Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-06 01:19 UTC

opendatalab / labelU

Open-source multimodal data annotation platform with AI auto-annotation support.

PythonApache-2.0★ 1,669 stars⑂ 182 forkssince Oct 2022View on GitHub ↗
KindCommand-line toolLibraryNetwork servicehow this is determined

opendatalab/labelU holds a health index of 62 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (69/100) and lowest on Security (33/100). It was last updated 39 days ago. A single contributor accounts for most of its recent work.

62
overall / 100
Moderate

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.

62
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 58 is calibrated to 62 on the published index scale (record calibration 2026-08-02).

Ownership

OpenDataLabOrganization
3,045 followers69 public repossince Jan 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIlabelu1.5.61,37612839 days ago

Metrics by category

Vitality

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

66Good · 21% of overall
How it's scored
18/36Push recencylast push 39 days ago
6.9/36Commit cadence10/52 weeks with commits
15.6/18Commit volume54 commits in the last year
10/10OpenSSF Scorecard: Maintained13 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year54
human_commit_share1
days_since_last_push39
active_weeks_last_year10
How it's scored
27/27Ships releases100 releases published
36/36Release recencylatest release 39 days ago
27/27Release cadencea release every ~10.9 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_tagv1.5.6
releases_from_tagsno
days_since_latest_release39
mean_days_between_releases10.9

Community & Adoption

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

62Moderate · 17% of overall
How it's scored
52.3/60Stars1,669 stars
18.8/25Forks182 forks
7/15Watchers19 watchers
Inputs used
forks182
stars1,669
watchers19
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
41.9/80Monthly downloads1,376 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packageslabelu
dependents
ecosystemspypi
total_downloads
monthly_downloads1,376
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?

69Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
9.2/22.5Commit distributiontop contributor authored 59% of commits
13.5/13.5Contributor breadth17 contributors
10/10OpenSSF Scorecard: Contributorsproject has 6 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled17
top_contributor_share0.592
How it's scored
29.8/42Issue resolution71% of issues closed
27.2/30PR acceptance165/182 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-ReviewFound 2/14 approved changesets -- score normalized to 1
Inputs used
merged_prs165
open_issues31
closed_issues76
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.71
closed_unmerged_prs17
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 backingorganization-owned
0/20Verified domain
25/25Owner reach3,045 followers of opendatalab
22.3/25Track record69 public repos, account ~4 yr old
Inputs used
followers3,045
owner_typeOrganization
is_verifiedno
owner_loginopendatalab
public_repos69
account_age_days1,698

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 39 days ago
20/20Version history128 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packageslabelu
ecosystemspypi
any_deprecatedno
min_days_since_publish39

Engineering Quality

Are baseline engineering and documentation practices in place?

55Moderate · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://opendatalab.github.io/labelU/
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepagehttps://opendatalab.github.io/labelU/
docs_sitehttps://opendatalab.github.io/labelU/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

33At Risk · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-ReviewFound 2/14 approved changesets -- score normalized to 1
2.5/2.5Contributorsproject has 6 contributing companies or organizations
0/10Dangerous-Workflowdangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained13 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities107 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate2.2
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging. Remaining weights renormalized.
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
10.2/25Indirect dependencies free of known advisories1 affected: ecdsa 0.19.2 (high 7.4)
33.8/40No advisories left outstanding1 advisory-carrying package(s) unaddressed past 90 days; oldest published 957 days ago
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages56
unassessed_packages0
affected_by_severityhigh 1
direct_affected_packages0
Matched the pypi:labelu@1.5.6 runtime dependency closure — what installing the published package pulls in — 56 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.

56Moderate · 4% of overall
How it's scored
45/45Agent instructionsCLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history98 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.98
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes3,783
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile, lockfile
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/127 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes48,950
source_files_sampled127
oversized_source_files0

Key facts

1,669GitHub stars
17contributors
54commits, last 12 months
39days since last push
100releases
1bus factor
31open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 182 ⇿
0Stars
182Forks
100Releases

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.

04080120160200182122022-112024-092026-07
Major 0Minor 4Patch 41

Each point covers 4 days.

