brief-extractor/backend/venv/lib/python3.10/site-packages/mprof.py
2026-03-06 18:42:46 +00:00

936 lines
34 KiB
Python
Executable file

import glob
import os
import os.path as osp
import sys
import re
import copy
import time
import math
import logging
import itertools
from ast import literal_eval
from collections import defaultdict
from argparse import ArgumentParser, ArgumentError, REMAINDER, RawTextHelpFormatter
import importlib
import memory_profiler as mp
ALL_ACTIONS = ("run", "rm", "clean", "list", "plot", "attach", "peak")
help_msg = """
Available commands:
run run a given command or python file
attach alias for 'run --attach': attach to an existing process by pid or name
rm remove a given file generated by mprof
clean clean the current directory from files created by mprof
list display existing profiles, with indices
plot plot memory consumption generated by mprof run
peak print the maximum memory used by an mprof run
Type mprof <command> --help for usage help on a specific command.
For example, mprof plot --help will list all plotting options.
"""
logger = logging.getLogger(__name__)
logging.basicConfig()
def print_usage():
print("Usage: %s <command> <options> <arguments>"
% osp.basename(sys.argv[0]))
print(help_msg)
def get_action():
"""Pop first argument, check it is a valid action."""
if len(sys.argv) <= 1:
print_usage()
sys.exit(1)
if not sys.argv[1] in ALL_ACTIONS:
print_usage()
sys.exit(1)
return sys.argv.pop(1)
def get_profile_filenames(args):
"""Return list of profile filenames.
Parameters
==========
args (list)
list of filename or integer. An integer is the index of the
profile in the list of existing profiles. 0 is the oldest,
-1 in the more recent.
Non-existing files cause a ValueError exception to be thrown.
Returns
=======
filenames (list)
list of existing memory profile filenames. It is guaranteed
that an given file name will not appear twice in this list.
"""
profiles = glob.glob("mprofile_??????????????.dat")
profiles.sort()
if args == "all":
filenames = copy.copy(profiles)
else:
filenames = []
for arg in args:
if arg == "--": # workaround
continue
try:
index = int(arg)
except ValueError:
index = None
if index is not None:
try:
filename = profiles[index]
except IndexError:
raise ValueError("Invalid index (non-existing file): %s" % arg)
if filename not in filenames:
filenames.append(filename)
else:
if osp.isfile(arg):
if arg not in filenames:
filenames.append(arg)
elif osp.isdir(arg):
raise ValueError("Path %s is a directory" % arg)
else:
raise ValueError("File %s not found" % arg)
# Add timestamp files, if any
for filename in reversed(filenames):
parts = osp.splitext(filename)
timestamp_file = parts[0] + "_ts" + parts[1]
if osp.isfile(timestamp_file) and timestamp_file not in filenames:
filenames.append(timestamp_file)
return filenames
def list_action():
"""Display existing profiles, with indices."""
parser = ArgumentParser(
usage='mprof list\nThis command takes no argument.')
parser.add_argument('--version', action='version', version=mp.__version__)
args = parser.parse_args()
filenames = get_profile_filenames("all")
for n, filename in enumerate(filenames):
ts = osp.splitext(filename)[0].split('_')[-1]
print("{index} {filename} {hour}:{min}:{sec} {day}/{month}/{year}"
.format(index=n, filename=filename,
year=ts[:4], month=ts[4:6], day=ts[6:8],
hour=ts[8:10], min=ts[10:12], sec=ts[12:14]))
def rm_action():
"""TODO: merge with clean_action (@pgervais)"""
parser = ArgumentParser(usage='mprof rm [options] numbers_or_filenames')
parser.add_argument('--version', action='version', version=mp.__version__)
parser.add_argument("--dry-run", dest="dry_run", default=False,
action="store_true",
help="""Show what will be done, without actually doing it.""")
