Assignment 2 - Usage Report

Weight: 10% of the overall grade

Due Date: Please follow the three stages of submission schedule:

Complete the algorithm document for this assignment script by July 31, 2020 and submit on Blackboard by 9:00 PM,
Complete the your Python script and push to Github by August 14, 2020 at 9:00 PM, and
Copy your Python script into a Word document and submit to Blackboard by August 14, 2020 at 9:00 PM.

Overview

Most system administrators would like to know the utilization of their systems by their users. On a Linux system, each user's login records are normally stored in the binary file /var/log/wtmp. The login records in this binary file can not be viewed or edited directly using normal Linux text commands like 'less', 'cat', etc. The 'last' command is often used to display the login records stored in this file in a human readable form. Please check the man page of the 'last' command for available options. The following is the contents of the file named "usage_data_file", which is a sample output of the 'last' command with the '-Fiw' flag on:

$ last -Fiw > usage_data_file
$ cat usage_data_file
rchan    pts/9        10.40.91.236     Tue Feb 13 16:53:42 2018 - Tue Feb 13 16:57:02 2018  (00:03)    
cwsmith  pts/10       10.40.105.130    Wed Feb 14 23:09:12 2018 - Thu Feb 15 02:11:23 2018  (03:02)
rchan    pts/2        10.40.91.236     Tue Feb 13 16:22:00 2018 - Tue Feb 13 16:45:00 2018  (00:23)    
rchan    pts/5        10.40.91.236     Tue Feb 15 16:22:00 2018 - Tue Feb 15 16:55:00 2018  (00:33)    
asmith   pts/2        10.43.115.162    Tue Feb 13 16:19:29 2018 - Tue Feb 13 16:22:00 2018  (00:02)    
tsliu2   pts/4        10.40.105.130    Tue Feb 13 16:17:21 2018 - Tue Feb 13 16:30:10 2018  (00:12)    
cwsmith  pts/13       10.40.91.247     Tue Mar 13 18:08:52 2018 - Tue Mar 13 18:46:52 2018  (00:38)    
asmith   pts/11       10.40.105.130    Tue Feb 13 14:07:43 2018 - Tue Feb 13 16:07:43 2018  (02:00)

It is always desirable to have a daily, weekly, or monthly usage reports by user or by remote host based on the above information.

Tasks for this assignment

In this assignment, your should preform the following activities:

Complete a detail algorithm for producing monthly usage reports by user or by remote host based on the information stored in any given files generated from the 'last' command.
Once you have complete the detail algorithm, you should then design the structure of your python script by identifying the appropriate python objects, functions and modules to be used for each task in your algorithm and the main control logic. Make sure to identify the followings:
1. input data,
2. computation tasks, and
3. outputs.
implement your computational solution using a single python script. You can use any built-in functions and functions from the python modules list in the "Allowed Python Modules" section below to implement your solution.
Test and review your working python code to see whether you can improve the interface of each function to facilitate better code re-use (this process is called refactoring).

Allowed Python Modules

the os, sys modules
the argparse module
The time module
The subprocess module
- Argparse Tutorial - should read this first.
- Argparse API reference information page

Instructions

Accept the Assignment #2 via the link on Blackboard, and clone the Github repository on a Linux machine of your choosing. Rename "a2_template.py" to "a2_<your myseneca username>.py, just as we did in Assignment 1. You may also want to create a symbolic link using ln -s a2_<myseneca_id>.py a2.py to save time.

Program Name and valid command line arguments

Name your Python3 script as a2_[student_id].py. Your script must accept one or more "file name" as its command line parameters and other optional parameters as shown below. Your python script should produce the following usage text when run with the --help option:

[eric@centos7 a1]$ python3 ./a2.py -h
usage: new_template.py [-h] [-l {user,host}] [-r RHOST] [-t {daily,monthly}]
                       [-u USER] [-s] [-v]
                       F [F ...]

Usage Report based on the last command

positional arguments:
  F                     list of files to be processed

optional arguments:
  -h, --help            show this help message and exit
  -l {user,host}, --list {user,host}
                        generate user name or remote host IP from the given
                        files
  -r RHOST, --rhost RHOST
                        usage report for the given remote host IP
  -t {daily,monthly}, --type {daily,monthly}
                        type of report: daily or weekly
  -u USER, --user USER  usage report for the given user name
  -s, --seconds         return times in seconds
  -v, --verbose         turn on output verbosity

Copyright 2020 - Eric Brauer

Replace the last line with your own full name.

Compare the usage output you have now with the one above. There is one option missing, you will need to change the argparse function to implement it.

You will that there is an 'args' object in a2_template.py. Once the parse_command_args() function is called, it will return an args object. The command line arguments will be stored as attributes of that object. Do not use sys.argv to parse arguments.

