Skip to main content

muTimer

muTimer is a hierarchical timing utility with nested context manager support. It provides fine-grained timing of code sections.

Features

  • Nested timing contexts that track parent-child relationships
  • Accumulation of time across multiple calls to the same timer
  • Call counting for repeated operations
  • Hierarchical summary output in tabular format
  • Optional depth limiting for nested timers
  • MPI-aware summaries (single output on rank 0 with min/mean/max across ranks)

Usage

from muTimer import Timer

timer = Timer()

with timer("outer"):
    # some code
    with timer("inner"):
        # nested code
    with timer("inner"):  # called again - time accumulates
        # more nested code

timer.print_summary()

Output:

==============================================================================
Timing Summary
==============================================================================
Name                                  Total    Calls      Average   % Parent
------------------------------ ------------ -------- ------------ ----------
outer                              22.55 ms        1            -          -
  inner                            12.50 ms        2      6.25 ms      55.4%
  (other)                          10.06 ms        -            -      44.6%
==============================================================================

MPI Support

When running under MPI, pass a communicator to avoid every rank printing its own summary. Both mpi4py communicators and muGrid communicators are accepted.

from mpi4py import MPI
from muTimer import Timer

timer = Timer(comm=MPI.COMM_WORLD)

with timer("outer"):
    # some code
    pass

timer.print_summary()  # printed once, on rank 0

Timing data is gathered to rank 0, which prints a single summary showing the mean, minimum and maximum time spent in each section across all ranks:

===========================================================================================
Timing Summary (4 MPI processes)
===========================================================================================
Name                                   Mean          Min          Max    Calls   % Parent
------------------------------ ------------ ------------ ------------ -------- ----------
outer                              23.30 ms     22.55 ms     24.05 ms        1          -
  inner                            12.95 ms     12.50 ms     13.40 ms        2      55.6%
  (other)                          10.35 ms            -            -        -      44.4%
===========================================================================================

If the communicator cannot gather Python objects (no underlying mpi4py communicator), the summary is still printed only on rank 0, using that rank's local timings.

muTimer has no dependency on mpi4py (or any other MPI package): the communicator is duck-typed. Anything that provides the mpi4py communicator interface works, e.g. NuMPI's MPI module, which falls back to a serial stub when mpi4py is not installed:

from NuMPI import MPI  # mpi4py if installed, serial stub otherwise
from muTimer import Timer

timer = Timer(comm=MPI.COMM_WORLD)

Memory Tracking

You can also track memory usage (Resident Set Size) by enabling track_memory=True. This requires the psutil package.

import time
from muTimer import Timer

# Create a timer with memory tracking enabled
timer = Timer(track_memory=True)

with timer("outer"):
    # allocate some memory
    large_list = [0] * 1000000
    time.sleep(0.01)
    
    with timer("inner"):
        another_list = [1] * 2000000
        time.sleep(0.01)

    with timer("inner"):
        more_memory = [2] * 500000
        time.sleep(0.005)

timer.print_summary()

Output:

============================================================================================
Timing Summary
============================================================================================
Name                                  Total    Calls      Average   % Parent       Memory
------------------------------ ------------ -------- ------------ ---------- ------------
outer                              33.74 ms        1            -          -     26.78 MB
  inner                            20.52 ms        2     10.26 ms      60.8%     19.12 MB
  (other)                          13.23 ms        -            -      39.2%      7.66 MB
============================================================================================

License

muTimer is distributed under the MIT License.

Metadata

Release files for muTimer 1.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for muTimer 1.1.0
File Size Uploaded
mutimer-1.1.0.tar.gz 11.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for muTimer 1.1.0
File Interpreter ABI Platform
mutimer-1.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 21.1 kB

Release files / mutimer-1.1.0.tar.gz

Download URL mutimer-1.1.0.tar.gz
Size 11.4 kB
Tags Source
SHA-256 checksum
How to use checksums
d38a2014cca5e133672ed6ac36790c8549c83aff2339cfea73efb23e0370a613
BLAKE2b-256 checksum
How to use checksums
b6f3fb3cc4a64e82d89a88ef6f5101432420dc0d14a7efa8a8e6543915a0398a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.12

Release files / mutimer-1.1.0-py3-none-any.whl

Download URL mutimer-1.1.0-py3-none-any.whl
Size 9.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
bf057715b74508df6fbee5478d265554b9d347d6d01d20b74aa5c0dee1175ec5
BLAKE2b-256 checksum
How to use checksums
575de014f4110a9d7cbe0625e9d4b25d29ac27d420d5472ada69dc43eb8a4e5b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.12

Release history Release notifications | RSS feed

This release

1.1.0 This release

2 release files

1.0.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page