parser.add_argument("numbers_or_filenames", nargs='*',
help="""numbers or filenames removed""")
args = parser.parse_args()
if len(args.numbers_or_filenames) == 0:
print("A profile to remove must be provided (number or filename)")
sys.exit(1)
filenames = get_profile_filenames(args.numbers_or_filenames)
if args.dry_run:
print("Files to be removed: ")
for filename in filenames:
print(filename)
else:
for filename in filenames:
os.remove(filename)
def clean_action():
"""Remove every profile file in current directory."""
parser = ArgumentParser(
usage='mprof clean\nThis command takes no argument.')
parser.add_argument('--version', action='version', version=mp.__version__)
parser.add_argument("--dry-run", dest="dry_run", default=False,
action="store_true",
help="""Show what will be done, without actually doing it.""")
args = parser.parse_args()
filenames = get_profile_filenames("all")
if args.dry_run:
print("Files to be removed: ")
for filename in filenames:
print(filename)
else:
for filename in filenames:
os.remove(filename)
def get_cmd_line(args):
"""Given a set or arguments, compute command-line."""
blanks = set(' \t')
args = [s if blanks.isdisjoint(s) else "'" + s + "'" for s in args]
return ' '.join(args)
def find_first_process(name):
for i in mp.psutil.process_iter():
if name in i.name():
return i
return None
def attach_action():
argv = sys.argv
sys.argv = argv[:1] + ['--attach'] + argv[1:]
run_action()
def run_action():
import time, subprocess
parser = ArgumentParser(usage="mprof run [options] program", formatter_class=RawTextHelpFormatter)
parser.add_argument('--version', action='version', version=mp.__version__)
parser.add_argument("--python", dest="python", action="store_true",
help="""Activates extra features when the profiling executable is a Python program (currently: function timestamping.)""")
parser.add_argument("--nopython", dest="nopython", action="store_true",
help="""Disables extra features when the profiled executable is a Python program (currently: function timestamping.)""")
parser.add_argument("--interval", "-T", dest="interval", default="0.1", type=float, action="store",
help="Sampling period (in seconds), defaults to 0.1")
parser.add_argument("--include-children", "-C", dest="include_children", action="store_true",
help="""Monitors forked processes as well (sum up all process memory)""")
parser.add_argument("--multiprocess", "-M", dest="multiprocess", action="store_true",
help="""Monitors forked processes creating individual plots for each child (disables --python features)""")
parser.add_argument("--exit-code", "-E", dest="exit_code", action="store_true", help="""Propagate the exit code""")
attach_arg = parser.add_argument("--attach", "-a", dest="attach_existing", action="store_true",
help="Attach to an existing process, by process name or by pid")
parser.add_argument("--timeout", "-t", dest="timeout", action="store", type=int,
help="timeout in seconds for the profiling, default new process has no timeout, attach existing is 1 hour")
parser.add_argument("--output", "-o", dest="filename",
default="mprofile_%s.dat" % time.strftime("%Y%m%d%H%M%S", time.localtime()),
help="""File to store results in, defaults to 'mprofile_<YYYYMMDDhhmmss>.dat' in the current directory,
(where <YYYYMMDDhhmmss> is the date-time of the program start).
This file contains the process memory consumption, in Mb (one value per line).""")
parser.add_argument("--backend", dest="backend", choices=["psutil", "psutil_pss", "psutil_uss", "posix", "tracemalloc"],
default="psutil",
help="Current supported backends: 'psutil', 'psutil_pss', 'psutil_uss', 'posix', 'tracemalloc'. Defaults to 'psutil'.")
