Logs Analysis Udacity

Full Stack Development ND

About

This project looks through a sql file and gives back the answers to these three questions

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

Prerequisites

• Python 3 (https://docs.python.org/3/download.html)
• Vagrant (https://www.vagrantup.com/downloads.html)
• VirtualBox (https://www.virtualbox.org/wiki/Downloads)

Steps

• Run psql -d news -f newsdata.sql on the virtual machine /vagrant folder to create the database

• Type psql into the virtual machine and run these lines to create the necessary views:

create view access as
select to_char(time, 'Month, DD, YYYY') as date, count(status) as access
from log
group by date
order by date

create view error as
select to_char(time, 'Month, DD, YYYY') as date, count(status) as error
from log
where status like '4%'
group by date
order by date

create view rate_of_error as
select access.date, round(100.00 * error / access, 2) as rate
from access, error
where access.date = error.date

• After creating these views you can run python3 Logs.py to generate the logs analysis

Built with

• Python3
• SQL

Author

Julian Parker

Acknowledgments

Thank you to my Udacity instructor who helped me write a better ReadMe!