def _check_color(): global _COLORS """user enforced no-color or if stdout is no tty we disable colors""" if sys.stdout.isatty() and args.stdio_color != "never": return
_COLORS = { "grey": "", "red": "", "green": "", "yellow": "", "blue": "", "violet": "", "reset": "",
}
def _parse_args(): global args
parser = argparse.ArgumentParser(description="Analyze tasks behavior")
parser.add_argument( "--time-limit",
default=[],
help= "print tasks only in time[s] window e.g" " --time-limit 123.111:789.222(print all between 123.111 and 789.222)" " --time-limit 123: (print all from 123)" " --time-limit :456 (print all until incl. 456)",
)
parser.add_argument( "--summary", action="store_true", help="print addtional runtime information"
)
parser.add_argument( "--summary-only", action="store_true", help="print only summary without traces"
)
parser.add_argument( "--summary-extended",
action="store_true",
help="print the summary with additional information of max inter task times" " relative to the prev task",
)
parser.add_argument( "--ns", action="store_true", help="show timestamps in nanoseconds"
)
parser.add_argument( "--ms", action="store_true", help="show timestamps in milliseconds"
)
parser.add_argument( "--extended-times",
action="store_true",
help="Show the elapsed times between schedule in/schedule out" " of this task and the schedule in/schedule out of previous occurrence" " of the same task",
)
parser.add_argument( "--filter-tasks",
default=[],
help="filter out unneeded tasks by tid, pid or processname." " E.g --filter-task 1337,/sbin/init ",
)
parser.add_argument( "--limit-to-tasks",
default=[],
help="limit output to selected task by tid, pid, processname." " E.g --limit-to-tasks 1337,/sbin/init",
)
parser.add_argument( "--highlight-tasks",
default="",
help="colorize special tasks by their pid/tid/comm." " E.g. --highlight-tasks 1:red,mutt:yellow" " Colors available: red,grey,yellow,blue,violet,green",
)
parser.add_argument( "--rename-comms-by-tids",
default="",
help="rename task names by using tid (:,:)" " This option is handy for inexpressive processnames like python interpreted" " process. E.g --rename 1337:my-python-app",
)
parser.add_argument( "--stdio-color",
default="auto",
choices=["always", "never", "auto"],
help="always, never or auto, allowing configuring color output" " via the command line",
)
parser.add_argument( "--csv",
default="",
help="Write trace to file selected by user. Options, like --ns or --extended" "-times are used.",
)
parser.add_argument( "--csv-summary",
default="",
help="Write summary to file selected by user. Options, like --ns or" " --summary-extended are used.",
)
args = parser.parse_args()
args.tid_renames = dict()
def _init_db(): global db
db = dict()
db["running"] = dict()
db["cpu"] = dict()
db["tid"] = dict()
db["global"] = [] if args.summary or args.summary_extended or args.summary_only:
db["task_info"] = dict()
db["runtime_info"] = dict() # min values for summary depending on the header
db["task_info"]["pid"] = len("PID")
db["task_info"]["tid"] = len("TID")
db["task_info"]["comm"] = len("Comm")
db["runtime_info"]["runs"] = len("Runs")
db["runtime_info"]["acc"] = len("Accumulated")
db["runtime_info"]["max"] = len("Max")
db["runtime_info"]["max_at"] = len("Max At")
db["runtime_info"]["min"] = len("Min")
db["runtime_info"]["mean"] = len("Mean")
db["runtime_info"]["median"] = len("Median") if args.summary_extended:
db["inter_times"] = dict()
db["inter_times"]["out_in"] = len("Out-In")
db["inter_times"]["inter_at"] = len("At")
db["inter_times"]["out_out"] = len("Out-Out")
db["inter_times"]["in_in"] = len("In-In")
db["inter_times"]["in_out"] = len("In-Out")
def _median(numbers): """phython3 hat statistics module - we have nothing"""
n = len(numbers)
index = n // 2 if n % 2: return sorted(numbers)[index] return sum(sorted(numbers)[index - 1 : index + 1]) / 2
class Timespans(object): """
The elapsed time between two occurrences of the same task is being tracked with the
help of this class. There are 4 of those Timespans Out-Out, In-Out, Out-In and
In-In.
