Mission-to-Mars - A Web Scraping Adventure

Objectives:

1. To build a web application that "srapes" data from various websites related to Mission to Mars and displays a summary output of all extracted data in an html landing page
2. To extract data via Web Scraping using Jupyter notebook & utilizing BeautifulSoup, & Splinter/Requests python libraries to obtain data & clean data using Pandas library
3. To use MongoDB with Flask templating (Jinja) and create the HTML landing page to display summarized data

Web Scraping

• The following sites were visited for Web Scraping:
• NASA Mars News Site- latest news title and paragraph text
• JPL Mars Space Images- Mars featured image in space
• Space Facts Site- Mars facts table
• USGS Astrogeology Site- high resolution images of hemispeheres in Mars
• scrape_mars.py - Jupyter notebook converted to a Python script that contains the "scrape" function that will execute all of your scraping code from above and returns one Python dictionary containing all of scraped data

Mongo DB and Flask Application

• app.py - is a Flask application that will import the `scrape` function from `scrape_mars`. The following routes are available in this app
• a root route `/` that will query the Mongo database and pass the mars data into an HTML template to display the data
• `/scrape` route that imports scrape_mars.py and calls the `scrape` function then stores the return value as a Python dictionary
• index.html - an html file using Jinja templating that will take the mars data dictionary and display all of the data in the appropriate HTML elements