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= Overview : du Improved =Programs such as screenfetch and top are used to generate <code>du</code> is a summary of tool for inspecting directories. It will return the computer's current state. These types contents of programs a directory along with how much drive space they are useful because they present a lot of information quicklyusing. However, and it can be parse its output quickly suggest a possible avenue of investigation for the systems administrator.For this assignment you will create , as it usually returns file sizes as a "System Information" type program. This program will briefly present important information about the state number of the computer system.bytes:

The preliminary code should look like this:<code><preb>Hostname: NeoMexKernel Release: 5.4.0user@host ~ $ du --48max-genericUptime: up depth 1 week, 1 day, 17 hours, 14 minutes/usr/local/lib</b></code>----------------------------------------<pre>164028 /usr/dev [ ] 0 %local/lib/heroku11072 / [============= ] 65 %usr/local/lib/python2.792608 /usr/local/bootlib/efi [==== ] 18 %node_modules8 /usr/home [=============== ] 77 %local/lib/python3.8----------------------------------------Mem [======== ] 40 %Swap [= ] 3 %267720 /usr/local/lib</pre>You will therefore be creating a tool called <b>duim (du improved></b>. Your script will call du and return the contents of a specified directory, and generate a bar graph for each subdirectory. The bar graph will represent the drive space as percent of the total drive space for the specified directory.An example of the finished code>your script might produce is this:

In addition<code><b>user@host ~ $ ./duim.py /usr/local/lib</b></code><pre> 61 % [============ ] 160.2 MiB /usr/local/lib/heroku 4 % [= ] 10.8 MiB /usr/local/lib/python2.7 34 % [======= ] 90.4 MiB /usr/local/lib/node_modules 0 % [ ] 8.0 kiB /usr/local/lib/python3.8Total: 261.4 MiB /usr/local/lib</pre> The details of the final output will be up to you, but you will be expected required to build fulfill some specific requirements before completing your script. Read on this capability with some relevant functions. ..

You will need to complete the functions inside the provided file called <code>assignment1duim.py</code>. The provided <code>checkA1.py</code> will be used to test these functions.

* <code>call_dfcall_du_sub()</code> should take no arguments the target directory as an argument and return a list of strings returned by the shell command<b>du -d 1<target directory></b>.** Use subprocess.Popen. ** '-d 1' specifies a <i>max depth</i> of 1. Your list shouldn't include files, just a list of subdirectories in the target directory.** Your list should <u>not</u> contain newline characters. * <code>call_freepercent_to_graph()</code> should take no two arguments, : percent and the total chars. It should return a list of strings from the shell'bar graph' as a string.* * Your function should check that the percent argument is a valid number between 0 and 100. It should fail if it isn't. You can <code>call_hostname()raise ValueError</code> and in this case.** <b>total chars</b> refers to the total number of characters that the bar graph will be composed of. You can use equal signs <code>call_uptime()=</code> should take no argumentsor any other character that makes sense, but the empty space <b>must be composed of spaces</b>, and should return strings from at least until you have passed the shellfirst milestone.* * The string returned by this function should only be composed of these two characters. For example, calling <code>percent_to_graph(percent50, 10)</code> will take an integer should return: 'percent===== ' and return * <code>create_dir_dict</code> should take a bar graph that represents this percentage. The bar graph should begin with '['list as the argument, and end with ']'. Then contents inside should be 20 characters longreturn a dictionary.* * The list can be the list returned by <code>print_percent_linecall_du_sub(name, percent)</code> is provided . ** The dictionary that you return should have the full directory name as a convenience for you. It will print a properly formatted line<i>key</i>, such and the number of bytes in the directory as the one in <i>value</i>. This value should be an integer. For example, using the example aboveof <b>/usr/local/lib</b>, the function would return: {'/usr/local/lib/heroku': 164028, '/usr/local/lib/python2.7': 11072, ...}

Your code will need to have some additional functions that will accomplish the following: * The output from <code>call_df()</code> should be filtered to omit any lines that contain <b>loop</b> or <b>tmpfs</b>. These are not proper file systems and should not be displayed.* The output from <code>call_free()</code> should be used to calculate a percent of <b>memory used</b> divided by <b>total memory</b>. * The output from uptime should be in "pretty" format, that is, in weeks, days, and so on. You may create this as a Python functionany other functions that you think appropriate, or especially when you may also want begin to explore another way to do thisbuild additional functionality. Part of your evaluation will be on how "re-usable" your functions are, and sensible use of arguments and return values.

You will be graded partly on the quality of your Github commits. You may make as many commits as you wish, it will have no impact on your grade. The only exception to this is <b>assignments with very few commits.</b> These will receive low marks for GitHub use and may be flagged for possible academic integrity violations.

* the code <i>should hopefully</i> run without errors after each commit, and

These guidelines are not always possible, but you will be expected to follow these guidelines as much as possible. Break your problem into smaller pieces, and work iteratively to solve each small problem. Test your code after each small change you make, and address errors as soon as they arise. It will make your life easier!  == Additional Features == After completing the above, you are expected to add some additional (two or more) functions providing useful information. Some programs you might want to look at are: * [https://https://ostechnix.com/neofetch-display-linux-systems-information/ screenfetch/neofetch]* [https://htop.dev/ top/htop/Bashtop] It is expected that the additional features you provided should be useful, non-trivial, they should not require super-user privileges and should not require the installation of additional modules or packages.<b>In this part of the assignment, it is better to try for something useful and fail than it is to implement something trivial! I am looking for evidence that you have worked with Linux machines and know what kinds of information are useful to see at a glance.</b> You might consider:* Network information/IP addresses* The state of some important daemons/systemd services* process information* information about online users* number of packages installed* cpu load You may even choose to make the output more attractive/colourful etc. If so, you <i>are permitted to use more modules</i> than those specified above, but make sure that the required functions still succeed as they are. You may want to look into default arguments, ask me for clarification if you're interested.

