This is the first project in Full Stack Web Developer Nano-Degree. It shows a report about viewing articles of authors.

main.py file is a python file implements three queries:

• What are the most popular three articles of all time?
• Who are the most popular article authors of all time?
• On which days did more than 1% of requests lead to errors?

It contains a view to help implementing the first two queries:

CREATE OR REPLACE VIEW logArticlesView AS
            SELECT a.title, COUNT(l.path) AS views, a.author
            FROM log AS l, articles AS a
            WHERE substr(l.path, 10) = a.slug
            GROUP BY a.author, a.title;

Since the keyword REPLACE will check the existing of the view, no need to omit that query before run code for multiple times.

The output of this code is in output.txt file.

• Vagrant: https://www.vagrantup.com/downloads.html
• Virtual Machine: https://www.virtualbox.org/wiki/Downloads
• Download a FSND virtual machine: https://github.com/udacity/fullstack-nanodegree-vm and probably you will find the file in your “Download” folder.

- You will also need a Unix-style terminal program. On Mac or Linux systems, you can use the built-in Terminal. On Windows, we recommend Git Bash, which is installed with the Git version control software.

Once you get the above software installed, follow the following instructions:

cd vagrant
vagrant up
vagrant ssh
cd /vagrant
mkdir log-analysis-pr

- For this project, all the work will be on your Linux machine, so always make sure you logged in by using the following commands: vagrant up, then vagrant ssh, then cd /vagrant. Note: Files in the VM's /vagrant directory are shared with the vagrant folder on your computer. But other data inside the VM is not.

• For this project, you need to download newsdata.sql from the project page or by clicking on the following link: https://d17h27t6h515a5.cloudfront.net/topher/2016/August/57b5f748_newsdata/newsdata.zip
• Move the newsdata.sql to your project folder log-analysis-project
• Load the data from the newsdata.sql by using the following command: Note that we are using PostgreSQL for this project:

  psql -d news -f newsdata.sql
  

• Once you have the data loaded into your database, connect to your database using:

  psql -d news