This project is presented for Udacity Full stack nano degree

This project is used to analyse a database/log of a news website.

The Queries that the code do is:

• What is the top 3 Viewed Articles?.
• Which authors has the most viewed Articles?
• Which day has more than 1% of errors in requesting the pages

Content of the database

The database has three tables

• Authors Table
  • Includes these columns :
    • name of the author.
    • id of the author.
    • his bio.
• Articles Table
  • Includes these columns:
    • The id of the article's author.
    • The article's title.
    • The article's slug which appears in the uri
    • The lead of the article
    • The body of the article
    • The time it was posted
    • The article's id
• Log table
  • Includes these columns:
    • The id of the request
    • The path of the request
    • The ip which requested the article
    • The method used to access it (get,post)
    • The status of request(200 ok , 404 not found)
    • Time of the request
    • Id of the request

Steps you need to run this code:

• Install the required software:

  • a.Vagrant: https://www.vagrantup.com/downloads.html
  • b. Virtual Machine: https://www.virtualbox.org/wiki/Downloads
  • c. Download a FSND virtual machine: https://github.com/udacity/fullstack-nanodegree-vm

• Once installed, download the project.py, and the database from : https://d17h27t6h515a5.cloudfront.net/topher/2016/August/57b5f748_newsdata/newsdat a.zip after downloading the files, put them in your vagrant file, and then, using your prefered command line , use the following commands:

   cd vagrant
   vagrant up 
   vagrant ssh
   cd /vagrant
  

• Once you're there you need to add views to your postqrese sql by doing :

  psql -d news
  create view FaultyRequests as 
          select 
              Date(time) as date ,count(*) as result
          from
               log 
          where
               status like '%404%'
          group by date;
  create view AllRequests as 
          select 
              Date(time) as date , count(*) as result
          from 
              log
          group by date;
  

  • now you're ready to execute the program enter "\q" to exit out of the psql , then enter "pip3 project.py" The project should be excuted and you should get the results as shown in Output.txt