Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-05 02:19 UTC

dmlc / xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

C++ · Python · CudaApache-2.0★ 28,626 stars⑂ 8,877 forkssince Feb 2014View on GitHub ↗

dmlc/xgboost holds a health index of 98 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (100/100) and lowest on AI Readiness (76/100). It was last updated today. 2 contributors account for most of its recent work.

98
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.

98
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 88 is calibrated to 98 on the published index scale (record calibration 2026-08-02).

Ownership

1,757 followers51 public repossince Mar 2015

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIxgboost3.4.0-920 days ago

Metrics by category

Vitality

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

99Exceptional · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
35.3/36Commit cadence51/52 weeks with commits
18/18Commit volume439 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year439
human_commit_share0.93
days_since_last_push0
active_weeks_last_year51

Release discipline

100Exceptional
How it's scored
27/27Ships releases77 releases published
36/36Release recencylatest release 0 days ago
27/27Release cadencea release every ~39.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count77
latest_release_tagv3.4.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases39.8

Community & Adoption

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

80Excellent · 17% of overall

Popularity & adoption

100Exceptional
How it's scored
60/60Stars28,626 stars
25/25Forks8,877 forks
15/15Watchers882 watchers
Inputs used
forks8,877
stars28,626
watchers882
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
7.2/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges12
has_contributingno
has_issue_templateyes
has_code_of_conductno
readme_badge_servicesapi.securityscorecards.dev, badge.fury.io, github.com, opencollective.com, readthedocs.org, shields.io
has_pull_request_templateno

Sustainability & Governance

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

82Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
16.1/22.5Commit distributiontop contributor authored 28% of commits
13.5/13.5Contributor breadth98 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor2
contributors_sampled98
top_contributor_share0.285
How it's scored
39.1/42Issue resolution93% of issues closed
24.2/30PR acceptance5,359/6,657 decided PRs merged
3.7/13Newcomer PR acceptance2/7 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs5,359
open_issues394
closed_issues5,299
prs_merged_7d19
prs_decided_7d26
prs_merged_30d40
prs_decided_30d58
issue_closed_ratio0.931
closed_unmerged_prs1,298
first_time_authors_30d7
first_time_prs_merged_30d2
first_time_prs_decided_30d7
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
23.3/25Owner reach1,757 followers of dmlc
24.5/25Track record51 public repos, account ~11 yr old
Inputs used
followers1,757
owner_typeOrganization
is_verified
owner_logindmlc
public_repos51
account_age_days4,159
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 0 days ago
20/20Version history92 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesxgboost
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

100Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows17 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://xgboost.readthedocs.io/
10/10Repository description
10/10Topics6 topics
10/10Wiki
Inputs used
topicsgbdt, gbrt, gbm, distributed-systems, xgboost, machine-learning
has_wikiyes
homepagehttps://xgboost.readthedocs.io/
docs_sitehttps://xgboost.readthedocs.io/
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
How it's scored
30/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsdoc/requirements.txt, jvm-packages/pom.xml, python-package/pyproject.toml
has_codeql_workflowno
has_security_policyyes
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages21
unassessed_packages32
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 21 resolved dependencies against OSV. 32 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

76Good · 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 history89 of 93 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.957
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdemo/c-api/basic/Makefile, doc/Makefile, doc/R-package/Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checkingpython-package/xgboost/py.typed
0/10Reproducible environment
6/10Demonstrated agent practice3 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance7 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageyes
bootstrap_filesdemo/c-api/basic/Makefile, doc/Makefile, doc/R-package/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configspython-package/xgboost/py.typed
agent_commit_share0.03
toolchain_manifestsjvm-packages/pom.xml, jvm-packages/xgboost4j-example/pom.xml, jvm-packages/xgboost4j-flink/pom.xml, jvm-packages/xgboost4j-spark-gpu/pom.xml, jvm-packages/xgboost4j-spark/pom.xml, jvm-packages/xgboost4j/pom.xml
dependency_bot_commit_share0.07
How it's scored
45/45Type-checkable codeC++ (statically typed)
54.5/55Manageable file sizes8/825 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes117,685
source_files_sampled825
oversized_source_files8
How it's scored
40/40API schema (OpenAPI/GraphQL/proto)plugin/federated/federated.proto
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexample
Inputs used
example_dirsexample
has_mcp_signalno
api_schema_filesplugin/federated/federated.proto
interfaces_expected_of
Excluded from scoring (no data or not applicable): MCP server. Remaining weights renormalized.

