6 perf-script-python - Process trace data with a Python script
11 'perf script' [-s [Python]:script[.py] ]
16 This perf script option is used to process perf script data using perf's
17 built-in Python interpreter. It reads and processes the input file and
18 displays the results of the trace analysis implemented in the given
19 Python script, if any.
24 This section shows the process, start to finish, of creating a working
25 Python script that aggregates and extracts useful information from a
26 raw perf script stream. You can avoid reading the rest of this
27 document if an example is enough for you; the rest of the document
28 provides more details on each step and lists the library functions
29 available to script writers.
31 This example actually details the steps that were used to create the
32 'syscall-counts' script you see when you list the available perf script
33 scripts via 'perf script -l'. As such, this script also shows how to
34 integrate your script into the list of general-purpose 'perf script'
35 scripts listed by that command.
37 The syscall-counts script is a simple script, but demonstrates all the
38 basic ideas necessary to create a useful script. Here's an example
39 of its output (syscall names are not yet supported, they will appear
46 ---------------------------------------- -----------
52 sys_sched_setparam 826
73 Basically our task is to keep a per-syscall tally that gets updated
74 every time a system call occurs in the system. Our script will do
75 that, but first we need to record the data that will be processed by
76 that script. Theoretically, there are a couple of ways we could do
79 - we could enable every event under the tracing/events/syscalls
80 directory, but this is over 600 syscalls, well beyond the number
81 allowable by perf. These individual syscall events will however be
82 useful if we want to later use the guidance we get from the
83 general-purpose scripts to drill down and get more detail about
84 individual syscalls of interest.
86 - we can enable the sys_enter and/or sys_exit syscalls found under
87 tracing/events/raw_syscalls. These are called for all syscalls; the
88 'id' field can be used to distinguish between individual syscall
91 For this script, we only need to know that a syscall was entered; we
92 don't care how it exited, so we'll use 'perf record' to record only
96 # perf record -a -e raw_syscalls:sys_enter
98 ^C[ perf record: Woken up 1 times to write data ]
99 [ perf record: Captured and wrote 56.545 MB perf.data (~2470503 samples) ]
102 The options basically say to collect data for every syscall event
103 system-wide and multiplex the per-cpu output into a single stream.
104 That single stream will be recorded in a file in the current directory
107 Once we have a perf.data file containing our data, we can use the -g
108 'perf script' option to generate a Python script that will contain a
109 callback handler for each event type found in the perf.data trace
110 stream (for more details, see the STARTER SCRIPTS section).
113 # perf script -g python
114 generated Python script: perf-script.py
116 The output file created also in the current directory is named
117 perf-script.py. Here's the file in its entirety:
119 # perf script event handlers, generated by perf script -g python
120 # Licensed under the terms of the GNU GPL License version 2
122 # The common_* event handler fields are the most useful fields common to
123 # all events. They don't necessarily correspond to the 'common_*' fields
124 # in the format files. Those fields not available as handler params can
125 # be retrieved using Python functions of the form common_*(context).
126 # See the perf-script-python Documentation for the list of available functions.
131 sys.path.append(os.environ['PERF_EXEC_PATH'] + \
132 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
134 from perf_trace_context import *
138 print "in trace_begin"
143 def raw_syscalls__sys_enter(event_name, context, common_cpu,
144 common_secs, common_nsecs, common_pid, common_comm,
146 print_header(event_name, common_cpu, common_secs, common_nsecs,
147 common_pid, common_comm)
149 print "id=%d, args=%s\n" % \
152 def trace_unhandled(event_name, context, common_cpu, common_secs, common_nsecs,
153 common_pid, common_comm):
154 print_header(event_name, common_cpu, common_secs, common_nsecs,
155 common_pid, common_comm)
157 def print_header(event_name, cpu, secs, nsecs, pid, comm):
158 print "%-20s %5u %05u.%09u %8u %-20s " % \
159 (event_name, cpu, secs, nsecs, pid, comm),
162 At the top is a comment block followed by some import statements and a
163 path append which every perf script script should include.
165 Following that are a couple generated functions, trace_begin() and
166 trace_end(), which are called at the beginning and the end of the
167 script respectively (for more details, see the SCRIPT_LAYOUT section
170 Following those are the 'event handler' functions generated one for
171 every event in the 'perf record' output. The handler functions take
172 the form subsystem__event_name, and contain named parameters, one for
173 each field in the event; in this case, there's only one event,
174 raw_syscalls__sys_enter(). (see the EVENT HANDLERS section below for
175 more info on event handlers).
