Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 01:47 UTC

moj-analytical-services / splink

Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends

Python · JavaScriptMIT★ 2,336 stars⑂ 253 forkssince Nov 2019View on GitHub ↗
KindLibraryhow this is determined
#record-linkage#spark#em-algorithm#deduplication#deduplicate-data#entity-resolution#data-matching#fuzzy-matching#data-science#duckdb#uk-gov-data-science

moj-analytical-services/splink holds a health index of 96 out of 100, placing it in the Exceptional band. It scores highest on Vitality (99/100) and lowest on AI Readiness (65/100). It was last updated today. 2 contributors account for most of its recent work.

96
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.

96
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 84 is calibrated to 96 on the published index scale (record calibration 2026-08-02).

Ownership

MoJ Analytical ServicesOrganization
537 followers21 public repossince Feb 2017

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIsplink4.0.16-162154 days ago

Metrics by category

Vitality

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

99Exceptional · 21% of overall

Development activity

99Exceptional
How it's scored
36/36Push recency — last push 0 days ago
35.3/36Commit cadence — 51/52 weeks with commits
18/18Commit volume — 1,424 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,424
human_commit_share0.79
days_since_last_push0
active_weeks_last_year51

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 42 days ago
27/27Release cadence — a release every ~21.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv5.0.0.dev4
releases_from_tagsno
days_since_latest_release42
mean_days_between_releases21.8
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?

79Good · 17% of overall

Popularity & adoption

81Excellent
How it's scored
54.6/60Stars — 2,336 stars
20/25Forks — 253 forks
6.5/15Watchers — 16 watchers
Inputs used
forks253
stars2,336
watchers16
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 (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateyes

Sustainability & Governance

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

82Excellent · 23% of overall

Maintainer resilience (bus factor)

62Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
12.8/22.5Commit distribution — top contributor authored 43% of commits
13.5/13.5Contributor breadth — 76 contributors
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled76
top_contributor_share0.432

Issue & PR responsiveness

85Excellent
How it's scored
32.2/42Issue resolution — 77% of issues closed
27.1/30PR acceptance — 1,684/1,866 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs1,684
open_issues191
closed_issues624
prs_merged_7d0
prs_decided_7d0
prs_merged_30d9
prs_decided_30d10
issue_closed_ratio0.766
closed_unmerged_prs182
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.

Ownership & stewardship

89Excellent
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
19.6/25Owner reach — 537 followers of moj-analytical-services
21.8/25Track record — 21 public repos, account ~9 yr old
Inputs used
followers537
owner_typeOrganization
is_verified—
owner_loginmoj-analytical-services
public_repos21
account_age_days3,460
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 154 days ago
20/20Version history — 162 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagessplink
ecosystemspypi
any_deprecatedno
min_days_since_publish154

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 15 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 19 out of 19 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://moj-analytical-services.github.io/splink/
10/10Repository description
10/10Topics — 11 topics
10/10Wiki
Inputs used
topicsrecord-linkage, spark, em-algorithm, deduplication, deduplicate-data, entity-resolution, data-matching, fuzzy-matching, data-science, duckdb, uk-gov-data-science
has_wikiyes
homepagehttps://moj-analytical-services.github.io/splink/
docs_sitehttps://moj-analytical-services.github.io/splink/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

78Good · 16% of overall

Security posture

72Good
How it's scored
5.2/7.5Binary-Artifacts — binaries present in source code
4.5/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 19 out of 19 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
2.5/2.5Contributors — project has 6 contributing companies or organizations
10/10Dangerous-Workflow — no 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 — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
4/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 8
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
1.5/7.5Vulnerabilities — 8 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.2
Excluded from scoring (no data or not applicable): 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
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_packages19
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:splink@4.0.16 runtime dependency closure — what installing the published package pulls in — 19 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.

65Good · 4% of overall

Agent context & guidance

22At Risk
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
21.6/40Legible commit history — 32 of 79 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.405
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

77Good
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
0/11Lint / format config
11/11Static type checking — splink/py.typed
10/10Reproducible environment — Dockerfile, lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 21 of the last 100 commits are automated dependency updates
8/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 8
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configno
typecheck_configssplink/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.21

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (splink/py.typed)
54.3/55Manageable file sizes — 3/252 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes920,153
source_files_sampled252
oversized_source_files3

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 — demos, examples
Inputs used
example_dirsdemos, examples
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

2,336GitHub stars
76contributors
1,424commits, last 12 months
0days since last push
100releases
2bus factor
191open 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 ★ / 253 ⇿
0Stars
253Forks
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.

05010015020025030025152020-032023-052026-08
Major 2Minor 9Patch 58

Each point covers 6 days.

