"tracemalloc" --- 跟踪内存分配
******************************

3.4 版新加入.

**原始碼：**Lib/tracemalloc.py

======================================================================

tracemalloc 模块是一个用于对 python 已申请的内存块进行debug的工具。它
能提供以下信息:

* 回溯对象分配内存的位置

* 按文件、按行统计python的内存块分配情况: 内存块总大小、数量以及块平均
  大小。

* 对比两个内存快照的差异，以便排查内存泄漏

To trace most memory blocks allocated by Python, the module should be
started as early as possible by setting the "PYTHONTRACEMALLOC"
environment variable to "1", or by using "-X" "tracemalloc" command
line option. The "tracemalloc.start()" function can be called at
runtime to start tracing Python memory allocations.

By default, a trace of an allocated memory block only stores the most
recent frame (1 frame). To store 25 frames at startup: set the
"PYTHONTRACEMALLOC" environment variable to "25", or use the "-X"
"tracemalloc=25" command line option.


範例
====


显示前10项
----------

显示内存分配最多的10个文件：

   import tracemalloc

   tracemalloc.start()

   # ... run your application ...

   snapshot = tracemalloc.take_snapshot()
   top_stats = snapshot.statistics('lineno')

   print("[ Top 10 ]")
   for stat in top_stats[:10]:
       print(stat)

Python测试套件的输出示例：

   [ Top 10 ]
   <frozen importlib._bootstrap>:716: size=4855 KiB, count=39328, average=126 B
   <frozen importlib._bootstrap>:284: size=521 KiB, count=3199, average=167 B
   /usr/lib/python3.4/collections/__init__.py:368: size=244 KiB, count=2315, average=108 B
   /usr/lib/python3.4/unittest/case.py:381: size=185 KiB, count=779, average=243 B
   /usr/lib/python3.4/unittest/case.py:402: size=154 KiB, count=378, average=416 B
   /usr/lib/python3.4/abc.py:133: size=88.7 KiB, count=347, average=262 B
   <frozen importlib._bootstrap>:1446: size=70.4 KiB, count=911, average=79 B
   <frozen importlib._bootstrap>:1454: size=52.0 KiB, count=25, average=2131 B
   <string>:5: size=49.7 KiB, count=148, average=344 B
   /usr/lib/python3.4/sysconfig.py:411: size=48.0 KiB, count=1, average=48.0 KiB

We can see that Python loaded "4855 KiB" data (bytecode and constants)
from modules and that the "collections" module allocated "244 KiB" to
build "namedtuple" types.

更多選項請見 "Snapshot.statistics()"。


计算差异
--------

获取两个快照并显示差异：

   import tracemalloc
   tracemalloc.start()
   # ... start your application ...

   snapshot1 = tracemalloc.take_snapshot()
   # ... call the function leaking memory ...
   snapshot2 = tracemalloc.take_snapshot()

   top_stats = snapshot2.compare_to(snapshot1, 'lineno')

   print("[ Top 10 differences ]")
   for stat in top_stats[:10]:
       print(stat)

Example of output before/after running some tests of the Python test
suite:

   [ Top 10 differences ]
   <frozen importlib._bootstrap>:716: size=8173 KiB (+4428 KiB), count=71332 (+39369), average=117 B
   /usr/lib/python3.4/linecache.py:127: size=940 KiB (+940 KiB), count=8106 (+8106), average=119 B
   /usr/lib/python3.4/unittest/case.py:571: size=298 KiB (+298 KiB), count=589 (+589), average=519 B
   <frozen importlib._bootstrap>:284: size=1005 KiB (+166 KiB), count=7423 (+1526), average=139 B
   /usr/lib/python3.4/mimetypes.py:217: size=112 KiB (+112 KiB), count=1334 (+1334), average=86 B
   /usr/lib/python3.4/http/server.py:848: size=96.0 KiB (+96.0 KiB), count=1 (+1), average=96.0 KiB
   /usr/lib/python3.4/inspect.py:1465: size=83.5 KiB (+83.5 KiB), count=109 (+109), average=784 B
   /usr/lib/python3.4/unittest/mock.py:491: size=77.7 KiB (+77.7 KiB), count=143 (+143), average=557 B
   /usr/lib/python3.4/urllib/parse.py:476: size=71.8 KiB (+71.8 KiB), count=969 (+969), average=76 B
   /usr/lib/python3.4/contextlib.py:38: size=67.2 KiB (+67.2 KiB), count=126 (+126), average=546 B

We can see that Python has loaded "8173 KiB" of module data (bytecode
and constants), and that this is "4428 KiB" more than had been loaded
before the tests, when the previous snapshot was taken. Similarly, the
"linecache" module has cached "940 KiB" of Python source code to
format tracebacks, all of it since the previous snapshot.