parser.add_argument("program", nargs=REMAINDER,
help='Option 1: "<EXECUTABLE> <ARG1> <ARG2>..." - profile executable\n'
'Option 2: "<PYTHON_SCRIPT> <ARG1> <ARG2>..." - profile python script\n'
'Option 3: (--python flag present) "<PYTHON_EXECUTABLE> <PYTHON_SCRIPT> <ARG1> <ARG2>..." - profile python script with specified interpreter\n'
'Option 4: (--python flag present) "<PYTHON_MODULE> <ARG1> <ARG2>..." - profile python module\n'
)
args = parser.parse_args()
if len(args.program) == 0:
print("A program to run must be provided. Use -h for help")
sys.exit(1)
print("{1}: Sampling memory every {0}s".format(
args.interval, osp.basename(sys.argv[0])))
mprofile_output = args.filename
program = args.program
if args.attach_existing:
print('attaching to existing process, using hint: {}'.format(program[0]))
if program[0].isdigit():
p = literal_eval(program[0])
cmd_line = get_cmd_line(program)
else:
proc = find_first_process(program[0])
if proc is None:
raise ArgumentError(attach_arg, '\nWhen attaching, program should be process name or pid.\nFailed to find a process using hint: {}'.format(program[0]))
p = proc.pid
try:
cmd_line = proc.cmdline()
except:
cmd_line = get_cmd_line(program)
if args.timeout is None:
args.timeout = 3600
else:
print('running new process')
# .. TODO: more than one script as argument ? ..
if program[0].endswith('.py') and not args.nopython:
if args.multiprocess:
# in multiprocessing mode you want to spawn a separate
# python process
if not program[0].startswith("python"):
program.insert(0, sys.executable)
args.python = False
else:
args.python = True
if args.python:
print("running as a Python program...")
if not program[0].startswith("python"):
program.insert(0, sys.executable)
cmd_line = get_cmd_line(program)
extra_args = ["-m", "memory_profiler", "--timestamp", "-o", mprofile_output]
if args.include_children:
extra_args.append("--include-children")
program[1:1] = extra_args
p = subprocess.Popen(program)
else:
cmd_line = get_cmd_line(program)
p = subprocess.Popen(program)
with open(mprofile_output, "a") as f:
f.write("CMDLINE {0}\n".format(cmd_line))
mp.memory_usage(proc=p, interval=args.interval, timeout=args.timeout, timestamps=True,
include_children=args.include_children,
multiprocess=args.multiprocess, stream=f, backend=args.backend)
if args.exit_code:
if p.returncode != 0:
logger.error('Program resulted with a non-zero exit code: %s', p.returncode)
sys.exit(p.returncode)
def add_brackets(xloc, yloc, xshift=0, color="r", label=None, options=None):
"""Add two brackets on the memory line plot.
This function uses the current figure.
Parameters
==========
xloc: tuple with 2 values
brackets location (on horizontal axis).
yloc: tuple with 2 values
brackets location (on vertical axis)
xshift: float
value to subtract to xloc.
"""
try:
import pylab as pl
except ImportError as e:
print("matplotlib is needed for plotting.")
print(e)
sys.exit(1)
height_ratio = 20.
vsize = (pl.ylim()[1] - pl.ylim()[0]) / height_ratio
hsize = (pl.xlim()[1] - pl.xlim()[0]) / (3. * height_ratio)
bracket_x = pl.asarray([hsize, 0, 0, hsize])
bracket_y = pl.asarray([vsize, vsize, -vsize, -vsize])
# Matplotlib workaround: labels starting with _ aren't displayed
if label[0] == '_':
label = ' ' + label
if options.xlim is None or options.xlim[0] <= (xloc[0] - xshift) <= options.xlim[1]:
pl.plot(bracket_x + xloc[0] - xshift, bracket_y + yloc[0],
"-" + color, linewidth=2, label=label)
if options.xlim is None or options.xlim[0] <= (xloc[1] - xshift) <= options.xlim[1]:
pl.plot(-bracket_x + xloc[1] - xshift, bracket_y + yloc[1],
"-" + color, linewidth=2)
# TODO: use matplotlib.patches.Polygon to draw a colored background for
# each function.
# with maplotlib 1.2, use matplotlib.path.Path to create proper markers
# see http://matplotlib.org/examples/pylab_examples/marker_path.html
# This works with matplotlib 0.99.1
## pl.plot(xloc[0], yloc[0], "<"+color, markersize=7, label=label)
## pl.plot(xloc[1], yloc[1], ">"+color, markersize=7)
def read_mprofile_file(filename):
"""Read an mprofile file and return its content.
