Tuesday, 6 June 2017

Web Scraping Techniques

Web Scraping Techniques

There can be various ways of accessing the web data. Some of the common techniques are using API, using the code to parse the web pages and browsing. The use of API is relevant if the site from where the data needs to be extracted supports such a system from before. Look at some of the common techniques of web scraping.

1. Text greping and regular expression matching

It is an easy technique and yet can be a powerful method of extracting information or data from the web. However, the web pages then need to be based on the grep utility of the UNIX operating system for matching regular expressions of the widely used programming languages. Python and Perl are some such programming languages.

2. HTTP programming

Often, it can be a big challenge to retrieve information from both static as well as dynamic web pages. However, it can be accomplished through sending your HTTP requests to a remote server through socket programming. By doing so, clients can be assured of getting accurate data, which can be a challenge otherwise.

3. HTML parsers

There are few data query languages in a semi-structured form that are capable of including HTQL and XQuery. These can be used to parse HTML web pages thus fetching and transforming the content of the web.

4. DOM Parsing

When you use web browsers like Mozilla or Internet Explorer, it is possible to retrieve contents of dynamic web pages generated by client scripting programs.

5. Reorganizing the semantic annotation

There are some web scraping services that can cater to web pages, which embrace metadata markup or semantic. These may be meant to track certain snippets. The web pages may embrace the annotations and can be also regarded as DOM parsing.
Setup or configuration needed to design a web crawler

The below-mentioned steps refer to the minimum configuration, which is required for designing a web scraping solution.

HTTP Fetcher– The fetcher extracts the web pages from the site servers targeted.

Dedup– Its job is to prevent extracting duplicate content from the web by making sure that the same text is not retrieved multiple times.

Extractor– This is a URL retrieval solution to fetch information from multiple external links.

URL Queue Manager– This queue manager puts the URLs in a queue and assigns a priority to the URLS that needs to be extracted and parsed.

Database– It is the place or the destination where data after being extracted by a web scraping tool is stored to process or analyze further.

Advantages of Data as a Service Providers

Outsourcing the data extraction process to a Data Services provider is the best option for businesses as it helps them focus on their core business functions. By relying on a data as a service provider, you are freed from the technically complicated tasks such as crawler setup, maintenance and quality check of the data. Since DaaS providers have expertise in extracting data and a pre-built infrastructure and team to take complete ownership of the process, the cost that you would incur will be significantly less than that of an in-house crawling setup.

Key advantages:

- Completely customisable for your requirement
- Takes complete ownership of the process
- Quality checks to ensure high quality data
- Can handle dynamic and complicated websites
- More time to focus on your core business

Source:https://www.promptcloud.com/blog/commercial-web-data-extraction-services-enterprise-growth

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