If there is only one file name provided at the command line, read the login/logout records from the contents of the given file. If the file name is "online", get the record on the system your script is being execute using the Linux command "last -iwF". The format of each line in the file should be the same as the output of 'last -Fiw'. Filter out incomplete login/logout record (hints: check for the number of fields in each record).

If there is more than one file name provided, merge all the files together with the first one at the top and the last one at the bottom. Read and process the file contents in that order in your program.

Header

All your Python codes for this assignment must be placed in a single source file. Please include the following declaration by you as the script level docstring in your Python source code file (replace [Student_id] with your Seneca email user name, and "Student Name" with your own name):

OPS435 Assignment 2 - Summer 2020
Program: a2_[seneca_id].py
Author: "Student Name"
The python code in this file a2_[seneca_id].py is original work written by
"Student Name". No code in this file is copied from any other source 
including any person, textbook, or on-line resource except those provided
by the course instructor. I have not shared this python file with anyone
or anything except for submission for grading.  
I understand that the Academic Honesty Policy will be enforced and violators 
will be reported and appropriate action will be taken.

Use of Github

You will once again be graded partly on correct use of version control, that is use of numerous commits with sensible commit messages. In professional practice, this is critically important for the timely delivery of code. You will be expected to use:

git add *.py
git commit -m "a message that describes the change"

git push after completing each step. There is no penalty for "too many commits", there is no such thing!

Suggested Process

Read the rest of this document, try and understand what is expected.
Use the invite link posted to Blackboard to accept the assignment, and clone the repo to a Linux machine.
Copy a2_template.py into a2_<myseneca_id>.py. Replace with your Myseneca username.
Run the script itself. Investigate argparse. Experiment with the various options, particularly -v. Read the docs, what option must you implement? Go ahead and implement it. Test with print() for now. Commit the change.
Investigate the `parse_user()` function, with the usage_data_file. This should take the list of lines from the file, and instead return a list of usernames. Commit the change.
Use argparse with `-l user` `usage__data_file` to call the `parse_user()` function. Commit the change.
Write a function to print the list from `parse_for_user()`. Now you have input -> processing -> output. Continue committing these changes as your proceed.
Implement the same things as parse_for_user but for `parse_for_hosts`. Output should be sorted.
Compare your output with the output below.
Write the `parse_for_daily()` function using the pseudocode given. This should be taking the list of lines from your file, and output a dictionary with start dates in DD/MM/YYYY format as the key and usage in seconds as the value.
{'01/01/1980': 1200, '02/01/1980': 2400, '03/01/1980': 2200}
Once your `parse_for_daily()` function works, call it with the argparse options, and display the contents.
Write (or modify) a function to do the same for remote hosts.
Implement the outputting of the duration in HH:MM:SS instead of seconds. It's recommended you write a function to take in seconds and return a string. Call this when the `-s` option is absent. Make sure this is working with remote hosts as well. You should now have x of y tests passing.
Finally, implement the `--monthly` option. Create a new function and get it working. start with seconds, then duration and make sure it works with remote as well.
Perform last checks and document your code. Write **why** your code is doing what it does, rather than **what** it's doing. You should have 100% of tests succeeding.

Output Format

The format of your log tables should be identical to the sample output below, in order to minimize test check error. The horizontal banner between title and data should be composed of equal signs (=), and be the length of the title string. List tables should need no extra formatting. For daily/montly tables with two columns, The first column should be 10 characters long and be left-aligned. The second column should be 15 characters long and be right-aligned.

Sample Outputs

The following are the reports generated by the usage report script (ur.py) with the "usage_data_file" mentioned in the overview section. You can download the file here to test your ur.py script.

User List

The following is the user list extracted from the usage_data_file created by the command:

[eric@centos7 a2]$ ./a2.py -l user usage_data_file

User list for usage_data_file
=============================
asmith
cwsmith
rchan
tsliu2

Remote Host List

The following is the remote host list extracted from the usage_file_file created by the command:

[eric@centos7 a2]$ ./a2.py -l host usage_data_file

Host list for usage_data_file
=============================
10.40.105.130
10.40.91.236
10.40.91.247
10.43.115.162

Daily Usage Report by User

The following are Daily Usage Reports created for user rchan. The output can be displayed either in seconds:

[eric@centos7 a2]$ ./a2.py -u rchan -t daily usage_data_file --seconds

Daily Usage Report for rchan
============================
Date                Usage
13/02/2018           1580
15/02/2018           1980
Total                3560

...or by omitting the --seconds option, in HH:MM:SS format.

[eric@centos a2]$ ./a2.py -u rchan -t daily usage_data_file

Daily Usage Report for rchan
============================
Date                Usage
13/02/2018       00:26:00
15/02/2018       00:33:00
Total            00:59:20

It's recommended you get the seconds working first, then create a function to converts seconds to HH:MM:SS.

