Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-16 10:47 UTC

ml6team / fondant

Production-ready data processing made easy and shareable

PythonApache-2.0★ 359 stars⑂ 28 forkssince Mar 2023View on GitHub ↗
KindLibraryCommand-line toolhow this is determined

ml6team/fondant holds a health index of 48 out of 100, placing it in the Weak band. It scores highest on Engineering Quality (91/100) and lowest on Security (17/100). It was last updated 177 days ago. 2 contributors account for most of its recent work.

48
overall / 100
Weak

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.

48
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 55 is calibrated to 57 on the published index scale (record calibration 2026-08-02).

Ownership

ML6Organization
93 followers23 public repossince Feb 2018

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIfondant0.12.148545845 days agodatamachine-learningfine-tuningfoundation-models

Metrics by category

Vitality

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

31At Risk · 21% of overall
How it's scored
9.9/36Push recencylast push 177 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push177
active_weeks_last_year0
How it's scored
27/27Ships releases42 releases published
0/36Release recencylatest release 845 days ago
27/27Release cadencea release every ~6.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count42
latest_release_tag0.12.1
releases_from_tagsno
days_since_latest_release845
mean_days_between_releases6.7

Community & Adoption

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

52Moderate · 17% of overall
How it's scored
41.4/60Stars359 stars
11.9/25Forks28 forks
3.9/15Watchers6 watchers
Inputs used
forks28
stars359
watchers6
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_badges4
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
35.8/80Monthly downloads485 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesfondant
dependents
ecosystemspypi
total_downloads
monthly_downloads485
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?

74Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
15.7/22.5Commit distributiontop contributor authored 30% of commits
13.5/13.5Contributor breadth20 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor2
contributors_sampled20
top_contributor_share0.303
How it's scored
34.7/42Issue resolution83% of issues closed
27/30PR acceptance553/615 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs553
open_issues55
closed_issues262
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.826
closed_unmerged_prs62
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 domainverified-domain status not read for this organization
14.2/25Owner reach93 followers of ml6team
22.1/25Track record23 public repos, account ~8 yr old
Inputs used
followers93
owner_typeOrganization
is_verified
owner_loginml6team
public_repos23
account_age_days3,097
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
4/35Publish recencylatest publish 845 days ago
20/20Version history45 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesfondant
ecosystemspypi
any_deprecatedno
min_days_since_publish845

Engineering Quality

Are baseline engineering and documentation practices in place?

91Excellent · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter configtox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
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 sitehttps://fondant.ai/en/stable/
10/10Repository description
10/10Topics6 topics
0/10Wiki
Inputs used
topicsdata-processing, fine-tuning, foundation-models, machine-learning, pipeline, python
has_wikino
homepagehttps://fondant.ai/en/stable/
docs_sitehttps://fondant.ai/en/stable/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

17Critical · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsdata_explorer/requirements.txt, pyproject.toml
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
12.8/25Indirect dependencies free of known advisories1 affected: distributed 2024.2.1 (moderate 6.1)
34.7/40No advisories left outstanding1 advisory-carrying package(s) unaddressed past 90 days; oldest published 211 days ago
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages41
unassessed_packages0
affected_by_severitymoderate 1
direct_affected_packages0
Matched the pypi:fondant@0.12.1 runtime dependency closure — what installing the published package pulls in — 41 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.

54Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history95 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 configtox.ini
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/108 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes36,796
source_files_sampled108
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples
Inputs used
example_dirsexamples
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

359GitHub stars
20contributors
0commits, last 12 months
177days since last push
42releases
2bus factor
55open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard did not return a usable result (2026/08/16 10:46:41 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 28 ⇿
0Stars
28Forks
42Releases

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.

0510152025302842023-052024-082025-12
Major 0Minor 12Patch 12

Each point covers 3 days.

