Public record
Software health reportschema 0.27.0 · metrics 2.5.0 · 2026-07-30 22:17 UTC

corteva / rioxarray

geospatial xarray extension powered by rasterio

PythonCustom license★ 621 stars⑂ 102 forkssince Apr 2019View on GitHub ↗

corteva/rioxarray holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on AI Readiness (58/100). It was last updated 3 days ago. A single contributor accounts for most of its recent work.

91
overall / 100
Excellent

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.

91
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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).

Ownership

57 followers24 public repossince May 2018

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIrioxarray0.23.01,085,084863 days agorioxarrayxarrayrasterio

Metrics by category

Vitality

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

81Excellent · 21% of overall
How it's scored
36/36Push recency — last push 3 days ago
12.5/36Commit cadence — 18/52 weeks with commits
16.3/18Commit volume — 65 commits in the last year
8/10OpenSSF Scorecard: Maintained — 10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
Inputs used
commits_last_year65
human_commit_share0.84
days_since_last_push3
active_weeks_last_year18
How it's scored
27/27Ships releases — 82 releases published
36/36Release recency — latest release 3 days ago
19.8/27Release cadence — a release every ~83.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count82
latest_release_tag0.23.0
releases_from_tagsno
days_since_latest_release3
mean_days_between_releases83.2
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?

77Good · 17% of overall
How it's scored
45.3/60Stars — 621 stars
16.7/25Forks — 102 forks
6.4/15Watchers — 15 watchers
Inputs used
forks102
stars621
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes
How it's scored
80/80Monthly downloads — 1,085,084 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesrioxarray
dependents
ecosystemspypi
total_downloads
monthly_downloads1,085,084
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?

66Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2.4/22.5Commit distribution — top contributor authored 89% of commits
13.5/13.5Contributor breadth — 46 contributors
10/10OpenSSF Scorecard: Contributors — project has 11 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled46
top_contributor_share0.892
How it's scored
32.8/42Issue resolution — 78% of issues closed
28.9/30PR acceptance — 392/407 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
6/15OpenSSF Scorecard: Code-Review — Found 10/23 approved changesets -- score normalized to 4
Inputs used
merged_prs392
open_issues72
closed_issues258
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.782
closed_unmerged_prs15
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 backing — organization-owned
0/20Verified domain
12.7/25Owner reach — 57 followers of corteva
22.2/25Track record — 24 public repos, account ~8 yr old
Inputs used
followers57
owner_typeOrganization
is_verified
owner_logincorteva
public_repos24
account_age_days2,990

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 3 days ago
20/20Version history — 86 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesrioxarray
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — .flake8, .pylintrc
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 19 out of 19 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://corteva.github.io/rioxarray
10/10Repository description
10/10Topics — 9 topics
0/10Wiki
Inputs used
topicsgis, rasterio, xarray, geospatial, python, gdal, raster, netcdf, hacktoberfest
has_wikino
homepagehttps://corteva.github.io/rioxarray
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

68Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 19 out of 19 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3/7.5Code-Review — Found 10/23 approved changesets -- score normalized to 4
2.5/2.5Contributors — project has 11 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
6/7.5Maintained — 10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
5/5Packaging — packaging workflow detected
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
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6
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 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_packages14
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:rioxarray@0.23.0 runtime dependency closure — what installing the published package pulls in — 14 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.

58Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
25.4/40Legible commit history — 40 of 84 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
legible_history_share0.476
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — .flake8, .pylintrc
11/11Static type checking — mypy.ini, rioxarray/py.typed
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 16 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsmypy.ini, rioxarray/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.16
How it's scored
27/45Type-checkable code — Python with type-check config (mypy.ini, rioxarray/py.typed)
53.4/55Manageable file sizes — 1/35 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes120,846
source_files_sampled35
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files

Key facts

621GitHub stars
46contributors
65commits, last 12 months
3days since last push
82releases
1bus factor
72open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 102 ⇿
0Stars
102Forks
80Releases

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.

02040608010012010232019-042022-112026-07
Major 0Minor 22Patch 57

Each point covers 7 days.

OpenSSF Scorecard 6.0 / 10
6.0aggregate

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 · 2026-07-30 22:16 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-Tests19 out of 19 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 10/23 approved changesets -- score normalized to 4
10Contributorsproject has 11 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
8Maintained10 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 8
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIpackagingpyproject.toml
PyPIrasterio>=1.4.3pyproject.toml
PyPIxarray>=2026.2pyproject.toml
PyPIpyproj>=3.3pyproject.toml
PyPInumpy>=2pyproject.toml
All dependencies 5

Full resolved dependency set from the GitHub dependency graph: 4 direct and 1 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpydirect
PyPIpyprojdirect
PyPIrasteriodirect
PyPIxarraydirect
PyPIpytestindirect
Dependency advisories 0

Installing pypi:rioxarray@0.23.0 pulls in 14 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

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 v2.5.0, schema v0.27.0 — full methodology · metrics wiki.

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