The first half of the name signals the first time point of the
first task. The second half of the name represents the second
timepoint of the second task. """
def feed(self, task): """
Called for every recorded trace event to find process pair and calculate the
task timespans. Chronological ordering, feed does not do reordering """ ifnot self._last_finish:
self._last_start = task.time_in(time_unit)
self._last_finish = task.time_out(time_unit) return
self._time_in = task.time_in()
time_in = task.time_in(time_unit)
time_out = task.time_out(time_unit)
self.in_in = time_in - self._last_start
self.out_in = time_in - self._last_finish
self.in_out = time_out - self._last_start
self.out_out = time_out - self._last_finish if args.summary_extended:
self._update_max_entries()
self._last_finish = task.time_out(time_unit)
self._last_start = task.time_in(time_unit)
def _update_max_entries(self): if self.in_in > self.max_in_in:
self.max_in_in = self.in_in if self.out_out > self.max_out_out:
self.max_out_out = self.out_out if self.in_out > self.max_in_out:
self.max_in_out = self.in_out if self.out_in > self.max_out_in:
self.max_out_in = self.out_in
self.max_at = self._time_in
class Summary(object): """
Primary instance for calculating the summary output. Processes the whole trace to
find and memorize relevant data such as mean, max et cetera. This instance handles
dynamic alignment aspects for summary output. """
def __init__(self):
self._body = []
class AlignmentHelper: """
Used to calculated the alignment for the output of the summary. """ def __init__(self, pid, tid, comm, runs, acc, mean,
median, min, max, max_at):
self.pid = pid
self.tid = tid
self.comm = comm
self.runs = runs
self.acc = acc
self.mean = mean
self.median = median
self.min = min
self.max = max
self.max_at = max_at if args.summary_extended:
self.out_in = None
self.inter_at = None
self.out_out = None
self.in_in = None
self.in_out = None
def _print_header(self): '''
Output is trimmed in _format_stats thus additional adjustment in the header is needed, depending on the choice of timeunit. The adjustment corresponds
to the amount of column titles being adjusted in _column_titles. '''
decimal_precision = 6 ifnot args.ns else 9
fmt = " {{:^{}}}".format(sum(db["task_info"].values()))
fmt += " {{:^{}}}".format(
sum(db["runtime_info"].values()) - 2 * decimal_precision
)
_header = ("Task Information", "Runtime Information")
def _column_titles(self): """
Cells are being processed and displayed in different way so an alignment adjust is implemented depeding on the choice of the timeunit. The positions of the max
values are being displayed in grey. Thus in their format two additional {},
are placed for color set and reset. """
separator, fix_csv_align = _prepare_fmt_sep()
decimal_precision, time_precision = _prepare_fmt_precision()
fmt = "{{:>{}}}".format(db["task_info"]["pid"] * fix_csv_align)
fmt += "{}{{:>{}}}".format(separator, db["task_info"]["tid"] * fix_csv_align)
fmt += "{}{{:>{}}}".format(separator, db["task_info"]["comm"] * fix_csv_align)
fmt += "{}{{:>{}}}".format(separator, db["runtime_info"]["runs"] * fix_csv_align)
fmt += "{}{{:>{}}}".format(separator, db["runtime_info"]["acc"] * fix_csv_align)
fmt += "{}{{:>{}}}".format(separator, db["runtime_info"]["mean"] * fix_csv_align)
fmt += "{}{{:>{}}}".format(
separator, db["runtime_info"]["median"] * fix_csv_align
)
fmt += "{}{{:>{}}}".format(
separator, (db["runtime_info"]["min"] - decimal_precision) * fix_csv_align
)
fmt += "{}{{:>{}}}".format(
separator, (db["runtime_info"]["max"] - decimal_precision) * fix_csv_align
)
fmt += "{}{{}}{{:>{}}}{{}}".format(
separator, (db["runtime_info"]["max_at"] - time_precision) * fix_csv_align
)
def _task_stats(self): """calculates the stats of every task and constructs the printable summary""" for tid in sorted(db["tid"]):
color_one_sample = _COLORS["grey"]
color_reset = _COLORS["reset"]
no_executed = 0
runtimes = []
time_in = []
timespans = Timespans() for task in db["tid"][tid]:
pid = task.pid
comm = task.comm
no_executed += 1
runtimes.append(task.runtime(time_unit))
time_in.append(task.time_in())
timespans.feed(task) if len(runtimes) > 1:
color_one_sample = ""
color_reset = ""
time_max = max(runtimes)
time_min = min(runtimes)
max_at = time_in[runtimes.index(max(runtimes))]
# The size of the decimal after sum,mean and median varies, thus we cut # the decimal number, by rounding it. It has no impact on the output, # because we have a precision of the decimal points at the output.
