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perf-script-python(1)
====================
NAME
----
perf-script-python - Process trace data with a Python script
SYNOPSIS
--------
[verse]
'perf script' [-s [Python]:script[.py] ]
DESCRIPTION
-----------
This perf script option is used to process perf script data using perf's
built-in Python interpreter. It reads and processes the input file and
displays the results of the trace analysis implemented in the given
Python script, if any.
A QUICK EXAMPLE
---------------
This section shows the process, start to finish, of creating a working
Python script that aggregates and extracts useful information from a
raw perf script stream. You can avoid reading the rest of this
document if an example is enough for you; the rest of the document
provides more details on each step and lists the library functions
available to script writers.
This example actually details the steps that were used to create the
'syscall-counts' script you see when you list the available perf script
scripts via 'perf script -l'. As such, this script also shows how to
integrate your script into the list of general-purpose 'perf script'
scripts listed by that command.
The syscall-counts script is a simple script, but demonstrates all the
basic ideas necessary to create a useful script. Here's an example
of its output (syscall names are not yet supported, they will appear
as numbers):
----
syscall events:
event count
---------------------------------------- -----------
sys_write 455067
sys_getdents 4072
sys_close 3037
sys_swapoff 1769
sys_read 923
sys_sched_setparam 826
sys_open 331
sys_newfstat 326
sys_mmap 217
sys_munmap 216
sys_futex 141
sys_select 102
sys_poll 84
sys_setitimer 12
sys_writev 8
15 8
sys_lseek 7
sys_rt_sigprocmask 6
sys_wait4 3
sys_ioctl 3
sys_set_robust_list 1
sys_exit 1
56 1
sys_access 1
----
Basically our task is to keep a per-syscall tally that gets updated
every time a system call occurs in the system. Our script will do
that, but first we need to record the data that will be processed by
that script. Theoretically, there are a couple of ways we could do
that:
- we could enable every event under the tracing/events/syscalls
directory, but this is over 600 syscalls, well beyond the number
allowable by perf. These individual syscall events will however be
useful if we want to later use the guidance we get from the
general-purpose scripts to drill down and get more detail about
individual syscalls of interest.
- we can enable the sys_enter and/or sys_exit syscalls found under
tracing/events/raw_syscalls. These are called for all syscalls; the
'id' field can be used to distinguish between individual syscall
numbers.
For this script, we only need to know that a syscall was entered; we
don't care how it exited, so we'll use 'perf record' to record only
the sys_enter events:
----
# perf record -a -e raw_syscalls:sys_enter
^C[ perf record: Woken up 1 times to write data ]
[ perf record: Captured and wrote 56.545 MB perf.data (~2470503 samples) ]
----
The options basically say to collect data for every syscall event
system-wide and multiplex the per-cpu output into a single stream.
That single stream will be recorded in a file in the current directory
called perf.data.
Once we have a perf.data file containing our data, we can use the -g
'perf script' option to generate a Python script that will contain a
callback handler for each event type found in the perf.data trace
stream (for more details, see the STARTER SCRIPTS section).
----
# perf script -g python
generated Python script: perf-script.py
The output file created also in the current directory is named
perf-script.py. Here's the file in its entirety:
# perf script event handlers, generated by perf script -g python
# Licensed under the terms of the GNU GPL License version 2
# The common_* event handler fields are the most useful fields common to
# all events. They don't necessarily correspond to the 'common_*' fields
# in the format files. Those fields not available as handler params can
# be retrieved using Python functions of the form common_*(context).
# See the perf-script-python Documentation for the list of available functions.
import os
import sys
sys.path.append(os.environ['PERF_EXEC_PATH'] + \
'/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
from perf_trace_context import *
from Core import *
def trace_begin():
print "in trace_begin"
def trace_end():
print "in trace_end"
def raw_syscalls__sys_enter(event_name, context, common_cpu,
common_secs, common_nsecs, common_pid, common_comm,
id, args):
print_header(event_name, common_cpu, common_secs, common_nsecs,
common_pid, common_comm)
print "id=%d, args=%s\n" % \
(id, args),
def trace_unhandled(event_name, context, event_fields_dict):
print ' '.join(['%s=%s'%(k,str(v))for k,v in sorted(event_fields_dict.items())])
def print_header(event_name, cpu, secs, nsecs, pid, comm):
print "%-20s %5u %05u.%09u %8u %-20s " % \
(event_name, cpu, secs, nsecs, pid, comm),
----
At the top is a comment block followed by some import statements and a
path append which every perf script script should include.
