Technology Tales

Keeping a graphical eye on CPU temperature and power consumption on the Linux command line

Following my main workstation upgrade in January, some extra monitoring has been needed. This follows on from the experience with building its predecessor more than three years ago.

Being able to do this in a terminal session keeps things lightweight, and I have done that with text displays like what you see below using a combination of sensors and nvidia-smi in the following command:

watch -n 2 "sensors | grep -i 'k10'; sensors | grep -i 'tdie'; sensors | grep -i 'tctl'; echo "" | tee /dev/fd/2; nvidia-smi"

Everything is done within a watch command that refreshes the display every two seconds. Then, the panels are built up by a succession of commands separated with semicolons, one for each portion of the display. The grep command is used to pick out the desired output of the sensors command that is piped to it; doing that twice gets us two lines. The next command, echo "" | tee /dev/fd/2, adds an extra line by sending a space to STDERR output before the output of nvidia-smi is displayed. The result can be seen in the screenshot below.

However, I also came across a more graphical way to do things using commands like turbostat or sensors along with AWK programming and ttyplot. Using the temperature output from the above and converting that needs the following:

while true; do sensors | grep -i 'tctl' | awk '{ printf("%.2f\n", $2); fflush(); }'; sleep 2; done | ttyplot -s 100 -t "CPU Temperature (Tctl)" -u "°C"

This is done in an infinite while loop to keep things refreshing; the watch command does not work for piping output from the sensors command to both the awk and ttyplot commands in sequence and on a repeating, periodic basis. The awk command takes the second field from the input text, formats it to two places of decimals and prints it before flushing the output buffer afterwards. The ttyplot command then plots those numbers on the plot seen below in the screenshot with a y-axis scaled to a maximum of 100 (-s), units of °C (-u) and a title of CPU Temperature (Tctl) (-t).

A similar thing can be done for the CPU wattage, which is how I learned of the graphical display possibilities in the first place. The command follows:

sudo turbostat --Summary --quiet --show PkgWatt --interval 1 | sudo awk '{ printf("%.2f\n", $1); fflush(); }' | sudo ttyplot -s 200 -t "Turbostat - CPU Power (watts)" -u "watts"

Handily, the turbostat can be made to update every so often (every second in the command above), avoiding the need for any infinite while loop. Since only a summary is needed for the wattage, all other output can be suppressed, though everything needs to work using superuser privileges, unlike the sensors command earlier. Then, awk is used like before to process the wattage for plotting; the first field is what is being picked out here. After that, ttyplot displays the plot seen in the screenshot below with appropriate title, units and scaling. All works with output from one command acting as input to another using pipes.

All of this offers a lightweight way to keep an eye on system load, with the top command showing the impact of different processes if required. While there are graphical tools for some things, command line possibilities cannot be overlooked either.

Upgrading Julia packages

Whenever a new version of Julia is released, I have certain actions to perform. With Julia 1.10, installing and updating it has become more automated thanks to shell scripting or the use of WINGET, depending on your operating system. Because my environment predates this, I found that the manual route still works best for me, and I will continue to do that.

Returning to what needs doing after an update, this includes updating Julia packages. In the REPL, this involves dropping to the PKG subshell using the ] key if you want to avoid using longer commands or filling your history with what is less important for everyday usage.

Previously, I often ran code to find a package was missing after updating Julia, so the add command was needed to reinstate it. That may raise its head again, but there also is the up command for upgrading all packages that were installed. This could be a time saver when only a single command is needed for all packages and not one command for each package as otherwise might be the case.

Rendering Markdown into HTML using PHP

One of the good things about using virtual private servers for hosting websites instead of shared hosting or using a web application service like WordPress.com or Tumblr is that you get added control and flexibility. There was a time when HTML, CSS and client-side scripting were all that was available from the shared hosting providers that I was using back then. Then, static websites were my lot until it became possible to use Perl server side scripting. PHP predominates now, but Python or Ruby cannot be discounted either.

