python-peps/pep-0454.txt

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PEP: 454
Title: Add a new tracemalloc module to trace Python memory allocations
Version: $Revision$
Last-Modified: $Date$
Author: Victor Stinner <victor.stinner@gmail.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 3-September-2013
Python-Version: 3.4
Abstract
========
This PEP proposes to add a new ``tracemalloc`` module to trace memory
blocks allocated by Python.
Rationale
=========
Common debug tools tracing memory allocations record the C filename
and line number where the allocation occurs. Using such tools to
analyze Python memory allocations does not help because most memory
blocks are allocated in the same C function, in ``PyMem_Malloc()`` for
example.
There are debug tools dedicated to the Python language like ``Heapy``
and ``PySizer``. These tools analyze objects type and/or content.
They are useful when most memory leaks are instances of the same type
and this type is only instantiated in a few functions. Problems arise
when the object type is very common like ``str`` or ``tuple``, and it
is hard to identify where these objects are instantiated.
Finding reference cycles is also a difficult problem. There are
different tools to draw a diagram of all references. These tools
cannot be used on large applications with thousands of objects because
the diagram is too huge to be analyzed manually.
Proposal
========
Using the customized allocation API from PEP 445, it becomes easy to
set up a hook on Python memory allocators. A hook can inspect Python
internals to retrieve Python tracebacks.
This PEP proposes to add a new ``tracemalloc`` module, as a debug tool
to trace memory blocks allocated by Python. The module provides the
following information:
* Computed differences between two snapshots to detect memory leaks
* Statistics on allocated memory blocks per filename and per line
number: total size, number and average size of allocated memory blocks
* Traceback where a memory block was allocated
The API of the tracemalloc module is similar to the API of the
faulthandler module: ``enable()``, ``disable()`` and ``is_enabled()``
functions, an environment variable (``PYTHONFAULTHANDLER`` and
``PYTHONTRACEMALLOC``), and a ``-X`` command line option (``-X
faulthandler`` and ``-X tracemalloc``). See the
`documentation of the faulthandler module
<http://docs.python.org/3/library/faulthandler.html>`_.
The tracemalloc module has been written for CPython. Other
implementations of Python may not be able to provide it.
API
===
Main Functions
--------------
``clear_traces()`` function:
Clear traces and statistics on Python memory allocations, and reset
the ``get_traced_memory()`` counter.
``disable()`` function:
Stop tracing Python memory allocations.
See also ``enable()`` and ``is_enabled()`` functions.
``enable()`` function:
Start tracing Python memory allocations.
At fork, the module is automatically disabled in the child process.
See also ``disable()`` and ``is_enabled()`` functions.
``get_stats()`` function:
Get statistics on traced Python memory blocks as a dictionary
``{filename (str): {line_number (int): stats}}`` where *stats* in a
``(size: int, count: int)`` tuple, *filename* and *line_number* can
be ``None``.
Return an empty dictionary if the ``tracemalloc`` module is
disabled.
See also the ``get_traces()`` function.
``get_traced_memory()`` function:
Get the current size and maximum size of memory blocks traced by the
``tracemalloc`` module as a tuple: ``(size: int, max_size: int)``.
``get_tracemalloc_memory()`` function:
Get the memory usage in bytes of the ``tracemalloc`` module as a
tuple: ``(size: int, free: int)``.
* *size*: total size of bytes allocated by the module,
including *free* bytes
* *free*: number of free bytes available to store data
``is_enabled()`` function:
``True`` if the ``tracemalloc`` module is tracing Python memory
allocations, ``False`` otherwise.
See also ``enable()`` and ``disable()`` functions.
Trace Functions
---------------
``get_traceback_limit()`` function:
Get the maximum number of frames stored in the traceback of a trace
of a memory block.
Use the ``set_traceback_limit()`` function to change the limit.
``get_object_address(obj)`` function:
Get the address of the main memory block of the specified Python object.
