Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-22 12:28 UTC

Labelbox / labelbox-python

The data factory for next gen AI

PythonApache-2.0★ 155 stars⑂ 73 forkssince Sep 2018View on GitHub ↗
KindLibraryhow this is determined
#python#sdk#ai#ml#mlops#annotation

Labelbox/labelbox-python holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (90/100) and lowest on Security (62/100). It was last updated today. 5 contributors account for most of its recent work.

94
overall / 100
Exceptional

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.

94
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 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

labelboxOrganization
124 followers34 public repossince Nov 2017

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIlabelbox7.11.0719,02619324 days agoaiedulabelboxlabelingllmmachinelearningml
PyPIlbox-clients1.1.2252,3513583 days agoaiedulabelboxlabelingllmmachinelearningml
PyPIlbox-alignerr0.1.0231297 days agoaialignerrlabelboxlabelinglbox-alignerrllmmachinelearningml

Metrics by category

Vitality

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

85Excellent · 21% of overall

Development activity

81Excellent
How it's scored
36/36Push recency — last push 0 days ago
17.3/36Commit cadence — 25/52 weeks with commits
18/18Commit volume — 125 commits in the last year
10/10OpenSSF Scorecard: Maintained — 17 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year125
human_commit_share0.94
days_since_last_push0
active_weeks_last_year25

Release discipline

90Excellent
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 24 days ago
27/27Release cadence — a release every ~36.4 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_tagv7.11.0
releases_from_tagsno
days_since_latest_release24
mean_days_between_releases36.4

Community & Adoption

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

75Good · 17% of overall

Popularity & adoption

57Moderate
How it's scored
35.5/60Stars — 155 stars
15.5/25Forks — 73 forks
5.6/15Watchers — 11 watchers
Inputs used
forks73
stars155
watchers11
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

77Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges9
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

100Exceptional
How it's scored
79.8/80Monthly downloads — 971,400 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packageslabelbox, lbox-clients, lbox-alignerr
dependents—
ecosystemspypi
total_downloads—
monthly_downloads971,400
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

89Excellent · 23% of overall

Maintainer resilience (bus factor)

80Excellent
How it's scored
45.9/54Bus factor — 5 contributor(s) cover half of all commits
17.8/22.5Commit distribution — top contributor authored 21% of commits
13.5/13.5Contributor breadth — 83 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor5
contributors_sampled83
top_contributor_share0.207

Issue & PR responsiveness

95Exceptional
How it's scored
41.5/42Issue resolution — 99% of issues closed
25.2/30PR acceptance — 1,668/1,982 decided PRs merged
13/13Newcomer PR acceptance — 4/4 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs1,668
open_issues1
closed_issues85
prs_merged_7d0
prs_decided_7d0
prs_merged_30d5
prs_decided_30d5
issue_closed_ratio0.988
closed_unmerged_prs314
first_time_authors_30d1
first_time_prs_merged_30d4
first_time_prs_decided_30d4

Ownership & stewardship

85Excellent
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
15.1/25Owner reach — 124 followers of Labelbox
23.2/25Track record — 34 public repos, account ~8 yr old
Inputs used
followers124
owner_typeOrganization
is_verified—
owner_loginLabelbox
public_repos34
account_age_days3,196
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 3 package(s) on pypi
35/35Publish recency — latest publish 24 days ago
20/20Version history — 193 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslabelbox, lbox-clients, lbox-alignerr
ecosystemspypi
any_deprecatedno
min_days_since_publish24

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 9 workflow(s)
24/24Tests present
16/16Linter config — libs/labelbox/pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://labelbox.com
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicspython, sdk, ai, ml, mlops, annotation
has_wikiyes
homepagehttps://labelbox.com
docs_sitehttps://labelbox.com
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

62Moderate · 16% of overall

Security posture

52Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 17 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
3.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
2.2/7.5Vulnerabilities — 7 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5.2

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages27
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:labelbox@7.11.0 runtime dependency closure — what installing the published package pulls in — 27 packages. 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.

