ScrapyRT: Turn Websites Into Real-Time APIs

If you’ve been using Scrapy for any period of time, you know the capabilities a well-designed Scrapy spider can give you.

Web Data Analysis: Exposing NFL Player Salaries With Python

Football. From throwing a pigskin with your dad, to crunching numbers to determine the probability of your favorite team winning the Super Bowl, it is a sport that's easy to grasp yet teeming with complexity. From game to game, the amount of complex data associated with every team - and every player - increases, creating a more descriptive, timely image of the League at hand.

By using web...

From The Creators Of Scrapy: Artificial Intelligence Data Extraction API

To accurately extract data from a web page, developers usually need to develop custom code for each website. This is manageable and recommended for tens or hundreds of websites and where data quality is of the utmost importance, but if you need to extract data from thousands of sites, or rapidly extract data from sites that are not yet covered by pre-existing code, this is often an...

Scrapinghub’s New AI Powered Developer Data Extraction API for E-Commerce & Article Extraction

Today, we’re delighted to announce the launch of the beta program for Scrapinghub’s new AI powered developer data extraction API for automated product and article extraction.

After much development and refinement with alpha users, our team have refined this machine learning technology to the point that data extraction engine is capable of automatically identifying common items on product and...

Solution Architecture Part 2: How to Define The Scope of Your Web Scraping Project

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

How to Architect a Web Scraping Solution: The Step-by-Step Guide

For many people (especially non-techies), trying to architect a web scraping solution for their needs and estimate the resources required to develop it, can be a tricky process.

Oftentimes, this is their first web scraping project and as a result have little reference experience to draw upon when investigating the feasibility of a data extraction project.

In this series of articles we’re going...

Navigating Compliance When Extracting Web Scraped Alternative Financial Data

When it comes to using web data as alternative data for investment decision making, one topic rules them all: compliance.

Regulatory compliance is such a pervasive issue in alternative data for finance, that it is often the number one barrier to investment firms using web data in their decision making processes. And matters aren’t helped by the regulatory ambiguity.

In this article, we’re...

St Patrick’s Day Special: Finding Dublin’s Best Pint of Guinness With Web Scraping

St Patrick’s Day Special: Finding Dublin’s Best Pint of Guinness With Web Scraping

At Scrapinghub we are known for our ability to help companies make mission critical business decisions through the use of web scraped data.

But for anyone who enjoys a freshly poured pint of stout, there is one mission critical question that creates a debate like no other…

“Who serves the best pint of Guinness?”

Spidermon: Scrapinghub’s Secret Sauce To Our Data Quality & Reliability Guarantee

If you know anything about Scrapinghub, you know that we are obsessed with data quality and data reliability.

Outside of building some of the most powerful web scraping tools in the world, we also specialise in helping companies extract the data they need for their mission-critical business requirements. Most notably companies who:

  • Rely on web data to make critical business decisions, or;
  • ...

Meet Spidermon: Scrapinghub’s Battle Tested Spider Monitoring Library [Now Open Sourced]

Your spider is developed and we are getting our structured data daily, so our job is done, right?

Absolutely not! Website changes (sometimes very subtly), anti-bot countermeasures and temporary problems often reduce the quality and reliability of our data.