Python 3.4 termasuk modul baru: tracemalloc. Ini memberikan statistik terperinci tentang kode mana yang mengalokasikan sebagian besar memori. Berikut adalah contoh yang menampilkan tiga baris teratas mengalokasikan memori.
from collections import Counter
import linecache
import os
import tracemalloc
def display_top(snapshot, key_type='lineno', limit=3):
snapshot = snapshot.filter_traces((
tracemalloc.Filter(False, "<frozen importlib._bootstrap>"),
tracemalloc.Filter(False, "<unknown>"),
))
top_stats = snapshot.statistics(key_type)
print("Top %s lines" % limit)
for index, stat in enumerate(top_stats[:limit], 1):
frame = stat.traceback[0]
# replace "/path/to/module/file.py" with "module/file.py"
filename = os.sep.join(frame.filename.split(os.sep)[-2:])
print("#%s: %s:%s: %.1f KiB"
% (index, filename, frame.lineno, stat.size / 1024))
line = linecache.getline(frame.filename, frame.lineno).strip()
if line:
print(' %s' % line)
other = top_stats[limit:]
if other:
size = sum(stat.size for stat in other)
print("%s other: %.1f KiB" % (len(other), size / 1024))
total = sum(stat.size for stat in top_stats)
print("Total allocated size: %.1f KiB" % (total / 1024))
tracemalloc.start()
counts = Counter()
fname = '/usr/share/dict/american-english'
with open(fname) as words:
words = list(words)
for word in words:
prefix = word[:3]
counts[prefix] += 1
print('Top prefixes:', counts.most_common(3))
snapshot = tracemalloc.take_snapshot()
display_top(snapshot)
Dan inilah hasilnya:
Top prefixes: [('con', 1220), ('dis', 1002), ('pro', 809)]
Top 3 lines
#1: scratches/memory_test.py:37: 6527.1 KiB
words = list(words)
#2: scratches/memory_test.py:39: 247.7 KiB
prefix = word[:3]
#3: scratches/memory_test.py:40: 193.0 KiB
counts[prefix] += 1
4 other: 4.3 KiB
Total allocated size: 6972.1 KiB
Kapan kebocoran memori bukan kebocoran?
Contoh itu bagus ketika memori masih ditahan di akhir perhitungan, tetapi kadang-kadang Anda memiliki kode yang mengalokasikan banyak memori dan kemudian melepaskan semuanya. Secara teknis ini bukan kebocoran memori, tetapi menggunakan lebih banyak memori dari yang Anda kira seharusnya. Bagaimana Anda bisa melacak penggunaan memori ketika semuanya dilepaskan? Jika ini kode Anda, Anda mungkin dapat menambahkan beberapa kode debug untuk mengambil snapshot saat sedang berjalan. Jika tidak, Anda dapat memulai utas latar belakang untuk memantau penggunaan memori saat utas utama berjalan.
Inilah contoh sebelumnya di mana kode semuanya telah dipindahkan ke count_prefixes()fungsi. Ketika fungsi itu kembali, semua memori dilepaskan. Saya juga menambahkan beberapa sleep()panggilan untuk mensimulasikan perhitungan yang sudah berjalan lama.
from collections import Counter
import linecache
import os
import tracemalloc
from time import sleep
def count_prefixes():
sleep(2) # Start up time.
counts = Counter()
fname = '/usr/share/dict/american-english'
with open(fname) as words:
words = list(words)
for word in words:
prefix = word[:3]
counts[prefix] += 1
sleep(0.0001)
most_common = counts.most_common(3)
sleep(3) # Shut down time.
return most_common
def main():
tracemalloc.start()
most_common = count_prefixes()
print('Top prefixes:', most_common)
snapshot = tracemalloc.take_snapshot()
display_top(snapshot)
def display_top(snapshot, key_type='lineno', limit=3):
snapshot = snapshot.filter_traces((
tracemalloc.Filter(False, "<frozen importlib._bootstrap>"),
tracemalloc.Filter(False, "<unknown>"),
))
top_stats = snapshot.statistics(key_type)
print("Top %s lines" % limit)
for index, stat in enumerate(top_stats[:limit], 1):
frame = stat.traceback[0]
# replace "/path/to/module/file.py" with "module/file.py"
filename = os.sep.join(frame.filename.split(os.sep)[-2:])
print("#%s: %s:%s: %.1f KiB"
% (index, filename, frame.lineno, stat.size / 1024))
line = linecache.getline(frame.filename, frame.lineno).strip()
if line:
print(' %s' % line)
other = top_stats[limit:]
if other:
size = sum(stat.size for stat in other)
print("%s other: %.1f KiB" % (len(other), size / 1024))
total = sum(stat.size for stat in top_stats)
print("Total allocated size: %.1f KiB" % (total / 1024))
main()
Ketika saya menjalankan versi itu, penggunaan memori telah dari 6MB ke 4KB, karena fungsi ini melepaskan semua memorinya ketika selesai.
