hdrhistogram
High Dynamic Range histogram in native python
Decision gist · record as of 2026-08-14
Yes. hdrhistogram is actively maintained, has no known vulnerabilities, and fills a specific need for efficient, precise latency distribution tracking. Install it if you need percentile-based performance analysis or are porting HDR Histogram code from Java or C. The prebuilt wheels make installation straightforward on common platforms; only consider friction if you're on an unsupported architecture.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; C compiler needed only if no prebuilt wheel matches your platform.
- Medium install friction due to C extension compilation fallback, though prebuilt wheels cover Linux, macOS, and Windows for Python 3.10–3.14.
- Active maintenance with recent release (66 days old) and no known vulnerabilities.
License · maintenance · safety
permissive license (permissive) — Licensed under Apache Software License (permissive), allowing commercial and private use with minimal restrictions.
last release 2026-06-09 (66 days) · last repo commit 2026-06-09 · 163 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 551,525 downloads/mo, #6,048 on PyPI
Alternatives
Verify before relying
pip install hdrhistogram
from hdrhistogram import HdrHistogram
histogram = HdrHistogram(1, 3600000, 2)
histogram.record_value(latency)
percentile_99_9 = histogram.get_value_at_percentile(99.9)- Whether the package's coordinated omission correction is suitable for your specific measurement scenario.
- Performance characteristics and memory overhead when recording millions of values.
- Interoperability guarantees with Java and C HDR Histogram versions beyond V2 format.
What it is and what it does
hdrhistogram is a Python port of the Java HDR Histogram library, designed to record and analyze latency and performance distributions with high precision across a wide dynamic range. It solves the problem of accurately capturing percentile-based performance metrics without the memory overhead of storing every individual measurement; instead, it uses a bucketing strategy that trades a small, controlled amount of precision for dramatic space efficiency.
The package supports recording values with optional correction for coordinated omission (a common measurement bias in latency testing), querying percentiles and statistical summaries, iterating over recorded values in multiple ways, and serializing histograms to portable formats for storage or cross-platform analysis. It includes a command-line tool (dump_hdrh) for inspecting encoded histograms and supports 16-bit, 32-bit, and 64-bit counters. Runtime dependencies are minimal (pbr and setuptools for build support).
Use it for
- Track API response latencies in production and analyze tail percentiles (p99, p99.9) without storing every request.
- Measure and compare performance distributions across multiple services or time windows by encoding histograms as portable blobs.
- Correct for coordinated omission bias when benchmarking systems under load, ensuring accurate latency reporting.
- Generate percentile distribution tables in .hgrm format for plotting and reporting performance characteristics.
- Aggregate histograms from distributed systems into a central histogram for unified performance analysis.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
hdrhistogram is actively maintained, has no known vulnerabilities, and fills a specific need for efficient, precise latency distribution tracking. Install it if you need percentile-based performance analysis or are porting HDR Histogram code from Java or C. The prebuilt wheels make installation straightforward on common platforms; only consider friction if you're on an unsupported architecture.
Install
hdrhistogram on PyPI
Before you install
Medium install friction due to C extension compilation fallback, though prebuilt wheels cover Linux, macOS, and Windows for Python 3.10–3.14. Active maintenance with recent release (66 days old) and no known vulnerabilities.
Requires Python 3.10 or later; C compiler needed only if no prebuilt wheel matches your platform.
License in practice
Licensed under Apache Software License (permissive), allowing commercial and private use with minimal restrictions.
Quickstart
pip install hdrhistogram
from hdrhistogram import HdrHistogram
histogram = HdrHistogram(1, 3600000, 2)
histogram.record_value(latency)
percentile_99_9 = histogram.get_value_at_percentile(99.9)Verify before relying
- Whether the package's coordinated omission correction is suitable for your specific measurement scenario.
- Performance characteristics and memory overhead when recording millions of values.
- Interoperability guarantees with Java and C HDR Histogram versions beyond V2 format.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 2 packagespbrsetuptools |
| Maintenance | Actively maintained 66 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 551,525 / month, #6,048 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersIntended Audience :: Information TechnologyIntended Audience :: System AdministratorsLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: hdrhistogram-0.10.7-cp310-cp310-macosx_11_0_arm64.whl; hdrhistogram-0.10.7-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl; hdrhistogram-0.10.7-cp310-cp310-musllinux_1_2_x86_64.whl; hdrhistogram-0.10.7-cp310-cp310-win32.whl; hdrhistogram-0.10.7-cp310-cp310-win_amd64.whl; hdrhistogram-0.10.7-cp311-cp311-macosx_11_0_arm64.whl; hdrhistogram-0.10.7-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl; hdrhistogram-0.10.7-cp311-cp311-musllinux_1_2_x86_64.whl; hdrhistogram-0.10.7-cp311-cp311-win32.whl; hdrhistogram-0.10.7-cp311-cp311-win_amd64.whl; hdrhistogram-0.10.7-cp312-cp312-macosx_11_0_arm64.whl; hdrhistogram-0.10.7-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl; hdrhistogram-0.10.7-cp312-cp312-musllinux_1_2_x86_64.whl; hdrhistogram-0.10.7-cp312-cp312-win32.whl; hdrhistogram-0.10.7-cp312-cp312-win_amd64.whl; hdrhistogram-0.10.7-cp313-cp313-macosx_11_0_arm64.whl; hdrhistogram-0.10.7-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl; hdrhistogram-0.10.7-cp313-cp313-musllinux_1_2_x86_64.whl; hdrhistogram-0.10.7-cp313-cp313-win32.whl; hdrhistogram-0.10.7-cp313-cp313-win_amd64.whl
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