177 The final couple of functions are, like the begin and end functions,
178 generated for every script. The first, trace_unhandled(), is called
179 every time the script finds an event in the perf.data file that
180 doesn't correspond to any event handler in the script. This could
181 mean either that the record step recorded event types that it wasn't
182 really interested in, or the script was run against a trace file that
183 doesn't correspond to the script.
185 The script generated by -g option simply prints a line for each
186 event found in the trace stream i.e. it basically just dumps the event
187 and its parameter values to stdout. The print_header() function is
188 simply a utility function used for that purpose. Let's rename the
189 script and run it to see the default output:
192 # mv perf-script.py syscall-counts.py
193 # perf script -s syscall-counts.py
195 raw_syscalls__sys_enter 1 00840.847582083 7506 perf id=1, args=
196 raw_syscalls__sys_enter 1 00840.847595764 7506 perf id=1, args=
197 raw_syscalls__sys_enter 1 00840.847620860 7506 perf id=1, args=
198 raw_syscalls__sys_enter 1 00840.847710478 6533 npviewer.bin id=78, args=
199 raw_syscalls__sys_enter 1 00840.847719204 6533 npviewer.bin id=142, args=
200 raw_syscalls__sys_enter 1 00840.847755445 6533 npviewer.bin id=3, args=
201 raw_syscalls__sys_enter 1 00840.847775601 6533 npviewer.bin id=3, args=
202 raw_syscalls__sys_enter 1 00840.847781820 6533 npviewer.bin id=3, args=
208 Of course, for this script, we're not interested in printing every
209 trace event, but rather aggregating it in a useful way. So we'll get
210 rid of everything to do with printing as well as the trace_begin() and
211 trace_unhandled() functions, which we won't be using. That leaves us
212 with this minimalistic skeleton:
218 sys.path.append(os.environ['PERF_EXEC_PATH'] + \
219 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
221 from perf_trace_context import *
227 def raw_syscalls__sys_enter(event_name, context, common_cpu,
228 common_secs, common_nsecs, common_pid, common_comm,
232 In trace_end(), we'll simply print the results, but first we need to
233 generate some results to print. To do that we need to have our
234 sys_enter() handler do the necessary tallying until all events have
235 been counted. A hash table indexed by syscall id is a good way to
236 store that information; every time the sys_enter() handler is called,
237 we simply increment a count associated with that hash entry indexed by
241 syscalls = autodict()
249 The syscalls 'autodict' object is a special kind of Python dictionary
250 (implemented in Core.py) that implements Perl's 'autovivifying' hashes
251 in Python i.e. with autovivifying hashes, you can assign nested hash
252 values without having to go to the trouble of creating intermediate
253 levels if they don't exist e.g syscalls[comm][pid][id] = 1 will create
254 the intermediate hash levels and finally assign the value 1 to the
255 hash entry for 'id' (because the value being assigned isn't a hash
256 object itself, the initial value is assigned in the TypeError
257 exception. Well, there may be a better way to do this in Python but
258 that's what works for now).
260 Putting that code into the raw_syscalls__sys_enter() handler, we
261 effectively end up with a single-level dictionary keyed on syscall id
262 and having the counts we've tallied as values.
264 The print_syscall_totals() function iterates over the entries in the
265 dictionary and displays a line for each entry containing the syscall
266 name (the dictonary keys contain the syscall ids, which are passed to
267 the Util function syscall_name(), which translates the raw syscall
268 numbers to the corresponding syscall name strings). The output is
269 displayed after all the events in the trace have been processed, by
270 calling the print_syscall_totals() function from the trace_end()
271 handler called at the end of script processing.
273 The final script producing the output shown above is shown in its
274 entirety below (syscall_name() helper is not yet available, you can
275 only deal with id's for now):
281 sys.path.append(os.environ['PERF_EXEC_PATH'] + \
282 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
284 from perf_trace_context import *
288 syscalls = autodict()
291 print_syscall_totals()
293 def raw_syscalls__sys_enter(event_name, context, common_cpu,
294 common_secs, common_nsecs, common_pid, common_comm,
301 def print_syscall_totals():
302 if for_comm is not None:
303 print "\nsyscall events for %s:\n\n" % (for_comm),
305 print "\nsyscall events:\n\n",
307 print "%-40s %10s\n" % ("event", "count"),
308 print "%-40s %10s\n" % ("----------------------------------------", \
311 for id, val in sorted(syscalls.iteritems(), key = lambda(k, v): (v, k), \
313 print "%-40s %10d\n" % (syscall_name(id), val),
316 The script can be run just as before:
318 # perf script -s syscall-counts.py
320 So those are the essential steps in writing and running a script. The
321 process can be generalized to any tracepoint or set of tracepoints
322 you're interested in - basically find the tracepoint(s) you're
323 interested in by looking at the list of available events shown by
324 'perf list' and/or look in /sys/kernel/debug/tracing events for
325 detailed event and field info, record the corresponding trace data
326 using 'perf record', passing it the list of interesting events,
327 generate a skeleton script using 'perf script -g python' and modify the
328 code to aggregate and display it for your particular needs.