A Python object can be composed by multiple memory blocks, the
function only returns the address of the main memory block.
See also ``get_object_trace()`` and ``gc.get_referrers()`` functions.
``get_object_trace(obj)`` function:
Get the trace of a Python object *obj* as a ``(size: int,
traceback)`` tuple where *traceback* is a tuple of ``(filename: str,
lineno: int)`` tuples, *filename* and *lineno* can be ``None``.
The function only returns the trace of the main memory block of the
object. The *size* of the trace is smaller than the total size of
the object if the object is composed by more than one memory block.
Return ``None`` if the ``tracemalloc`` module did not trace the
allocation of the object.
See also ``get_object_address()``, ``get_trace()``,
``get_traces()``, ``gc.get_referrers()`` and ``sys.getsizeof()``
functions.
``get_trace(address)`` function:
Get the trace of a memory block as a ``(size: int, traceback)``
tuple where *traceback* is a tuple of ``(filename: str, lineno:
int)`` tuples, *filename* and *lineno* can be ``None``.
Return ``None`` if the ``tracemalloc`` module did not trace the
allocation of the memory block.
See also ``get_object_trace()``, ``get_stats()`` and
``get_traces()`` functions.
``get_traces()`` function:
Get traces of Python memory allocations as a dictionary ``{address
(int): trace}`` where *trace* is a ``(size: int, traceback)`` and
*traceback* is a list of ``(filename: str, lineno: int)``.
*traceback* can be empty, *filename* and *lineno* can be None.
Return an empty dictionary if the ``tracemalloc`` module is disabled.
See also ``get_object_trace()``, ``get_stats()`` and ``get_trace()``
functions.
``set_traceback_limit(nframe: int)`` function:
Set the maximum number of frames stored in the traceback of a trace
of a memory block.
Storing the traceback of each memory allocation has an important
overhead on the memory usage. Use the ``get_tracemalloc_memory()``
function to measure the overhead and the ``add_filter()`` function
to select which memory allocations are traced.
Use the ``get_traceback_limit()`` function to get the current limit.
Filter Functions
----------------
``add_filter(filter)`` function:
Add a new filter on Python memory allocations, *filter* is a
``Filter`` instance.
All inclusive filters are applied at once, a memory allocation is
only ignored if no inclusive filters match its trace. A memory
allocation is ignored if at least one exclusive filter matchs its
trace.
The new filter is not applied on already collected traces. Use the
``clear_traces()`` function to ensure that all traces match the new
filter.
``add_include_filter(filename: str, lineno: int=None, traceback: bool=False)`` function:
Add an inclusive filter: helper for the ``add_filter()`` method
creating a ``Filter`` instance with the ``Filter.include`` attribute
set to ``True``.
Example: ``tracemalloc.add_include_filter(tracemalloc.__file__)``
only includes memory blocks allocated by the ``tracemalloc`` module.
``add_exclude_filter(filename: str, lineno: int=None, traceback: bool=False)`` function:
Add an exclusive filter: helper for the ``add_filter()`` method
creating a ``Filter`` instance with the ``Filter.include`` attribute
set to ``False``.
Example: ``tracemalloc.add_exclude_filter(tracemalloc.__file__)``
ignores memory blocks allocated by the ``tracemalloc`` module.
``clear_filters()`` function:
Reset the filter list.
See also the ``get_filters()`` function.
``get_filters()`` function:
Get the filters on Python memory allocations as list of ``Filter``
instances.
See also the ``clear_filters()`` function.
Filter
------
``Filter(include: bool, pattern: str, lineno: int=None, traceback: bool=False)`` class:
Filter to select which memory allocations are traced. Filters can be
used to reduce the memory usage of the ``tracemalloc`` module, which
can be read using the ``get_tracemalloc_memory()`` function.
``match(filename: str, lineno: int)`` method:
Return ``True`` if the filter matchs the filename and line number,
``False`` otherwise.
