:mod:`tracemalloc` --- Trace memory allocations =============================================== .. module:: tracemalloc :synopsis: Trace memory allocations. .. versionadded:: 3.4 The tracemalloc module is a debug tool to trace memory blocks allocated by Python. It provides the following information: * Traceback where an object was allocated * Statistics on allocated memory blocks per filename and per line number: total size, number and average size of allocated memory blocks * Compute the differences between two snapshots to detect memory leaks To trace most memory blocks allocated by Python, the module should be started as early as possible by setting the :envvar:`PYTHONTRACEMALLOC` environment variable to ``1``, or by using :option:`-X` ``tracemalloc`` command line option. The :func:`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 :envvar:`PYTHONTRACEMALLOC` environment variable to ``25``, or use the :option:`-X` ``tracemalloc=25`` command line option. Examples ======== Display the top 10 ------------------ Display the 10 files allocating the most memory:: 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) Example of output of the Python test suite:: [ Top 10 ] :716: size=4855 KiB, count=39328, average=126 B :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 :1446: size=70.4 KiB, count=911, average=79 B :1454: size=52.0 KiB, count=25, average=2131 B :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 ``4.8 MiB`` data (bytecode and constants) from modules and that the :mod:`collections` module allocated ``244 KiB`` to build :class:`~collections.namedtuple` types. See :meth:`Snapshot.statistics` for more options. Compute differences ------------------- Take two snapshots and display the differences:: 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 ] :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 :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 ``8.2 MiB`` of module data (bytecode and constants), and that this is ``4.4 MiB`` more than had been loaded before the tests, when the previous snapshot was taken. Similarly, the :mod:`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 :meth:`Snapshot.dump` method to analyze the snapshot offline. Then use the :meth:`Snapshot.load` method reload the snapshot. Get the traceback of a memory block ----------------------------------- Code to display the traceback of the biggest memory block:: 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) Example of output of the Python test suite (traceback limited to 25 frames):: 903 memory blocks: 870.1 KiB File "", line 716 File "", line 1036 File "", line 934 File "", line 1068 File "", line 619 File "", line 1581 File "", line 1614 File "/usr/lib/python3.4/doctest.py", line 101 import pdb File "", line 284 File "", line 938 File "", line 1068 File "", line 619 File "", line 1581 File "", 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 :mod:`importlib` module to load data (bytecode and constants) from modules: ``870 KiB``. The traceback is where the :mod:`importlib` loaded data most recently: on the ``import pdb`` line of the :mod:`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 ```` and ```` files:: import linecache import os import tracemalloc def display_top(snapshot, group_by='lineno', limit=10): snapshot = snapshot.filter_traces(( tracemalloc.Filter(False, ""), tracemalloc.Filter(False, ""), )) top_stats = snapshot.statistics(group_by) 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() # ... run your application ... snapshot = tracemalloc.take_snapshot() display_top(snapshot) Example of output of the Python test suite:: 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: :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 See :meth:`Snapshot.statistics` for more options. API === Functions --------- .. function:: clear_traces() Clear traces of memory blocks allocated by Python. See also :func:`stop`. .. function:: get_object_traceback(obj) Get the traceback where the Python object *obj* was allocated. Return a :class:`Traceback` instance, or ``None`` if the :mod:`tracemalloc` module is not tracing memory allocations or did not trace the allocation of the object. See also :func:`gc.get_referrers` and :func:`sys.getsizeof` functions. .. function:: get_traceback_limit() Get the maximum number of frames stored in the traceback of a trace. The :mod:`tracemalloc` module must be tracing memory allocations to get the limit, otherwise an exception is raised. The limit is set by the :func:`start` function. .. function:: get_traced_memory() Get the current size and peak size of memory blocks traced by the :mod:`tracemalloc` module as a tuple: ``(current: int, peak: int)``. .. function:: get_tracemalloc_memory() Get the memory usage in bytes of the :mod:`tracemalloc` module used to store traces of memory blocks. Return an :class:`int`. .. function:: is_tracing() ``True`` if the :mod:`tracemalloc` module is tracing Python memory allocations, ``False`` otherwise. See also :func:`start` and :func:`stop` functions. .. function:: 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``. Storing more than ``1`` frame is only useful to compute statistics grouped by ``'traceback'`` or to compute cumulative statistics: see the :meth:`Snapshot.compare_to` and :meth:`Snapshot.statistics` methods. Storing more frames increases the memory and CPU overhead of the :mod:`tracemalloc` module. Use the :func:`get_tracemalloc_memory` function to measure how much memory is used by the :mod:`tracemalloc` module. The :envvar:`PYTHONTRACEMALLOC` environment variable (``PYTHONTRACEMALLOC=NFRAME``) and the :option:`-X` ``tracemalloc=NFRAME`` command line option can be used to start tracing at startup. See also :func:`stop`, :func:`is_tracing` and :func:`get_traceback_limit` functions. .. function:: 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 :func:`take_snapshot` function to take a snapshot of traces before clearing them. See also :func:`start`, :func:`is_tracing` and :func:`clear_traces` functions. .. function:: take_snapshot() Take a snapshot of traces of memory blocks allocated by Python. Return a new :class:`Snapshot` instance. The snapshot does not include memory blocks allocated before the :mod:`tracemalloc` module started to trace memory allocations. Tracebacks of traces are limited to :func:`get_traceback_limit` frames. Use the *nframe* parameter of the :func:`start` function to store more frames. The :mod:`tracemalloc` module must be tracing memory allocations to take a snapshot, see the the :func:`start` function. See also the :func:`get_object_traceback` function. Filter ------ .. class:: Filter(inclusive: bool, filename_pattern: str, lineno: int=None, all_frames: bool=False) Filter on traces of memory blocks. See the :func:`fnmatch.fnmatch` function for the syntax of *filename_pattern*. The ``'.pyc'`` and ``'.pyo'`` file extensions are replaced with ``'.py'``. Examples: * ``Filter(True, subprocess.