330 After you've done that you may end up with a general-purpose script
331 that you want to keep around and have available for future use. By
332 writing a couple of very simple shell scripts and putting them in the
333 right place, you can have your script listed alongside the other
334 scripts listed by the 'perf script -l' command e.g.:
337 root@tropicana:~# perf script -l
338 List of available trace scripts:
339 wakeup-latency system-wide min/max/avg wakeup latency
340 rw-by-file <comm> r/w activity for a program, by file
341 rw-by-pid system-wide r/w activity
344 A nice side effect of doing this is that you also then capture the
345 probably lengthy 'perf record' command needed to record the events for
348 To have the script appear as a 'built-in' script, you write two simple
349 scripts, one for recording and one for 'reporting'.
351 The 'record' script is a shell script with the same base name as your
352 script, but with -record appended. The shell script should be put
353 into the perf/scripts/python/bin directory in the kernel source tree.
354 In that script, you write the 'perf record' command-line needed for
358 # cat kernel-source/tools/perf/scripts/python/bin/syscall-counts-record
361 perf record -a -e raw_syscalls:sys_enter
364 The 'report' script is also a shell script with the same base name as
365 your script, but with -report appended. It should also be located in
366 the perf/scripts/python/bin directory. In that script, you write the
367 'perf script -s' command-line needed for running your script:
370 # cat kernel-source/tools/perf/scripts/python/bin/syscall-counts-report
373 # description: system-wide syscall counts
374 perf script -s ~/libexec/perf-core/scripts/python/syscall-counts.py
377 Note that the location of the Python script given in the shell script
378 is in the libexec/perf-core/scripts/python directory - this is where
379 the script will be copied by 'make install' when you install perf.
380 For the installation to install your script there, your script needs
381 to be located in the perf/scripts/python directory in the kernel
385 # ls -al kernel-source/tools/perf/scripts/python
387 root@tropicana:/home/trz/src/tip# ls -al tools/perf/scripts/python
389 drwxr-xr-x 4 trz trz 4096 2010-01-26 22:30 .
390 drwxr-xr-x 4 trz trz 4096 2010-01-26 22:29 ..
391 drwxr-xr-x 2 trz trz 4096 2010-01-26 22:29 bin
392 -rw-r--r-- 1 trz trz 2548 2010-01-26 22:29 check-perf-script.py
393 drwxr-xr-x 3 trz trz 4096 2010-01-26 22:49 Perf-Trace-Util
394 -rw-r--r-- 1 trz trz 1462 2010-01-26 22:30 syscall-counts.py
397 Once you've done that (don't forget to do a new 'make install',
398 otherwise your script won't show up at run-time), 'perf script -l'
399 should show a new entry for your script:
402 root@tropicana:~# perf script -l
403 List of available trace scripts:
404 wakeup-latency system-wide min/max/avg wakeup latency
405 rw-by-file <comm> r/w activity for a program, by file
406 rw-by-pid system-wide r/w activity
407 syscall-counts system-wide syscall counts
410 You can now perform the record step via 'perf script record':
412 # perf script record syscall-counts
414 and display the output using 'perf script report':
416 # perf script report syscall-counts
421 You can quickly get started writing a script for a particular set of
422 trace data by generating a skeleton script using 'perf script -g
423 python' in the same directory as an existing perf.data trace file.
424 That will generate a starter script containing a handler for each of
425 the event types in the trace file; it simply prints every available
426 field for each event in the trace file.
428 You can also look at the existing scripts in
429 ~/libexec/perf-core/scripts/python for typical examples showing how to
430 do basic things like aggregate event data, print results, etc. Also,
431 the check-perf-script.py script, while not interesting for its results,
432 attempts to exercise all of the main scripting features.
437 When perf script is invoked using a trace script, a user-defined
438 'handler function' is called for each event in the trace. If there's
439 no handler function defined for a given event type, the event is
440 ignored (or passed to a 'trace_handled' function, see below) and the
441 next event is processed.
443 Most of the event's field values are passed as arguments to the
444 handler function; some of the less common ones aren't - those are
445 available as calls back into the perf executable (see below).
447 As an example, the following perf record command can be used to record
448 all sched_wakeup events in the system:
450 # perf record -a -e sched:sched_wakeup
452 Traces meant to be processed using a script should be recorded with
453 the above option: -a to enable system-wide collection.