Following that are a couple generated functions, trace_begin() and
trace_end(), which are called at the beginning and the end of the
script respectively (for more details, see the SCRIPT_LAYOUT section
below).
Following those are the 'event handler' functions generated one for
every event in the 'perf record' output. The handler functions take
the form subsystem\__event_name, and contain named parameters, one for
each field in the event; in this case, there's only one event,
raw_syscalls__sys_enter(). (see the EVENT HANDLERS section below for
more info on event handlers).
The final couple of functions are, like the begin and end functions,
generated for every script. The first, trace_unhandled(), is called
every time the script finds an event in the perf.data file that
doesn't correspond to any event handler in the script. This could
mean either that the record step recorded event types that it wasn't
really interested in, or the script was run against a trace file that
doesn't correspond to the script.
The script generated by -g option simply prints a line for each
event found in the trace stream i.e. it basically just dumps the event
and its parameter values to stdout. The print_header() function is
simply a utility function used for that purpose. Let's rename the
script and run it to see the default output:
----
# mv perf-script.py syscall-counts.py
# perf script -s syscall-counts.py
raw_syscalls__sys_enter 1 00840.847582083 7506 perf id=1, args=
raw_syscalls__sys_enter 1 00840.847595764 7506 perf id=1, args=
raw_syscalls__sys_enter 1 00840.847620860 7506 perf id=1, args=
raw_syscalls__sys_enter 1 00840.847710478 6533 npviewer.bin id=78, args=
raw_syscalls__sys_enter 1 00840.847719204 6533 npviewer.bin id=142, args=
raw_syscalls__sys_enter 1 00840.847755445 6533 npviewer.bin id=3, args=
raw_syscalls__sys_enter 1 00840.847775601 6533 npviewer.bin id=3, args=
raw_syscalls__sys_enter 1 00840.847781820 6533 npviewer.bin id=3, args=
.
.
.
----
Of course, for this script, we're not interested in printing every
trace event, but rather aggregating it in a useful way. So we'll get
rid of everything to do with printing as well as the trace_begin() and
trace_unhandled() functions, which we won't be using. That leaves us
with this minimalistic skeleton:
----
import os
import sys
sys.path.append(os.environ['PERF_EXEC_PATH'] + \
'/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
from perf_trace_context import *
from Core import *
def trace_end():
print "in trace_end"
def raw_syscalls__sys_enter(event_name, context, common_cpu,
common_secs, common_nsecs, common_pid, common_comm,
id, args):
----
In trace_end(), we'll simply print the results, but first we need to
generate some results to print. To do that we need to have our
sys_enter() handler do the necessary tallying until all events have
been counted. A hash table indexed by syscall id is a good way to
store that information; every time the sys_enter() handler is called,
we simply increment a count associated with that hash entry indexed by
that syscall id:
----
syscalls = autodict()
try:
syscalls[id] += 1
except TypeError:
syscalls[id] = 1
----
The syscalls 'autodict' object is a special kind of Python dictionary
(implemented in Core.py) that implements Perl's 'autovivifying' hashes
in Python i.e. with autovivifying hashes, you can assign nested hash
values without having to go to the trouble of creating intermediate
levels if they don't exist e.g syscalls[comm][pid][id] = 1 will create
the intermediate hash levels and finally assign the value 1 to the
hash entry for 'id' (because the value being assigned isn't a hash
object itself, the initial value is assigned in the TypeError
exception. Well, there may be a better way to do this in Python but
that's what works for now).
Putting that code into the raw_syscalls__sys_enter() handler, we
effectively end up with a single-level dictionary keyed on syscall id
and having the counts we've tallied as values.
