Project: Logs Analysis @ Udacity Full Stack Nanodegree

This is a reporting project for a newspaper site, with the database behind it. The exact task is to generate following three reports:

1. The most popular three articles of all time
2. The most popular article authors of all time
3. Days when more than 1% of requests lead to errors

Included files

File	Comment
logs-analysis.py	python code
Vagrantfile	Vagrant configuration file
README.md	this file
output.txt	expected run output

Dependencies

Software	Version	Download
Python	3.6.6	link
VirtualBox	5.2.16	link
Vagrant	2.1.2	link

Setup and run instructions:

1. Download database from this link

2. Start virtual machine with command:

   vagrant up

3. Connect to virtial machine with command:

   vagrant ssh

4. Move to the working directory:

   vagrant@vagrant:/vagrant/logs-analysis$ cd /vagrant

5. Load data with command:

   vagrant@vagrant:/vagrant/logs-analysis$ psql -d news -f newsdata.sql

6. Check the database includes following three tables:

Table	Content
authors	information about the authors of articles
articles	the news articles
log	includes one entry for each time a user has accessed the site

7. In PSQL prompt execute following SQL command to create the first helper view:

   CREATE VIEW path_slug AS

   SELECT DISTINCT log.path as path, articles.slug as slug

   FROM log, articles

   WHERE position(articles.slug in log.path) > 0

8. In PSQL prompt execute following SQL command to create a second helper view:

   CREATE VIEW article_stat AS

   SELECT articles.id as id, count(log.path) as count

   FROM log, path_slug, articles

   WHERE articles.slug = path_slug.slug AND

   path_slug.path = log.path

   GROUP BY articles.id

9. Run the project code by executing following command on operting system prompt:

   vagrant@vagrant:/vagrant/logs-analysis$ python3 logs-analysis.py

10. Compare the output with the content of output.txt file.