If the system has little free memory, snapshots can be written on disk
using the "Snapshot.dump()" method to analyze the snapshot offline.
Then use the "Snapshot.load()" method reload the snapshot.


获取一个内存块的溯源
--------------------

一段找出程序中最大内存块溯源的代码:

   import tracemalloc

   # Store 25 frames
   tracemalloc.start(25)

   # ... run your application ...

   snapshot = tracemalloc.take_snapshot()
   top_stats = snapshot.statistics('traceback')

   # pick the biggest memory block
   stat = top_stats[0]
   print("%s memory blocks: %.1f KiB" % (stat.count, stat.size / 1024))
   for line in stat.traceback.format():
       print(line)

一段Python单元测试的输出案例(限制最大25层堆栈)

   903 memory blocks: 870.1 KiB
     File "<frozen importlib._bootstrap>", line 716
     File "<frozen importlib._bootstrap>", line 1036
     File "<frozen importlib._bootstrap>", line 934
     File "<frozen importlib._bootstrap>", line 1068
     File "<frozen importlib._bootstrap>", line 619
     File "<frozen importlib._bootstrap>", line 1581
     File "<frozen importlib._bootstrap>", line 1614
     File "/usr/lib/python3.4/doctest.py", line 101
       import pdb
     File "<frozen importlib._bootstrap>", line 284
     File "<frozen importlib._bootstrap>", line 938
     File "<frozen importlib._bootstrap>", line 1068
     File "<frozen importlib._bootstrap>", line 619
     File "<frozen importlib._bootstrap>", line 1581
     File "<frozen importlib._bootstrap>", line 1614
     File "/usr/lib/python3.4/test/support/__init__.py", line 1728
       import doctest
     File "/usr/lib/python3.4/test/test_pickletools.py", line 21
       support.run_doctest(pickletools)
     File "/usr/lib/python3.4/test/regrtest.py", line 1276
       test_runner()
     File "/usr/lib/python3.4/test/regrtest.py", line 976
       display_failure=not verbose)
     File "/usr/lib/python3.4/test/regrtest.py", line 761
       match_tests=ns.match_tests)
     File "/usr/lib/python3.4/test/regrtest.py", line 1563
       main()
     File "/usr/lib/python3.4/test/__main__.py", line 3
       regrtest.main_in_temp_cwd()
     File "/usr/lib/python3.4/runpy.py", line 73
       exec(code, run_globals)
     File "/usr/lib/python3.4/runpy.py", line 160
       "__main__", fname, loader, pkg_name)

We can see that the most memory was allocated in the "importlib"
module to load data (bytecode and constants) from modules: "870.1
KiB". The traceback is where the "importlib" loaded data most
recently: on the "import pdb" line of the "doctest" module. The
traceback may change if a new module is loaded.


Pretty top
----------

Code to display the 10 lines allocating the most memory with a pretty
output, ignoring "<frozen importlib._bootstrap>" and "<unknown>"
files:

   import linecache
   import os
   import tracemalloc

   def display_top(snapshot, key_type='lineno', limit=10):
       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]
           print("#%s: %s:%s: %.1f KiB"
                 % (index, frame.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()

   # ... run your application ...

   snapshot = tracemalloc.take_snapshot()
   display_top(snapshot)

Python测试套件的输出示例：

   Top 10 lines
   #1: Lib/base64.py:414: 419.8 KiB
       _b85chars2 = [(a + b) for a in _b85chars for b in _b85chars]
   #2: Lib/base64.py:306: 419.8 KiB
       _a85chars2 = [(a + b) for a in _a85chars for b in _a85chars]
   #3: collections/__init__.py:368: 293.6 KiB
       exec(class_definition, namespace)
   #4: Lib/abc.py:133: 115.2 KiB
       cls = super().__new__(mcls, name, bases, namespace)
   #5: unittest/case.py:574: 103.1 KiB
       testMethod()
   #6: Lib/linecache.py:127: 95.4 KiB
       lines = fp.readlines()
   #7: urllib/parse.py:476: 71.8 KiB
       for a in _hexdig for b in _hexdig}
   #8: <string>:5: 62.0 KiB
   #9: Lib/_weakrefset.py:37: 60.0 KiB
       self.data = set()
   #10: Lib/base64.py:142: 59.8 KiB
       _b32tab2 = [a + b for a in _b32tab for b in _b32tab]
   6220 other: 3602.8 KiB
   Total allocated size: 5303.1 KiB

