Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 04:00 UTC

Digdgeo / Ndvi2Gif

Library to create Multi Seasonal remote sensing indexes composites

Jupyter Notebook · PythonMIT★ 41 stars⑂ 13 forkssince Apr 2020View on GitHub ↗

Digdgeo/Ndvi2Gif holds a health index of 65 out of 100, placing it in the Good band. It scores highest on Vitality (85/100) and lowest on AI Readiness (33/100). It was last updated 6 days ago. A single contributor accounts for most of its recent work.

65
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.

65
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 60 is calibrated to 65 on the published index scale (record calibration 2026-08-02).

Ownership

Diego Garcia DiazPersonal account
60 followers53 public repossince Mar 2015Consejo Superior de Investigaciones Científicas (CSIC)

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIndvi2gif1.3.1-269 days ago

Metrics by category

Vitality

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

85Excellent · 21% of overall
How it's scored
36/36Push recencylast push 6 days ago
12.5/36Commit cadence18/52 weeks with commits
16.6/18Commit volume69 commits in the last year
10/10OpenSSF Scorecard: Maintained16 commit(s) and 13 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year69
human_commit_share
days_since_last_push6
active_weeks_last_year18

Release discipline

100Exceptional
How it's scored
27/27Ships releases22 releases published
36/36Release recencylatest release 9 days ago
27/27Release cadencea release every ~34.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count22
latest_release_tagv1.3.1
releases_from_tagsno
days_since_latest_release9
mean_days_between_releases34.8
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?

53Moderate · 17% of overall
How it's scored
26/60Stars41 stars
9/25Forks13 forks
2.7/15Watchers4 watchers
Inputs used
forks13
stars41
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

57Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0/22.5Commit distributiontop contributor authored 100% of commits
1.4/13.5Contributor breadth1 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
42/42Issue resolution100% of issues closed
0/30PR acceptanceno decided pull requests or no data
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues14
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio1
closed_unmerged_prs0
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): PR acceptance, Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
12.8/25Owner reach60 followers of Digdgeo
24.6/25Track record53 public repos, account ~11 yr old
Inputs used
followers60
owner_typeUser
is_verified
owner_loginDigdgeo
public_repos53
account_age_days4,154
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 9 days ago
20/20Version history26 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesndvi2gif
ecosystemspypi
any_deprecatedno
min_days_since_publish9

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall
How it's scored
24/24CI workflows3 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://digdgeo.github.io/Ndvi2Gif/
10/10Repository description
10/10Topics5 topics
10/10Wiki
Inputs used
topicselter, ndvi, phenology, remote-sensing, sumhal
has_wikiyes
homepagehttps://digdgeo.github.io/Ndvi2Gif/
docs_sitehttps://digdgeo.github.io/Ndvi2Gif/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

40Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Testsno data
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained16 commit(s) and 13 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTno SAST tool detected
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4
Excluded from scoring (no data or not applicable): CI-Tests, Packaging, Signed-Releases. 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.

33At Risk · 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
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
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 codeJupyter Notebook without a type-check config
44/55Manageable file sizes2/10 source files over 60KB
Inputs used
primary_languageJupyter Notebook
largest_source_bytes195,608
source_files_sampled10
oversized_source_files2
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesnotebooks
Inputs used
example_dirsnotebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

41GitHub stars
1contributors
69commits, last 12 months
6days since last push
22releases
1bus factor
0open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.0 / 10
4.0aggregate

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 · 2026-07-17 03:59 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained16 commit(s) and 13 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
0SASTno SAST tool detected
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 18
RegistryPackageVersion constraintManifest
PyPIgeemap>=0.29.5setup.cfg
PyPIearthengine-api>=0.1.347setup.cfg
PyPInumpy>=1.24setup.cfg
PyPIpandassetup.cfg
PyPIscipysetup.cfg
PyPImatplotlibsetup.cfg
PyPIseabornsetup.cfg
PyPIpillowsetup.cfg
PyPIimageiosetup.cfg
PyPItqdmsetup.cfg
PyPIrequestssetup.cfg
PyPIgeopandassetup.cfg
PyPIfionasetup.cfg
PyPIrasteriosetup.cfg
PyPIpycrssetup.cfg
PyPIdeims>=4.0setup.cfg
PyPIstatsmodels>=0.13setup.cfg
PyPIscikit-learn>=1.0setup.cfg
All dependencies 16

Full resolved dependency set from the GitHub dependency graph: 6 direct and 10 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIearthengine-apidirect
PyPIgeemapdirect
PyPImatplotlibdirect
PyPInumpydirect
PyPIpandasdirect
PyPIseaborndirect
PyPIghp-importindirect
PyPIjupyter-bookindirect
PyPImyst-nbindirect
PyPIndvi2gifindirect
PyPIpytestindirect
PyPIpytest-covindirect
PyPIsphinxindirect
PyPIsphinx-book-themeindirect
PyPIsphinx-copybuttonindirect
PyPIsphinxcontrib-bibtexindirect
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.