OPS435 Online Assignment 2

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Assignment 2 - Usage Report

Weight: 10% of the overall grade

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

  • Complete the for the monthly algorithm for this assignment script by July 27, 2020 and submit on Blackboard,
  • Complete the your Python script and push to Github by August 14, 2020 at 9:00 PM,


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     Tue Feb 13 16:53:42 2018 - Tue Feb 13 16:57:02 2018  (00:03)    
cwsmith  pts/10    Wed Feb 14 23:09:12 2018 - Thu Feb 15 02:11:23 2018  (03:02)
rchan    pts/2     Tue Feb 13 16:22:00 2018 - Tue Feb 13 16:45:00 2018  (00:23)    
rchan    pts/5     Tue Feb 15 16:22:00 2018 - Tue Feb 15 16:55:00 2018  (00:33)    
asmith   pts/2    Tue Feb 13 16:19:29 2018 - Tue Feb 13 16:22:00 2018  (00:02)    
tsliu2   pts/4    Tue Feb 13 16:17:21 2018 - Tue Feb 13 16:30:10 2018  (00:12)    
cwsmith  pts/13     Tue Mar 13 18:08:52 2018 - Tue Mar 13 18:46:52 2018  (00:38)    
asmith   pts/11    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:

  1. 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.
  2. 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.
  3. 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.
  4. 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


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:

[rchan@centos7 a1]$ python3 ./ur.py -h
usage: ur_rchan.py [-h] [-l {user,host}] [-r RHOST] [-t {daily,weekly,monthly}]
             [-u USER] [-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
  -r RHOST, --rhost RHOST
                        usage report for the given remote host IP
  -t {daily,weekly,monthly}, --type {daily,weekly,monthly}
                        type of report: daily, weekly, and monthly
  -u USER, --user USER  usage report for the given user name
  -v, --verbose         tune on output verbosity

Copyright 2020 - Raymond Chan 

Replace the last line with your own full name

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.


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:

  1. git add *.py
  2. git commit -m "a message that describes the change"
  3. git push after completing each step. There is no penalty for "too many commits", there is no such thing!

    Suggested Process

    0. Read the rest of this document, try and understand what is expected. 1. Use the invite link posted to Blackboard to accept the assignment, and clone the repo to a Linux machine. 2. Copy a2_template.py into a2_<myseneca_id>.py. Replace with your Myseneca username. 3. 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. 4. 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. 5. Use argparse with `-l user` `usage__data_file` to call the `parse_user()` function. Commit the change. 6. Write a function to print the list from `parse_for_user()`. Now you have input -> processing -> output. Continue committing these changes as your proceed. 7. Implement the same things as parse_for_user but for `parse_for_hosts`. Output should be sorted. 8. Compare your output with the output below. 9. Write the `parse_for_daily()` function using the pseudocode given. This should be taking the list of lines from your file, and output a list of lists with start dates in DD/MM/YYYY format as well usage in seconds. 10. [['01/01/1980', '1200'], ['02/01/1980', '2400'], ['03/01/1980', '2200']] 11. Once your `parse_for_daily()` function works, call it with the argparse options, and display the contents. 12. Write (or modify) a function to do the same for remote hosts. 13. 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. 14. 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. 15. 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.

    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:

    [rchan@centos7 a2]$ ./ur.py -l user usage_data_file
    User list for usage_data_file

    Remote Host List

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

    [rchan@centos7 a2]$ ./ur.py -l host usage_data_file
    Host list for usage_data_file

    Daily Usage Report by User

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

    [rchan@centos7 a2]$ ./ur.py -u rchan -t daily usage_data_file
    Daily Usage Report for rchan
    Date          Usage in Seconds
    2018 02 15        1980
    2018 02 13        1580
    Total             3560
    [rchan@centos a2]$ ./ur.py -u cwsmith -t daily usage_data_file
    Daily Usage Report for cwsmith
    Date          Usage in Seconds
    2018 03 13        2280
    2018 02 15        7883
    2018 02 14        3047
    Total            13210

    Daily Usage Report by Remote Host

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

    [rchan@centos7 a2]$ ./ur.py -r -t daily usage_data_file
    Daily Usage Report for
    Date          Usage in Seconds
    2018 02 15        7883
    2018 02 14        3047
    2018 02 13        7969
    Total            18899

    Weekly Usage Report by User

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

    [rchan@centos7 a2]$ ./ur.py -u rchan -t weekly usage_data_file
    Weekly Usage Report for rchan
    Week #        Usage in Seconds
    2018 07           3560
    Total             3560
    [rchan@centos7 a2]$ ./ur.py -u cwsmith -t weekly usage_data_file
    Weekly Usage Report for cwsmith
    Week #        Usage in Seconds
    2018 11           2280
    2018 07          10930
    Total            13210

    Weekly Usage Report by Remote Host

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

    [rchan@centos7 a2]$ ./ur.py -r -t weekly usage_data_file
    Weekly Usage Report for
    Week #        Usage in Seconds
    2018 07          18899
    Total            18899

    Detail Algorithm Document

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


    • 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.


    • 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 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 function which generates daily usage reports by user and/or by remote host
    • create function which generates weekly usage reports by user and/or by remote host

    To help you with this assignment, you can use the ur_template.py in the sample ops435-a2 repository as a starting point in designing your own Python Usage Report script. If you don't have enough time to create all the functions for the data processing steps, you should study the functions in the ur_funcs.py (provided by your teacher), pick and use the one that may help. If you use any of the functions from ur_funcs.py, there will be a cost of 10% to your overall grade. If you create all the functions yourself, you will get a bonus of 10%.

    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.


    Task Maximum mark Actual mark
    User Requirement Document 20
    Program usage and Options 20
    Generate user name list 10
    Generate remote host IP list 10
    Daily Usage Report by User 10
    Daily Usage Report by Remote Host 10
    Weekly Usage Report by User 10
    Weekly Usage Report by Remote Host 10
    Total 100


    • Stage 1: upload your algorithm document file to your ops435-a2 repository in github.com by March 20, 2020
    • Stage 2: upload your python script for this assignment to your ops435-a2 repository in github.com and to your vm in myvmlab by March 26, 2020
    • Stage 3: After fully tested and debugged your python script for this assignment, update your algorithm, your python script, and your est results to your ops435-a2 repository in github.com. Also submit the algorithm document, the python script and final test result to blackboard by April 3, 2020