Public recordExcellent
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-24 20:29 UTC
h2oai / h2o-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
h2oai/h2o-3 holds a health index of 87 out of 100, placing it in the Excellent band. It scores highest on Sustainability & Governance (87/100) and lowest on Vitality (53/100). It was last updated today. 5 contributors account for most of its recent work.
87
overall / 100Software 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.
87
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)
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 73 is calibrated to 87 on the published index scale (record calibration 2026-08-02).
Ownership
H2O.aiOrganization · verified domain
1,899 followers196 public repossince Feb 2012
This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.
Package ecosystems
| Registry | Package | Version | Downloads / mo | Versions | Last publish | Tags |
|---|---|---|---|---|---|---|
| PyPI | h2o_client | 3.46.0.12 | 2,815 | 23 | 12 days ago | machine-learningdata-miningstatistical-analysismodelingbig-datadistributedparallel |
| PyPI | sphinx_rtd_themepoints to another repo — not scored | 3.1.0 | 13,373,943 | 63 | 224 days ago | — |
| PyPI | h2o_mlflow_flavor | 0.1.0 | 271 | 1 | 1015 days ago | ml-flowh2o-3 |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
53
Development activity
87Excellent
How it's scored
| 36/36 | Push recency — last push 0 days ago |
| 22.8/36 | Commit cadence — 33/52 weeks with commits |
| 18/18 | Commit volume — 153 commits in the last year |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 12 issue activity found in the last 90 days -- score normalized to 10 |
Inputs used
| commits_last_year | 153 |
| human_commit_share | 1 |
| days_since_last_push | 0 |
| active_weeks_last_year | 33 |
Release discipline
1Critical
How it's scored
| 0/27 | Ships releases — no releases published |
| 0/36 | Release recency — no releases |
| 0/27 | Release cadence — no releases |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 0 |
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?
79
Popularity & adoption
99Exceptional
How it's scored
| 60/60 | Stars — 7,495 stars |
| 25/25 | Forks — 2,025 forks |
| 14.2/15 | Watchers — 361 watchers |
Inputs used
| forks | 2,025 |
| stars | 7,495 |
| watchers | 361 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
70Good
How it's scored
| 22.5/22.5 | README |
| 22.5/22.5 | License — recognized license (Apache-2.0) |
| 18/18 | CONTRIBUTING guide |
| 0/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 0/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| readme_badges | 3 |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | no |
| readme_badge_services | shields.io |
| has_pull_request_template | no |
Ecosystem adoption (downloads)
58Moderate
How it's scored
| 46.5/80 | Monthly downloads — 3,086 downloads/month across pypi |
| 0/20 | Registry dependents — not reported by this ecosystem |
Inputs used
| packages | h2o_client, h2o_mlflow_flavor |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 3,086 |
| 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?
87
Maintainer resilience (bus factor)
88Excellent
How it's scored
| 45.9/54 | Bus factor — 5 contributor(s) cover half of all commits |
| 18.5/22.5 | Commit distribution — top contributor authored 18% of commits |
| 13.5/13.5 | Contributor breadth — 100 contributors |
| 10/10 | OpenSSF Scorecard: Contributors — project has 14 contributing companies or organizations |
Inputs used
| bus_factor | 5 |
| contributors_sampled | 100 |
| top_contributor_share | 0.18 |
Issue & PR responsiveness
64Moderate
How it's scored
| 29.7/42 | Issue resolution — 71% of issues closed |
| 26.2/30 | PR acceptance — 6,195/7,089 decided PRs merged |
| 0/13 | Newcomer PR acceptance — no first-time contributor's PR decided in 30d |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 2/30 approved changesets -- score normalized to 0 |
Inputs used
| merged_prs | 6,195 |
| open_issues | 2,832 |
| closed_issues | 6,859 |
| prs_merged_7d | 2 |
| prs_decided_7d | 2 |
| prs_merged_30d | 26 |
| prs_decided_30d | 28 |
| issue_closed_ratio | 0.708 |
| closed_unmerged_prs | 894 |
| first_time_authors_30d | 0 |
| first_time_prs_merged_30d | 0 |
| first_time_prs_decided_30d | 0 |
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
Ownership & stewardship
99Exceptional
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 20/20 | Verified domain |
| 23.6/25 | Owner reach — 1,899 followers of h2oai |
| 25/25 | Track record — 196 public repos, account ~14 yr old |
Inputs used
| followers | 1,899 |
| owner_type | Organization |
| is_verified | yes |
| owner_login | h2oai |
| public_repos | 196 |
| account_age_days | 5,317 |
Package maintenance
100Exceptional
How it's scored
| 25/25 | Published & resolvable — 2 package(s) on pypi |
| 35/35 | Publish recency — latest publish 12 days ago |
| 20/20 | Version history — 23 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | h2o_client, h2o_mlflow_flavor |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 12 |
Engineering Quality
Are baseline engineering and documentation practices in place?