__file__)`` only includes traces of the :mod:`subprocess` module * ``Filter(False, tracemalloc.__file__)`` excludes traces of the :mod:`tracemalloc` module * ``Filter(False, "")`` excludes empty tracebacks .. attribute:: inclusive If *inclusive* is ``True`` (include), only trace memory blocks allocated in a file with a name matching :attr:`filename_pattern` at line number :attr:`lineno`. If *inclusive* is ``False`` (exclude), ignore memory blocks allocated in a file with a name matching :attr:`filename_pattern` at line number :attr:`lineno`. .. attribute:: lineno Line number (``int``) of the filter. If *lineno* is ``None``, the filter matches any line number. .. attribute:: filename_pattern Filename pattern of the filter (``str``). .. attribute:: 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 :func:`get_traceback_limit` function and :attr:`Snapshot.traceback_limit` attribute. Frame ----- .. class:: Frame Frame of a traceback. The :class:`Traceback` class is a sequence of :class:`Frame` instances. .. attribute:: filename Filename (``str``). .. attribute:: lineno Line number (``int``). Snapshot -------- .. class:: Snapshot Snapshot of traces of memory blocks allocated by Python. The :func:`take_snapshot` function creates a snapshot instance. .. method:: compare_to(old_snapshot: Snapshot, group_by: str, cumulative: bool=False) Compute the differences with an old snapshot. Get statistics as a sorted list of :class:`StatisticDiff` instances grouped by *group_by*. See the :meth:`statistics` method for *group_by* and *cumulative* parameters. The result is sorted from the biggest to the smallest by: absolute value of :attr:`StatisticDiff.size_diff`, :attr:`StatisticDiff.size`, absolute value of :attr:`StatisticDiff.count_diff`, :attr:`Statistic.count` and then by :attr:`StatisticDiff.traceback`. .. method:: dump(filename) Write the snapshot into a file. Use :meth:`load` to reload the snapshot. .. method:: filter_traces(filters) Create a new :class:`Snapshot` instance with a filtered :attr:`traces` sequence, *filters* is a list of :class:`Filter` instances. If *filters* is an empty list, return a new :class:`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 matchs it. .. classmethod:: load(filename) Load a snapshot from a file. See also :meth:`dump`. .. method:: statistics(group_by: str, cumulative: bool=False) Get statistics as a sorted list of :class:`Statistic` instances grouped by *group_by*: ===================== ======================== group_by description ===================== ======================== ``'filename'`` filename ``'lineno'`` filename and line number ``'traceback'`` traceback ===================== ======================== 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 *group_by* equals to ``'filename'`` and ``'lineno'``. The result is sorted from the biggest to the smallest by: :attr:`Statistic.size`, :attr:`Statistic.count` and then by :attr:`Statistic.traceback`. .. attribute:: traceback_limit Maximum number of frames stored in the traceback of :attr:`traces`: result of the :func:`get_traceback_limit` when the snapshot was taken. .. attribute:: traces Traces of all memory blocks allocated by Python: sequence of :class:`Trace` instances. The sequence has an undefined order. Use the :meth:`Snapshot.statistics` method to get a sorted list of statistics. Statistic --------- .. class:: Statistic Statistic on memory allocations. :func:`Snapshot.statistics` returns a list of :class:`Statistic` instances. See also the :class:`StatisticDiff` class. .. attribute:: count Number of memory blocks (``int``). .. attribute:: size Total size of memory blocks in bytes (``int``). .. attribute:: traceback Traceback where the memory block was allocated, :class:`Traceback` instance. StatisticDiff ------------- .. class:: StatisticDiff Statistic difference on memory allocations between an old and a new :class:`Snapshot` instance. :func:`Snapshot.compare_to` returns a list of :class:`StatisticDiff` instances. See also the :class:`Statistic` class. .. attribute:: count Number of memory blocks in the new snapshot (``int``): ``0`` if the memory blocks have been released in the new snapshot. .. attribute:: 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. .. attribute:: 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. .. attribute:: 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. .. attribute:: traceback Traceback where the memory blocks were allocated, :class:`Traceback` instance. Trace ----- .. class:: Trace Trace of a memory block. The :attr:`Snapshot.traces` attribute is a sequence of :class:`Trace` instances. .. attribute:: size Size of the memory block in bytes (``int``). .. attribute:: traceback Traceback where the memory block was allocated, :class:`Traceback` instance. Traceback --------- .. class:: Traceback Sequence of :class:`Frame` instances sorted from the most recent frame to the oldest frame. A traceback contains at least ``1`` frame. If the ``tracemalloc`` module failed to get a frame, the filename ``""`` at line number ``0`` is used. When a snapshot is taken, tracebacks of traces are limited to :func:`get_traceback_limit` frames. See the :func:`take_snapshot` function. The :attr:`Trace.traceback` attribute is an instance of :class:`Traceback` instance. .. method:: format(limit=None) Format the traceback as a list of lines with newlines. Use the :mod:`linecache` module to retrieve lines from the source code. If *limit* is set, only format the *limit* most recent frames. Similar to the :func:`traceback.format_tb` function, except that :meth:`format` does not include newlines. Example:: print("Traceback (most recent call first):") for line in traceback: print(line) Output:: Traceback (most recent call first): File "test.py", line 9 obj = Object() File "test.py", line 12 tb = tracemalloc.get_object_traceback(f())