OpenSSF Scorecard 2.2 / 10
2.2aggregate

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 · 2026-09-06 01:18 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 8 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 2/14 approved changesets -- score normalized to 1
10Contributorsproject has 6 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained13 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
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
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities107 existing vulnerabilities detected
Direct dependencies 21
RegistryPackageVersion constraintManifest
PyPIfastapi>=0.100.0pyproject.toml
PyPIloguru>=0.6.0pyproject.toml
PyPIsqlalchemy>=2.0.0pyproject.toml
PyPIboto3pyproject.toml
PyPIcryptography>=41.0.0pyproject.toml
PyPIpython-jose>=3.3.0pyproject.toml
PyPIpydantic>=2.0.0pyproject.toml
PyPIpydantic-settings>=2.0.0pyproject.toml
PyPItyper>=0.7.0pyproject.toml
PyPIuvicorn>=0.19.0pyproject.toml
PyPIemail-validator>=2.0.0pyproject.toml
PyPIpython-multipart>=0.0.5pyproject.toml
PyPIpython-dotenv>=0.21.0pyproject.toml
PyPIappdirs>=1.4.4pyproject.toml
PyPIaiofiles>=22.1.0pyproject.toml
PyPIpillow>=9.3.0pyproject.toml
PyPIalembic>=1.9.4pyproject.toml
PyPIhttpx>=0.27.0pyproject.toml
PyPItfrecord>=1.14.5pyproject.toml
PyPIwebsockets>=10.0.0pyproject.toml
PyPIbcrypt==4.3.0pyproject.toml
All dependencies 86

Full resolved dependency set from the GitHub dependency graph: 25 direct and 61 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiofiles25.1.0direct
PyPIalembic1.18.4direct
PyPIappdirs1.4.4direct
PyPIbcrypt4.3.0direct
PyPIboto31.42.90direct
PyPIcryptography46.0.5direct
PyPIemail-validator2.3.0direct
PyPIfastapidirect
PyPIfastapi0.125.0direct
PyPIhttpxdirect
PyPIhttpx0.28.1direct
PyPIloguru0.7.3direct
PyPIpillowdirect
PyPIpillow12.1.1direct
PyPIpydantic2.12.5direct
PyPIpydantic-settings2.13.1direct
PyPIpython-dotenv1.2.2direct
PyPIpython-jose3.5.0direct
PyPIpython-multipart0.0.22direct
PyPIsqlalchemy2.0.48direct
PyPItfrecord1.14.6direct
PyPItyper0.7.0direct
PyPIuvicorndirect
PyPIuvicorn0.42.0direct
PyPIwebsockets16.0direct
PyPIannotated-doc0.0.4indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.12.1indirect
PyPIblack26.3.1indirect
PyPIbotocore1.42.90indirect
PyPIcertifi2026.2.25indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.6indirect
PyPIclick8.3.1indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.13.5indirect
PyPIcrc32c2.8indirect
PyPIdnspython2.8.0indirect
PyPIecdsa0.19.1indirect
PyPIeinopsindirect
PyPIflake87.3.0indirect
PyPIgreenlet3.3.2indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIidna3.11indirect
PyPIiniconfig2.3.0indirect
PyPIjmespath1.1.0indirect
PyPIlabelu1.3.6indirect
PyPImako1.3.10indirect
PyPImarkupsafe3.0.3indirect
PyPImccabe0.7.0indirect
PyPImypy-extensions1.1.0indirect
PyPImysqlclient2.2.8indirect
PyPInumpyindirect
PyPInumpy2.4.3indirect
PyPIopencv-python-headlessindirect
PyPIpackaging26.0indirect
PyPIpathspec1.0.4indirect
PyPIplatformdirs4.9.4indirect
PyPIpluggy1.6.0indirect
PyPIprotobuf7.34.0indirect
PyPIpyasn10.6.3indirect
PyPIpycodestyle2.14.0indirect
PyPIpycparser3.0indirect
PyPIpydantic-core2.41.5indirect
PyPIpyflakes3.4.0indirect
PyPIpygments2.19.2indirect
PyPIpytest9.0.2indirect
PyPIpytest-cov7.0.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpytokens0.4.1indirect
PyPIrequests2.32.5indirect
PyPIrsa4.9.1indirect
PyPIs3transfer0.16.0indirect
PyPIsam3indirect
PyPIsix1.17.0indirect
PyPIstarlette0.50.0indirect
PyPItimmindirect
PyPItomli2.4.0indirect
PyPItorchindirect
PyPItorchvisionindirect
PyPItransformersindirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPIurllib32.6.3indirect
PyPIwin32-setctime1.2.0indirect
Dependency advisories 1

Installing pypi:labelu@1.5.6 pulls in 56 packages, direct and transitive: 1 carry known advisories, of which 0 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
ecdsa0.19.2indirecthigh2

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 statisticsPyPI.