time_sum = round(sum(runtimes), 3)
time_mean = round(_mean(runtimes), 3)
time_median = round(_median(runtimes), 3)
def _calc_alignments_summary(self, align_helper): # Length is being cut in 3 groups so that further addition is easier to handle. # The length of every argument from the alignment helper is being checked if it # is longer than the longest until now. In that case the length is being saved. for key in db["task_info"]: if len(str(getattr(align_helper, key))) > db["task_info"][key]:
db["task_info"][key] = len(str(getattr(align_helper, key))) for key in db["runtime_info"]: if len(str(getattr(align_helper, key))) > db["runtime_info"][key]:
db["runtime_info"][key] = len(str(getattr(align_helper, key))) if args.summary_extended: for key in db["inter_times"]: if len(str(getattr(align_helper, key))) > db["inter_times"][key]:
db["inter_times"][key] = len(str(getattr(align_helper, key)))
ifnot args.csv_summary:
print("\nSummary")
self._print_header()
self._column_titles() for i in range(len(self._body)):
fd_sum.write(fmt.format(*tuple(self._body[i])) + "\n")
class Task(object): """ The class is used to handle the information of a given task."""
def __init__(self, id, tid, cpu, comm):
self.id = id
self.tid = tid
self.cpu = cpu
self.comm = comm
self.pid = None
self._time_in = None
self._time_out = None
def schedule_in_at(self, time): """set the time where the task was scheduled in"""
self._time_in = time
def schedule_out_at(self, time): """set the time where the task was scheduled out"""
self._time_out = time
def time_out(self, unit="s"): """return time where a given task was scheduled out"""
factor = time_uniter(unit) return self._time_out * decimal.Decimal(factor)
def time_in(self, unit="s"): """return time where a given task was scheduled in"""
factor = time_uniter(unit) return self._time_in * decimal.Decimal(factor)
def _print_task_finish(task): """calculating every entry of a row and printing it immediately"""
c_row_set = ""
c_row_reset = ""
out_in = -1
out_out = -1
in_in = -1
in_out = -1
fmt = _fmt_body() # depending on user provided highlight option we change the color # for particular tasks if str(task.tid) in args.highlight_tasks_map:
c_row_set = _COLORS[args.highlight_tasks_map[str(task.tid)]]
c_row_reset = _COLORS["reset"] if task.comm in args.highlight_tasks_map:
c_row_set = _COLORS[args.highlight_tasks_map[task.comm]]
c_row_reset = _COLORS["reset"] # grey-out entries if PID == TID, they # are identical, no threaded model so the # thread id (tid) do not matter
c_tid_set = ""
c_tid_reset = "" if task.pid == task.tid:
c_tid_set = _COLORS["grey"]
c_tid_reset = _COLORS["reset"] if task.tid in db["tid"]: # get last task of tid
last_tid_task = db["tid"][task.tid][-1] # feed the timespan calculate, last in tid db # and second the current one
timespan_gap_tid = Timespans()
timespan_gap_tid.feed(last_tid_task)
timespan_gap_tid.feed(task)
out_in = timespan_gap_tid.out_in
out_out = timespan_gap_tid.out_out
in_in = timespan_gap_tid.in_in
in_out = timespan_gap_tid.in_out
def _record_cleanup(_list): """
no need to store more then one element if --summarize isnot enabled """ ifnot args.summary and len(_list) > 1:
_list = _list[len(_list) - 1 :]
def _record_by_tid(task):
tid = task.tid if tid notin db["tid"]:
db["tid"][tid] = []
db["tid"][tid].append(task)
_record_cleanup(db["tid"][tid])
def _record_by_cpu(task):
cpu = task.cpu if cpu notin db["cpu"]:
db["cpu"][cpu] = []
db["cpu"][cpu].append(task)
_record_cleanup(db["cpu"][cpu])
def _record_global(task): """record all executed task, ordered by finish chronological"""
db["global"].append(task)
_record_cleanup(db["global"])
def _handle_task_finish(tid, cpu, time, perf_sample_dict): if tid == 0: return
_id = _task_id(tid, cpu) if _id notin db["running"]: # may happen, if we missed the switch to # event. Seen in combination with --exclude-perf # where the start is filtered out, but not the # switched in. Probably a bug in exclude-perf # option. return
task = db["running"][_id]
task.schedule_out_at(time)
# record tid, during schedule in the tid # is not available, update now
pid = int(perf_sample_dict["sample"]["pid"])
task.update_pid(pid) del db["running"][_id]
# print only tasks which are not being filtered and no print of trace # for summary only, but record every task. ifnot _limit_filtered(tid, pid, task.comm) andnot args.summary_only:
_print_task_finish(task)
_record_by_tid(task)
_record_by_cpu(task)
_record_global(task)
def _handle_task_start(tid, cpu, comm, time): if tid == 0: return if tid in args.tid_renames:
comm = args.tid_renames[tid]
_id = _task_id(tid, cpu) if _id in db["running"]: # handle corner cases where already running tasks # are switched-to again - saw this via --exclude-perf # recorded traces. We simple ignore this "second start" # event. return assert _id notin db["running"]
task = Task(_id, tid, cpu, comm)
task.schedule_in_at(time)
db["running"][_id] = task
def _time_to_internal(time_ns): """
To prevent float rounding errors we use Decimal internally """ return decimal.Decimal(time_ns) / decimal.Decimal(1e9)
def _limit_filtered(tid, pid, comm): if args.filter_tasks: if str(tid) in args.filter_tasks or comm in args.filter_tasks: returnTrue else: returnFalse if args.limit_to_tasks: if str(tid) in args.limit_to_tasks or comm in args.limit_to_tasks: returnFalse else: returnTrue
def _argument_filter_sanity_check(): if args.limit_to_tasks and args.filter_tasks:
sys.exit("Error: Filter and Limit at the same time active.") if args.extended_times and args.summary_only:
sys.exit("Error: Summary only and extended times active.") if args.time_limit and":"notin args.time_limit:
sys.exit( "Error: No bound set for time limit. Please set bound by ':' e.g :123."