Direct dependencies 15
RegistryPackageVersion constraintManifest
PyPIfsspec>= 2023.4.0pyproject.toml
PyPIimportlib-resources>= 1.3pyproject.toml
PyPIjsonschema>= 4.18pyproject.toml
PyPIpyarrow>= 11.0.0pyproject.toml
PyPIpyyaml>= 5.3.1pyproject.toml
PyPIdask>= 2023.4.1, <2024.3.0pyproject.toml
PyPIdocker>= 6.1.3pyproject.toml
PyPIdask-cuda>=23.4.1pyproject.toml
PyPIgcsfs>= 2023.10.0pyproject.toml
PyPIs3fs>= 2023.4.0pyproject.toml
PyPIadlfs>= 2023.4.0pyproject.toml
PyPIkfp2.6.0pyproject.toml
PyPIgoogle-cloud-aiplatform1.34.0pyproject.toml
PyPIsagemaker>= 2.197.0pyproject.toml
PyPIboto31.28.64pyproject.toml
All dependencies 63

Full resolved dependency set from the GitHub dependency graph: 18 direct and 45 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIadlfsdirect
PyPIboto31.28.64direct
PyPIboto31.34.4direct
PyPIdaskdirect
PyPIdask2023.5.0direct
PyPIdask-cudadirect
PyPIdockerdirect
PyPIfsspecdirect
PyPIfsspec2023.6.0direct
PyPIgcsfsdirect
PyPIgoogle-cloud-aiplatform1.34.0direct
PyPIimportlib-resourcesdirect
PyPIjsonschemadirect
PyPIkfp2.6.0direct
PyPIpyarrowdirect
PyPIpyyamldirect
PyPIs3fsdirect
PyPIsagemakerdirect
PyPIalbumentations1.3.0indirect
PyPIaleph-alpha-client3.5.1indirect
PyPIbeautifulsoup44.12.2indirect
PyPIcohere4.27indirect
PyPIdatasets2.10.1indirect
PyPIdatasketch1.5.9indirect
PyPIfaiss-cpu1.7.4indirect
PyPIfasttext-wheel0.9.2indirect
PyPIfpdf1.7.2indirect
PyPIgraphviz0.20.1indirect
PyPIhttpx0.24.1indirect
PyPIhuggingface-hub0.14.1indirect
PyPIhuggingface-hub0.21.3indirect
PyPIimagesize1.4.1indirect
PyPIlangchain0.0.329indirect
PyPImatplotlib3.7.1indirect
PyPInltk3.8.1indirect
PyPInumpy1.24.4indirect
PyPIopenai0.28.1indirect
PyPIopencv-python-headlessindirect
PyPIopensearch-py2.4.2indirect
PyPIpandas1.5.0indirect
PyPIpandas2.0.3indirect
PyPIpillow10.0.1indirect
PyPIplotly5.15.0indirect
PyPIpymupdf1.23.8indirect
PyPIpytest7.4.0indirect
PyPIpytest7.4.2indirect
PyPIpytest-mock3.12.0indirect
PyPIqdrant-client1.6.9indirect
PyPIrespx0.20.2indirect
PyPIretry0.9.2indirect
PyPIsentence-transformers2.2.2indirect
PyPIst-pages0.4.5indirect
PyPIstreamlit1.28.2indirect
PyPIstreamlit-aggrid0.3.4indirect
PyPIstreamlit-extras0.3.5indirect
PyPItiktoken0.5.1indirect
PyPItorch2.0.1indirect
PyPItorch2.2.1indirect
PyPItqdm4.65.0indirect
PyPItransformers4.28.0indirect
PyPItransformers4.29.2indirect
PyPItransformers4.38.1indirect
PyPIweaviate-client3.24.2indirect
Dependency advisories 1

Installing pypi:fondant@0.12.1 pulls in 41 packages, direct and transitive: 1 carry known advisories, of which 0 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
distributed2024.2.1indirectmoderate22026.1.0

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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.