更多選項請見 "Snapshot.statistics()"。


Record the current and peak size of all traced memory blocks
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The following code computes two sums like "0 + 1 + 2 + ..."
inefficiently, by creating a list of those numbers. This list consumes
a lot of memory temporarily. We can use "get_traced_memory()" and
"reset_peak()" to observe the small memory usage after the sum is
computed as well as the peak memory usage during the computations:

   import tracemalloc

   tracemalloc.start()

   # Example code: compute a sum with a large temporary list
   large_sum = sum(list(range(100000)))

   first_size, first_peak = tracemalloc.get_traced_memory()

   tracemalloc.reset_peak()

   # Example code: compute a sum with a small temporary list
   small_sum = sum(list(range(1000)))

   second_size, second_peak = tracemalloc.get_traced_memory()

   print(f"{first_size=}, {first_peak=}")
   print(f"{second_size=}, {second_peak=}")

輸出：

   first_size=664, first_peak=3592984
   second_size=804, second_peak=29704

Using "reset_peak()" ensured we could accurately record the peak
during the computation of "small_sum", even though it is much smaller
than the overall peak size of memory blocks since the "start()" call.
Without the call to "reset_peak()", "second_peak" would still be the
peak from the computation "large_sum" (that is, equal to
"first_peak"). In this case, both peaks are much higher than the final
memory usage, and which suggests we could optimise (by removing the
unnecessary call to "list", and writing "sum(range(...))").


API
===


函式
----

tracemalloc.clear_traces()

   清空 Python 所分配的内存块的追踪数据。

   另請參閱 "stop()"。

tracemalloc.get_object_traceback(obj)

   Get the traceback where the Python object *obj* was allocated.
   Return a "Traceback" instance, or "None" if the "tracemalloc"
   module is not tracing memory allocations or did not trace the
   allocation of the object.

   另請參閱 "gc.get_referrers()" 與 "sys.getsizeof()" 函式。

tracemalloc.get_traceback_limit()

   Get the maximum number of frames stored in the traceback of a
   trace.

   The "tracemalloc" module must be tracing memory allocations to get
   the limit, otherwise an exception is raised.

   The limit is set by the "start()" function.

tracemalloc.get_traced_memory()

   Get the current size and peak size of memory blocks traced by the
   "tracemalloc" module as a tuple: "(current: int, peak: int)".

tracemalloc.reset_peak()

   Set the peak size of memory blocks traced by the "tracemalloc"
   module to the current size.

   Do nothing if the "tracemalloc" module is not tracing memory
   allocations.

   This function only modifies the recorded peak size, and does not
   modify or clear any traces, unlike "clear_traces()". Snapshots
   taken with "take_snapshot()" before a call to "reset_peak()" can be
   meaningfully compared to snapshots taken after the call.

   另請參閱 "get_traced_memory()"。

   3.9 版新加入.

tracemalloc.get_tracemalloc_memory()

   Get the memory usage in bytes of the "tracemalloc" module used to
   store traces of memory blocks. Return an "int".

tracemalloc.is_tracing()

   "True" if the "tracemalloc" module is tracing Python memory
   allocations, "False" otherwise.

   另請參閱 "start()" 與 "stop()" 函式。

tracemalloc.start(nframe: int = 1)

   Start tracing Python memory allocations: install hooks on Python
   memory allocators. Collected tracebacks of traces will be limited
   to *nframe* frames. By default, a trace of a memory block only
   stores the most recent frame: the limit is "1". *nframe* must be
   greater or equal to "1".

   You can still read the original number of total frames that
   composed the traceback by looking at the "Traceback.total_nframe"
   attribute.

   Storing more than "1" frame is only useful to compute statistics
   grouped by "'traceback'" or to compute cumulative statistics: see
   the "Snapshot.compare_to()" and "Snapshot.statistics()" methods.

   Storing more frames increases the memory and CPU overhead of the
   "tracemalloc" module. Use the "get_tracemalloc_memory()" function
   to measure how much memory is used by the "tracemalloc" module.

   The "PYTHONTRACEMALLOC" environment variable
   ("PYTHONTRACEMALLOC=NFRAME") and the "-X" "tracemalloc=NFRAME"
   command line option can be used to start tracing at startup.

   See also "stop()", "is_tracing()" and "get_traceback_limit()"
   functions.

tracemalloc.stop()

   Stop tracing Python memory allocations: uninstall hooks on Python
   memory allocators. Also clears all previously collected traces of
   memory blocks allocated by Python.

   Call "take_snapshot()" function to take a snapshot of traces before
   clearing them.

