Python Web Scraper Github

‘Web scraping’ is a logic to get web page data as HTML format. With this information, not only could get text/image data inside of target page, we could also find out which tag has been used and which link is been included in. When you need lots of data for research in your system, this is one of the common way to get data.

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AutoScraper: A Smart, Automatic, Fast and Lightweight Web Scraper for Python This project is made for automatic web scraping to make scraping easy. It gets a url or the html content of a web page and a list of sample data which we want to scrape from that page. Python - Web scraping with Python Web scraping with Python Web scraping is an automated, programmatic process through which data can be constantly 'scraped' off webpages. Also known as screen scraping or web harvesting, web scraping can provide instant.

Use parser

Web Scraping Using Python What is Data Extraction? Data extraction is a process that involves retrieval of data from different website sources. Firms extract data in order to analyze it, migrate the data to a data repository (data warehouse) or use it in their businesses.
Navigate to the folder called PythonWebScrape that you downloaded to your desktop and double-click on the folder Within the PythonWebScrape folder, double-click on the file with the word “BLANK” in the name (PythonWebScrapeBLANK.ipynb). A pop-up window will ask you to Select.
According to this GitHub issue, these versions work well together: chromedriver 2.43; severless-chrome 1.0.0-55; selenium 3.14; The full story. I recently spent several frustrating weeks trying to deploy a Selenium web scraper that runs every night on its own and saves the results to a database on Amazon S3.

But not like CSV or Excel sheet, raw HTML is pretty rough and disordered data.

This is the case of getting raw HTML data from Bleacher Report. It will return data like this.

It is inconvenient for workers to find target data from here. You need a process of organizing before going further. Maybe you could make a parser yourself, but that’s not an effective way. Python have some great modules for this, and I will use one of this named BeautifulSoap.

Before going on, install it via python package manager with pip install beautifulsoup4.

With this code, raw HTML data has been converted to beautifulsoap object. Now you can get data with text or tag info.

Why it needs to use browser

There are a problem on process above, not in parser, but in HTML request process. If we just request data by http request method, it cannot get dynamically rendered part because they are not in HTML file before loading process. Here is some example for this case.

This is the main page of Samsung SDS official site.

This is the ordinary form of main page. Now let’s check how this will be look like after disabling javascript.

Menu in top has been disappeared, because they are being rendered dynamically from javascript controller. And also, menu texts will not being scraped when you get this HTML page with http request process. So, to get all of these data, you need to get fully rendered result data. For getting it, it has to be rendered in some kind of ‘fake browser’, and that’s why we will use ‘headless browser’.

This is description of headless browser in wikipedia.

Scraping via headless browser

To make scraper via headless browser, we need headless browser, and module to make this run in virtual. I will use PhantomJS here for headless browser, and will make it run with Selenium. You need to install these first.

PhantomJS can be installed by downloading from main page, but can be installed with brew or npm. You can use one of 2 command below.