The print_syscall_totals() function iterates over the entries in the
dictionary and displays a line for each entry containing the syscall
name (the dictionary keys contain the syscall ids, which are passed to
the Util function syscall_name(), which translates the raw syscall
numbers to the corresponding syscall name strings). The output is
displayed after all the events in the trace have been processed, by
calling the print_syscall_totals() function from the trace_end()
handler called at the end of script processing.
The final script producing the output shown above is shown in its
entirety below (syscall_name() helper is not yet available, you can
only deal with id's for now):
----
import os
import sys
sys.path.append(os.environ['PERF_EXEC_PATH'] + \
'/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
from perf_trace_context import *
from Core import *
from Util import *
syscalls = autodict()
def trace_end():
print_syscall_totals()
def raw_syscalls__sys_enter(event_name, context, common_cpu,
common_secs, common_nsecs, common_pid, common_comm,
id, args):
try:
syscalls[id] += 1
except TypeError:
syscalls[id] = 1
def print_syscall_totals():
if for_comm is not None:
print "\nsyscall events for %s:\n\n" % (for_comm),
else:
print "\nsyscall events:\n\n",
print "%-40s %10s\n" % ("event", "count"),
print "%-40s %10s\n" % ("----------------------------------------", \
"-----------"),
for id, val in sorted(syscalls.iteritems(), key = lambda(k, v): (v, k), \
reverse = True):
print "%-40s %10d\n" % (syscall_name(id), val),
----
The script can be run just as before:
# perf script -s syscall-counts.py
So those are the essential steps in writing and running a script. The
process can be generalized to any tracepoint or set of tracepoints
you're interested in - basically find the tracepoint(s) you're
interested in by looking at the list of available events shown by
'perf list' and/or look in /sys/kernel/debug/tracing/events/ for
detailed event and field info, record the corresponding trace data
using 'perf record', passing it the list of interesting events,
generate a skeleton script using 'perf script -g python' and modify the
code to aggregate and display it for your particular needs.
After you've done that you may end up with a general-purpose script
that you want to keep around and have available for future use. By
writing a couple of very simple shell scripts and putting them in the
right place, you can have your script listed alongside the other
scripts listed by the 'perf script -l' command e.g.:
----
# perf script -l
List of available trace scripts:
wakeup-latency system-wide min/max/avg wakeup latency
rw-by-file <comm> r/w activity for a program, by file
rw-by-pid system-wide r/w activity
----
A nice side effect of doing this is that you also then capture the
probably lengthy 'perf record' command needed to record the events for
the script.
To have the script appear as a 'built-in' script, you write two simple
scripts, one for recording and one for 'reporting'.
The 'record' script is a shell script with the same base name as your
script, but with -record appended. The shell script should be put
into the perf/scripts/python/bin directory in the kernel source tree.
In that script, you write the 'perf record' command-line needed for
your script:
----
# cat kernel-source/tools/perf/scripts/python/bin/syscall-counts-record
#!/bin/bash
perf record -a -e raw_syscalls:sys_enter
----
The 'report' script is also a shell script with the same base name as
your script, but with -report appended. It should also be located in
the perf/scripts/python/bin directory. In that script, you write the
'perf script -s' command-line needed for running your script:
----
# cat kernel-source/tools/perf/scripts/python/bin/syscall-counts-report
#!/bin/bash
# description: system-wide syscall counts
perf script -s ~/libexec/perf-core/scripts/python/syscall-counts.py
----
Note that the location of the Python script given in the shell script
is in the libexec/perf-core/scripts/python directory - this is where
the script will be copied by 'make install' when you install perf.
For the installation to install your script there, your script needs
to be located in the perf/scripts/python directory in the kernel
source tree:
----
# ls -al kernel-source/tools/perf/scripts/python
total 32
drwxr-xr-x 4 trz trz 4096 2010-01-26 22:30 .
drwxr-xr-x 4 trz trz 4096 2010-01-26 22:29 ..