   See also "start()", "is_tracing()" and "clear_traces()" functions.

tracemalloc.take_snapshot()

   Take a snapshot of traces of memory blocks allocated by Python.
   Return a new "Snapshot" instance.

   The snapshot does not include memory blocks allocated before the
   "tracemalloc" module started to trace memory allocations.

   Tracebacks of traces are limited to "get_traceback_limit()" frames.
   Use the *nframe* parameter of the "start()" function to store more
   frames.

   The "tracemalloc" module must be tracing memory allocations to take
   a snapshot, see the "start()" function.

   另請參閱 "get_object_traceback()" 函式。


DomainFilter
------------

class tracemalloc.DomainFilter(inclusive: bool, domain: int)

   Filter traces of memory blocks by their address space (domain).

   3.6 版新加入.

   inclusive

      If *inclusive* is "True" (include), match memory blocks
      allocated in the address space "domain".

      If *inclusive* is "False" (exclude), match memory blocks not
      allocated in the address space "domain".

   domain

      Address space of a memory block ("int"). Read-only property.


过滤器
------

class tracemalloc.Filter(inclusive: bool, filename_pattern: str, lineno: int = None, all_frames: bool = False, domain: int = None)

   对内存块的跟踪进行筛选。

   See the "fnmatch.fnmatch()" function for the syntax of
   *filename_pattern*. The "'.pyc'" file extension is replaced with
   "'.py'".

   範例：

   * "Filter(True, subprocess.__file__)" 只包括 "subprocess" 模块的追
     踪数据

   * "Filter(False, tracemalloc.__file__)" 排除了 "tracemalloc" 模块的
     追踪数据

   * "Filter(False, "<unknown>")" 排除了空的回溯信息

   3.5 版更變: "'.pyo'" 文件扩展名不会再被替换为 "'.py'"。

   3.6 版更變: 新增 "domain" 屬性。

   domain

      Address space of a memory block ("int" or "None").

      tracemalloc uses the domain "0" to trace memory allocations made
      by Python. C extensions can use other domains to trace other
      resources.

   inclusive

      If *inclusive* is "True" (include), only match memory blocks
      allocated in a file with a name matching "filename_pattern" at
      line number "lineno".

      If *inclusive* is "False" (exclude), ignore memory blocks
      allocated in a file with a name matching "filename_pattern" at
      line number "lineno".

   lineno

      Line number ("int") of the filter. If *lineno* is "None", the
      filter matches any line number.

   filename_pattern

      Filename pattern of the filter ("str"). Read-only property.

   all_frames

      If *all_frames* is "True", all frames of the traceback are
      checked. If *all_frames* is "False", only the most recent frame
      is checked.

      This attribute has no effect if the traceback limit is "1".  See
      the "get_traceback_limit()" function and
      "Snapshot.traceback_limit" attribute.


Frame
-----

class tracemalloc.Frame

   Frame of a traceback.

   The "Traceback" class is a sequence of "Frame" instances.

   filename

      文件名（"字符串"）

   lineno

      行号（"整形"）


快照
----

class tracemalloc.Snapshot

   Snapshot of traces of memory blocks allocated by Python.

   The "take_snapshot()" function creates a snapshot instance.

   compare_to(old_snapshot: Snapshot, key_type: str, cumulative: bool = False)

      Compute the differences with an old snapshot. Get statistics as
      a sorted list of "StatisticDiff" instances grouped by
      *key_type*.

      See the "Snapshot.statistics()" method for *key_type* and
      *cumulative* parameters.

      The result is sorted from the biggest to the smallest by:
      absolute value of "StatisticDiff.size_diff",
      "StatisticDiff.size", absolute value of
      "StatisticDiff.count_diff", "Statistic.count" and then by
      "StatisticDiff.traceback".

   dump(filename)

      将快照写入文件

      使用 "load()" 重载快照。

   filter_traces(filters)

      Create a new "Snapshot" instance with a filtered "traces"
      sequence, *filters* is a list of "DomainFilter" and "Filter"
      instances.  If *filters* is an empty list, return a new
      "Snapshot" instance with a copy of the traces.

      All inclusive filters are applied at once, a trace is ignored if
      no inclusive filters match it. A trace is ignored if at least
      one exclusive filter matches it.