Being able to install whatever you want is a bonus as well, though it means that you also are responsible for the security of the containers that you use. There will be infrastructure security, but that of your own machine will be your own concern. Added power always means added responsibility, as many might say.

The reason that these thought emerge here is that getting PHP to render Markdown as HTML needs the installation of Composer. Without that, you cannot use the CommonMark package to do the required back-work. All the command that you see here will work on Ubuntu 22.04. First, you need to download Composer and executing the following command will accomplish this:

curl https://getcomposer.org/installer -o /tmp/composer-setup.php

Before the installation, it does no harm to ensure that all is well with the script before proceeding. That means that capturing the signature for the script using the following command is wise:

HASH=`curl https://composer.github.io/installer.sig`

Once you have the script signature, then you can check its integrity using this command:

php -r "if (hash_file('SHA384', '/tmp/composer-setup.php') === '$HASH') { echo 'Installer verified'; } else { echo 'Installer corrupt'; unlink('composer-setup.php'); } echo PHP_EOL;"

The result that you want is "Installer verified". If not, you have some investigating to do. Otherwise, just execute the installation command:

sudo php /tmp/composer-setup.php --install-dir=/usr/local/bin --filename=composer

With Composer installed, the next step is to run the following command in the area where your web server expects files to be stored. That is important when calling the package in a PHP script.

composer require league/commonmark

Then, you can use it in a PHP script like so:

define("ROOT_LOC",$_SERVER['DOCUMENT_ROOT']);
include ROOT_LOC . '/vendor/autoload.php';
use League\CommonMark\CommonMarkConverter;
$converter = new CommonMarkConverter();
echo $converter->convertToHtml(file_get_contents(ROOT_LOC . '<location of markdown file>));

The first line finds the absolute location of your web server file directory before using it when defining the locations of the autoload script and the required markdown file. The third line then calls in the CommonMark package, while the fourth sets up a new object for the desired transformation. The last line converts the input to HTML and outputs the result.

If you need to render the output of more than one Markdown file, then repeating the last line from the preceding block with a different file location is all you need to do. The CommonMark object persists and can be used like a variable without needing the reinitialisation to be repeated every time.

The idea of building a website using PHP to render Markdown has come to mind, but I will leave it at custom web pages for now. If an opportunity comes, then I can examine the idea again. Before, I had to edit HTML, but Markdown is friendlier to edit, so that is a small advance for now.

Using multi-line commenting in Perl to inactivate blocks of code during testing

Recently, I needed to inactivate blocks of code in a Perl script while doing some testing. Since this is something that I often do in other computing languages, I sought the same in Perl. To accomplish that, I need to use the POD methodology. This meant enclosing the code as follows.

=start

<< Code to be inactivated by inclusion in a comment >>

=cut

While the =start line could use any word after the equality sign, it seems that =cut is required to close the multi-line comment. If this was actual programming documentation, then the comment block should include some meaningful text for use with perldoc. However, that was not a concern here because the commenting statements would be removed afterwards anyway. It also is good practice not to leave commented code in a production script or program to avoid any later confusion.

In my case, this facility allowed me to isolate the code that I had to alter and test before putting everything back as needed. It also saved time since I did not need to individually comment out every executable line because multiple lines could be inactivated at a time.

