Context mid-level interview exercise

This repository contains the skeleton Django servers application that you have been asked to complete. Below is a description of the problem, and what features you need to implement.

While completing this exercise please be aware that your use of git is examined as well as your code, so please ensure your history is clean and commit messages are clear and meaningful. Please submit your code as a Github fork, or in a format that contains the .git directory.

You may also use any external packages if you feel the need.

Timing: We expect this task to take between 2 to 4 hours. It does not have to be fully complete to be submitted, and will form part of the discussion in your final interview. Please implement as much as you can, but do not feel you have to spend excessive amounts of time working out every minor detail. Adding comments describing any limitations or mostly-complete portions of the functionality is acceptable.

Server monitoring

Context has a lot of servers, and successful logins to them are logged to a central service. This service outputs the last successful login for each user on the server, a sample of which can be found in data/logins.csv.

The task is to implement a management command (monitoring/managements/commands/import.py) that can process this CSV file and store the results in a database, which you will need to model. A brief overview of the file is given below.

As well as the management command you must implement a single view that, for each server, displays the name and IP, a list of users who have logged in, the time they logged in, and any contact information stored for the users.

This view does not need to be pretty (no CSS is required, just plain HTML), but it does need to use as few database queries as possible.

logins.csv

The logins.CSV is a snapshot of the output of the hypothetical central login service. Unfortunately the CSV file contains some abnormalities that you need to clean up while processing, which are described below.

The following headers are present in the CSV file:

server-name,server-ip,username,full-name,contact,login-time

An example row would be:

foster-chapman,3.82.209.138,amiller,Alex Taylor,+44(0)0705 97317,2017-06-19

The server-name and/or contact column is sometimes missing from rows in the output. You can choose to ignore these rows, or attempt to fill in the missing information, as long as you justify your choice.

Each login has an individual row in the CSV. However, if the user that has logged in has multiple items of contact information associated with their account, then there will be multiple rows per login.

For example, "Alex Taylor" has an email address and a phone number. Therefore, a single login attempt will have two lines in the CSV file:

foster-chapman,3.82.209.138,amiller,Alex Taylor,+44(0)0705 97317,2017-06-19
foster-chapman,3.82.209.138,amiller,Alex Taylor,alex@test.com,2017-06-19

The Django application should treat multiple lines like this as a single login attempt. At a minimum, the system should store one piece of contact information per user.

Bonus points: If users have multiple contacts, store all values that the CSV provides.

Dates

The output has inconsistent data in the login-time column. It could be a standard ISO formatted date time, an ISO formatted date or a random python strftime formatted string containing the day, month and year joined by /, \ or |. For example:

12\10\2016
10|12|2016
2016/10/12

Best-attempt parsing of these ambiguous dates is acceptable, it does not have to be foolproof.

Testing

Please include some tests in the monitoring application where you feel they are appropriate.