Top prefixes: [('con', 1220), ('dis', 1002), ('pro', 809)]
Top 3 lines
#1: collections/__init__.py:537: 0.7 KiB
self.update(*args, **kwds)
#2: collections/__init__.py:555: 0.6 KiB
return _heapq.nlargest(n, self.items(), key=_itemgetter(1))
#3: python3.6/heapq.py:569: 0.5 KiB
result = [(key(elem), i, elem) for i, elem in zip(range(0, -n, -1), it)]
10 other: 2.2 KiB
Total allocated size: 4.0 KiB
Sekarang inilah versi yang terinspirasi oleh jawaban lain yang memulai utas kedua untuk memantau penggunaan memori.
from collections import Counter
import linecache
import os
import tracemalloc
from datetime import datetime
from queue import Queue, Empty
from resource import getrusage, RUSAGE_SELF
from threading import Thread
from time import sleep
def memory_monitor(command_queue: Queue, poll_interval=1):
tracemalloc.start()
old_max = 0
snapshot = None
while True:
try:
command_queue.get(timeout=poll_interval)
if snapshot is not None:
print(datetime.now())
display_top(snapshot)
return
except Empty:
max_rss = getrusage(RUSAGE_SELF).ru_maxrss
if max_rss > old_max:
old_max = max_rss
snapshot = tracemalloc.take_snapshot()
print(datetime.now(), 'max RSS', max_rss)
def count_prefixes():
sleep(2) # Start up time.
counts = Counter()
fname = '/usr/share/dict/american-english'
with open(fname) as words:
words = list(words)
for word in words:
prefix = word[:3]
counts[prefix] += 1
sleep(0.0001)
most_common = counts.most_common(3)
sleep(3) # Shut down time.
return most_common
def main():
queue = Queue()
poll_interval = 0.1
monitor_thread = Thread(target=memory_monitor, args=(queue, poll_interval))
monitor_thread.start()
try:
most_common = count_prefixes()
print('Top prefixes:', most_common)
finally:
queue.put('stop')
monitor_thread.join()
def display_top(snapshot, key_type='lineno', limit=3):
snapshot = snapshot.filter_traces((
tracemalloc.Filter(False, "<frozen importlib._bootstrap>"),
tracemalloc.Filter(False, "<unknown>"),
))
top_stats = snapshot.statistics(key_type)
print("Top %s lines" % limit)
for index, stat in enumerate(top_stats[:limit], 1):
frame = stat.traceback[0]
# replace "/path/to/module/file.py" with "module/file.py"
filename = os.sep.join(frame.filename.split(os.sep)[-2:])
print("#%s: %s:%s: %.1f KiB"
% (index, filename, frame.lineno, stat.size / 1024))
line = linecache.getline(frame.filename, frame.lineno).strip()
if line:
print(' %s' % line)
other = top_stats[limit:]
if other:
size = sum(stat.size for stat in other)
print("%s other: %.1f KiB" % (len(other), size / 1024))
total = sum(stat.size for stat in top_stats)
print("Total allocated size: %.1f KiB" % (total / 1024))
main()
The resourceModul memungkinkan Anda memeriksa penggunaan memori saat ini, dan menyimpan snapshot dari penggunaan memori puncak. Antrian memungkinkan utas utama memberitahu utas monitor memori kapan harus mencetak laporannya dan dimatikan. Saat dijalankan, ini menunjukkan memori yang digunakan oleh list()panggilan:
2018-05-29 10:34:34.441334 max RSS 10188
2018-05-29 10:34:36.475707 max RSS 23588
2018-05-29 10:34:36.616524 max RSS 38104
2018-05-29 10:34:36.772978 max RSS 45924
2018-05-29 10:34:36.929688 max RSS 46824
2018-05-29 10:34:37.087554 max RSS 46852
Top prefixes: [('con', 1220), ('dis', 1002), ('pro', 809)]
2018-05-29 10:34:56.281262
Top 3 lines
#1: scratches/scratch.py:36: 6527.0 KiB
words = list(words)
#2: scratches/scratch.py:38: 16.4 KiB
prefix = word[:3]
#3: scratches/scratch.py:39: 10.1 KiB
counts[prefix] += 1
19 other: 10.8 KiB
Total allocated size: 6564.3 KiB
Jika Anda menggunakan Linux, Anda mungkin menemukan /proc/self/statmlebih berguna daripada resourcemodul.