Using the IN operator in SAS Macro programming

This useful addition came in SAS 9.2, and I am amazed that it isn’t enabled by default. To accomplish that, you need to set the MINOPERATOR option, unless someone has done it for you in the SAS AUTOEXEC or another configuration program. Thus, the safety first approach is to have code like the following:

options minoperator;

%macro inop(x);
    %if &x in (a b c) %then %do;
        %put Value is included;
    %end;
    %else %do;
        %put Value not included;
    %end;
%mend inop;

%inop(a);

Also, the default delimiter is the space, so if you need to change that, then the MINDELIMITER option needs setting. Adjusting the above code so that the delimiter now is the comma character gives us the following:

options minoperator mindelimiter=",";

%macro inop(x);
    %if &x in (a b c) %then %do;
        %put Value is included;
    %end;
    %else %do;
        %put Value not included;
    %end;
%mend inop;

%inop(a);

Without any of the above, the only approach is to have the following, and that is what we had to do for SAS versions before 9.2:

%macro inop(x);
    %if &x=a or &x=b or &x=c %then %do;
        %put Value is included;
    %end;
    %else %do;
        %put Value not included;
    %end;
%mend inop;

%inop(a);

While it may be clunky, it does work and remains a fallback in newer versions of SAS. Saying that, having the IN operator available makes writing SAS Macro code that little bit more swish, so it's a good thing to know.

On Making PROC REPORT Work Harder

In the early years of my SAS programming career, there seemed to be just the one procedure to use if you wanted to create a summary table. That was TABULATE and it was great for generating columns according to the value of a variable such as the treatment received by a subject in a clinical study. To a point, it could generate statistics for you too, and I often used it to sum frequency and percentage variables. Since then, it seems to have been enhanced a little and surprised me with the statistics it could produce when I had a recent play. Here's the code:

proc tabulate data=sashelp.class;
    class sex;
    var age;
    table age*(n median*f=8. mean*f=8.1 std*f=8.1 min*f=8. max*f=8. lclm*f=8.1 uclm*f=8.1),sex
	  / misstext="0";
run;

When you compare that with the idea of creating one variable per column and then defining them in PROC REPORT as many do, it looks more elegant and the results aren't bad either, though they can be tweaked further from the quick example that I generated. That last comment brings me to the point that PROC REPORT seems to have taken over from TABULATE wherever I care to look these days, and I do ask myself if it is the right tool for that for which it is being used or if it is being used in the best way.

While using Data Step to create one variable per column in a PROC REPORT output doesn't strike me as the best way to write reusable code, there are ways to make PROC REPORT do more for you. For example, by defining GROUP, ACROSS and ANALYSIS columns in an output, you can persuade the procedure to do the summarising for you and there's some example code below with the comma nesting height under sex in the resulting table. Sums are created by default if you do this, and forgoing an analysis column definition means that you get a frequency table, not at all a useless thing in numerous instances.

proc report data=sashelp.class nowd missing;
    columns age sex,height;
    define age / group "Age";
    define sex / across "Sex";
    define height / analysis mean f=missing. "Mean Height";
run;

For those times when you need to create more heavily formatted statistics (summarising range as min-max rather showing min and max separately, for example), you might feel that the GROUP/ACROSS set-up's non-display of character values puts a stop to using that approach. However, I found that making every value combination unique and attaching a cell ID helps to work around the problem. Then, you can create a format control data set from the data like in the code below and create a format from that which you can apply to the cell ID's to display things as you need them. This method does make things more portable from situation to situation than adding or removing columns depending on the values of a classification variable.

proc sql noprint;
    create table cntlin as
        select distinct "fmtname" as fmtname, cellid as start, cellid as end, decode as label
            from report;
quit;

proc format lib=work cntlin=cnlin;
run;

About Perl's Binding Operator

While this piece is as much an aide de memoire for myself as anything else, putting it here seems worthwhile if it answers questions for others. The binding operators, =~ or !~, come in handy when you are framing conditional statements in Perl using Regular Expressions, for example, testing whether x =~ /\d+/ or not. The =~ variant is also used for changing strings using the s/[pattern1]/[pattern2]/ regular expression construct (here, s stands for "substitute"). What has brought this to mind is that I wanted to ensure that something was done for strings that did not contain a certain pattern, and that's where the !~ binding operator came in useful; ^~ might have come to mind for some reason, but it wasn't what I needed.

