Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-28 08:42 UTC

SwanHubX / SwanLab

⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.

PythonApache-2.0★ 4,176 stars⑂ 216 forkssince Nov 2023View on GitHub ↗
KindCommand-line toolLibraryNetwork servicehow this is determined
#data-science#deep-learning#machine-learning#python#pytorch#tensorflow#transformers#mlops#model-versioning#tracking#visualization#tensorboard#logging#llm#training#ai-infra

SwanHubX/SwanLab holds a health index of 93 out of 100, placing it in the Exceptional band. It scores highest on Vitality (92/100) and lowest on Security (54/100). It was last updated today. 2 contributors account 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

SwanLabOrganization
142 followers14 public repossince Mar 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIswanlab0.9.8155,282682 days agomachine-learningreproducibilityvisualization
Gogithub.com/SwanHubX/SwanLabv0.9.8-1302 days ago—

Metrics by category

Vitality

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

92Excellent · 21% of overall

Development activity

94Exceptional
How it's scored
36/36Push recency — last push 0 days ago
29.8/36Commit cadence — 43/52 weeks with commits
18/18Commit volume — 278 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year278
human_commit_share1
days_since_last_push0
active_weeks_last_year43

Release discipline

90Excellent
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 2 days ago
27/27Release cadence — a release every ~4.5 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_tagv0.9.8
releases_from_tagsno
days_since_latest_release2
mean_days_between_releases4.5

Community & Adoption

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

87Excellent · 17% of overall

Popularity & adoption

83Excellent
How it's scored
58.7/60Stars — 4,176 stars
19.4/25Forks — 216 forks
5.3/15Watchers — 10 watchers
Inputs used
forks216
stars4,176
watchers10
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
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
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges9
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

86Excellent
How it's scored
69.2/80Monthly downloads — 155,282 downloads/month across go, pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesswanlab, github.com/SwanHubX/SwanLab
dependents—
ecosystemsgo, pypi
total_downloads—
monthly_downloads155,282
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

Maintainer resilience (bus factor)

60Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
11.4/22.5Commit distribution — top contributor authored 49% of commits
13.5/13.5Contributor breadth — 42 contributors
10/10OpenSSF Scorecard: Contributors — project has 12 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled42
top_contributor_share0.494

Issue & PR responsiveness

83Excellent
How it's scored
38.9/42Issue resolution — 93% of issues closed
28.5/30PR acceptance — 909/956 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-Review — Found 11/30 approved changesets -- score normalized to 3
Inputs used
merged_prs909
open_issues56
closed_issues701
prs_merged_7d8
prs_decided_7d9
prs_merged_30d26
prs_decided_30d30
issue_closed_ratio0.926
closed_unmerged_prs47
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

61Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
15.5/25Owner reach — 142 followers of SwanHubX
15.5/25Track record — 14 public repos, account ~3 yr old
Inputs used
followers142
owner_typeOrganization
is_verifiedno
owner_loginSwanHubX
public_repos14
account_age_days1,263

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 2 package(s) on go, pypi
35/35Publish recency — latest publish 2 days ago
20/20Version history — 130 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesswanlab, github.com/SwanHubX/SwanLab
ecosystemsgo, pypi
any_deprecatedno
min_days_since_publish2

Engineering Quality

Are baseline engineering and documentation practices in place?

91Excellent · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config — .golangci.yml, pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 27 out of 30 merged PRs checked by a CI test -- score normalized to 9
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://swanlab.cn
10/10Repository description
10/10Topics — 16 topics
0/10Wiki
Inputs used
topicsdata-science, deep-learning, machine-learning, python, pytorch, tensorflow, transformers, mlops, model-versioning, tracking, visualization, tensorboard, logging, llm, training, ai-infra
has_wikino
homepagehttps://swanlab.cn
docs_sitehttps://swanlab.cn
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

54Moderate · 16% of overall

Security posture

43Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.2/2.5CI-Tests — 27 out of 30 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-Review — Found 11/30 approved changesets -- score normalized to 3
2.5/2.5Contributors — project has 12 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
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 — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 80 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.3
Excluded from scoring (no data or not applicable): Packaging. 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_packages34
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:swanlab@0.9.8 runtime dependency closure — what installing the published package pulls in — 34 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

Agent context & guidance

55Moderate
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.swanlab.cn/llms.txt)
40/40Legible commit history — 100 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.swanlab.cn/llms.txt
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

63Moderate
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — .golangci.yml, pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
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
lockfilesgo.sum, uv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.01
toolchain_manifestscore/go.mod
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/441 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes47,405
source_files_sampled441
oversized_source_files0

