topplot 0.0.3

Munge top logs in to graphs

topplot

Munge logs from the commandline utility top in to useful graphs

Introduction

topplot produces graphs of information it munges from top logs. It can select which processes to focus on, and it can split out information by cpu core (if top was configured to record the cpu core column, and/or display the cpu summary info by core).

topplot can save the graphs as PNG files. It can also print information derived from the logs to stdout, with or without emitting the graphs.

There may be better, more efficient ways of collecting live system information, but if for some reason you've hundreds of thousands of lines of top logs and you want to see what's in them, topplot can help.

(I wrote topplot when one of Codethink's clients asked us to investigate an issue which had 300,000 lines of top logs attached to it.)

Turn this...

Truncated first iteration of 300 in the log file:

top - 13:35:22 up 1 min,  0 users,  load average: 0.71, 0.47, 0.18
Tasks: 203 total,   1 running, 202 sleeping,   0 stopped,   0 zombie
%Cpu0  :  5.9 us,  5.9 sy,  0.0 ni, 88.2 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu1  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu2  :  5.6 us,  0.0 sy,  0.0 ni, 94.4 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu3  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
MiB Mem :  15717.0 total,  13778.2 free,   1030.7 used,    908.1 buff/cache
MiB Swap:  15792.0 total,  15792.0 free,      0.0 used.  14327.6 avail Mem 

  PID USER      PR  NI    VIRT    RES    SHR S  %CPU  %MEM     TIME+ P COMMAND
 2430 jonatha+  20   0    9164   3704   3120 R   6.2   0.0   0:00.02 0 top -bd 1 -n 300
    1 root      20   0  167036  10768   7800 S   0.0   0.1   0:01.33 3 /sbin/init
    2 root      20   0       0      0      0 S   0.0   0.0   0:00.00 3 [kthreadd]
    3 root       0 -20       0      0      0 I   0.0   0.0   0:00.00 0 [rcu_gp]
    4 root       0 -20       0      0      0 I   0.0   0.0   0:00.00 0 [rcu_par_gp]
    .
    .
------->8  snip 193 lines
    .
    .
 2057 jonatha+  20   0  270244  35968  32508 S   0.0   0.2   0:00.04 2 /usr/bin/plasma-browser-integration-host /usr+
 2064 jonatha+  20   0  341308  38504  32424 S   0.0   0.2   0:00.07 2 /usr/lib/x86_64-linux-gnu/libexec/vvvvvvvvvvv
 2069 jonatha+  20   0    6640   3136   2888 S   0.0   0.0   0:00.00 3 /bin/bash /home/jonathansambrook/.config/wwww+
 2070 jonatha+  20   0  657204  43148  26504 S   0.0   0.3   0:00.18 3 /home/jonathansambrook/xxxxxxxxxxxxxxxx/yyyyy+
 2098 jonatha+  20   0 2414952  77112  54068 S   0.0   0.5   0:00.27 2 /opt/firefox/firefox-bin -contentproc -childI+

... in to these:

The overview graph:

Processes of interest by cpu core:

Installing topplot:

If you just want to have topplot installed:

pip3 install topplot

Note: some distros only have Python3 installed, so where I'm using pip3 you may need to use the unadorned pip.

If you want to hack on topplot, install the dependencies, clone the repo, and symlink the topplot.py file in to ~/.local/bin:

pip3 install -U matplotlib mplcursors numpy pandas

REPO_PATH="/path/to/repo_parent_directory"
cd "${REPO_PATH}"

git clone https://gitlab.com/eBardie/topplot
ln -s "${REPO_PATH}"/topplot/topplot.py ~/.local/bin/topplot

Assumptions:

• you're running Linux (although there's very little Linux specific code remaining, so porting to Windows/Max should be trivial. Patches welcome.)
• the following Python modules are installed: matplotlib, numpy, pandas, and (optionally) mplcursors.

(mplcursors enables clicking on plotted lines to display data annotations.)

Specifying which log file to use

By default topplot expects the log to be a file called top.log in the current working directory. You can use the -f commandline option to specify a file path.