      3.6 版更變: "DomainFilter" instances are now also accepted in
      *filters*.

   classmethod load(filename)

      从文件载入快照。

      另請參閱 "dump()"。

   statistics(key_type: str, cumulative: bool = False)

      获取 "Statistic" 信息列表，按 *key_type* 分组排序：

      +-----------------------+--------------------------+
      | key_type              | 描述                     |
      |=======================|==========================|
      | "'filename'"          | 文件名                   |
      +-----------------------+--------------------------+
      | "'lineno'"            | 文件名和行号             |
      +-----------------------+--------------------------+
      | "'traceback'"         | 回溯                     |
      +-----------------------+--------------------------+

      If *cumulative* is "True", cumulate size and count of memory
      blocks of all frames of the traceback of a trace, not only the
      most recent frame. The cumulative mode can only be used with
      *key_type* equals to "'filename'" and "'lineno'".

      The result is sorted from the biggest to the smallest by:
      "Statistic.size", "Statistic.count" and then by
      "Statistic.traceback".

   traceback_limit

      Maximum number of frames stored in the traceback of "traces":
      result of the "get_traceback_limit()" when the snapshot was
      taken.

   traces

      Traces of all memory blocks allocated by Python: sequence of
      "Trace" instances.

      The sequence has an undefined order. Use the
      "Snapshot.statistics()" method to get a sorted list of
      statistics.


统计
----

class tracemalloc.Statistic

   统计内存分配

   "Snapshot.statistics()" 返回 "Statistic" 实例的列表。.

   参见 "StatisticDiff" 类。

   count

      内存块数（"整形"）。

   size

      Total size of memory blocks in bytes ("int").

   traceback

      Traceback where the memory block was allocated, "Traceback"
      instance.


StatisticDiff
-------------

class tracemalloc.StatisticDiff

   Statistic difference on memory allocations between an old and a new
   "Snapshot" instance.

   "Snapshot.compare_to()" returns a list of "StatisticDiff"
   instances. See also the "Statistic" class.

   count

      Number of memory blocks in the new snapshot ("int"): "0" if the
      memory blocks have been released in the new snapshot.

   count_diff

      Difference of number of memory blocks between the old and the
      new snapshots ("int"): "0" if the memory blocks have been
      allocated in the new snapshot.

   size

      Total size of memory blocks in bytes in the new snapshot
      ("int"): "0" if the memory blocks have been released in the new
      snapshot.

   size_diff

      Difference of total size of memory blocks in bytes between the
      old and the new snapshots ("int"): "0" if the memory blocks have
      been allocated in the new snapshot.

   traceback

      Traceback where the memory blocks were allocated, "Traceback"
      instance.


跟踪
----

class tracemalloc.Trace

   Trace of a memory block.

   The "Snapshot.traces" attribute is a sequence of "Trace" instances.

   3.6 版更變: 新增 "domain" 屬性。

   domain

      Address space of a memory block ("int"). Read-only property.

      tracemalloc uses the domain "0" to trace memory allocations made
      by Python. C extensions can use other domains to trace other
      resources.

   size

      Size of the memory block in bytes ("int").

   traceback

      Traceback where the memory block was allocated, "Traceback"
      instance.


回溯
----

class tracemalloc.Traceback

   Sequence of "Frame" instances sorted from the oldest frame to the
   most recent frame.

   A traceback contains at least "1" frame. If the "tracemalloc"
   module failed to get a frame, the filename ""<unknown>"" at line
   number "0" is used.

   When a snapshot is taken, tracebacks of traces are limited to
   "get_traceback_limit()" frames. See the "take_snapshot()" function.
   The original number of frames of the traceback is stored in the
   "Traceback.total_nframe" attribute. That allows to know if a
   traceback has been truncated by the traceback limit.

   The "Trace.traceback" attribute is an instance of "Traceback"
   instance.

   3.7 版更變: Frames are now sorted from the oldest to the most
   recent, instead of most recent to oldest.

   total_nframe

      Total number of frames that composed the traceback before
      truncation. This attribute can be set to "None" if the
      information is not available.

   3.9 版更變: The "Traceback.total_nframe" attribute was added.

   format(limit=None, most_recent_first=False)

      Format the traceback as a list of lines. Use the "linecache"
      module to retrieve lines from the source code. If *limit* is
      set, format the *limit* most recent frames if *limit* is
      positive. Otherwise, format the "abs(limit)" oldest frames. If
      *most_recent_first* is "True", the order of the formatted frames
      is reversed, returning the most recent frame first instead of
      last.

      Similar to the "traceback.format_tb()" function, except that
      "format()" does not include newlines.

      範例：

         print("Traceback (most recent call first):")
         for line in traceback:
             print(line)

      輸出：

         Traceback (most recent call first):
           File "test.py", line 9
             obj = Object()
           File "test.py", line 12
             tb = tracemalloc.get_object_traceback(f())