Machine-readable interfaces

40Weak
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — protos/swanlab/grpc/core/v1/core.proto, protos/swanlab/grpc/core/v1/sync.proto, protos/swanlab/grpc/probe/v1/probe.proto, protos/swanlab/metric/column/v1/column.proto, protos/swanlab/metric/data/v1/data.proto, protos/swanlab/operation/v1/operation.proto, protos/swanlab/probe/v1/metadata.proto, protos/swanlab/record/v1/record.proto, protos/swanlab/run/v1/run.proto, protos/swanlab/save/v1/save.proto, protos/swanlab/settings/core/v1/core.proto, protos/swanlab/settings/probe/v1/probe.proto, protos/swanlab/terminal/v1/log.proto
0/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalno
api_schema_filesprotos/swanlab/grpc/core/v1/core.proto, protos/swanlab/grpc/core/v1/sync.proto, protos/swanlab/grpc/probe/v1/probe.proto, protos/swanlab/metric/column/v1/column.proto, protos/swanlab/metric/data/v1/data.proto, protos/swanlab/operation/v1/operation.proto, protos/swanlab/probe/v1/metadata.proto, protos/swanlab/record/v1/record.proto, protos/swanlab/run/v1/run.proto, protos/swanlab/save/v1/save.proto, protos/swanlab/settings/core/v1/core.proto, protos/swanlab/settings/probe/v1/probe.proto, protos/swanlab/terminal/v1/log.proto
interfaces_expected_ofnetwork-service

Key facts

4,176GitHub stars
42contributors
278commits, last 12 months
0days since last push
100releases
2bus factor
56open issues
Go, npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch npm package 'swanlab' from its registry

More detail

Star and fork history 0 ★ / 216 ⇿
0Stars
216Forks
99Releases

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.

0408012016020024021652023-122025-042026-08
Major 0Minor 6Patch 84

Each point covers 3 days.

OpenSSF Scorecard 4.3 / 10
4.3aggregate

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 08:41 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
9CI-Tests27 out of 30 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 11/30 approved changesets -- score normalized to 3
10Contributorsproject has 12 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 24 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
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities80 existing vulnerabilities detected
Direct dependencies 25
RegistryPackageVersion constraintManifest
Gogolang.org/x/sysv0.47.0core/go.mod
Gogoogle.golang.org/grpcv1.83.0core/go.mod
Gogoogle.golang.org/protobufv1.36.12core/go.mod
PyPIurllib3>=1.26.0pyproject.toml
PyPIrequests>=2.28.0pyproject.toml
PyPIsetuptools—pyproject.toml
PyPIclick—pyproject.toml
PyPIpyyaml—pyproject.toml
PyPIpsutil>=5.0.0pyproject.toml
PyPInvidia-ml-py—pyproject.toml
PyPIpydantic~=2.0pyproject.toml
PyPIpyecharts>=2.0.0pyproject.toml
PyPIwrapt>=1.17.0pyproject.toml
PyPIplatformdirs>=4.2.0pyproject.toml
PyPIprotobuf>=6.31.1,!=6.31.0,<7pyproject.toml
PyPIprotobuf>=6.31.1,!=6.31.0,<7pyproject.toml
PyPIprotobuf>=6.31.1,!=6.31.0,<7pyproject.toml
PyPIrich>=13.6.0pyproject.toml
PyPIpydantic-settings>=2.8.1pyproject.toml
PyPIorjson<=3.11.5pyproject.toml
PyPIorjson—pyproject.toml
PyPIwatchdog—pyproject.toml
PyPIpwinput>=1.0.3pyproject.toml
PyPIpyroaring>=1.0.0,<1.0.4pyproject.toml
PyPIpyroaring>=1.0.4pyproject.toml
All dependencies 218

Full resolved dependency set from the GitHub dependency graph: 27 direct and 191 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIscipy1.17.1indirect
PyPIsentry-sdk2.54.0indirect
PyPIsimplejson3.20.2indirect
PyPIsix1.17.0indirect
PyPIsmmap5.0.2indirect
PyPIsoundfile0.13.1indirect
PyPIstack-data0.6.3indirect
PyPIstarlette0.49.3indirect
PyPIstarlette0.52.1indirect
PyPIswanboard0.1.10b2indirect
PyPIsympy1.14.0indirect
PyPItermcolor3.1.0indirect
PyPItermcolor3.3.0indirect
PyPIthreadpoolctl3.6.0indirect
PyPItomli2.4.0indirect
PyPItorch2.10.0indirect
PyPItorch2.8.0indirect
PyPItorchvision0.23.0indirect
PyPItorchvision0.25.0indirect
PyPItornado6.5.4indirect
PyPItqdm4.67.3indirect
PyPItraitlets5.14.3indirect
PyPItriton3.4.0indirect
PyPItriton3.6.0indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.3indirect
PyPIujson5.11.0indirect
PyPIuvicorn0.39.0indirect
PyPIuvicorn0.41.0indirect
PyPIvirtualenv21.1.0indirect
PyPIwandb0.25.0indirect
PyPIwcwidth0.6.0indirect
PyPIyapf0.43.0indirect
PyPIzipp3.23.0indirect
Dependency advisories 0

Installing pypi:swanlab@0.9.8 pulls in 34 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.

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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 v0.34.0 — full methodology · metrics wiki.

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