Returns
=======
content: dict
Keys:
- "mem_usage": (list) memory usage values, in MiB
- "timestamp": (list) time instant for each memory usage value, in
second
- "func_timestamp": (dict) for each function, timestamps and memory
usage upon entering and exiting.
- 'cmd_line': (str) command-line ran for this profile.
"""
func_ts = {}
mem_usage = []
timestamp = []
children = defaultdict(list)
cmd_line = None
f = open(filename, "r")
for l in f:
if l == '\n':
raise ValueError('Sampling time was too short')
field, value = l.split(' ', 1)
if field == "MEM":
# mem, timestamp
values = value.split(' ')
mem_usage.append(float(values[0]))
timestamp.append(float(values[1]))
elif field == "FUNC":
values = value.split(' ')
f_name, mem_start, start, mem_end, end = values[:5]
ts = func_ts.get(f_name, [])
to_append = [float(start), float(end), float(mem_start), float(mem_end)]
if len(values) >= 6:
# There is a stack level field
stack_level = values[5]
to_append.append(int(stack_level))
ts.append(to_append)
func_ts[f_name] = ts
elif field == "CHLD":
values = value.split(' ')
chldnum = values[0]
children[chldnum].append(
(float(values[1]), float(values[2]))
)
elif field == "CMDLINE":
cmd_line = value
else:
pass
f.close()
return {"mem_usage": mem_usage, "timestamp": timestamp,
"func_timestamp": func_ts, 'filename': filename,
'cmd_line': cmd_line, 'children': children}
def plot_file(filename, index=0, timestamps=True, children=True, options=None):
try:
import pylab as pl
except ImportError as e:
print("matplotlib is needed for plotting.")
print(e)
sys.exit(1)
import numpy as np # pylab requires numpy anyway
mprofile = read_mprofile_file(filename)
if len(mprofile['timestamp']) == 0:
print('** No memory usage values have been found in the profile '
'file.**\nFile path: {0}\n'
'File may be empty or invalid.\n'
'It can be deleted with "mprof rm {0}"'.format(
mprofile['filename']))
sys.exit(0)
# Merge function timestamps and memory usage together
ts = mprofile['func_timestamp']
t = mprofile['timestamp']
mem = mprofile['mem_usage']
chld = mprofile['children']
if len(ts) > 0:
for values in ts.values():
for v in values:
t.extend(v[:2])
mem.extend(v[2:4])
mem = np.asarray(mem)
t = np.asarray(t)
ind = t.argsort()
mem = mem[ind]
t = t[ind]
# Plot curves
global_start = float(t[0])
t = t - global_start
max_mem = mem.max()
max_mem_ind = mem.argmax()
all_colors = ("c", "y", "g", "r", "b")
mem_line_colors = ("k", "b", "r", "g", "c", "y", "m")
show_trend_slope = options is not None and hasattr(options, 'slope') and options.slope is True
mem_line_label = time.strftime("%d / %m / %Y - start at %H:%M:%S",
time.localtime(global_start)) \
+ ".{0:03d}".format(int(round(math.modf(global_start)[0] * 1000)))
mem_trend = None
if show_trend_slope:
# Compute trend line
mem_trend = np.polyfit(t, mem, 1)
# Append slope to label
mem_line_label = mem_line_label + " slope {0:.5f}".format(mem_trend[0])
pl.plot(t, mem, "+-" + mem_line_colors[index % len(mem_line_colors)],
label=mem_line_label)
if show_trend_slope:
# Plot the trend line
pl.plot(t, t*mem_trend[0] + mem_trend[1], "--", linewidth=0.5, color="#00e3d8")
bottom, top = pl.ylim()
bottom += 0.001
top -= 0.001
# plot children, if any
if len(chld) > 0 and children:
cmpoint = (0,0) # maximal child memory
for idx, (proc, data) in enumerate(chld.items()):
# Create the numpy arrays from the series data
cts = np.asarray([item[1] for item in data]) - global_start
cmem = np.asarray([item[0] for item in data])
cmem_trend = None
child_mem_trend_label = ""
if show_trend_slope:
# Compute trend line
cmem_trend = np.polyfit(cts, cmem, 1)
child_mem_trend_label = " slope {0:.5f}".format(cmem_trend[0])
# Plot the line to the figure
pl.plot(cts, cmem, "+-" + mem_line_colors[(idx + 1) % len(mem_line_colors)],
label="child {}{}".format(proc, child_mem_trend_label))
if show_trend_slope:
# Plot the trend line
pl.plot(cts, cts*cmem_trend[0] + cmem_trend[1], "--", linewidth=0.5, color="black")
# Detect the maximal child memory point
cmax_mem = cmem.max()
if cmax_mem > cmpoint[1]:
cmpoint = (cts[cmem.argmax()], cmax_mem)
# Add the marker lines for the maximal child memory usage
pl.vlines(cmpoint[0], pl.ylim()[0]+0.001, pl.ylim()[1] - 0.001, 'r', '--')
pl.hlines(cmpoint[1], pl.xlim()[0]+0.001, pl.xlim()[1] - 0.001, 'r', '--')
# plot timestamps, if any
if len(ts) > 0 and timestamps:
func_num = 0
f_labels = function_labels(ts.keys())
for f, exec_ts in ts.items():
for execution in exec_ts:
add_brackets(execution[:2], execution[2:], xshift=global_start,
color=all_colors[func_num % len(all_colors)],
label=f_labels[f]
+ " %.3fs" % (execution[1] - execution[0]), options=options)
func_num += 1
if timestamps:
pl.hlines(max_mem,
pl.xlim()[0] + 0.001, pl.xlim()[1] - 0.001,
colors="r", linestyles="--")
pl.vlines(t[max_mem_ind], bottom, top,
colors="r", linestyles="--")
return mprofile
FLAME_PLOTTER_VARS = {
'hovered_rect': None,
'hovered_text': None,
'alpha': None
}
def flame_plotter(filename, index=0, timestamps=True, children=True, options=None):
try:
import pylab as pl
except ImportError as e:
print("matplotlib is needed for plotting.")
print(e)
sys.exit(1)
import numpy as np # pylab requires numpy anyway
mprofile = read_mprofile_file(filename)
if len(mprofile['timestamp']) == 0:
print('** No memory usage values have been found in the profile '
'file.**\nFile path: {0}\n'
'File may be empty or invalid.\n'
'It can be deleted with "mprof rm {0}"'.format(
mprofile['filename']))
sys.exit(0)
# Merge function timestamps and memory usage together
ts = mprofile['func_timestamp']
t = mprofile['timestamp']
mem = mprofile['mem_usage']
chld = mprofile['children']
if len(ts) > 0:
for values in ts.values():
for v in values:
t.extend(v[:2])
mem.extend(v[2:4])
mem = np.asarray(mem)
t = np.asarray(t)
ind = t.argsort()
mem = mem[ind]
t = t[ind]
if ts:
stack_size = 1 + max(ex[4] for executions in ts.values() for ex in executions)
else:
stack_size = 0
def level_to_saturation(level):
return 1 - 0.75 * level / stack_size
colors = [
itertools.cycle([
pl.matplotlib.colors.hsv_to_rgb((0, level_to_saturation(level), 1)),
pl.matplotlib.colors.hsv_to_rgb((0.1, level_to_saturation(level), 1)),
]) for level in range(stack_size)
]
# Plot curves
global_start = float(t[0])
t = t - global_start
max_mem = mem.max()
max_mem_ind = mem.argmax()
# cmap = pl.cm.get_cmap('gist_rainbow')
mem_line_colors = ("k", "b", "r", "g", "c", "y", "m")
mem_line_label = time.strftime("%d / %m / %Y - start at %H:%M:%S",