``match_filename(filename: str)`` method:
Return ``True`` if the filter matchs the filename, ``False`` otherwise.
``match_lineno(lineno: int)`` method:
Return ``True`` if the filter matchs the line number, ``False``
otherwise.
``match_traceback(traceback)`` method:
Return ``True`` if the filter matchs the *traceback*, ``False``
otherwise.
*traceback* is a tuple of ``(filename: str, lineno: int)`` tuples.
``include`` attribute:
If *include* is ``True``, only trace memory blocks allocated in a
file with a name matching filename ``pattern`` at line number
``lineno``.
If *include* is ``False``, ignore memory blocks allocated in a file
with a name matching filename ``pattern`` at line number ``lineno``.
``lineno`` attribute:
Line number (``int``). If is is ``None`` or less than ``1``, it
matches any line number.
``pattern`` attribute:
The filename *pattern* can contain one or many ``*`` joker
characters which match any substring, including an empty string. The
``.pyc`` and ``.pyo`` file extensions are replaced with ``.py``. On
Windows, the comparison is case insensitive and the alternative
separator ``/`` is replaced with the standard separator ``\``.
``traceback`` attribute:
If *traceback* is ``True``, all frames of the traceback are checked.
If *traceback* is ``False``, only the most recent frame is checked.
This attribute is ignored if the traceback limit is less than ``2``.
See the ``get_traceback_limit()`` function.
GroupedStats
------------
``GroupedStats(timestamp: datetime.datetime, stats: dict, group_by: str, cumulative=False, metrics: dict=None)`` class:
Top of allocated memory blocks grouped by *group_by* as a
dictionary.
The ``Snapshot.top_by()`` method creates a ``GroupedStats``
instance.
``compare_to(old_stats: GroupedStats=None)`` method:
Compare to an older ``GroupedStats`` instance. Return a
``StatsDiff`` instance.
The ``StatsDiff.differences`` list is not sorted: call the
``StatsDiff.sort()`` method to sort the list.
``None`` values are replaced with an empty string for filenames or
zero for line numbers, because ``str`` and ``int`` cannot be
compared to ``None``.
``cumulative`` attribute:
If ``True``, cumulate size and count of memory blocks of all frames
of the traceback of a trace, not only the most recent frame.
``metrics`` attribute:
Dictionary storing metrics read when the snapshot was created:
``{name (str): metric}`` where *metric* type is ``Metric``.
``group_by`` attribute:
Determine how memory allocations were grouped: see
``Snapshot.top_by()`` for the available values.
``stats`` attribute:
Dictionary ``{key: stats}`` where the *key* type depends on the
``group_by`` attribute and *stats* is a ``(size: int, count: int)``
tuple.
See the ``Snapshot.top_by()`` method.
``timestamp`` attribute:
Creation date and time of the snapshot, ``datetime.datetime``
instance.
Metric
------
``Metric(name: str, value: int, format: str)`` class:
Value of a metric when a snapshot is created.
``name`` attribute:
Name of the metric.
``value`` attribute:
Value of the metric.
``format`` attribute:
Format of the metric (``str``).
Snapshot
--------
``Snapshot(timestamp: datetime.datetime, traces: dict=None, stats: dict=None)`` class:
Snapshot of traces and statistics on memory blocks allocated by Python.
``add_metric(name: str, value: int, format: str)`` method:
Helper to add a ``Metric`` instance to ``Snapshot.metrics``. Return
the newly created ``Metric`` instance.
Raise an exception if the name is already present in
``Snapshot.metrics``.
``apply_filters(filters)`` method:
Apply filters on the ``traces`` and ``stats`` dictionaries,
*filters* is a list of ``Filter`` instances.
``create(traces=False)`` classmethod:
Take a snapshot of traces and/or statistics of allocated memory blocks.
If *traces* is ``True``, ``get_traces()`` is called and its result
is stored in the ``Snapshot.traces`` attribute. This attribute
contains more information than ``Snapshot.stats`` and uses more
memory and more disk space. If *traces* is ``False``,
``Snapshot.traces`` is set to ``None``.
