Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 20:35 UTC

netaddr / netaddr

A network address manipulation library for Python

PythonCustom license★ 831 stars⑂ 176 forkssince May 2010View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

netaddr/netaddr holds a health index of 32 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (74/100) and lowest on Vitality (25/100). It was last updated 798 days ago. A single contributor accounts for most of its recent work.

32
overall / 100
At Risk

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

32
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 53 is calibrated to 54 on the published index scale (record calibration 2026-08-02).

Ownership

netaddrOrganization
4 followers1 public reposince Jan 2020

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPInetaddr1.3.0-34836 days agonetworkingsystems-administrationianaieeecidripipv4ipv6euimacmac-48eui-48eui-64

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

25At Risk · 21% of overall
How it's scored
0/36Push recency — last push 798 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share0.97
days_since_last_push798
active_weeks_last_year0
How it's scored
27/27Ships releases — 7 releases published
0/36Release recency — latest release 836 days ago
27/27Release cadence — a release every ~42 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count7
latest_release_tag1.3.0
releases_from_tagsno
days_since_latest_release836
mean_days_between_releases42
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

61Moderate · 17% of overall
How it's scored
47.4/60Stars — 831 stars
18.7/25Forks — 176 forks
8.7/15Watchers — 37 watchers
Inputs used
forks176
stars831
watchers37
growth_stateorganic
growth_factor_pct100
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

55Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
10.1/22.5Commit distribution — top contributor authored 55% of commits
13.5/13.5Contributor breadth — 36 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled36
top_contributor_share0.549
How it's scored
34.4/42Issue resolution — 82% of issues closed
23/30PR acceptance — 161/210 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 3/27 approved changesets -- score normalized to 1
Inputs used
merged_prs161
open_issues33
closed_issues150
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.82
closed_unmerged_prs49
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
5/25Owner reach — 4 followers of netaddr
14.2/25Track record — 1 public repos, account ~6 yr old
Inputs used
followers4
owner_typeOrganization
is_verifiedno
owner_loginnetaddr
public_repos1
account_age_days2,426
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 836 days ago
20/20Version history — 34 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesnetaddr
ecosystemspypi
any_deprecatedno
min_days_since_publish836

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 10 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://netaddr.readthedocs.io/en/latest/
10/10Repository description
10/10Topics — 15 topics
0/10Wiki
Inputs used
topicspython, subnet, ipv4, ipv6, devops, networking, netaddr, mac, iab, sysadmin, cidr, eui, ip-address, oui, oui-database
has_wikino
homepagehttps://netaddr.readthedocs.io/en/latest/
docs_sitehttps://netaddr.readthedocs.io/en/latest/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

53Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0/2.5CI-Tests — 0 out of 10 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-Review — Found 3/27 approved changesets -- score normalized to 1
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
5/5Fuzzing — project is fuzzed
2.2/2.5License — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 32 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.1
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories61
affected_packages9
assessed_packages39
unassessed_packages0
affected_by_severityhigh 5, moderate 3, low 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 39 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

51Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
24.7/40Legible commit history — 45 of 97 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.464
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 3 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.03
How it's scored
0/45Type-checkable code — Python without a type-check config
54/55Manageable file sizes — 1/53 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes71,337
source_files_sampled53
oversized_source_files1

Key facts

831GitHub stars
36contributors
0commits, last 12 months
798days since last push
7releases
1bus factor
33open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-07-06: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 831 stars today.
  • pypi download statistics for 'netaddr' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 827 ★ / 176 ⇿
827Stars
176Forks
7Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Star history is shown as collected on 2026-07-06. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

02004006008001,000827172292010-052018-062026-06
Major 1Minor 4Patch 2

Each point covers 15 days.

OpenSSF Scorecard 4.1 / 10
4.1aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-12 20:35 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
0CI-Tests0 out of 10 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 3/27 approved changesets -- score normalized to 1
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
10Fuzzingproject is fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities32 existing vulnerabilities detected
All dependencies 39

Full resolved dependency set from the GitHub dependency graph: 0 direct and 39 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIalabaster0.7.13indirect
PyPIbabel2.14.0indirect
PyPIbeautifulsoup44.12.2indirect
PyPIcertifi2023.11.17indirect
PyPIcharset-normalizer3.3.2indirect
PyPIcolorama0.4.6indirect
PyPIcoverage6.5.0indirect
PyPIdocutils0.20.1indirect
PyPIexceptiongroup1.2.0indirect
PyPIfuro2023.9.10indirect
PyPIidna3.7indirect
PyPIimagesize1.4.1indirect
PyPIiniconfig2.0.0indirect
PyPIjinja23.1.4indirect
PyPIlivereload2.6.3indirect
PyPImarkupsafe2.1.3indirect
PyPIpackaging23.2indirect
PyPIpluggy1.2.0indirect
PyPIpygments2.17.2indirect
PyPIpytest7.4.4indirect
PyPIpytest-cov4.1.0indirect
PyPIrequests2.32.2indirect
PyPIruff0.1.11indirect
PyPIsix1.16.0indirect
PyPIsnowballstemmer2.2.0indirect
PyPIsoupsieve2.5indirect
PyPIsphinx7.2.6indirect
PyPIsphinx-autobuild2021.3.14indirect
PyPIsphinx-basic-ng1.0.0b2indirect
PyPIsphinx-issues4.0.0indirect
PyPIsphinxcontrib-applehelp1.0.7indirect
PyPIsphinxcontrib-devhelp1.0.5indirect
PyPIsphinxcontrib-htmlhelp2.0.4indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp1.0.6indirect
PyPIsphinxcontrib-serializinghtml1.1.9indirect
PyPItomli2.0.1indirect
PyPItornado6.4indirect
PyPIurllib32.1.0indirect
Dependency advisories 9

This repository publishes no package the index resolves, so its own dependency graph was assessed — 39 packages, which also include development and test pins that never ship: 9 carry known advisories, of which 0 are direct.

PackageVersionRelationSeverityAdvisoriesFixed in
certifi2023.11.17indirecthigh22024.7.4
jinja23.1.4indirecthigh63.1.6
soupsieve2.5indirecthigh42.8.4
tornado6.4indirecthigh276.5.8
urllib32.1.0indirecthigh122.7.0
idna3.7indirectmoderate23.15
pytest7.4.4indirectmoderate29.0.3
requests2.32.2indirectmoderate42.33.0
pygments2.17.2indirectlow22.20.0

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.