An internal python reporting tool to analyze server data from a PosgreSQL database.

This python script tool will connect to and read from the provided news database, in order to analyze user activiy by answering three questions:

1. What are the three articles with the most views?
2. Who are the three authors with the most overall views?
3. On Which days days did user requests lead to more than 1% errors?

• python 2.7.12 - Or later version
• VirtualBox - A cross-platform virtualization software
• Vagrant - A tool for working with virtual environments
• git - A version control tool

1. Install Vagrant.
2. Install VirtualBox.
3. Clone this repository with the needed VirtualBox configuration.

$ git clone https://github.com/udacity/fullstack-nanodegree-vm

4. cd into the vagrant reposiotry.

$ cd fullstack-nanodegree-vm/vagrant/

5. Clone this reposiotry with the database and python script into the vagrant directory.

$ git clone https://github.com/neagkv/Logs_Analysis.git

6. Start up the virtual machine. Note this may take several minutes.

$ vagrant up

7. log into the virtual machine.

$ vagrant ssh

8. cd into the Logs_Analysis directory.

$ cd /vagrant/Logs_Analysis

9. Unzip the database.

$ unzip newsdata.zip

10. Load data.

$ psql -d news -f newsdata.sql

1. Connect to database.

$ psql -d news

2. Create first view.

news=> create view all_requests as select date_trunc('day', time) "day", count(*) as good from log group by day order by day;

3. Create second view.

news=> create view error_requests as select date_trunc('day', time) "day", count(*) as bad from log where status != '200 OK' group by day order by day;

1. Run file with python

$ python logs_report.py

2. compare output with output.txt