72Good · 4% of overall

Agent context & guidance

55Moderate
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.labelbox.com/llms.txt)
40/40Legible commit history — 72 of 94 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.labelbox.com/llms.txt
legible_history_share0.766
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

71Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — libs/labelbox/pyproject.toml ([tool.ruff])
11/11Static type checking — libs/labelbox/mypy.ini
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 9 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
7/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configslibs/labelbox/mypy.ini
agent_commit_share0.09
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (libs/labelbox/mypy.ini)
54.4/55Manageable file sizes — 4/366 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes931,526
source_files_sampled366
oversized_source_files4

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — example, examples, notebooks
Inputs used
example_dirsexample, examples, notebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

155GitHub stars
83contributors
125commits, last 12 months
0days since last push
100releases
5bus factor
1open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'labelbox-python' from its registry
  • Could not fetch pypi package 'lbox-example' from its registry

More detail

Star and fork history 0 ★ / 73 ⇿
0Stars
73Forks
97Releases

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.

01325385063757222019-032022-102026-06
Major 1Minor 8Patch 2

Each point covers 7 days.

OpenSSF Scorecard 5.2 / 10
5.2aggregate

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 · 2026-08-22 12:27 UTC

10Binary-Artifactsno binaries found in the repo
1Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained17 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
7Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 7
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
3Vulnerabilities7 existing vulnerabilities detected
Direct dependencies 18
RegistryPackageVersion constraintManifest
PyPIsphinx-multiproject>=1.0.0rc1pyproject.toml
PyPIsphinx>=7.1.2pyproject.toml
PyPIsphinx-rtd-theme>=2.0.0pyproject.toml
PyPIgoogle-api-core>=1.22.1libs/labelbox/pyproject.toml
PyPIpydantic>=2.0libs/labelbox/pyproject.toml
PyPIpython-dateutil>=2.8.2, <2.10.0libs/labelbox/pyproject.toml
PyPIrequests>=2.22.0libs/labelbox/pyproject.toml
PyPIstrenum>=0.4.15libs/labelbox/pyproject.toml
PyPItqdm>=4.66.2libs/labelbox/pyproject.toml
PyPIgeojson>=3.1.0libs/labelbox/pyproject.toml
PyPIlbox-clients==1.1.2libs/labelbox/pyproject.toml
PyPIPyYAML>=6.0libs/labelbox/pyproject.toml
PyPIlabelbox>=0.1.0libs/lbox-alignerr/pyproject.toml
PyPIpydantic>=2.0.0libs/lbox-alignerr/pyproject.toml
PyPIpyyaml>=6.0libs/lbox-alignerr/pyproject.toml
PyPIrequests>=2.22.0libs/lbox-clients/pyproject.toml
PyPIgoogle-api-core>=1.22.1libs/lbox-clients/pyproject.toml
PyPIart>=6.2libs/lbox-example/pyproject.toml
All dependencies 130