drwxr-xr-x 2 trz trz 4096 2010-01-26 22:29 bin
-rw-r--r-- 1 trz trz 2548 2010-01-26 22:29 check-perf-script.py
drwxr-xr-x 3 trz trz 4096 2010-01-26 22:49 Perf-Trace-Util
-rw-r--r-- 1 trz trz 1462 2010-01-26 22:30 syscall-counts.py
----
Once you've done that (don't forget to do a new 'make install',
otherwise your script won't show up at run-time), 'perf script -l'
should show a new entry for your script:
----
# perf script -l
List of available trace scripts:
wakeup-latency system-wide min/max/avg wakeup latency
rw-by-file <comm> r/w activity for a program, by file
rw-by-pid system-wide r/w activity
syscall-counts system-wide syscall counts
----
You can now perform the record step via 'perf script record':
# perf script record syscall-counts
and display the output using 'perf script report':
# perf script report syscall-counts
STARTER SCRIPTS
---------------
You can quickly get started writing a script for a particular set of
trace data by generating a skeleton script using 'perf script -g
python' in the same directory as an existing perf.data trace file.
That will generate a starter script containing a handler for each of
the event types in the trace file; it simply prints every available
field for each event in the trace file.
You can also look at the existing scripts in
~/libexec/perf-core/scripts/python for typical examples showing how to
do basic things like aggregate event data, print results, etc. Also,
the check-perf-script.py script, while not interesting for its results,
attempts to exercise all of the main scripting features.
EVENT HANDLERS
--------------
When perf script is invoked using a trace script, a user-defined
'handler function' is called for each event in the trace. If there's
no handler function defined for a given event type, the event is
ignored (or passed to a 'trace_unhandled' function, see below) and the
next event is processed.
Most of the event's field values are passed as arguments to the
handler function; some of the less common ones aren't - those are
available as calls back into the perf executable (see below).
As an example, the following perf record command can be used to record
all sched_wakeup events in the system:
# perf record -a -e sched:sched_wakeup
Traces meant to be processed using a script should be recorded with
the above option: -a to enable system-wide collection.
The format file for the sched_wakeup event defines the following fields
(see /sys/kernel/debug/tracing/events/sched/sched_wakeup/format):
----
format:
field:unsigned short common_type;
field:unsigned char common_flags;
field:unsigned char common_preempt_count;
field:int common_pid;
field:char comm[TASK_COMM_LEN];
field:pid_t pid;
field:int prio;
field:int success;
field:int target_cpu;
----
The handler function for this event would be defined as:
----
def sched__sched_wakeup(event_name, context, common_cpu, common_secs,
common_nsecs, common_pid, common_comm,
comm, pid, prio, success, target_cpu):
pass
----
The handler function takes the form subsystem__event_name.
The common_* arguments in the handler's argument list are the set of
arguments passed to all event handlers; some of the fields correspond
to the common_* fields in the format file, but some are synthesized,
and some of the common_* fields aren't common enough to to be passed
to every event as arguments but are available as library functions.
Here's a brief description of each of the invariant event args:
event_name the name of the event as text
context an opaque 'cookie' used in calls back into perf
common_cpu the cpu the event occurred on
common_secs the secs portion of the event timestamp
common_nsecs the nsecs portion of the event timestamp
common_pid the pid of the current task
common_comm the name of the current process
All of the remaining fields in the event's format file have
counterparts as handler function arguments of the same name, as can be
seen in the example above.
The above provides the basics needed to directly access every field of
every event in a trace, which covers 90% of what you need to know to
write a useful trace script. The sections below cover the rest.
SCRIPT LAYOUT
-------------
Every perf script Python script should start by setting up a Python
module search path and 'import'ing a few support modules (see module
descriptions below):
----
import os
import sys
sys.path.append(os.environ['PERF_EXEC_PATH'] + \
'/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
from perf_trace_context import *
from Core import *
----
The rest of the script can contain handler functions and support
functions in any order.
Aside from the event handler functions discussed above, every script
can implement a set of optional functions:
*trace_begin*, if defined, is called before any event is processed and
gives scripts a chance to do setup tasks:
----
def trace_begin():
pass
----
*trace_end*, if defined, is called after all events have been
processed and gives scripts a chance to do end-of-script tasks, such
as display results:
----
def trace_end():
pass
----
*trace_unhandled*, if defined, is called after for any event that
doesn't have a handler explicitly defined for it. The standard set
of common arguments are passed into it:
----
def trace_unhandled(event_name, context, event_fields_dict):
pass
----
*process_event*, if defined, is called for any non-tracepoint event
----
def process_event(param_dict):
pass
----
*context_switch*, if defined, is called for any context switch
----
def context_switch(ts, cpu, pid, tid, np_pid, np_tid, machine_pid, out, out_preempt, *x):
pass
----
*auxtrace_error*, if defined, is called for any AUX area tracing error
----
def auxtrace_error(typ, code, cpu, pid, tid, ip, ts, msg, cpumode, *x):
pass
----
The remaining sections provide descriptions of each of the available
built-in perf script Python modules and their associated functions.
