Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-28 10:48 UTC

roboflow / roboflow-python

The official Roboflow Python package. Manage your datasets, models, and deployments. Roboflow has everything you need to build a computer vision application.

PythonApache-2.0★ 626 stars⑂ 138 forkssince May 2020View on GitHub ↗
KindCommand-line toolhow this is determined

roboflow/roboflow-python holds a health index of 97 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Community & Adoption (73/100). It was last updated 3 days ago. 5 contributors account for most of its recent work.

97
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.

97
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 85 is calibrated to 97 on the published index scale (record calibration 2026-08-02).

Ownership

RoboflowOrganization · verified domain
5,288 followers170 public repossince Jul 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIroboflowpoints to another repo — not scored1.4.13,391,92614910 days ago

Metrics by category

Vitality

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

92Excellent · 21% of overall
How it's scored
36/36Push recencylast push 3 days ago
22.2/36Commit cadence32/52 weeks with commits
18/18Commit volume314 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year314
human_commit_share0.97
days_since_last_push3
active_weeks_last_year32

Release discipline

100Exceptional
How it's scored
27/27Ships releases100 releases published
36/36Release recencylatest release 10 days ago
27/27Release cadencea release every ~12.5 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count100
latest_release_tagv1.4.1
releases_from_tagsno
days_since_latest_release10
mean_days_between_releases12.5
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?

73Good · 17% of overall
How it's scored
45.4/60Stars626 stars
17.8/25Forks138 forks
6.4/15Watchers15 watchers
Inputs used
forks138
stars626
watchers15
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)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, shields.io
has_pull_request_templateyes

Sustainability & Governance

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

86Excellent · 23% of overall
How it's scored
45.9/54Bus factor5 contributor(s) cover half of all commits
19.3/22.5Commit distributiontop contributor authored 14% of commits
13.5/13.5Contributor breadth62 contributors
10/10OpenSSF Scorecard: Contributorsproject has 20 contributing companies or organizations
Inputs used
bus_factor5
contributors_sampled62
top_contributor_share0.143
How it's scored
20.8/42Issue resolution50% of issues closed
26.1/30PR acceptance342/393 decided PRs merged
6.5/13Newcomer PR acceptance2/4 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs342
open_issues54
closed_issues53
prs_merged_7d0
prs_decided_7d0
prs_merged_30d4
prs_decided_30d6
issue_closed_ratio0.495
closed_unmerged_prs51
first_time_authors_30d1
first_time_prs_merged_30d2
first_time_prs_decided_30d4
How it's scored
30/30Ownership backingorganization-owned
20/20Verified domain
25/25Owner reach5,288 followers of roboflow
25/25Track record170 public repos, account ~7 yr old
Inputs used
followers5,288
owner_typeOrganization
is_verifiedyes
owner_loginroboflow
public_repos170
account_age_days2,596

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests12 out of 12 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://docs.roboflow.com/python
10/10Repository description
10/10Topics4 topics
10/10Wiki
Inputs used
topicspython, machine-learning, computer-vision, deep-learning
has_wikiyes
homepagehttps://docs.roboflow.com/python
docs_sitehttps://docs.roboflow.com/python
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

77Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 20 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
4.5/5SASTSAST tool is not run on all commits -- score normalized to 9
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
6.8/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities45 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.1
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages32
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:roboflow@1.4.1 runtime dependency closure — what installing the published package pulls in — 32 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.

78Good · 4% of overall
How it's scored
45/45Agent instructionsCLAUDE.md
15/15Machine-readable docs (llms.txt)llms.txt served by the project website (https://docs.roboflow.com/llms.txt)
37.9/40Legible commit history69 of 97 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.roboflow.com/llms.txt
legible_history_share0.711
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes6,435
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environmentdevcontainer, Dockerfile
10/10Demonstrated agent practice25 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
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontaineryes
has_linter_configyes
typecheck_configs
agent_commit_share0.25
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
54.2/55Manageable file sizes2/138 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes77,889
source_files_sampled138
oversized_source_files2

Key facts

626GitHub stars
62contributors
314commits, last 12 months
3days since last push
100releases
5bus factor
54open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'roboflow' points at a different repository (https://github.com/roboflow-ai/roboflow-python); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 138 ⇿
0Stars
138Forks
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.

025507510012515013832021-092024-032026-08
Major 0Minor 3Patch 95

Each point covers 5 days.

OpenSSF Scorecard 7.1 / 10
7.1aggregate

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 · 2026-08-28 10:47 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
10CI-Tests12 out of 12 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 20 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 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
9SASTSAST tool is not run on all commits -- score normalized to 9
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities45 existing vulnerabilities detected
All dependencies 31

Full resolved dependency set from the GitHub dependency graph: 0 direct and 31 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcertifiindirect
PyPIclickindirect
PyPIcyclerindirect
PyPIfiletypeindirect
PyPIidnaindirect
PyPIkiwisolverindirect
PyPImatplotlibindirect
PyPImypyindirect
PyPInumpyindirect
PyPIopencv-python4.8.0.74indirect
PyPIopencv-python-headlessindirect
PyPIpi-heifindirect
PyPIpillowindirect
PyPIpillow-avif-pluginindirect
PyPIpython-dateutilindirect
PyPIpython-dotenvindirect
PyPIpyyamlindirect
PyPIrequestsindirect
PyPIrequests-toolbeltindirect
PyPIresponsesindirect
PyPIruffindirect
PyPIsetuptoolsindirect
PyPIsixindirect
PyPItqdmindirect
PyPItyperindirect
PyPItypes-pyyamlindirect
PyPItypes-requestsindirect
PyPItypes-setuptoolsindirect
PyPItypes-tqdmindirect
PyPIurllib3indirect
PyPIwheelindirect
Dependency advisories 0

Installing pypi:roboflow@1.4.1 pulls in 32 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 statisticsPyPI.