80
Engineering practices
90Excellent
How it's scored
| 24/24 | CI workflows — 2 workflow(s) |
| 24/24 | Tests present |
| 16/16 | Linter config — h2o-bindings/setup.cfg ([flake8]), h2o-py-cloud-extensions/setup.cfg ([flake8]), h2o-py-mlflow-flavor/setup.cfg ([flake8]), h2o-py/setup.cfg ([flake8]) |
| 0/9.6 | Pre-commit hooks |
| 6.4/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 20 out of 20 merged PRs checked by a CI test -- score normalized to 10 |
Inputs used
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | yes |
| has_linter_config | yes |
| has_precommit_config | no |
Documentation
65Good
How it's scored
| 30/30 | README |
| 0/25 | Documentation directory |
| 15/15 | Documentation / homepage site — http://h2o.ai |
| 10/10 | Repository description |
| 10/10 | Topics — 20 topics |
| 0/10 | Wiki |
Inputs used
| topics | h2o, machine-learning, data-science, deep-learning, big-data, ensemble-learning, gbm, random-forest, naive-bayes, pca, opensource, distributed, java, python, r, hadoop, spark, gpu, automl, h2o-automl |
| has_wiki | no |
| homepage | http://h2o.ai |
| docs_site | http://h2o.ai |
| has_readme | yes |
| has_docs_dir | no |
| has_description | yes |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
66
Security posture
57Moderate
How it's scored
| 6/7.5 | Binary-Artifacts — binaries present in source code |
| 0/7.5 | Branch-Protection — no data |
| 2.5/2.5 | CI-Tests — 20 out of 20 merged PRs checked by a CI test -- score normalized to 10 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 2/30 approved changesets -- score normalized to 0 |
| 2.5/2.5 | Contributors — project has 14 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | License — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 12 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — no data |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 5/5 | SAST — SAST tool is run on all commits |
| 5/5 | Security-Policy — security policy file detected |
| 0/7.5 | Signed-Releases — no data |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 0/7.5 | Vulnerabilities — 21 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 15 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 3 |
| scorecard_aggregate | 5.7 |
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.
Dependency advisories
100Exceptional
How it's scored
| 35/35 | Direct dependencies free of known advisories — no direct dependency carries a known advisory |
| 25/25 | Indirect dependencies free of known advisories — no indirect dependency carries a known advisory |
| 0/40 | No advisories left outstanding — no advisory carries a publication date |
Inputs used
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 6 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:h2o_client@3.46.0.12 runtime dependency closure — what installing the published package pulls in — 6 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.
