Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-15 23:49 UTC

openclimatefix / graph_weather

Graph-based weather forecasting models. Originally, PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)

PythonMIT★ 301 stars⑂ 97 forkssince Feb 2022View on GitHub ↗

openclimatefix/graph_weather holds a health index of 67 out of 100, placing it in the Good band. It scores highest on Vitality (82/100) and lowest on Security (1/100). It was last updated 2 days ago. 2 contributors account for most of its recent work.

67
overall / 100
Good

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.

67
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 61 is calibrated to 67 on the published index scale (record calibration 2026-08-02).

Ownership

Open Climate FixOrganization
913 followers44 public repossince Mar 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIgraph_weather1.0.146-1152 days ago

Metrics by category

Vitality

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

82Excellent · 21% of overall
How it's scored
36/36Push recencylast push 2 days ago
11.1/36Commit cadence16/52 weeks with commits
16.1/18Commit volume61 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year61
human_commit_share
days_since_last_push2
active_weeks_last_year16

Release discipline

100Exceptional
How it's scored
27/27Ships releases100 releases published
36/36Release recencylatest release 2 days ago
27/27Release cadencea release every ~2.9 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count100
latest_release_tagv1.0.146
releases_from_tagsno
days_since_latest_release2
mean_days_between_releases2.9

Community & Adoption

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

59Moderate · 17% of overall
How it's scored
40.2/60Stars301 stars
16.5/25Forks97 forks
3.3/15Watchers5 watchers
Inputs used
forks97
stars301
watchers5
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

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

75Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
11.7/22.5Commit distributiontop contributor authored 48% of commits
13.5/13.5Contributor breadth23 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor2
contributors_sampled23
top_contributor_share0.482
How it's scored
16.1/42Issue resolution38% of issues closed
26.1/30PR acceptance87/100 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs87
open_issues69
closed_issues43
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.384
closed_unmerged_prs13
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
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
21.3/25Owner reach913 followers of openclimatefix
24/25Track record44 public repos, account ~7 yr old
Inputs used
followers913
owner_typeOrganization
is_verified
owner_loginopenclimatefix
public_repos44
account_age_days2,686
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 2 days ago
20/20Version history115 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesgraph_weather
ecosystemspypi
any_deprecatedno
min_days_since_publish2

Engineering Quality

Are baseline engineering and documentation practices in place?

79Good · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter config
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

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics4 topics
10/10Wiki
Inputs used
topicspytorch, weather, graph-neural-networks, forecasting-models
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

1Critical · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestspyproject.toml, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

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.

38Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno data
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
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_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
54.5/55Manageable file sizes1/113 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes240,252
source_files_sampled113
oversized_source_files1

Key facts

301GitHub stars
23contributors
61commits, last 12 months
2days since last push
100releases
2bus factor
69open issues
PyPIpackage ecosystems

Data collection warnings

  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPItorch-harmonicspyproject.toml
PyPIanemoi-datasets>=0.4.5,<0.5pyproject.toml
All dependencies 1

Full resolved dependency set from the GitHub dependency graph: 1 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIanemoi-datasetsdirect
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 v0.11.0 — full methodology · metrics wiki.

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