Tracebacks of traces are limited to ``traceback_limit`` frames. Call
``set_traceback_limit()`` before calling ``Snapshot.create()`` to
store more frames.
The ``tracemalloc`` module must be enabled to take a snapshot. See
the the ``enable()`` function.
``get_metric(name, default=None)`` method:
Get the value of the metric called *name*. Return *default* if the
metric does not exist.
``load(filename, traces=True)`` classmethod:
Load a snapshot from a file.
If *traces* is ``False``, don't load traces.
``top_by(group_by: str, cumulative: bool=False)`` method:
Compute top statistics grouped by *group_by* as a ``GroupedStats``
instance:
===================== ======================== ================================
group_by description key type
===================== ======================== ================================
``'filename'`` filename ``str``
``'line'`` filename and line number ``(filename: str, lineno: int)``
``'address'`` memory block address ``int``
``'traceback'`` traceback ``(address: int, traceback)``
===================== ======================== ================================
The ``traceback`` type is a tuple of ``(filename: str, lineno:
int)`` tuples, *filename* and *lineno* can be ``None``.
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* parameter is ignored if *group_by*
is ``'address'`` or if the traceback limit is less than ``2``.
``write(filename)`` method:
Write the snapshot into a file.
``metrics`` attribute:
Dictionary storing metrics read when the snapshot was created:
``{name (str): metric}`` where *metric* type is ``Metric``.
``stats`` attribute:
Statistics on traced Python memory, result of the ``get_stats()``
function.
``traceback_limit`` attribute:
Maximum number of frames stored in a trace of a memory block
allocated by Python.
``traces`` attribute:
Traces of Python memory allocations, result of the ``get_traces()``
function, can be ``None``.
``timestamp`` attribute:
Creation date and time of the snapshot, ``datetime.datetime``
instance.
StatsDiff
---------
``StatsDiff(differences, old_stats, new_stats)`` class:
Differences between two ``GroupedStats`` instances.
The ``GroupedStats.compare_to()`` method creates a ``StatsDiff``
instance.
``sort()`` method:
Sort the ``differences`` list from the biggest difference to the
smallest difference. Sort by ``abs(size_diff)``, *size*,
``abs(count_diff)``, *count* and then by *key*.
``differences`` attribute:
Differences between ``old_stats`` and ``new_stats`` as a list of
``(size_diff, size, count_diff, count, key)`` tuples. *size_diff*,
*size*, *count_diff* and *count* are ``int``. The key type depends
on the ``GroupedStats.group_by`` attribute of ``new_stats``: see the
``Snapshot.top_by()`` method.
``old_stats`` attribute:
Old ``GroupedStats`` instance, can be ``None``.
``new_stats`` attribute:
New ``GroupedStats`` instance.
Links
=====
tracemalloc:
* `#18874: Add a new tracemalloc module to trace Python
memory allocations <http://bugs.python.org/issue18874>`_
* `pytracemalloc on PyPI
<https://pypi.python.org/pypi/pytracemalloc>`_
Similar projects:
* `Meliae: Python Memory Usage Analyzer
<https://pypi.python.org/pypi/meliae>`_
* `Guppy-PE: umbrella package combining Heapy and GSL
<http://guppy-pe.sourceforge.net/>`_
* `PySizer <http://pysizer.8325.org/>`_: developed for Python 2.4
* `memory_profiler <https://pypi.python.org/pypi/memory_profiler>`_
* `pympler <http://code.google.com/p/pympler/>`_
* `Dozer <https://pypi.python.org/pypi/Dozer>`_: WSGI Middleware version
of the CherryPy memory leak debugger
* `objgraph <http://mg.pov.lt/objgraph/>`_
* `caulk <https://github.com/smartfile/caulk/>`_
Copyright
=========
This document has been placed in the public domain.
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