AVAILABLE MODULES AND FUNCTIONS
-------------------------------
The following sections describe the functions and variables available
via the various perf script Python modules. To use the functions and
variables from the given module, add the corresponding 'from XXXX
import' line to your perf script script.
Core.py Module
~~~~~~~~~~~~~~
These functions provide some essential functions to user scripts.
The *flag_str* and *symbol_str* functions provide human-readable
strings for flag and symbolic fields. These correspond to the strings
and values parsed from the 'print fmt' fields of the event format
files:
flag_str(event_name, field_name, field_value) - returns the string representation corresponding to field_value for the flag field field_name of event event_name
symbol_str(event_name, field_name, field_value) - returns the string representation corresponding to field_value for the symbolic field field_name of event event_name
The *autodict* function returns a special kind of Python
dictionary that implements Perl's 'autovivifying' hashes in Python
i.e. with autovivifying hashes, you can assign nested hash values
without having to go to the trouble of creating intermediate levels if
they don't exist.
autodict() - returns an autovivifying dictionary instance
perf_trace_context Module
~~~~~~~~~~~~~~~~~~~~~~~~~
Some of the 'common' fields in the event format file aren't all that
common, but need to be made accessible to user scripts nonetheless.
perf_trace_context defines a set of functions that can be used to
access this data in the context of the current event. Each of these
functions expects a context variable, which is the same as the
context variable passed into every tracepoint event handler as the second
argument. For non-tracepoint events, the context variable is also present
as perf_trace_context.perf_script_context .
common_pc(context) - returns common_preempt count for the current event
common_flags(context) - returns common_flags for the current event
common_lock_depth(context) - returns common_lock_depth for the current event
perf_sample_insn(context) - returns the machine code instruction
perf_set_itrace_options(context, itrace_options) - set --itrace options if they have not been set already
perf_sample_srcline(context) - returns source_file_name, line_number
perf_sample_srccode(context) - returns source_file_name, line_number, source_line
Util.py Module
~~~~~~~~~~~~~~
Various utility functions for use with perf script:
nsecs(secs, nsecs) - returns total nsecs given secs/nsecs pair
nsecs_secs(nsecs) - returns whole secs portion given nsecs
nsecs_nsecs(nsecs) - returns nsecs remainder given nsecs
nsecs_str(nsecs) - returns printable string in the form secs.nsecs
avg(total, n) - returns average given a sum and a total number of values
SUPPORTED FIELDS
----------------
Currently supported fields:
ev_name, comm, pid, tid, cpu, ip, time, period, phys_addr, addr,
symbol, symoff, dso, time_enabled, time_running, values, callchain,
brstack, brstacksym, datasrc, datasrc_decode, iregs, uregs,
weight, transaction, raw_buf, attr, cpumode.
Fields that may also be present:
flags - sample flags
flags_disp - sample flags display
insn_cnt - instruction count for determining instructions-per-cycle (IPC)
cyc_cnt - cycle count for determining IPC
addr_correlates_sym - addr can correlate to a symbol
addr_dso - addr dso
addr_symbol - addr symbol
addr_symoff - addr symbol offset
Some fields have sub items:
brstack:
from, to, from_dsoname, to_dsoname, mispred,
predicted, in_tx, abort, cycles.
brstacksym:
items: from, to, pred, in_tx, abort (converted string)
For example,
We can use this code to print brstack "from", "to", "cycles".
if 'brstack' in dict:
for entry in dict['brstack']:
print "from %s, to %s, cycles %s" % (entry["from"], entry["to"], entry["cycles"])
SEE ALSO
--------
linkperf:perf-script[1]