Filtering the output

Limit the range of log entries by timestamp: topplot -s 18:38:00 -S 18:39:15

  -s TIMESTAMP, --start TIMESTAMP      Start with time stamp ([D:]HH:MM:SS)
  -S TIMESTAMP, --stop TIMESTAMP       Stop with time stamp  ([D:]HH:MM:SS)

These arguments select processes of interest for graphing:

  -c [N], --acc-cpu [N]        Top N processes ranked by accumulated CPU use (default: 10)
  -m [N], --acc-mem [N]        Top N processes ranked by accumulated MEM use (default: 10)

         --peak-cpu [N]        Top N processes ranked by peak CPU use (default: 10)
         --peak-mem [N]        Top N processes ranked by peak MEM use (default: 10)

        --pct-cpu [PCT]        Any process using more than pct% of memory will be graphed (default: 20)
        --pct-mem [PCT]        Any process using more than pct% of cpu will be graphed (default: 3)

        --prio [cmpPRIO]       Any process with priority =, <=, >=, <, or > to PRIO (default: '=RT', note the prefixed comparison operator)

These two arguments can make the processes graph clearer by plotting only one or the other of CPU or MEM related information:

    -C, --only-proc-cpu         Don't plot processes' mem info
    -M, --only-proc-mem         Don't plot processes' cpu info

Filtering by process name:

  REGEX                        Python style regex for names of processes to graph
  -I REGEX, --ignore REGEX     Python style regex for names of processes to completely ignore

  -i                           Use case insensitive matching

Textual output

Use one or more instances of the --list argument, or -l or -ll or -lll, to display increasing levels of information about processes.

Use -v to increase the verbosity of other optional filtering arguments such as --peak-cpu.

Use --no-graph or -G to surpress graphing.

More commandline options

To see the full set of commandline options:

  -h, --help                   show this help message and exit

The GUI

Once topplot has parsed and munged the data, by default it will display the overview graph.

Press the 1 key to display the top left graph in a separate window, 2 to display the top right, 3 lower left, 4 lower right, or 0 to re-open the overview graph from another window.

Press h to display helpful infomation about using topplot.

Limiting the displayed data

If you want to narrow down the data displayed, click on the items in a graph's legend to toggle their visibility.

Click on a legend's title to toggle all of its lines.

Right click on a legend's title to make all of its lines visible.

Caveat: the "mem data" graph's legend doesn't need or implement toggling.

Legends

Press l (lowercase 'ell') to toggle legend visibility. If the mouse pointer is over a particular graph, then only the legend(s) on that graph will be affected. If the mouse pointer is between graphs, the legends on all graphs on that figure will be toggled.

Legends can be dragged around within their windows but be careful to not leave a legend from one graph entire within a separate graph - it will not be possible to interact with it any more, including moving it off of that graph!

Saving to png files

Press p to 'print' an image of the current figure to a PNG file to the current working directory.

Press P to 'print' images of all the open figures to PNG files to the current working directoty.

Press s to save an image of the current figure via a file dialogue window.

Zooming in

tl;dr : Click on the Pan/Zoom button (the arrow-headed cross), then whilst keeping the CONTROL key depressed, right click on the area of a graph you wish to zoom in on, and drag the mouse around.

For full details see: https://matplotlib.org/3.1.1/users/navigation_toolbar.html. [Note that topplot overrides some keypresses.]

Special features of the "processes of interest" graph

Press t swap between having the mem axis, the cpu axis, or both axes visible.

Special features of the "cpu data" graph

For top logs with per core cpu data available, the "cpu (grouped)" legend toggles lines across all cores.

Caveat emptor

top versions

topplot is known to work with log formats generated by top from the procps package versions 3.2.8 and 3.3.15.

Handling further formats may be as simple as adding new regexs to the Re_Variants instances.

Issues with pandas and mplcursors

In developing topplot I've come across and fixed a couple of minor issues with the pandas and mplcursors libraries. I've submitted my the fixes so future versions of these libraries should be good to go.

The pandas issue means that the timestamp labels are only displayed on the bottom row of some multi-graph figures. (The fix here is awaiting code review at the time of writing.)

The mplcursors issue (fixed here) is that when a line has been made invisible by clicking on its legend line, clicking on the invisible line still evinces an annotation.