common misconception about scraping personal data is that public personal data does not fall under the GDPR. Many businesses assume that because the data has already been made public on another website that it is fair game to scrape. In actuality, GDPR makes no blanket exceptions for public personal data and the same analysis for any other personal data must be conducted prior to scraping...

Solution Architecture Part 5: Designing A Well-Optimised Web Scraping Solution

In the fifth and final post of this solution architecture series, we will share with you how we architect a web scraping solution, all the core components of a well-optimized solution, and the resources required to execute it.