Full resolved dependency set from the GitHub dependency graph: 21 direct and 109 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIart—direct
PyPIgeojson—direct
PyPIgoogle-api-core—direct
PyPIlabelbox—direct
PyPIlbox-clients1.1.2direct
PyPIpydantic—direct
PyPIpython-dateutil—direct
PyPIpyyaml—direct
PyPIrequests—direct
PyPIrequests2.22.0direct
PyPIrequests2.32.5direct
PyPIsphinx2.1.2direct
PyPIsphinx7.4.7direct
PyPIsphinx8.1.3direct
PyPIsphinx8.2.3direct
PyPIsphinx-multiproject1.0.0direct
PyPIsphinx-rtd-theme0.4.3direct
PyPIsphinx-rtd-theme3.0.2direct
PyPIstrenum—direct
PyPItqdm—direct
PyPItqdm4.32.2direct
PyPIaffine2.2.2indirect
PyPIalabaster0.7.12indirect
PyPIalabaster0.7.16indirect
PyPIalabaster1.0.0indirect
PyPIastroid2.2.5indirect
PyPIatomicwrites1.3.0indirect
PyPIattrs19.1.0indirect
PyPIbabel2.17.0indirect
PyPIbabel2.7.0indirect
PyPIbleach3.1.0indirect
PyPIcertifi2019.6.16indirect
PyPIcertifi2025.8.3indirect
PyPIchardet3.0.4indirect
PyPIcharset-normalizer3.4.3indirect
PyPIcheck-manifest0.39indirect
PyPIclick7.0indirect
PyPIclick-plugins1.1.1indirect
PyPIcligj0.5.0indirect
PyPIcolorama0.4.6indirect
PyPIcoverage4.5.3indirect
PyPIdocutils0.14indirect
PyPIdocutils0.21.2indirect
PyPIentrypoints0.3indirect
PyPIfilelock3.0.12indirect
PyPIflake83.7.8indirect
PyPIhatchling—indirect
PyPIidna2.8indirect
PyPIidna3.10indirect
PyPIimagesize—indirect
PyPIimagesize1.1.0indirect
PyPIimagesize1.4.1indirect
PyPIimportlib-metadata0.18indirect
PyPIimportlib-metadata8.7.0indirect
PyPIisort4.3.21indirect
PyPIjinja22.10.1indirect
PyPIjinja23.1.6indirect
PyPIlabelbox-python0.1.0indirect
PyPIlazy-object-proxy1.4.1indirect
PyPIlbox-alignerr—indirect
PyPImarkupsafe1.1.1indirect
PyPImarkupsafe3.0.2indirect
PyPImccabe0.6.1indirect
PyPImore-itertools7.1.0indirect
PyPImypy0.720indirect
PyPImypy-extensions0.4.1indirect
PyPInumpy—indirect
PyPInumpy1.16.4indirect
PyPIopencv-python-headless—indirect
PyPIpackaging19.0indirect
PyPIpackaging25.0indirect
PyPIpillow—indirect
PyPIpillow6.1.0indirect
PyPIpkginfo1.5.0.1indirect
PyPIpluggy0.12.0indirect
PyPIpockets0.7.2indirect
PyPIpy1.8.0indirect
PyPIpycodestyle2.5.0indirect
PyPIpyflakes2.1.1indirect
PyPIpygeotile—indirect
PyPIpygments2.19.2indirect
PyPIpygments2.4.2indirect
PyPIpylint2.3.1indirect
PyPIpyparsing2.4.0indirect
PyPIpyproj—indirect
PyPIpytest5.0.1indirect
PyPIpytest-cov2.7.1indirect
PyPIpytz2019.1indirect
PyPIrasterio1.0.24indirect
PyPIreadme-renderer24.0indirect
PyPIrequests-toolbelt0.9.1indirect
PyPIroman-numerals-py3.1.0indirect
PyPIshapely—indirect
PyPIshapely1.6.4.post2indirect
PyPIsimplification0.4.2indirect
PyPIsix1.12.0indirect
PyPIsnowballstemmer1.9.0indirect
PyPIsnowballstemmer3.0.1indirect
PyPIsnuggs1.4.6indirect
PyPIsphinxcontrib-applehelp1.0.1indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp1.0.1indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp1.0.2indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jquery4.1indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-napoleon0.7indirect
PyPIsphinxcontrib-qthelp1.0.2indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml1.1.3indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPItoml0.10.0indirect
PyPItomli2.2.1indirect
PyPItox3.13.2indirect
PyPItwine1.13.0indirect
PyPItyped-ast1.4.0indirect
PyPItypeguard—indirect
PyPItyping-extensions—indirect
PyPItyping-extensions3.7.4indirect
PyPIurllib31.25.3indirect
PyPIurllib32.5.0indirect
PyPIvirtualenv16.6.2indirect
PyPIwcwidth0.1.7indirect
PyPIwebencodings0.5.1indirect
PyPIwheel0.33.4indirect
PyPIwrapt1.11.2indirect
PyPIxmltodict0.12.0indirect
PyPIzipp0.5.2indirect
PyPIzipp3.23.0indirect
Dependency advisories 0

Installing pypi:labelbox@7.11.0 pulls in 27 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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.

Related records

Inspected repositories sharing catalogue tags or ecosystems with Labelbox/labelbox-python. Read them side by side →

98Netflix/metaflowBuild, Manage and Deploy AI/ML SystemsExceptional100deepset-ai/haystackOpen-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.Exceptional99ag2ai/ag2AG2 (formerly AutoGen): The Open-Source AgentOS.Join us at: https://discord.gg/sNGSwQME3xExceptional99langchain-ai/langgraphBuild resilient agents.Exceptional99microsoft/agent-frameworkA framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.Exceptional98Significant-Gravitas/AutoGPTAutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.Exceptional

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.