A web scraping application which retrieves and presents summary information, the latest news, and images of Mars. A project designed to loads the data into MongoDB and displays the information in a single HTML page.
Scrape data from several websites containing Mars news. Different types of data included were images of Mars, tweets about the current Mars weather, a table of Mars facts, and headlines with the latest Mars news. After scraping, the data is stored in MongoDB and then loaded it into an HTML file using a Flask template that interfaces with Python and formatted with HTML using Bootstrap.
- To scrape various websites for data related to the Mission to Mars and display output on Jupyter Notebook [Scraping_mission_to_mars.ipynb]
- To create a Python Script [scrape_mars.py] to scrape and execute all scraping code and return one Python dictionary containing all of the scraped data
- To create a Flask App [app.py] to create route (index and scrape). The root route / will query Mongo database and pass the mars data into an HTML template to display the data
- To create HTML file [index.html] that will take the mars data dictionary and display all of the data in the appropriate HTML elements
- To create Mongo db and collection to store the scraped data. PyMongo was used to set up mongo connection and to define db and collection
- The Python libraries flask, flask_pymongo, BeautifulSoup, and splinter must be installed in order for the code to run. The initial data scraping can be run either in a Jupyter Notebook or in Python
- HTML, CSS, BootStrap, Jupyter, Python
- Python Libraries - Pandas, Beautiful Soup, Splinter, PyMongo
- Database - Mongo DB
- App Server - Flask
- Nasa Mars News Scrape the latest NASA Mars news using BeautifulSoup, splinter, pandas in a jupyter notebook.
- JPL Space Images Using Splinter to navigate the site and scrape the JPL featured image of mars in full resolution.
- Mars Weather Twitter Visit the Mars Weather Twitter account and scrape the latest Mars weather data.
- Space Facts Mars facts table from Space-Facts.
- USGS From United States Geological Survey Astrogeology to obtain high resulution images for each of Mar's Hemisphere.
- Copy/gather the files in this repo (don't need the .gitignore)
- Start a MongoDB daemon in the terminal, then start mongo instance
- Run the app.py in the terminal. Copy the local url to your web browser