AND & OR, a cautionary tale

The inspiration for this post is a situation where having the string "OR" or "AND" as an input to a piece of SAS Macro code, breaking a program that I had written. Here is a simplified example of what I was doing:

%macro test;
    %let doms=GE GT NE LT LE AND OR;
    %let lv_count=1;
    %do %while (%scan(&doms,&lv_count,' ') ne );
        %put &lv_count;
        %let lv_count=%eval(&lv_count+1);
    %end;
%mend test;

%test;

The loop proceeds well until the string "AND" is met and "OR" has the same effect. The result is the following message appears in the log:

ERROR: A character operand was found in the %EVAL function or %IF condition where a numeric operand is required. The condition was: %scan(&doms,&lv_count,' ') ne
ERROR: The condition in the %DO %WHILE loop, , yielded an invalid or missing value, . The macro will stop executing.
ERROR: The macro TEST will stop executing.

Both AND & OR (case doesn't matter, but I am sticking with upper case for sake of clarity) seem to be reserved words in a macro DO WHILE loop, while equality mnemonics like GE cause no problem. Perhaps, the fact that and equality operator is already in the expression helps. Regardless, the fix is simple:

%macro test;
    %let doms=GE GT NE LT LE AND OR;
    %let lv_count=1;
    %do %while ("%scan(&doms,&lv_count,' ')" ne "");
        %put &lv_count;
        %let lv_count=%eval(&lv_count+1);
    %end;
%mend test;

%test;

Now none of the strings extracted from the macro variable &DOMS will appear as bare words and confuse the SAS Macro processor, but you do have to make sure that you are testing for the null string ("" or '') or you'll send your program into an infinite loop, always a potential problem with DO WHILE loops so they need to be used with care. All in all, an odd-looking message gets an easy solution without recourse to macro quoting functions like %NRSTR or %SUPERQ.

Controlling the post revision feature in WordPress 2.6

While this may seem esoteric for some, I like to be in charge of the technology that I use. So, when Automattic included post revision retention to WordPress 2.6, I had my reservations about how much it would clutter my database with things that I didn't need. Thankfully, there is a way to control the feature, but you won't find the option in the administration screens (they seem to view this as an advanced setting and so don't want to be adding clutter to the interface for the sake of something that only a few might ever use); you have to edit wp-config.php yourself to add it. Here are the lines that can be added and the effects that they have:

Code: define('WP_POST_REVISIONS','0');

Effect: turns off post revision retention

Code: define('WP_POST_REVISIONS','-1');

Effect: turns it on (the default setting)

Code: define('WP_POST_REVISIONS','2');

Effect: only retains two previous versions of a post (the number can be whatever you want, so long as it's an integer with a value more than zero).

Update (2008-07-23):

There is now a plugin from Dion Hulse that does the above for you and more.

Append or update?

SAS can generate many types of output: plain text, XML, PDF, RTF, Excel, etc. With all of these and the SAS procedures like PROC REPORT, PROC TABULATE and so on, it might seem surprising for me to say that I have been generating output with data step PUT and FILE statements. There was, of course, a reason for this: creating text files for loading into a new database-driven software application. At one stage, I also did some data interleaving at the output stage and that's when I discovered that the default behaviour for SAS FILE statements is to completely overwrite a file unless the MOD option was specified. Adding that switches on APPEND behaviour. The code below adds a header in one step, while adding data below it in another. While I know that there are better ways to achieve this, like setting up your data as you want it or using _N_ to ensure that something only appears once, here's another way. As per the Perl, there's often more than one way to do something with SAS.

data _null_;
    file ds_data;
    put "fieldtype;datasetname;datasetlabel;datasetlayout;datasetclass;datasetstandardversion";
run;

data _null_;
    set ds_ispec;
    file ds_data mod;
    line="datasetstandard;"||trim(memname)||";"||trim(memlabel)||";;;"||trim(memver);
    put line;
run;