topplot

Munge logs from the commandline utility top in to useful graphs

[For latest updates see RELEASE.md]

[[TOC]]

Introduction

topplot produces graphs from 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).

As of version 0.0.5 topplot runs on Linux and Windows. (It should run on any platform that suports Python's tkinter module. Please send reports if you can test this.)

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...

Snipped 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 of process information
    .
    .
 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 figure:

Processes of interest (POI) by cpu core:

Note that the overview figure is a screen capture, hence the coloured background, whilst the POI figure was produced by topplot. Click on either image to embiggen it.

You can see that some plotted lines have been turned off (by clicking on a legend line), and that various points have been annotated with text in yellow boxes in the second figure (by clicking on the line itself).

Installing topplot

Dependencies

Dependencies should mostly be handled by pip or your package manager.

The only currently known exception is that your Python3 installation must have the Tkinter module available.

On Debian this can be done by running:

sudo apt install python3-tk

Installing for normal usage

If you just want to have topplot installed so you can use it:

If you're running on Debian Linux:

sudo apt install topplot

Otherwise:

pip3 install topplot

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

Installing for hacking on topplot

If you want to hack on topplot, clone the repo and setup a Python virtual environment:

# clone the repo
git clone https://gitlab.com/eBardie/topplot
cd topplot

# create and activate a Python virtual environment to isolate dependencies from your base system
python3 -m venv .venv
source .venv/bin/activate

# install dependencies inside the virtual environment
python3 -m pip install -e .

# hack on topplot

# .
# .
# .

# When done, leave the virtual environment
deactivate

For subsequent sessions all you'll need to do is:

# cd to where ever you cloned the topplot repo
cd topplot

# Active the Python virtual environment
source venv/bin/activate

# hack some more on topplot

# .
# .
# .

# When done, leave the virtual environment
deactivate

See also: External issues: Glitches and fixes in dependencies.

Getting the logs from top

See generating top logs.

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 input

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.

If top was configured to output the process data with teh last core it ran on, press uppercase c to display the graphs for processes running on individual cores.

If top was configured to output the CPU data for each individual core, press uppercase C to display the CPU graphs for individual graphs.

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 uppercase 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-ng package versions 3.2.8 and 3.3.15.

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

Android uses Toybox to provide top, and is not yet handled by topplot. Busybox's top has not been tried, but seeing as Toybox was forked from Busybox I'd guess Busybox's top won't be compatible either.

External Issues: Glitches and fixes in dependencies

Currently the only known issue is Matplotlib not (yet) having adapted to changes in Python's Tk library. The effect for Topplot is that keyboard control doesn't work on Windows if you're using Python 3.10 or a clean install of Python 3.9.9. (If your Python 3.9.9 was upgraded from an earlier install of Python 3.9.x where x<=8, you may be in luck if the Python installer didn't upgrade the Tk DLL.)

See this Topplot bug report for a quick fix. See this Matplotlib PR for details of the proposed full fix.