Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 14:23 UTC

google / langextract

A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.

PythonApache-2.0★ 38,608 stars⑂ 2,704 forkssince Jul 2025View on GitHub ↗
KindPluginLibraryhow this is determined

google/langextract holds a health index of 93 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (92/100) and lowest on AI Readiness (61/100). It was last updated 3 days ago. A single contributor accounts for most of its recent work.

93
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.

93
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 79 is calibrated to 93 on the published index scale (record calibration 2026-08-02).

Ownership

GoogleOrganization · verified domain
78,696 followers2,904 public repossince Jan 2012

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIlangextract1.7.0-253 days ago

Metrics by category

Vitality

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

87Excellent · 21% of overall
How it's scored
36/36Push recency — last push 3 days ago
15.2/36Commit cadence — 22/52 weeks with commits
16.5/18Commit volume — 68 commits in the last year
10/10OpenSSF Scorecard: Maintained — 16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year68
human_commit_share1
days_since_last_push3
active_weeks_last_year22

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 19 releases published
36/36Release recency — latest release 3 days ago
27/27Release cadence — a release every ~42 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count19
latest_release_tagv1.7.0
releases_from_tagsno
days_since_latest_release3
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?

91Excellent · 17% of overall
How it's scored
60/60Stars — 38,608 stars
25/25Forks — 2,704 forks
12.4/15Watchers — 172 watchers
Inputs used
forks2,704
stars38,608
watchers172
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

65Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
3.3/22.5Commit distribution — top contributor authored 85% of commits
13.5/13.5Contributor breadth — 24 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled24
top_contributor_share0.853
How it's scored
25.9/42Issue resolution — 62% of issues closed
15.7/30PR acceptance — 125/239 decided PRs merged
2.2/13Newcomer PR acceptance — 2/12 first-time contributors' PRs merged in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 4/30 approved changesets -- score normalized to 1
Inputs used
merged_prs125
open_issues77
closed_issues124
prs_merged_7d3
prs_decided_7d8
prs_merged_30d5
prs_decided_30d18
issue_closed_ratio0.617
closed_unmerged_prs114
first_time_authors_30d11
first_time_prs_merged_30d2
first_time_prs_decided_30d12
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
25/25Owner reach — 78,696 followers of google
25/25Track record — 2,904 public repos, account ~14 yr old
Inputs used
followers78,696
owner_typeOrganization
is_verifiedyes
owner_logingoogle
public_repos2,904
account_age_days5,356

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 3 days ago
20/20Version history — 25 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslangextract
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall
How it's scored
24/24CI workflows — 11 workflow(s)
24/24Tests present
16/16Linter config — .pylintrc, pyproject.toml ([tool.isort]), tox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pypi.org/project/langextract/
10/10Repository description
10/10Topics — 11 topics
0/10Wiki
Inputs used
topicsllm, nlp, python, gemini-ai, information-extration, large-language-models, structured-data, gemini, gemini-api, gemini-flash, gemini-pro
has_wikino
homepagehttps://pypi.org/project/langextract/
docs_sitehttps://pypi.org/project/langextract/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

63Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
6/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 29 out of 29 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
0.8/7.5Code-Review — Found 4/30 approved changesets -- score normalized to 1
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
0/10Dangerous-Workflow — dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
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
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.4
Excluded from scoring (no data or not applicable): 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
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_packages55
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:langextract@1.7.0 runtime dependency closure — what installing the published package pulls in — 55 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.

61Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 95 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.95
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — .pylintrc, pyproject.toml ([tool.isort]), tox.ini
11/11Static type checking — langextract/py.typed
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configslangextract/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
27/45Type-checkable code — Python with type-check config (langextract/py.typed)
53.8/55Manageable file sizes — 2/91 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes91,722
source_files_sampled91
oversized_source_files2
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 — examples, notebooks
Inputs used
example_dirsexamples, 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

38,608GitHub stars
24contributors
68commits, last 12 months
3days since last push
19releases
1bus factor
77open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 13 authors (cap 12)
  • pypi download statistics for 'langextract' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 2,704 ⇿
0Stars
2,704Forks
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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

1,5001,7502,0002,2502,5002,7502,7041192026-022026-052026-09
Major 0Minor 6Patch 1
OpenSSF Scorecard 5.4 / 10
5.4aggregate

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 · 2026-09-17 14:22 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 4/30 approved changesets -- score normalized to 1
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 17
RegistryPackageVersion constraintManifest
PyPIabsl-py>=1.0.0pyproject.toml
PyPIaiohttp>=3.8.0pyproject.toml
PyPIasync_timeout>=4.0.0pyproject.toml
PyPIexceptiongroup>=1.1.0pyproject.toml
PyPIgoogle-genai>=1.39.0pyproject.toml
PyPIgoogle-cloud-storage>=2.14.0pyproject.toml
PyPIml-collections>=0.1.0pyproject.toml
PyPImore-itertools>=8.0.0pyproject.toml
PyPInumpy>=1.20.0pyproject.toml
PyPIpandas>=1.3.0pyproject.toml
PyPIpydantic>=1.8.0pyproject.toml
PyPIpython-dotenv>=0.19.0pyproject.toml
PyPIPyYAML>=6.0pyproject.toml
PyPIregex>=2023.0.0pyproject.toml
PyPIrequests>=2.25.0pyproject.toml
PyPItqdm>=4.64.0pyproject.toml
PyPItyping-extensions>=4.0.0pyproject.toml
All dependencies 31

Full resolved dependency set from the GitHub dependency graph: 17 direct and 14 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIabsl-py—direct
PyPIaiohttp—direct
PyPIasync-timeout—direct
PyPIexceptiongroup—direct
PyPIgoogle-cloud-storage—direct
PyPIgoogle-genai—direct
PyPIml-collections—direct
PyPImore-itertools—direct
PyPInumpy—direct
PyPIpandas—direct
PyPIpydantic—direct
PyPIpython-dotenv—direct
PyPIpyyaml—direct
PyPIregex—direct
PyPIrequests—direct
PyPItqdm—direct
PyPItyping-extensions—direct
PyPIimport-linter—indirect
PyPIipython—indirect
PyPIisort5.13.2indirect
PyPInotebook—indirect
PyPIopenai—indirect
PyPIpre-commit—indirect
PyPIpyink24.3.0indirect
PyPIpylint—indirect
PyPIpytest—indirect
PyPIpytype—indirect
PyPIsetuptools—indirect
PyPItomli—indirect
PyPItox—indirect
PyPItypes-regex—indirect
Dependency advisories 0

Installing pypi:langextract@1.7.0 pulls in 55 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.

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.