Daily Usage Report by Remote Host

The following is a Daily Usage Report created for the Remote Host 10.40.105.103 by the command:

[eric@centos7 a2]$ ./a2.py -r 10.40.105.130 -t daily usage_data_file -s

Daily Usage Report for 10.40.105.130
====================================
Date             Usage
15/02/2018        7883
14/02/2018        3047
13/02/2018        7969
Total            18899

Just as you did with --user, your script should also display the time in HH:MM:SS by omitting the --seconds option.

Monthly Usage Report by User

The following is a Monthly Usage Report created for user rchan by the command:

[eric@centos7 a2]$ ./a2.py -u rchan -t monthly usage_data_file -s

Monthly Usage Report for rchan
==============================
Date                Usage
02/2018              3560
Total                3560

[eric@centos7 a2]$ ./a2.py -u cwsmith -t monthly usage_data_file

Monthly Usage Report for cwsmith
================================
Date                Usage
02/2018          03:02:11
03/2018          00:38:00
Total            03:40:11

Monthly Usage Report by Remote Host

The following is a Monthly Usage Report created for the remote host 10.40.105.130 by the command:

[eric@centos7 a2]$ ./a2.py -r 10.40.105.130 -t monthly usage_data_file

Monthly Usage Report for 10.40.105.130
======================================
Date                Usage
02/2018          05:15:00
Total            05:15:00

As discussed before, this command should also accept the --seconds option.

List Users With Verbose

Calling any of the previous commands with the --verbose option should cause the script to output more information:

[eric@centos7 a2]$ ./a2.py -l user usage_data_file -v

Files to be processed: ['usage_data_file']
Type of args for files <class 'list'>
User list for usage_data_file
=============================
asmith
cwsmith
rchan
tsliu2

[eric@centos7 a2]$ ./a2.py -r 10.40.105.130 -t monthly usage_data_file -v

Files to be processed: ['usage_data_file']
Type of args for files <class 'list'>
usage report for remote host: 10.40.105.130
usage report type: monthly
Monthly Usage Report for 10.40.105.130
======================================
Date                Usage
02/2018          05:15:00
Total            05:15:00

Daily Report From Online

Running the script with "online" as a file argument should call a subprocess.Popen object and run the command last -Fiw.

[eric@mtrx-node06pd ~]$ ./a2.py -l user online

(Example Output from Matrix):

User list for online
====================
aabbas28
aaddae1
aali309
aaljajah
aalves-staffa
aanees1
aarham
aassankanov
abalandin
abhaseen
abholay
acamuzcu
acchikoti
adas20
adeel.javed
...

[eric@mtrx-node06pd ~]$ ./a2.py -u adas20 -t daily online

Daily Usage Report for abholay
==============================
Date                Usage
16/07/2020       00:13:09
17/07/2020       00:08:59
Total            00:22:08

Detail Algorithm Document

Follow the standard computation procedure: input - process - ouput when creating the algorithm document for this assignment.

input

get data (command line arguments/options) from the user using the functions provided by the argparse module
according to the arguments/options given at the command line, take appropriate processing action.

processing

based on the file(s) specified, read the contents of each file and use appropriate objects to store it
based on the command line arguments/options, process the data accordingly, which includes
- data preprocessing (split a multi-day record into single day record)
- record processing (preform required computation)

output

output the required report based on the processed data

identify and select appropriate python objects and functions

The following python functions (to be created, you may have more) are useful in handling the following sub-tasks:

reads login records from files and filters out unwanted records
convert login records into proper python object type so that it can be processed using as much built-in functions as possible
create functions which generate daily usage reports by user and/or by remote host
create functions which generate weekly usage reports by user and/or by remote host

To help you with this assignment, you should use the a2_template.py in the repository as a starting point in designing your own Python Usage Report script.

Python script coding and debugging

For each function, identify what type of objects should be passed to the function, and what type of objects should be returned to the caller. Once you have finished coding a function, you should start a Python3 interactive shell, import your functions and manually test each function and verify its correctness.

Final Test

Once you have all the individual function tested and that each is working properly, perform the final test with test data provided by your professor and verify that your script produces the correct results before submitting your python program on Blackboard. Upload all the files for this assignment 2 to your vm in myvmlab and perform the final test.

Rubric

Task	Maximum mark	Actual mark
Algorithm Submission	10
Check Script Results	30
Additional Check: 'online'	5
GitHub Use	15
List Functions	5
Daily/Monthly Functions	10
Output Functions	5
Other Functions	5
Overall Design/Coherence	10
Documentation	5
Total	100

Submission

Stage 1: Submit your algorithm document file to Blackboard by July 31, 2020.
Stage 2: Use commits to push your python script for this assignment to Github.com. The final state of your repository will be looked at on August 14, 2020 at 9:00 PM.
Stage 3: Copy your python script into a Word document and submit to Blackboard by August 14, 2020 at 9:00 PM.

OPS435 Online Assignment 2

Contents