455 The format file for the sched_wakep event defines the following fields
456 (see /sys/kernel/debug/tracing/events/sched/sched_wakeup/format):
460 field:unsigned short common_type;
461 field:unsigned char common_flags;
462 field:unsigned char common_preempt_count;
463 field:int common_pid;
465 field:char comm[TASK_COMM_LEN];
469 field:int target_cpu;
472 The handler function for this event would be defined as:
475 def sched__sched_wakeup(event_name, context, common_cpu, common_secs,
476 common_nsecs, common_pid, common_comm,
477 comm, pid, prio, success, target_cpu):
481 The handler function takes the form subsystem__event_name.
483 The common_* arguments in the handler's argument list are the set of
484 arguments passed to all event handlers; some of the fields correspond
485 to the common_* fields in the format file, but some are synthesized,
486 and some of the common_* fields aren't common enough to to be passed
487 to every event as arguments but are available as library functions.
489 Here's a brief description of each of the invariant event args:
491 event_name the name of the event as text
492 context an opaque 'cookie' used in calls back into perf
493 common_cpu the cpu the event occurred on
494 common_secs the secs portion of the event timestamp
495 common_nsecs the nsecs portion of the event timestamp
496 common_pid the pid of the current task
497 common_comm the name of the current process
499 All of the remaining fields in the event's format file have
500 counterparts as handler function arguments of the same name, as can be
501 seen in the example above.
503 The above provides the basics needed to directly access every field of
504 every event in a trace, which covers 90% of what you need to know to
505 write a useful trace script. The sections below cover the rest.
510 Every perf script Python script should start by setting up a Python
511 module search path and 'import'ing a few support modules (see module
518 sys.path.append(os.environ['PERF_EXEC_PATH'] + \
519 '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
521 from perf_trace_context import *
525 The rest of the script can contain handler functions and support
526 functions in any order.
528 Aside from the event handler functions discussed above, every script
529 can implement a set of optional functions:
531 *trace_begin*, if defined, is called before any event is processed and
532 gives scripts a chance to do setup tasks:
539 *trace_end*, if defined, is called after all events have been
540 processed and gives scripts a chance to do end-of-script tasks, such
548 *trace_unhandled*, if defined, is called after for any event that
549 doesn't have a handler explicitly defined for it. The standard set
550 of common arguments are passed into it:
553 def trace_unhandled(event_name, context, common_cpu, common_secs,
554 common_nsecs, common_pid, common_comm):
558 The remaining sections provide descriptions of each of the available
559 built-in perf script Python modules and their associated functions.
561 AVAILABLE MODULES AND FUNCTIONS
562 -------------------------------
564 The following sections describe the functions and variables available
565 via the various perf script Python modules. To use the functions and
566 variables from the given module, add the corresponding 'from XXXX
567 import' line to your perf script script.
572 These functions provide some essential functions to user scripts.
574 The *flag_str* and *symbol_str* functions provide human-readable
575 strings for flag and symbolic fields. These correspond to the strings
576 and values parsed from the 'print fmt' fields of the event format
579 flag_str(event_name, field_name, field_value) - returns the string represention corresponding to field_value for the flag field field_name of event event_name
580 symbol_str(event_name, field_name, field_value) - returns the string represention corresponding to field_value for the symbolic field field_name of event event_name
582 The *autodict* function returns a special kind of Python
583 dictionary that implements Perl's 'autovivifying' hashes in Python
584 i.e. with autovivifying hashes, you can assign nested hash values
585 without having to go to the trouble of creating intermediate levels if
588 autodict() - returns an autovivifying dictionary instance
591 perf_trace_context Module
592 ~~~~~~~~~~~~~~~~~~~~~~~~~
594 Some of the 'common' fields in the event format file aren't all that
595 common, but need to be made accessible to user scripts nonetheless.
597 perf_trace_context defines a set of functions that can be used to
598 access this data in the context of the current event. Each of these
599 functions expects a context variable, which is the same as the
600 context variable passed into every event handler as the second
603 common_pc(context) - returns common_preempt count for the current event
604 common_flags(context) - returns common_flags for the current event
605 common_lock_depth(context) - returns common_lock_depth for the current event
610 Various utility functions for use with perf script:
612 nsecs(secs, nsecs) - returns total nsecs given secs/nsecs pair
613 nsecs_secs(nsecs) - returns whole secs portion given nsecs
614 nsecs_nsecs(nsecs) - returns nsecs remainder given nsecs
615 nsecs_str(nsecs) - returns printable string in the form secs.nsecs
616 avg(total, n) - returns average given a sum and a total number of values
620 linkperf:perf-script[1]