) if args.time_limit and (args.summary or args.summary_only or args.summary_extended):
sys.exit("Error: Cannot set time limit and print summary") if args.csv_summary:
args.summary = True if args.csv == args.csv_summary:
sys.exit("Error: Chosen files for csv and csv summary are the same") if args.csv and (args.summary_extended or args.summary) andnot args.csv_summary:
sys.exit("Error: No file chosen to write summary to. Choose with --csv-summary " "") if args.csv and args.summary_only:
sys.exit("Error: --csv chosen and --summary-only. Standard task would not be" "written to csv file.")
def _argument_prepare_check(): global time_unit, fd_task, fd_sum if args.filter_tasks:
args.filter_tasks = args.filter_tasks.split(",") if args.limit_to_tasks:
args.limit_to_tasks = args.limit_to_tasks.split(",") if args.time_limit:
args.time_limit = args.time_limit.split(":") for rename_tuple in args.rename_comms_by_tids.split(","):
tid_name = rename_tuple.split(":") if len(tid_name) != 2: continue
args.tid_renames[int(tid_name[0])] = tid_name[1]
args.highlight_tasks_map = dict() for highlight_tasks_tuple in args.highlight_tasks.split(","):
tasks_color_map = highlight_tasks_tuple.split(":") # default highlight color to red if no color set by user if len(tasks_color_map) == 1:
tasks_color_map.append("red") if args.highlight_tasks and tasks_color_map[1].lower() notin _COLORS:
sys.exit( "Error: Color not defined, please choose from grey,red,green,yellow,blue," "violet"
) if len(tasks_color_map) != 2: continue
args.highlight_tasks_map[tasks_color_map[0]] = tasks_color_map[1]
time_unit = "us" if args.ns:
time_unit = "ns" elif args.ms:
time_unit = "ms"
def _is_within_timelimit(time): """
Check if a time limit was given by parameter, if so ignore the rest. Ifnot,
process the recorded trace in its entirety. """ ifnot args.time_limit: returnTrue
lower_time_limit = args.time_limit[0]
upper_time_limit = args.time_limit[1] # check for upper limit if upper_time_limit == "": if time >= decimal.Decimal(lower_time_limit): returnTrue # check for lower limit if lower_time_limit == "": if time <= decimal.Decimal(upper_time_limit): returnTrue # quit if time exceeds upper limit. Good for big datasets else:
quit() if lower_time_limit != ""and upper_time_limit != "": if (time >= decimal.Decimal(lower_time_limit) and
time <= decimal.Decimal(upper_time_limit)): returnTrue # quit if time exceeds upper limit. Good for big datasets elif time > decimal.Decimal(upper_time_limit):
quit()
def trace_end(): if args.summary or args.summary_extended or args.summary_only:
Summary().print()
def sched__sched_switch(event_name, context, common_cpu, common_secs, common_nsecs,
common_pid, common_comm, common_callchain, prev_comm,
prev_pid, prev_prio, prev_state, next_comm, next_pid,
next_prio, perf_sample_dict): # ignore common_secs & common_nsecs cause we need # high res timestamp anyway, using the raw value is # faster
time = _time_to_internal(perf_sample_dict["sample"]["time"]) ifnot _is_within_timelimit(time): # user specific --time-limit a:b set return
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