OpenSSF Scorecard 7.2 / 10
7.2aggregate

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 · 2026-08-13 01:46 UTC

7Binary-Artifactsbinaries present in source code
6Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests19 out of 19 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
10Contributorsproject has 6 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
8Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 8
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
2Vulnerabilities8 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIduckdb>=0.9.2pyproject.toml
PyPIsqlglot>=17.6.0pyproject.toml
PyPIaltair>=5.0.1pyproject.toml
PyPIJinja2>=3.0.3pyproject.toml
PyPIigraph>=0.11.2pyproject.toml
All dependencies 196

Full resolved dependency set from the GitHub dependency graph: 6 direct and 190 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaltair6.2.2direct
PyPIduckdb1.5.4direct
PyPIigraph1.0.0direct
PyPIjinja23.1.6direct
PyPIsqlglot30.11.0direct
PyPIsqlglot30.14.0direct
PyPIannotated-types0.7.0indirect
PyPIanyio4.13.0indirect
PyPIappnope0.1.4indirect
PyPIast-serialize0.5.0indirect
PyPIasttokens3.0.1indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbackrefs7.0indirect
PyPIbeautifulsoup44.14.3indirect
PyPIbleach6.4.0indirect
PyPIblosc24.3.3indirect
PyPIblosc24.5.1indirect
PyPIcachecontrol0.14.4indirect
PyPIcertifi2026.5.20indirect
PyPIcertifi2026.6.17indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIclick8.4.1indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcomm0.2.3indirect
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PyPIdebugpy1.8.21indirect
PyPIdecorator5.3.1indirect
PyPIdefusedxml0.7.1indirect
PyPIessentials1.1.9indirect
PyPIessentials-openapi1.4.0indirect
PyPIexceptiongroup1.3.1indirect
PyPIexecnet2.1.2indirect
PyPIexecuting2.2.1indirect
PyPIfastjsonschema2.21.2indirect
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PyPIghp-import2.1.0indirect
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PyPIgriffelib2.1.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
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PyPIidna3.17indirect
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PyPIjsonschema-specifications2025.9.1indirect
PyPIjupyter-client8.8.0indirect
PyPIjupyter-client8.9.1indirect
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PyPIjupyterlab-widgets3.0.16indirect
PyPIjupytext1.19.4indirect
PyPIlayered-config-tree4.1.3indirect
PyPIlibrt0.11.0indirect
PyPIlinkify-it-py2.1.0indirect
PyPIloguru0.7.3indirect
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PyPImarkdown-it-py3.0.0indirect
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PyPImergedeep1.3.4indirect
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PyPImkdocs-get-deps0.2.2indirect
PyPImkdocs-llmstxt0.5.0indirect
PyPImkdocs-material9.7.7indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImkdocs-rss-plugin1.19.0indirect
PyPImkdocs-video1.5.0indirect
PyPImkdocstrings1.0.6indirect
PyPImkdocstrings-python2.0.5indirect
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PyPImsgpack1.2.1indirect
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PyPIpackaging26.2indirect
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PyPIpandas-stubs2.2.3.250308indirect
PyPIpandocfilters1.5.1indirect
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PyPIpycparser3.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
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PyPIpymdown-extensions10.21.3indirect
PyPIpyspark3.5.8indirect
PyPIpyspark4.1.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-xdist3.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpytz2026.2indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIpyzmq27.1.0indirect
PyPIrapidfuzz3.14.5indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrich15.0.0indirect
PyPIrpds-py0.30.0indirect
PyPIrpds-py2026.5.1indirect
PyPIruff0.15.18indirect
PyPIscipy1.15.3indirect
PyPIscipy1.17.1indirect
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PyPIsmmap5.0.3indirect
PyPIsoupsieve2.8.4indirect
PyPIsplink5.0.0.dev4indirect
PyPIsplink-demos5.0.0indirect
PyPIsqlalchemy2.0.51indirect
PyPIstack-data0.6.3indirect
PyPItables3.10.1indirect
PyPItables3.11.1indirect
PyPItexttable1.7.0indirect
PyPItextual8.2.7indirect
PyPItextual-plotext1.0.1indirect
PyPIthreadpoolctl3.6.0indirect
PyPItinycss21.4.0indirect
PyPItomli2.4.1indirect
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PyPItqdm4.68.3indirect
PyPItraitlets5.15.0indirect
PyPItraitlets5.15.1indirect
PyPIty0.0.52indirect
PyPItypes-pytz2026.2.0.20260518indirect
PyPItypes-pyyaml6.0.12.20260518indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.3indirect
PyPItzdata2026.2indirect
PyPIuc-micro-py2.0.0indirect
PyPIurllib32.7.0indirect
PyPIvivarium2.3.7indirect
PyPIvivarium-build-utils1.1.2indirect
PyPIvivarium-dependencies1.0.4indirect
PyPIwatchdog6.0.0indirect
PyPIwcwidth0.7.0indirect
PyPIwcwidth0.8.1indirect
PyPIwebencodings0.5.1indirect
PyPIwidgetsnbextension4.0.15indirect
PyPIwin32-setctime1.2.0indirect
Dependency advisories 0

Installing pypi:splink@4.0.16 pulls in 19 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

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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 v0.31.0 — full methodology · metrics wiki.

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