Key facts

28,626GitHub stars
98contributors
439commits, last 12 months
0days since last push
77releases
2bus factor
394open issues
Maven, 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 14 authors (cap 12)
  • deps.dev does not index pypi:xgboost@3.4.0; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard did not return a usable result (2026/08/05 02:18:05 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 ★ / 8,877 ⇿
0Stars
8,877Forks
34Releases

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.

7,5008,0008,5009,0008,87792022-052024-062026-08
Major 2Minor 5Patch 22

Each point covers 4 days.

Direct dependencies 5
RegistryPackageVersion constraintManifest
Mavencom.esotericsoftware:kryo5.6.2jvm-packages/pom.xml
Mavencommons-logging:commons-logging1.3.4jvm-packages/pom.xml
PyPInumpypython-package/pyproject.toml
PyPIscipypython-package/pyproject.toml
PyPInvidia-nccl-cu13python-package/pyproject.toml
All dependencies 53

Full resolved dependency set from the GitHub dependency graph: 4 direct and 49 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
Mavencom.esotericsoftware:kryo5.6.2direct
Mavencommons-logging:commons-logging1.3.4direct
PyPInumpydirect
PyPIscipydirect
Mavencom.fasterxml.jackson.core:jackson-databindindirect
Mavenjunit:junitindirect
Mavenml.dmlc:xgboost4j-flink_2.123.5.0-SNAPSHOTindirect
Mavenml.dmlc:xgboost4j-spark_2.123.5.0-SNAPSHOTindirect
Mavenml.dmlc:xgboost4j_2.123.5.0-SNAPSHOTindirect
Mavennet.alchim31.maven:scala-maven-plugin4.9.2indirect
Mavenorg.apache.flink:flink-clientsindirect
Mavenorg.apache.flink:flink-ml-servable-core2.2.0indirect
Mavenorg.apache.hadoop:hadoop-commonindirect
Mavenorg.apache.hadoop:hadoop-hdfsindirect
Mavenorg.apache.maven.plugins:maven-assembly-pluginindirect
Mavenorg.apache.maven.plugins:maven-checkstyle-plugin3.6.0indirect
Mavenorg.apache.maven.plugins:maven-gpg-plugin3.2.7indirect
Mavenorg.apache.maven.plugins:maven-jar-plugin3.4.2indirect
Mavenorg.apache.maven.plugins:maven-javadoc-plugin3.11.3indirect
Mavenorg.apache.maven.plugins:maven-release-plugin3.1.1indirect
Mavenorg.apache.maven.plugins:maven-resources-plugin3.3.1indirect
Mavenorg.apache.maven.plugins:maven-shade-pluginindirect
Mavenorg.apache.maven.plugins:maven-site-plugin3.21.0indirect
Mavenorg.apache.maven.plugins:maven-source-plugin3.3.1indirect
Mavenorg.apache.maven.plugins:maven-surefire-pluginindirect
Mavenorg.apache.maven.plugins:maven-surefire-plugin3.5.2indirect
Mavenorg.codehaus.mojo:exec-maven-plugin3.5.0indirect
Mavenorg.scala-lang:scala-compilerindirect
Mavenorg.scala-lang:scala-libraryindirect
Mavenorg.scalactic:scalactic_2.123.2.19indirect
Mavenorg.scalatest:scalatest-maven-pluginindirect
Mavenorg.scalatest:scalatest-maven-plugin2.2.0indirect
Mavenorg.scalatest:scalatest_2.123.2.19indirect
Mavenorg.sonatype.central:central-publishing-maven-plugin0.11.0indirect
PyPIbreatheindirect
PyPIcloudpickleindirect
PyPIdaskindirect
PyPIgraphvizindirect
PyPImatplotlibindirect
PyPImockindirect
PyPImyst-parserindirect
PyPIpandasindirect
PyPIpysparkindirect
PyPIrayindirect
PyPIscikit-build-coreindirect
PyPIscikit-learnindirect
PyPIsetuptoolsindirect
PyPIshindirect
PyPIsphinxindirect
PyPIsphinx-galleryindirect
PyPIsphinx-issuesindirect
PyPIsphinx-rtd-themeindirect
PyPIsphinx-tabsindirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 21 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 32 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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 v0.31.0 — full methodology · metrics wiki.

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