Semalt: Using Python To Scrape Websites
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Source: Semalt Writer semalt.com

Semalt: Using Python To Scrape Websites

by Semalt Writer

Web scraping also defined as web data extraction is a process of obtaining data from the web and exporting the data into usable formats.

In most cases, this technique is used by webmasters to extract large amounts of valuable data from web pages, where the scraped data is saved to Microsoft Excel or local file.

How To Scrape A Website With Python

For beginners, Python is one of the commonly used programming languages that highly emphasizes on code readability. Currently, Python is running as Python 2 and Python 3.

This programming language features automated memory management and dynamic type system. Now, Python programming language also features community-based development.

Why Python?

Getting data from dynamic websites that require login has been a significant challenge for many webmasters.

In this scraping tutorial, you will learn how to scrape a site that requires a login authorization using Python.

Here is a step-by-step guide that will enable you to complete the scraping process efficiently.

Step 1: Studying Target-Website

To extract data from dynamic websites that require a login authorization, you need to organize the required details.

To get started, right-click on "Username" and select on the "Inspect element" option. "Username" will be the key.

Right-click on the "Password" icon and choose "Inspect element".

Search "authentication_token" under the page source. Let your hidden input tag be your value. However, it is important to note that different websites use different hidden input tags.

Some websites use simple login form while others take the complicated forms.

In case you are working on static sites that use complicated structures, check your browser's request log and mark significant values and keys that will be used to log in a website.

Step 2: Performing Log Into Your Site

In this step, create a session object that will allow you to carry on the login session as per all your requests.

The second thing to consider is extracting the "csrf token" from your target-web page. The token will help you during login. In this case, use XPath and lxml to retrieve the token.

Perform a login phase by sending a request to the login URL.

Step 3: Scraping Data

Now you can extract data from your target-site. Use XPath to identify your target element and produce the results.

To validate your results, check the output status code form each requests results.

However, verifying the results do not notify you whether the login phase was successful but acts as an indicator.

For scraping experts, it is important to note that the return values of XPath evaluations vary. The results depend on the XPath expression run by the end-user.

Knowledge of using Regular expressions in XPath and generating XPath expressions will help you to extract data from sites that require login authorization.

With Python, you don't need a custom back up plan or worry about hard-disk crashing.

Python efficiently extracts data from static and dynamic sites that require login authorization to access content.

Take your web scraping experience to the next level by installing Python version on your computer.

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