time.localtime(global_start)) \
+ ".{0:03d}".format(int(round(math.modf(global_start)[0] * 1000)))
pl.plot(t, mem, "-" + mem_line_colors[index % len(mem_line_colors)],
label=mem_line_label)
bottom, top = pl.ylim()
bottom += 0.001
top -= 0.001
ax = pl.gca()
ax.grid(True)
timestamp_ax = ax.twinx()
timestamp_ax.set_yticks([])
timestamp_ax.set_ylim((0, stack_size + 1))
timestamp_ax.grid(False)
# plot children, if any
if len(chld) > 0 and children:
cmpoint = (0,0) # maximal child memory
for idx, (proc, data) in enumerate(chld.items()):
# Create the numpy arrays from the series data
cts = np.asarray([item[1] for item in data]) - global_start
cmem = np.asarray([item[0] for item in data])
# Plot the line to the figure
pl.plot(cts, cmem, "+-" + mem_line_colors[(idx+1) % len(mem_line_colors)],
label="child {}".format(proc))
# Detect the maximal child memory point
cmax_mem = cmem.max()
if cmax_mem > cmpoint[1]:
cmpoint = (cts[cmem.argmax()], cmax_mem)
# Add the marker lines for the maximal child memory usage
pl.vlines(cmpoint[0], pl.ylim()[0]+0.001, pl.ylim()[1] - 0.001, 'r', '--')
pl.hlines(cmpoint[1], pl.xlim()[0]+0.001, pl.xlim()[1] - 0.001, 'r', '--')
def mouse_motion_handler(event):
x, y = event.xdata, event.ydata
if x is not None and y is not None:
for coord, (name, text, rect) in rectangles.items():
x0, y0, x1, y1 = coord
if x0 < x < x1 and y0 < y < y1:
if FLAME_PLOTTER_VARS['hovered_rect'] == rect:
return
if FLAME_PLOTTER_VARS['hovered_rect'] is not None:
FLAME_PLOTTER_VARS['hovered_rect'].set_alpha(FLAME_PLOTTER_VARS['alpha'])
FLAME_PLOTTER_VARS['hovered_text'].set_color((0, 0, 0, 0))
FLAME_PLOTTER_VARS['hovered_rect'].set_linewidth(1)
FLAME_PLOTTER_VARS['hovered_text'] = text
FLAME_PLOTTER_VARS['hovered_rect'] = rect
FLAME_PLOTTER_VARS['alpha'] = rect.get_alpha()
FLAME_PLOTTER_VARS['hovered_rect'].set_alpha(0.8)
FLAME_PLOTTER_VARS['hovered_rect'].set_linewidth(3)
FLAME_PLOTTER_VARS['hovered_text'].set_color((0, 0, 0, 1))
pl.draw()
return
if FLAME_PLOTTER_VARS['hovered_rect'] is not None:
FLAME_PLOTTER_VARS['hovered_text'].set_color((0, 0, 0, 0))
FLAME_PLOTTER_VARS['hovered_rect'].set_alpha(FLAME_PLOTTER_VARS['alpha'])
FLAME_PLOTTER_VARS['hovered_rect'].set_linewidth(1)
pl.draw()
FLAME_PLOTTER_VARS['hovered_rect'] = None
FLAME_PLOTTER_VARS['hovered_text'] = None
def mouse_click_handler(event):
x, y = event.xdata, event.ydata
if x is None or y is None:
return
for coord, _ in rectangles.items():
x0, y0, x1, y1 = coord
if x0 < x < x1 and y0 < y < y1:
toolbar = pl.gcf().canvas.toolbar
toolbar.push_current()
timestamp_ax.set_xlim(x0, x1)
timestamp_ax.set_ylim(y0, stack_size + 1)
toolbar.push_current()
pl.draw()
return
# plot timestamps, if any
if len(ts) > 0 and timestamps:
func_num = 0
f_labels = function_labels(ts.keys())
rectangles = {}
for f, exec_ts in ts.items():
for execution in exec_ts:
x0, x1 = execution[:2]
y0 = execution[4]
y1 = y0 + 1
x0 -= global_start
x1 -= global_start
color = next(colors[y0])
rect, text = add_timestamp_rectangle(
timestamp_ax,
x0, x1, y0, y1, f,
color=color
)
rectangles[(x0, y0, x1, y1)] = (f, text, rect)
func_num += 1
# Disable hovering if there are too many rectangle to prevent slow down
if len(rectangles) < 100:
pl.gcf().canvas.mpl_connect('motion_notify_event', mouse_motion_handler)
pl.gcf().canvas.mpl_connect('button_release_event', mouse_click_handler)
if timestamps:
pl.hlines(max_mem,
pl.xlim()[0] + 0.001, pl.xlim()[1] - 0.001,
colors="r", linestyles="--")
pl.vlines(t[max_mem_ind], bottom, top,
colors="r", linestyles="--")
pl.sca(ax)
return mprofile
def add_timestamp_rectangle(ax, x0, x1, y0, y1, func_name, color='none'):
rect = ax.fill_betweenx((y0, y1), x0, x1, color=color, alpha=0.5, linewidth=1)
text = ax.text(x0, y1, func_name,
horizontalalignment='left',
verticalalignment='top',
color=(0, 0, 0, 0)
)
return rect, text
def function_labels(dotted_function_names):
state = {}
def set_state_for(function_names, level):
for fn in function_names:
label = ".".join(fn.split(".")[-level:])
label_state = state.setdefault(label, {"functions": [],
"level": level})
label_state["functions"].append(fn)
set_state_for(dotted_function_names, 1)
while True:
ambiguous_labels = [label for label in state if len(state[label]["functions"]) > 1]
for ambiguous_label in ambiguous_labels:
function_names = state[ambiguous_label]["functions"]
new_level = state[ambiguous_label]["level"] + 1
del state[ambiguous_label]
set_state_for(function_names, new_level)
if len(ambiguous_labels) == 0:
break
fn_to_label = dict((label_state["functions"][0] , label) for label, label_state in state.items())
return fn_to_label
def plot_action():
def xlim_type(value):
try:
newvalue = [float(x) for x in value.split(',')]
except:
raise ArgumentError("'%s' option must contain two numbers separated with a comma" % value)
if len(newvalue) != 2:
raise ArgumentError("'%s' option must contain two numbers separated with a comma" % value)
return newvalue
desc = """Plots using matplotlib the data file `file.dat` generated
using `mprof run`. If no .dat file is given, it will take the most recent
such file in the current directory."""
parser = ArgumentParser(usage="mprof plot [options] [file.dat]", description=desc)
parser.add_argument('--version', action='version', version=mp.__version__)
parser.add_argument("--title", "-t", dest="title", default=None,
type=str, action="store",
help="String shown as plot title")
parser.add_argument("--no-function-ts", "-n", dest="no_timestamps", action="store_true",
help="Do not display function timestamps on plot.")
parser.add_argument("--output", "-o",
help="Save plot to file instead of displaying it.")
parser.add_argument("--window", "-w", dest="xlim", type=xlim_type,
help="Plot a time-subset of the data. E.g. to plot between 0 and 20.5 seconds: --window 0,20.5")
parser.add_argument("--flame", "-f", dest="flame_mode", action="store_true",
help="Plot the timestamps as a flame-graph instead of the default brackets")
parser.add_argument("--slope", "-s", dest="slope", action="store_true",
help="Plot a trend line and its numerical slope")
parser.add_argument("--backend",
help="Specify the Matplotlib backend to use")
parser.add_argument("profiles", nargs="*",
help="profiles made by mprof run")
args = parser.parse_args()
try:
if args.backend is not None:
import matplotlib
matplotlib.use(args.backend)
import pylab as pl
except ImportError as e:
print("matplotlib is needed for plotting.")
