pymemtrace 0.6.1

Python memory tracing.

pymemtrace provides tools for tracking and understanding Python memory usage at different levels, at different granularities and with different runtime costs.

Full documentation: https://pymemtrace.readthedocs.io

pymemtrace Tools

The tools provided by pymemtrace are:

process_tree

A command line tool that shows the total memory usage of a process and its child processes at regular time intervals. It can log this data to a JSON file for later analysis. See some process_tree examples

process

A very lightweight way of logging the total memory usage of a single process at regular time intervals. It can plot memory over time with plotting programs such as gnuplot. See some process examples

cPyMemTrace

This module, written in C, provides real time logging of Python and C actions:

• pymemtrace.cPyMemTrace.Profile is a memory tracer written in C that can report total memory usage for every function call/return for both C and Python sections. This is more suitable for logging C code, for example Python’s C extensions.

• pymemtrace.cPyMemTrace.Trace is a memory tracer written in C that can report total memory usage for every function call/return/line for Python sections. This is more suitable for logging pure Python code.

• pymemtrace.cPyMemTrace.ReferenceTracing can report every object allocation and de-allocation with Reference Tracing. This is quite invasive but the API allows this to filter out most of the noise or target specific types of interest. (Python 3.13+ only).

See some cPyMemTrace examples and a technical note on cPyMemTrace.

DTrace

There are a number of D scripts that can trace the low level malloc() and free() system calls and report how much memory was allocated and by whom. See some DTrace examples and a technical note on DTrace.

trace_malloc

A convenience wrapper around the Python standard library tracemalloc module. This can report Python memory usage by module and line compensating for the cost of tracemalloc. This can take memory snapshots before and after code blocks and show the change on memory caused by that code. See some trace_malloc examples

debug_malloc_stats

Awrapper around the sys._debugmallocstats function that can take snapshots of memory before and after code execution and report the significant differences of the Python small object allocator. See some debug_malloc_stats examples

Tool Characteristics

Each tool can be characterised by:

• Memory Granularity: In how much detail is a memory change is observed. An example of coarse memory granularity is measuring the Resident Set Size (RSS) which is normally in chunks of 4096 bytes. An example of fine memory granularity is recording every malloc() and free().

• Execution Granularity: In how much code detail is the memory change observed. An example of coarse execution granularity is measuring the memory usage every second. An example of fine execution granularity is recording the memory usage every Python line.

• Memory Cost: How much extra memory the tool needs.

• Execution Cost: How much the execution time is increased.

Clearly there are trade-offs between these depending on the problem you are trying to solve.

Firstly granularity:

Tool Granularity

Tool	Memory Granularity	Execution Granularity
process_tree	RSS.	Regular time intervals.
process	RSS.	Regular time intervals.
cPyMemTrace.Profile	RSS.	Per Python line, Python function and return. C function call and return.
cPyMemTrace.Trace	RSS.	Per Python line, Python function and return. Python Opcode and exception.
cPyMemTrace.ReferenceTracing	RSS.	Every object allocation/de-allocation.
DTrace	Every malloc() and free().	Per function call and return.
trace_malloc	Every Python object.	Per Python line, per function call.
debug_malloc_stats	Python memory pool.	Snapshots the CPython memory pool either side of a block of code.

Secondly cost:

Tool Cost

Tool	Memory Cost	Execution Cost
process_tree	Near zero.	Near zero.
process	Near zero.	Near zero.
cPyMemTrace.Profile	Near zero.	10x to 40x.
cPyMemTrace.Trace	Near zero.	20x to 60x.
cPyMemTrace.ReferenceTracing	Near zero.	2x to 80x.
DTrace	Minimal.	90x to 100x.
trace_malloc	Significant but compensated.	900x for small objects, 6x for large objects.
debug_malloc_stats	Minimal.	+2000x for small objects, 12x for large objects.

Installation

To install pymemtrace, run this command in your terminal:

$ pip install pymemtrace

Licence

Python memory tracing.

• Free software: MIT license

• Documentation: https://pymemtrace.readthedocs.io.

• Project: https://github.com/paulross/pymemtrace.

Credits

Phil Smith (AHL) with whom a casual lunch time chat lead to the creation of an earlier, but quite different implementation, of cPyMemTrace in pure Python.

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.6.1 (2026-06-24)

• Fixes: #5 (macros setting for strdup()).

• Some debug improvements.

• Added magic numbers to opaque data structures.

• Add gnuplot output of live object count.

• Documentation improvements.

• Supported Python versions are: 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, 3.14, 3.15

• Development Status :: 5 - Production/Stable

0.6.0 (2026-05-19)

• Add a hash table of live type counts to Reference Tracing. This can be accessed from Python as a dictionary.

• Fix Reference tracing example for build_all.sh.

