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6.6.2016
Nearly 60 percent business owners believe it’s more difficult to run a business now than it was a few years ago, according a recent Constant Contact survey. With the market getting more aggressive, businesses today cannot afford to overlook any important information about their competitors, industry, and market trends. To help your business grow, you need to make timely and informed business decisions based on loads of external data extracted from the web. This is exactly where Python web scraping tools can help you. Let’s first understand why your business needs web scraping.
Not all websites provide an application programming interface (API) or RSS feeds to allow for structured data. While websites like Google, Facebook, and Twitter allow you to access their data in a structured way, many websites do not give users access to structured data or do not have the technical knowhow to provide an API. The only way to extract data from such websites is through web scraping.
While there are many tools to perform web data extraction, the ease and simplicity provided by Python are unparalleled, thanks to its easy-to-use and intuitive library Beautiful Soup and the module Urllib2. While Urllib2helps fetch URLs or web pages by defining classes and functions, Beautiful Soup helps extract information from the web pages. Together, they help you extract tables, price lists, and other data from targeted websites. Using Python tools, you can extract loads of data from a website within a few seconds. Moreover, Python ensures the highest level of security in external web data collection.
Python web scraping technique enables you to discover and extract information from web pages, browser logs, and links between pages, people, etc. Businesses can use this information for pricing analysis, competitor monitoring, reputation management, and strategic decision making.
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