= Submission Guidelines and Process =  == Clone Your Repo (ASAP) ==

== The First Milestone (due October 19February 14) ==* Before For the first milestone you begin programming, it is important will have two functions to plan your algorithmcomplete. Therefore your first task * <code>call_du_sub</code> will be to complete take one argument and submit an algorithm documentreturn a list. This document should be named '''algorithmThe argument is a target directory.txt'''The function will use <code>subprocess. This file should be plaintext and located in your GitHub repositoryPopen</code> to run the command <b>du -d l <target_directory></b>. The document * <code>percent_to_graph</code> will contain take two sections:arguments and return a string.  * A description of how you plan In order to implement the "complete <code>percent_to_graph()" function</code>, it's helpful to know the equation for converting a number from one scale to another. This explanation should be line-by [[File:Scaling-lineformula. You png]] In this equation, ``x`` refers to your input value percent and ``y`` will be graded based on your attention refer to the number of symbols to detailprint. * A description The max of how you plan to implement percent is 100 and the required output overallmin of percent is 0. Consider the input Be sure that you are working withrounding to an integer, and consider then print that number of symbols to represent the output you need to presentpercentage. Break the problem down into smaller problems, and consider any issues The number of spaces that you might encounter. You print will be graded on evidence that you have considered the task, but not on "getting it right the first timeinverse." * A brief description of the additional features you'd like to implement. * Once you have completed this file, add it to Test your GitHub repositoryfunctions with the Python interpreter. Use <code>git add algorithm.txtpython3</code>, then : import duim duim.percent_to_graph(50, 10) To test with the check script, run the following: <code>git commit python3 checkA1.py -m "added algorithm.txt"</code> and <code>git pushf -v TestPercent</code>.

== The Assignment Second Milestone (due November 2, 11:59pmFebruary 21) ==* As stated before, your code will be inside the file "assignment1.py". Begin by completing For the required functions, committing your changes as second milestone you go. Complete and test each will have one more function before moving to the nextcomplete. * When you have completed the task, make sure that all your changes have been committed and pushed to GitHub. <bcode>create_dir_dict</code>In addition, you will submit take your list from <code>assignment1.pycall_du_sub</code> to Blackboardand return a dictionary. ** Every item in your list should create a key in your dictionary.** Your dictionary values should be a number of bytes.</b>

For example: <code>{'/usr/lib/local': 33400}</code> ** Again, test using your Python interpreter or the check script. To run the check script, enter the following: <code>python checkA1.py -f -v TestDirDict</code> == The Debrief (due November 24) Minimum Viable Product ==This part of Once you have achieved the assignment Milestones, you will be completed under GitHubhave to do the following to get a minimum viable product:* In your <code>if __name__ == '__main__'s "Issues" tab</code> block, you will have to check command line arguments. ** If the user has entered no command line argument, use the current directory. * Your professor will examine * If the code and post questions under "Issues"user has entered more than one argument, or their argument isn't a valid directory, print an error message. Answer ** Otherwise, the questions for full credit of argument will be your worktarget directory.* Call <code>call_du_sub</code> with the target directory.* Create new issues Pass the return value from that function to answer <code>create_dir_dict</code>* You may wish to create one or more functions to do the following questions: * Is * Use the total size of the target directory to calculate percentage.** For each subdirectory of target directory, you will need to calculate a percentage, using the total of the target directory.** Once you've calculated percentage, call <code>percent_to_graph</code> with a max_size of your code portablechoice. ** For every subdirectory, print <i>at least</i> the percent, the bar graph, ieand the name of the subdirectory. ** The target directory <b>should not</b> have a bar graph. == Additional Features == After completing the above, you tested on other Linux machines? How can we are expected to add some additional features. Some improvements you could make programs portable?are: * Format the output in a way that is easy to read. * Why did you choose Add colour to the output.* Add more error checking, print a usage message to the user.* Convert bytes to a human-readable format. NOTE: This doesn't have to be 100% accurate to get marks.* Accept more options from the user.* Sort the output by percentage, or by filename. It is expected that the additional features that you did?provided should be useful, non-trivial, they should not require super-user privileges and should not require the installation of additional packages to work. (ie: I shouldn't have to run pip to make your assignment work). == The Assignment (due March 7, 11:59pm) == * What challenges did you encounter during Be sure to make your final commit before the deadline.* Then, copy the assignmentcontents of your <b>duim.py</b> file into a Word document, and what resources did you submit it to Blackboard. <i>I will use GitHub to solve evaluate your issues? (help from classmatesdeadline, help from Stackoverflow, debuggers, etcbut submitting to Blackboard tells me that you wish to be evaluated.)</i>

| Check script passed required functions design || 20 5 |||-| required functions readability || 5 ||

| given functions main loop design || 5 10 ||

| df/free filtering functions design main loop readability || 10 ||

| additional features appropriate output function design || 10 5 ||

| additional features implemented output function readability || 10 5 ||

| docstrings additional features implemented || 5 20 ||

| in-line docstrings and comments || 5 ||

| First Milestone ||10||

| Debrief Second Milestone || 10 ||

* [ ] your algorithm document, named as 'algorithm.txt', in your GitHub repo, by October 19.* [ ] your python script, named as 'assignment1duim.py', in your repository, and also '''submitted to Blackboard''', by November 2 March 7 at 11:59pm.* [ ] your debrief answers should be submitted as issues to GitHub by November 24.