Background

For this project I built a web application that scrapes various websites for data related to the Mission to Mars and displays the information in a single HTML page.

For the initial scraping I used Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter.

Step 1 - Scrape the Web

NASA Mars News

• Scraped the NASA Mars News Site and collected the latest News Title and Paragraph Text.

JPL Mars Space Images - Featured Image

• Visited the url for JPL Featured Space Image here.

• Used splinter to navigate the site and find the full size .jpg image url for the current Featured Mars Image.

Mars Weather

• Visited the Mars Weather twitter account here and scraped the latest Mars weather tweet from the page.

Mars Facts

• Visited the Mars Facts webpage here and used Pandas to scrape the table containing facts about the planet including Diameter, Mass, etc.

• Used Pandas to convert the data to a HTML table string.

Mars Hemispheres

• Visited the USGS Astrogeology site here to obtain high resolution images for each of Mar's hemispheres.

• Saved the image url string for the full resolution hemisphere image and the Hemisphere title containing the hemisphere name. Used a Python dictionary to store the data using the keys img_url and title.

• Appended the dictionary with the image url string and the hemisphere title to a list. The list contains one dictionary for each hemisphere.

Step 2 - MongoDB and Flask Application

Used MongoDB with Flask templating to create a new HTML page that displays all of the information that was scraped from the URLs above.

• Started by converting my Jupyter notebook into a Python script called scrape_mars.py with a function called scrape that executes all of the scraping code from above and returns one Python dictionary containing all of the scraped data.

• Next, created a route called /scrape that imports the scrape_mars.py script and called the scrape function.

  • Stored the return value in Mongo as a Python dictionary.

• Created a root route / that queries the Mongo database and passes the Mars data into an HTML template to display the data.

• Created a template HTML file called index.html that takes the mars data dictionary and displays all of the data in the appropriate HTML elements.