This is a web application that scrapes various websites for data related to the Mission to Mars and displays the information in a single HTML page. The following outlines the details.

Initial scraping used Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter is recommended so you can visualize as you go. It can be moved to Python Flask later.

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

# Example:
news_title = "NASA's Next Mars Mission to Investigate Interior of Red Planet"

news_p = "Preparation of NASA's next spacecraft to Mars, InSight, has ramped up this summer, on course for launch next May from Vandenberg Air Force Base in central California -- the first interplanetary launch in history from America's West Coast."

• Next visited the url for JPL's Featured Space Image here.

• Splinter was used to navigate the site and find the image url for the current Featured Mars Image and assign the url string to the variable featured_image_url.

# Example:
featured_image_url = 'https://www.jpl.nasa.gov/spaceimages/images/largesize/PIA16225_hires.jpg'

• Next visited the Mars Weather twitter account here was scraped for the latest Mars weather tweet from the page. Saved the weather report in the variable mars_weather.

# Example:
mars_weather = 'Sol 1801 (Aug 30, 2017), Sunny, high -21C/-5F, low -80C/-112F, pressure at 8.82 hPa, daylight 06:09-17:55'

• Next visited the Mars Facts webpage here Used Pandas to scrape the table containing facts about the planet including Diameter, Mass, etc and convert the data to an html table string.

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

# Example:
hemisphere_image_urls = [
    {"title": "Valles Marineris Hemisphere", "img_url": "..."},
    {"title": "Cerberus Hemisphere", "img_url": "..."},
    {"title": "Schiaparelli Hemisphere", "img_url": "..."},
    {"title": "Syrtis Major Hemisphere", "img_url": "..."},
]

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

• Spliter, BeautifulSoup, Pymongo, Bootstrap, Flask