News site logs Analysis

This program utilizes the postgreSQL database "news" from a news website to answer questions about that site's traffic. It will tell you the 3 most-visited articles, show how many views the site's authors have across all of their articles, and the days where more than 1% of requests led to errors.

Getting Started

The first thing to do is download answers.py and create-views.sql. Then, on a machine with PostgreSQL installed, you can create a database called "news" containing the following tables, and fill those tables with records:

CREATE TABLE articles (
    author integer NOT NULL,
    title text NOT NULL,
    slug text NOT NULL,
    lead text,
    body text,
    "time" timestamp with time zone DEFAULT now(),
    id integer NOT NULL
);

CREATE TABLE authors (
    name text NOT NULL,
    bio text,
    id integer NOT NULL
);

CREATE TABLE log (
    path text,
    ip inet,
    method text,
    status text,
    "time" timestamp with time zone DEFAULT now(),
    id integer NOT NULL
);

At that point, make sure answers.py and create-views.sql are in the same directory, and execute one of the following commands (depending on your python configuration):

python answers.py

or

python3 answers.py

Prerequisites

• Make sure you have Python 3 installed
• Make sure you have PostgreSQL installed
• Make sure you have the psycopg2 library installed

pip3 psycopg2

Built With

• Python 3
• The psycopg2 library
• PostgreSQL

Authors

• Bryan Williams - Initial work - willimsbw
• Udacity's team, who provided a pre-configured Vagrant VM and the database's content

See also the list of contributors who participated in this project.

Acknowledgments

• Thanks to Udacity for their nanodegree programs
• PurpleBooth, for providing this really great readme template