64
Agent context & guidance
77Good
How it's scored
| 45/45 | Agent instructions — CLAUDE.md |
| 0/15 | Machine-readable docs (llms.txt) |
| 32/40 | Legible commit history — 60 of 100 human commits state their intent (structured subject or explanatory body) |
Inputs used
| has_llms_txt | no |
| llms_txt_url | — |
| legible_history_share | 0.6 |
| agent_instruction_files | CLAUDE.md |
| agent_instruction_max_bytes | 18,022 |
How it's scored
| 18/18 | One-command bootstrap — Makefile, docker/Makefile, ec2/Makefile, h2o-docs-theme/demo_docs/Makefile, h2o-docs/src/booklets/v2_2015/source/Makefile, h2o-docs/src/product/Makefile, h2o-docs/src/product/architecture/src/Makefile, h2o-py/docs/Makefile |
| 22/22 | Automated tests |
| 11/11 | Lint / format config — h2o-bindings/setup.cfg ([flake8]), h2o-py-cloud-extensions/setup.cfg ([flake8]), h2o-py-mlflow-flavor/setup.cfg ([flake8]), h2o-py/setup.cfg ([flake8]) |
| 0/11 | Static type checking |
| 10/10 | Reproducible environment — Dockerfile, lockfile |
| 6/10 | Demonstrated agent practice — 3 of the last 100 commits agent-authored or agent-credited |
| 0/8 | Automated maintenance — no automated dependency updates observed |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | Gemfile.lock |
| has_dockerfile | yes |
| typed_language | no |
| bootstrap_files | Makefile, docker/Makefile, ec2/Makefile, h2o-docs-theme/demo_docs/Makefile, h2o-docs/src/booklets/v2_2015/source/Makefile, h2o-docs/src/product/Makefile, h2o-docs/src/product/architecture/src/Makefile, h2o-py/docs/Makefile |
| has_devcontainer | no |
| has_linter_config | yes |
| typecheck_configs | — |
| agent_commit_share | 0.03 |
| toolchain_manifests | build.gradle, buildSrc/build.gradle, h2o-admissibleml/build.gradle, h2o-algos/build.gradle, h2o-app/build.gradle, h2o-assemblies/genmodel/build.gradle, h2o-assemblies/main/build.gradle, h2o-assemblies/minimal/build.gradle, h2o-assemblies/steam/build.gradle, h2o-automl/build.gradle, h2o-bindings/build.gradle, h2o-clustering/build.gradle, h2o-core/build.gradle, h2o-docs/build.gradle, h2o-extensions/example/build.gradle, h2o-extensions/jython-cfunc/build.gradle, h2o-extensions/krbstandalone/build.gradle, h2o-extensions/mojo-pipeline/build.gradle, h2o-extensions/steam/build.gradle, h2o-extensions/target-encoder/build.gradle, h2o-extensions/xgboost/build.gradle, h2o-genmodel-extensions/deepwater/build.gradle, h2o-genmodel-extensions/jgrapht/build.gradle, h2o-genmodel-extensions/mojo-pipeline/build.gradle, h2o-genmodel-extensions/xgboost/build.gradle, h2o-genmodel/build.gradle, h2o-hadoop-2/h2o-cdh5.10-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.13-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.14-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.15-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.16-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.4-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.5-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.6-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.7-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.8-assembly/build.gradle, h2o-hadoop-2/h2o-cdh5.9-assembly/build.gradle, h2o-hadoop-2/h2o-iop4.2-assembly/build.gradle, h2o-hadoop-2/h2o-mapr4.0-assembly/build.gradle, h2o-hadoop-2/h2o-mapr5.0-assembly/build.gradle, h2o-hadoop-2/h2o-mapr5.1-assembly/build.gradle, h2o-hadoop-2/h2o-mapr5.2-assembly/build.gradle, h2o-hadoop-2/h2o-mapr6.0-assembly/build.gradle, h2o-hadoop-2/h2o-mapr6.1-assembly/build.gradle, h2o-hadoop-2/h2o-mapr6.2-assembly/build.gradle, h2o-hadoop-2/h2o-mapr7.0-assembly/build.gradle, h2o-hadoop-3/h2o-cdh6.0-assembly/build.gradle, h2o-hadoop-3/h2o-cdh6.1-assembly/build.gradle, h2o-hadoop-3/h2o-cdh6.2-assembly/build.gradle, h2o-hadoop-3/h2o-cdh6.3-assembly/build.gradle, h2o-hadoop-3/h2o-cdp7.0-assembly/build.gradle, h2o-hadoop-3/h2o-cdp7.1-assembly/build.gradle, h2o-hadoop-3/h2o-