scope-profiler

scope-profiler#

A lightweight, low-overhead profiling framework for Python and HPC applications.

scope-profiler lets you instrument code regions with decorators or context managers, collect nanosecond-resolution timing traces, and optionally integrate LIKWID hardware performance counters or line_profiler line-by-line analysis — all through a single, unified API.

Key features#

  • Two instrumentation styles — @ProfileManager.profile decorator and with ProfileManager.profile_region() context manager.

  • Near-zero overhead — the default timing mode adds ~700 ns per call; profiling can be toggled off at startup with no code changes.

  • HDF5 time traces — start/end timestamps are flushed to disk and merged automatically, ready for post-hoc analysis and Gantt charts.

  • MPI-aware — per-rank data is collected and merged transparently via mpi4py.

  • LIKWID integration — hardware counter regions are opened/closed alongside timing, with no extra boilerplate.

  • Line profiler integration — enable line_profiler per-line stats on any decorated function with a single flag.

  • CLI post-processing — scope-profiler-pproc reads HDF5 output and generates Gantt charts with region/rank filtering.

Quick example#

from scope_profiler import ProfileManager

ProfileManager.setup(time_trace=True, flush_to_disk=True)

@ProfileManager.profile("compute")
def compute():
    return sum(i * i for i in range(100_000))

compute()
ProfileManager.finalize()

Documentation#

Getting started

User guide

Reference

Tutorials & examples

Contents