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Web data extraction is used for extracting data from external websites. In this assignment, 5 different websites are scraped and the results are stored in MongoDB. Flask application is then used to render the scraped data to a HTML webpage.

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abidor13/Mission-to-Mars

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Mission-to-Mars

Overview of the Project:

Background:

Robin's web app is looking good and functioning well, but she wants to add more polish to it. She had been admiring images of Mars’s hemispheres online and realized that the site is scraping-friendly. She would like to adjust the current web app to include all four of the hemisphere images. To do this, you’ll use BeautifulSoup and Splinter to scrape full-resolution images of Mars’s hemispheres and the titles of those images, store the scraped data on a Mongo database, use a web application to display the data, and alter the design of the web app to accommodate these images.

The websites below were scraped in order to get data for our website:

News - link_news
Mars Facts - link_marsfacts
Weather - link_weather
Hemispheres - link_hemispheres

Results:

We were able to create our website with index.html file.

Our sscraping.py file helped scrape through all websites for all needed information.

We updated the Web App with Mars Hemisphere Images and Titles.

Our website is mobile-responsive.

Added two additional Bootstrap 3 components and edited the original style of the website.

Results:

The goal of this project was to create a webpage in which we could scrape data from different websites, then display it whenever needed by calling Flask app.

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Web data extraction is used for extracting data from external websites. In this assignment, 5 different websites are scraped and the results are stored in MongoDB. Flask application is then used to render the scraped data to a HTML webpage.

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