Logs Analysis Project

Project Description

The logs_analysis.py script uses pyscopg2 to query a PostgreSQL database for a fictional news website.

The script answers 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?

The database is structured with three tables:

• articles - includes the articles themselves.
  • author (integer)
  • title (text)
  • slug (text)
  • lead (text)
  • body (text)
  • time (timestamp with time zone)
  • id (integer)
• authors - includes information about the authors of articles.
  • name (text)
  • bio (text)
  • id (integer)
• log - includes one entry for each time a user has accessed the site.
  • path (text)
  • ip (inet)
  • method (text)
  • status (text)
  • time (timestamp with time zone)
  • id (integer)

Requirements

• Python 2.7
• PostgreSQL
• psycopg2

Set-Up

• Unzip newsdata.zip file to get uncompressed newsdata.sql file.
• Run psql -d news -f newsdata.sql to connect to your installed PostgreSQL database server and execute the SQL commands to set up the schema and load up sample data.
• Run the script with ./logs_analysis.py.