cdp7.2-assembly/build.gradle, h2o-hadoop-3/h2o-emr6.10-assembly/build.gradle, h2o-hadoop-common/build.gradle, h2o-hive/build.gradle, h2o-jaas-pam/build.gradle, h2o-jetty-8/build.gradle, h2o-jetty-9-minimal/build.gradle, h2o-jetty-9/build.gradle, h2o-k8s-comp/build.gradle, h2o-k8s-int/build.gradle, h2o-k8s/build.gradle, h2o-logger/build.gradle, h2o-logging/impl-classic/build.gradle, h2o-logging/impl-log4j2/build.gradle, h2o-logging/safe4j/build.gradle, h2o-mapreduce-generic/build.gradle, h2o-parsers/h2o-avro-parser/build.gradle, h2o-parsers/h2o-orc-parser/build.gradle, h2o-parsers/h2o-parquet-compat/h2o-parquet-v17-compat/build.gradle, h2o-parsers/h2o-parquet-parser-tests/build.gradle, h2o-parsers/h2o-parquet-parser/build.gradle, h2o-persist-drive/build.gradle, h2o-persist-gcs/build.gradle, h2o-persist-hdfs/build.gradle, h2o-persist-http/build.gradle, h2o-persist-s3/build.gradle, h2o-py-cloud-extensions/build.gradle, h2o-py-mlflow-flavor/build.gradle, h2o-py/build.gradle, h2o-r/build.gradle, h2o-security/build.gradle, h2o-test-accuracy/build.gradle, h2o-test-support/build.gradle, h2o-web/build.gradle, h2o-webserver-iface/build.gradle |
| dependency_bot_commit_share | 0 |
Code legibility for models
54Moderate
How it's scored
| 0/45 | Type-checkable code — Jupyter Notebook without a type-check config |
| 54.1/55 | Manageable file sizes — 72/4,637 source files over 60KB |
Inputs used
| primary_language | Jupyter Notebook |
| largest_source_bytes | 550,060 |
| source_files_sampled | 4,637 |
| oversized_source_files | 72 |
How it's scored
| 0/40 | API schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP server |
| 40/40 | Runnable examples — demos, example, examples, notebooks, recipes |
Inputs used
| example_dirs | demos, example, examples, notebooks, recipes |
| has_mcp_signal | no |
| api_schema_files | — |
| interfaces_expected_of | network-service |
Key facts
7,495GitHub stars
100contributors
153commits, last 12 months
0days since last push
0releases
5bus factor
2,832open issues
Maven, npm, PyPI, RubyGemspackage ecosystems
Data collection warnings
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- Could not fetch npm package 'h2o-web' from its registry
- pypi package 'sphinx_rtd_theme' points at a different repository (https://github.com/readthedocs/sphinx_rtd_theme); excluded from ecosystem scoring
- Could not fetch pypi package 'h2o_cloud_extensions' from its registry
More detail
Star and fork history 0 ★ / 2,025 ⇿
0Stars
2,025Forks
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.
Each point covers 8 days.
OpenSSF Scorecard 5.7 / 10
5.7aggregate
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).
| 8 | Binary-Artifacts | binaries present in source code |
| n/a | Branch-Protection | internal 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 |
| 10 | CI-Tests | 20 out of 20 merged PRs checked by a CI test -- score normalized to 10 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 2/30 approved changesets -- score normalized to 0 |
| 10 | Contributors | project has 14 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 12 issue activity found in the last 90 days -- score normalized to 10 |
| n/a | Packaging | packaging workflow not detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 10 | SAST | SAST tool is run on all commits |
| 10 | Security-Policy | security policy file detected |
| n/a | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 0 | Vulnerabilities | 21 existing vulnerabilities detected |
Direct dependencies 1
| Registry | Package | Version constraint | Manifest |
|---|---|---|---|
| RubyGems | compass | — | h2o-docs-theme/Gemfile |
All dependencies 96
Full resolved dependency set from the GitHub dependency graph: 1 direct and 95 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| RubyGems | compass | 0.12.2 | direct |
| npm | bower | ^1.8.8 | indirect |
| npm | coffeescript | ^2.3.2 | indirect |
