Utilize web application and MongoDB to scrape, store, display Mars's Information

Create a web application that scrapes Mars's Hemisphere images and title by utilizing BeautifulSoup and Splinter modules. Then store the scraped data on a Mongo database and further use a web application to display the data on a web browser. In order to do so, below technical analysis are performed:

Deliverable 1: Scrape Full-Resolution Mars Hemisphere Images and Titles

Deliverable 2: Update the Web App with Mars Hemisphere Images and Titles

Deliverable 3: Add Bootstrap 3 Components

• Used Codes: Mission_to_Mars_Challange.py, scraping.py, app.py
• Software: Jupytor Notebook, MongoDB, Python, Visual Studio Code

Scraped below data by coding Mission_to_Mars_Challange.ipynb:

• NASA Mars News: The latest News Title and Paragraph Text
• JPL Mars Space Images: Featured Mars Images and URL to the full size image
• Mars Facts: Table containing facts about the planet as Pandas DataFrame and HTML table string
• Mars Hemisphere: image URL string and the Hemisphere title with the hemisphere name

Created below files to convert Jupytor Notebook file to Python and create a new HTML page:

• scraping.app: converted Jupytor Notebook file into Python code. Added codes to define scraping scripts as function to run smoothly.
• app.py: created Flask app with / route and /scrape route that import the scraping.py script and query the Mongo database and convert the Mars Data into HTML template
• index.html: created HTML file that will display the Mars Data Dictionary