# dfeneyrou/palanteer

Visual Python and C++ nanosecond profiler, logger, tests enabler

Repository: https://github.com/dfeneyrou/palanteer
Canonical: https://ross.abutalabs.com/products/palanteer
Language: C++
License: NOASSERTION
License Family: other
Topics: developer-tools, profiler, profiling, python, cpp, c-plus-plus, memory-profiler, performance, optimization, logging, embedded, header-only
Last push: 2025-05-12T13:06:37+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 21, release rhythm 8, longevity 100
- inputs: {"age_days": 1901, "days_push": 478, "days_rel": 526, "gap_med": 188, "n_releases_24m": 2}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2212, forks 97 (observed 2026-08-28T04:06:26.888750+00:00)

## What it is
Palanteer is a visual nanosecond profiler and logger for C++ and Python programs, with a single-header C++ instrumentation library and mostly automatic Python instrumentation. It provides interactive timeline, flame graph, and histogram views, plus Python-scriptable remote commands for deep testing.

## Use cases
- profile a C++ application with nanosecond timing
- find memory leaks with a memory profiler
- visualize multithreaded execution on a timeline
- automatically instrument Python functions and allocations
- script remote commands to test a running program
- generate flame graphs from recorded events
- log efficiently with printf-style nanosecond logging

## When to choose
- you need low-overhead profiling for C++ or Python
- you want visual timeline and flame graph analysis
- you need combined profiling, logging, and scripted testing in one tool
- you want automatic instrumentation without code changes in Python

## When to avoid
- you need a distributed-systems tracer like OpenTelemetry
- you only want a simple sampling profiler with no instrumentation
- you need a license-permissive tool for strict compliance (license is custom)

## Facets
- artifact type: library
- maturity: active
- function: monitoring, logging, testing, benchmarking, tracing
- domain: developer-tools, performance, testing
- platform: cpp, python, windows, cross-platform
- tags: profiler, memory-profiler, flame-graph, timeline-viewer, remote-scripting, header-only, instrumentation, linux, macos

## Member repositories
- dfeneyrou/palanteer (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:26.888750+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:46:02.534504+00:00, confidence not recorded.
  - readme: https://github.com/dfeneyrou/palanteer (fetched 2026-08-28T04:06:26.888750+00:00, sha 98d8bb530031)
- Data as of 2026-08-30T08:39:29.467469+00:00.