print(e)
sys.exit(1)
pl.ioff()
filenames = get_profiles(args)
fig = pl.figure(figsize=(14, 6), dpi=90)
if not args.flame_mode:
ax = fig.add_axes([0.1, 0.1, 0.6, 0.75])
else:
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
if args.xlim is not None:
pl.xlim(args.xlim[0], args.xlim[1])
if len(filenames) > 1 or args.no_timestamps:
timestamps = False
else:
timestamps = True
plotter = plot_file
if args.flame_mode:
plotter = flame_plotter
for n, filename in enumerate(filenames):
mprofile = plotter(filename, index=n, timestamps=timestamps, options=args)
pl.xlabel("time (in seconds)")
pl.ylabel("memory used (in MiB)")
if args.title is None and len(filenames) == 1:
pl.title(mprofile['cmd_line'])
else:
if args.title is not None:
pl.title(args.title)
# place legend within the plot, make partially transparent in
# case it obscures part of the lineplot
if not args.flame_mode:
leg = ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
leg.get_frame().set_alpha(0.5)
pl.grid()
if args.output:
pl.savefig(args.output)
else:
pl.show()
def filter_mprofile_mem_usage_by_function(prof, func):
if func is None:
return prof["mem_usage"]
if func not in prof["func_timestamp"]:
raise ValueError(str(func) + " was not found.")
time_ranges = prof["func_timestamp"][func]
filtered_memory = []
# The check here could be improved, but it's done in this
# inefficient way to make sure we don't miss overlapping
# ranges.
for mib, ts in zip(prof["mem_usage"], prof["timestamp"]):
for rng in time_ranges:
if rng[0] <= ts <= rng[1]:
filtered_memory.append(mib)
return filtered_memory
def peak_action():
desc = """Prints the peak memory used in data file `file.dat` generated
using `mprof run`. If no .dat file is given, it will take the most recent
such file in the current directory."""
parser = ArgumentParser(usage="mprof peak [options] [file.dat]", description=desc)
parser.add_argument("profiles", nargs="*",
help="profiles made by mprof run")
parser.add_argument("--func", dest="func", default=None,
help="""Show the peak for this function. Does not support child processes.""")
args = parser.parse_args()
filenames = get_profiles(args)
for filename in filenames:
prof = read_mprofile_file(filename)
try:
mem_usage = filter_mprofile_mem_usage_by_function(prof, args.func)
except ValueError:
print("{}\tNaN MiB".format(prof["filename"]))
continue
print("{}\t{:.3f} MiB".format(prof["filename"], max(mem_usage)))
for child, values in prof["children"].items():
child_peak = max([ mem_ts[0] for mem_ts in values ])
print(" Child {}\t\t\t{:.3f} MiB".format(child, child_peak))
def get_profiles(args):
profiles = glob.glob("mprofile_??????????????.dat")
profiles.sort()
if len(args.profiles) == 0:
if len(profiles) == 0:
print("No input file found. \nThis program looks for "
"mprofile_*.dat files, generated by the "
"'mprof run' command.")
sys.exit(-1)
print("Using last profile data.")
filenames = [profiles[-1]]
else:
filenames = []
for prof in args.profiles:
if osp.exists(prof):
if not prof in filenames:
filenames.append(prof)
else:
try:
n = int(prof)
if not profiles[n] in filenames:
filenames.append(profiles[n])
except ValueError:
print("Input file not found: " + prof)
if not len(filenames):
print("No files found from given input.")
sys.exit(-1)
return filenames
def main():
# Workaround for optparse limitation: insert -- before first negative
# number found.
negint = re.compile("-[0-9]+")
for n, arg in enumerate(sys.argv):
if negint.match(arg):
sys.argv.insert(n, "--")
break
actions = {"rm": rm_action,
"clean": clean_action,
"list": list_action,
"run": run_action,
"attach": attach_action,
"plot": plot_action,
"peak": peak_action}
actions[get_action()]()
if __name__ == "__main__":
main()