| npm | connect-livereload | ~0.3.0 | indirect |
| npm | diecut | ^0.0.1 | indirect |
| npm | fiction | ^0.0.5 | indirect |
| npm | fs-extra | ^7.0.1 | indirect |
| npm | grunt | ~0.4.1 | indirect |
| npm | grunt-contrib-clean | 0.5.0 | indirect |
| npm | grunt-contrib-connect | 0.5.0 | indirect |
| npm | grunt-contrib-copy | 0.5.0 | indirect |
| npm | grunt-contrib-sass | ~0.7.2 | indirect |
| npm | grunt-contrib-watch | ~0.4.3 | indirect |
| npm | grunt-exec | ~0.4.2 | indirect |
| npm | grunt-open | 0.2.2 | indirect |
| npm | htmlparser2 | ^3.10.0 | indirect |
| npm | js-yaml | ^3.13.1 | indirect |
| npm | lodash | ^4.17.11 | indirect |
| npm | marked | ^0.6.2 | indirect |
| npm | matchdep | ~0.1.2 | indirect |
| npm | minimist | ^1.2.0 | indirect |
| npm | mkdirp | ^0.5.1 | indirect |
| npm | puppeteer | ^1.10.0 | indirect |
| npm | request | ^2.88.0 | indirect |
| PyPI | boto3 | 1.18.65 | indirect |
| PyPI | causalml | 0.12.3 | indirect |
| PyPI | causalml | 0.14.1 | indirect |
| PyPI | colorama | — | indirect |
| PyPI | cython | 0.29.34 | indirect |
| PyPI | datatable | 1.0.0 | indirect |
| PyPI | future | — | indirect |
| PyPI | grip | 4.4.0 | indirect |
| PyPI | gssapi | — | indirect |
| PyPI | gssapi | 1.6.14 | indirect |
| PyPI | gssapi | 1.8.3 | indirect |
| PyPI | h2o-mlops-client | — | indirect |
| PyPI | lifelines | — | indirect |
| PyPI | matplotlib | 3.1.1 | indirect |
| PyPI | mlflow | — | indirect |
| PyPI | mypy | 0.971 | indirect |
| PyPI | mypy | 1.4.1 | indirect |
| PyPI | mypy | 1.8.0 | indirect |
| PyPI | mysqlclient | 1.4.6 | indirect |
| PyPI | numpy | — | indirect |
| PyPI | numpy | 1.23.5 | indirect |
| PyPI | numpy | 1.26.4 | indirect |
| PyPI | numpydoc | 0.7.0 | indirect |
| PyPI | pandas | 0.24.2 | indirect |
| PyPI | pandas | 1.3.5 | indirect |
| PyPI | pandas | 1.5.3 | indirect |
| PyPI | patsy | 0.5.3 | indirect |
| PyPI | patsy | 0.5.6 | indirect |
| PyPI | polars | 0.19.17 | indirect |
| PyPI | pyarrow | 10.0.1 | indirect |
| PyPI | pyarrow | 14.0.1 | indirect |
| PyPI | pygments | 2.15.1 | indirect |
| PyPI | pykerberos | — | indirect |
| PyPI | recommonmark | 0.4.0 | indirect |
| PyPI | requests | — | indirect |
| PyPI | requests | 2.27.1 | indirect |
| PyPI | scikit-learn | 0.24.2 | indirect |
| PyPI | scikit-learn | 1.2.2 | indirect |
| PyPI | scipy | 1.10.1 | indirect |
| PyPI | scipy | 1.5.4 | indirect |
| PyPI | scipy | 1.6.3 | indirect |
| PyPI | seaborn | 0.8.1 | indirect |
| PyPI | shap | 0.29.1 | indirect |
| PyPI | six | 1.11.0 | indirect |
| PyPI | slam | 0.6.0 | indirect |
| PyPI | sphinx | — | indirect |
| PyPI | sphinx | 3.0.4 | indirect |
| PyPI | sphinx | 3.5.4 | indirect |
| PyPI | sphinx | 6.1.3 | indirect |
| PyPI | sphinx-prompt | 1.1.0 | indirect |
| PyPI | sphinx-rtd-theme | 0.2.4 | indirect |
| PyPI | sphinx-substitution-extensions | 2019.6.15.0 | indirect |
| PyPI | sphinx-tabs | 1.1.12 | indirect |
| PyPI | sphinxcontrib-osexample | — | indirect |
| PyPI | statsmodels | 0.12.2 | indirect |
| PyPI | statsmodels | 0.13.5 | indirect |
| PyPI | statsmodels | 0.14.5 | indirect |
| PyPI | tabulate | — | indirect |
| PyPI | tabulate | 0.8.10 | indirect |
| PyPI | twine | 1.10.0 | indirect |
| PyPI | typing-extensions | 4.1.1 | indirect |
| PyPI | typing-extensions | 4.7.1 | indirect |
| PyPI | typing-extensions | 4.9.0 | indirect |
| PyPI | urllib3 | 1.26.5 | indirect |
| PyPI | wheel | — | indirect |
| PyPI | wheel | 0.42.0 | indirect |
| PyPI | winkerberos | — | indirect |
| PyPI | xgboost | 1.7.6 | indirect |
| PyPI | xlsxwriter | 1.3.7 | indirect |
| RubyGems | chunky_png | 1.2.9 | indirect |
| RubyGems | fssm | 0.2.10 | indirect |
| RubyGems | sass | 3.2.12 | indirect |
Dependency advisories 0
Installing pypi:h2o_client@3.46.0.12 pulls in 6 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.
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.