This is a python program that uses psycopg2 to connect to a PostgreSQL database with tables: articles, authors, and logs in order to answer 3 questions.
- What are the 3 most requested articles?
- Who are the most requested authors?
- On which days did more than 1% of requests lead to errors?
To run this program, you will need:
- Python 2.7
- psycopg2
- PostgreSQL 9.5
- the file 'newsdata.sql'
Instructions to run program:
- load data of 'newsdata.sql' into database named 'news' with command:
psql -d news -f newsdata.sql - connect to database with command:
psql news - create view consisting of total http requests per day with command:
create view reqs_per_day as select date(time) as day, count(status) as reqs from log group by day; - create view consisting of total http errors per day with command:
create view err_per_day as select date(time) as day, count(status) as errors from log where status != '200 OK' group by day order by errors; - run python file 'logs-analysis.py' with command:
python logs-analysis.py - program will create and populate a file 'logs-analysis.txt' with answers to each of the 3 questions on each respective line of the file.