• Add module level functions to write to the Profile/Trace/Reference Trace log files.

• Add some asserts and clean up test_cpyreftraceexample.py.

• Add Reference Tracing minimal example in C, a Python module and tests.

• Add Doxygen documentation.

• Reorganise debug code.

• Add basic example of Reference Tracing in C to debug code.

• Supported Python versions are: 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, 3.14, 3.15

• Development Status :: 5 - Production/Stable

0.5.0 (2026-05-12)

• Add two console entry points in the distro: pymemtrace_ref_trace_analyse and pymemtrace_dtrace_log_analyse

• Make option names for ref_trace_analyse.py more intuitive.

• Fix issues with initialising the datatime capsule.

• Minor change to the Reference Tracing log file format.

• ref_trace_analyse.py can now merge log files.

• Add the ability to get reference counts from arbitrary addresses.

• Added documentation.

• Supported Python versions are: 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, 3.14, 3.15

• Development Status :: 5 - Production/Stable

0.4.1 (2026-05-03)

• Add example of using Reference Tracing to detect memory leaks.

0.4.0 (2026-04-18)

• cPyMemTrace:

  • User filtering of Reference Tracing events to include/exclude specific events.

  • Reference Tracing runs the Garbage Collector on exit to make the log more accurate.

  • Much more reliable processing of Reference Tracing events.

  • Fix the issue with Reference Tracing where handling type “frame” and “code” was causing pytest and CPython runtime assert failures.

  • Write profile/trace/reference tracing context switches to the appropriate log file.

  • Add cPyMemTrace.ReferenceTracingSimple as an example. Includes documentation and test code.

  • Add suspend() and resume() methods for Reference Tracing.

  • Document pytest issues with Reference Tracing (now historical information).

• General documentation improvements, now around 140 PDF A4 pages.

• Add Doxygen documentation of the C source.

• Supported Python versions are: 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, 3.14, 3.15

• Development Status :: 5 - Production/Stable

0.3.1 (2026-03-23)

• pymemtrace:

  • Add decorator for pymemtrace.process.

  • pymemtrace.process can now summarise JSON in the log to stdout.

• cPyMemTrace:

  • Add decorators for Python functions for Profile, Trace and ReferenceTracing.

  • Fix a SIGSEGV when bad keyword arguments were passed to cPyMemTrace.ReferenceTracing.

0.3.0 (2026-03-19)

• Add process-tree.py for logging a process and its children.

• cPyMemTrace:

  • Add Reference Tracing (Python 3.13+) that can record every object allocation or de-allocation.

  • Add an option to log to a specific file.

  • Add an API write_message_to_log() to inject text into the log file.

  • Better structure of the log file format.

  • Define the log file format.

  • Add debug exploration code with debug_cPyMemtrace().

  • Fix stacking pop() issue with trace/profile functions with linked list of tTraceFileWrapperLinkedList.

• Add support for Python 3.14

• Remove support for Python 3.7

• Supported Python versions are: 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, 3.14

• Development Status :: 5 - Production/Stable

0.2.0 (2024-11-17)

• cPyMemTrace:

  • Add P/T, stack depth and python version to log file name, example: "20241107_195847_62264_P_0_PY3.13.0b3.log"

  • Add stacking of trace/profile functions with linked list of tTraceFileWrapperLinkedList.

  • Add an option to log to a specific file.

  • Add an API write_to_log() to inject text into the log file.

  • Add an optional message to the log file in cPyMemTrace.

  • Add Python API to get log file being written to by cPyMemTrace.

  • Bug fixes in cPyMemTrace.c

  • Safety fix for file path name lengths.

  • Fix for log files where '#' was being concatenated.

0.1.7 (2024-09-12)

• Minor fix for a single test.

0.1.6 (2024-09-11)

• Add support for Python versions 3.12, 3.13. Now supports Python versions 3.7, 3.8, 3.9, 3.10, 3.11, 3.12, 3.13.

0.1.5 (2023-06-21)

• Add support for Python versions 3.10, 3.11. Now supports Python versions 3.7, 3.8, 3.9, 3.10, 3.11.

0.1.4 (2022-03-19)

• Fix Linux build.

0.1.3 (2022-03-17)

• Fix some tests.

0.1.2 (2022-03-17)

• Fix source distribution that had missing headers.

0.1.1 (2020-11-17)

• Add cPyMemTrace the C level profiler.

• Add DTrace scripts for low level tracing.

• Add debug_malloc_stats the wrapper around sys._debugmallocstats.

• Add process.py from the TotalDepth project.

• Add redirect_stdout for debug_malloc_stats.

• Add trace_malloc, a wrapper around the tracemalloc module.

• Includes extensive documentation and performance measurement.

• First release on PyPI.

0.1.0 (2017-12-04)

• Initial idea and implementation, never released.