Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 20:59 UTC

Nixtla / utilsforecast

Helper functions to plot, evaluate, preprocess and engineer features for forecasting

PythonApache-2.0★ 109 stars⑂ 25 forkssince Aug 2023View on GitHub ↗

Nixtla/utilsforecast holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (88/100) and lowest on Community & Adoption (74/100). It was last updated today. A single contributor accounts for most of its recent work.

94
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.

94
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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

NixtlaOrganization · verified domain
2,845 followers40 public repossince Mar 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIutilsforecast0.2.162,242,88257121 days agotime-seriesanalysisforecasting

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 recencylast push 0 days ago
18/36Commit cadence26/52 weeks with commits
16.2/18Commit volume63 commits in the last year
10/10OpenSSF Scorecard: Maintained17 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year63
human_commit_share0.64
days_since_last_push0
active_weeks_last_year26
How it's scored
27/27Ships releases57 releases published
27/36Release recencylatest release 121 days ago
19.8/27Release cadencea release every ~61.2 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count57
latest_release_tagv0.2.16
releases_from_tagsno
days_since_latest_release121
mean_days_between_releases61.2
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?

74Good · 17% of overall
How it's scored
33/60Stars109 stars
11.5/25Forks25 forks
3.3/15Watchers5 watchers
Inputs used
forks25
stars109
watchers5
growth_stateorganic
growth_factor_pct100

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateno
How it's scored
80/80Monthly downloads2,242,882 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesutilsforecast
dependents
ecosystemspypi
total_downloads
monthly_downloads2,242,882
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?

78Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
6.3/22.5Commit distributiontop contributor authored 72% of commits
13.5/13.5Contributor breadth20 contributors
10/10OpenSSF Scorecard: Contributorsproject has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled20
top_contributor_share0.718
How it's scored
37.9/42Issue resolution90% of issues closed
27.3/30PR acceptance202/222 decided PRs merged
8.7/13Newcomer PR acceptance2/3 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs202
open_issues4
closed_issues37
prs_merged_7d1
prs_decided_7d1
prs_merged_30d2
prs_decided_30d3
issue_closed_ratio0.902
closed_unmerged_prs20
first_time_authors_30d2
first_time_prs_merged_30d2
first_time_prs_decided_30d3
How it's scored
30/30Ownership backingorganization-owned
20/20Verified domain
24.8/25Owner reach2,845 followers of Nixtla
22.7/25Track record40 public repos, account ~5 yr old
Inputs used
followers2,845
owner_typeOrganization
is_verifiedyes
owner_loginNixtla
public_repos40
account_age_days2,003

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 121 days ago
20/20Version history57 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesutilsforecast
ecosystemspypi
any_deprecatedno
min_days_since_publish121

Engineering Quality

Are baseline engineering and documentation practices in place?

88Excellent · 19% of overall
How it's scored
24/24CI workflows6 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://nixtlaverse.nixtla.io/utilsforecast
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics
has_wikino
homepagehttps://nixtlaverse.nixtla.io/utilsforecast
docs_sitehttps://nixtlaverse.nixtla.io/utilsforecast
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

77Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3.8/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 4 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained17 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
3/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 6
4/5SASTSAST tool is not run on all commits -- score normalized to 8
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
6/7.5Vulnerabilities2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate7.1
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages6
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:utilsforecast@0.2.16 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.

79Good · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt)llms.txt served by the project website (https://nixtlaverse.nixtla.io/llms.txt)
40/40Legible commit history60 of 64 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://nixtlaverse.nixtla.io/llms.txt
legible_history_share0.938
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
11/11Static type checkingutilsforecast/py.typed
10/10Reproducible environmentlockfile
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance36 of the last 100 commits are automated dependency updates
6/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 6
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configsutilsforecast/py.typed
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0.36
How it's scored
27/45Type-checkable codePython with type-check config (utilsforecast/py.typed)
55/55Manageable file sizes0/29 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes48,068
source_files_sampled29
oversized_source_files0
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

109GitHub stars
20contributors
63commits, last 12 months
0days since last push
57releases
1bus factor
4open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-07-09: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 109 stars today.

More detail

Star and fork history 106 ★ / 25 ⇿
106Stars
25Forks
57Releases

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.

Star history is shown as collected on 2026-07-09. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

0204060801001201062532023-082025-022026-08
Major 0Minor 2Patch 55

Each point covers 3 days.

OpenSSF Scorecard 7.1 / 10
7.1aggregate

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 · 2026-08-27 20:58 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained17 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
6Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 6
8SASTSAST tool is not run on all commits -- score normalized to 8
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPInumpypyproject.toml
PyPIpackagingpyproject.toml
PyPIpandaspyproject.toml
PyPInarwhals>=2.0pyproject.toml
All dependencies 107

Full resolved dependency set from the GitHub dependency graph: 6 direct and 101 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInarwhals2.15.0direct
PyPInumpy2.2.6direct
PyPInumpy2.3.5direct
PyPIpackaging26.0direct
PyPIpandas2.3.3direct
PyPIpandas3.0.3direct
PyPIadagio0.2.6indirect
PyPIaiohappyeyeballs2.6.1indirect
PyPIaiohttp3.14.3indirect
PyPIaiosignal1.4.0indirect
PyPIasync-timeout5.0.1indirect
PyPIattrs25.4.0indirect
PyPIblinker1.9.0indirect
PyPIcertifi2026.1.4indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.4indirect
PyPIclick8.3.1indirect
PyPIcloudpickle3.1.2indirect
PyPIcolorama0.4.6indirect
PyPIcontourpy1.3.2indirect
PyPIcontourpy1.3.3indirect
PyPIcoverage7.13.1indirect
PyPIcycler0.12.1indirect
PyPIdash3.4.0indirect
PyPIdask2026.1.1indirect
PyPIdatasetsforecast0.0.8indirect
PyPIdistlib0.4.0indirect
PyPIdistributed2026.1.1indirect
PyPIexceptiongroup1.3.1indirect
PyPIfilelock3.20.3indirect
PyPIflask3.1.3indirect
PyPIfonttools4.61.1indirect
PyPIfrozenlist1.8.0indirect
PyPIfsspec2026.1.0indirect
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PyPIgriffe2md1.5.0indirect
PyPIgriffelib2.0.0indirect
PyPIidentify2.6.16indirect
PyPIidna3.15indirect
PyPIimportlib-metadata8.7.1indirect
PyPIiniconfig2.3.0indirect
PyPIitsdangerous2.2.0indirect
PyPIjinja23.1.6indirect
PyPIkiwisolver1.4.9indirect
PyPIllvmlite0.46.0indirect
PyPIlocket1.0.0indirect
PyPImarkdown-it-py4.0.0indirect
PyPImarkupsafe3.0.3indirect
PyPImatplotlib3.10.8indirect
PyPImdformat1.0.0indirect
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PyPImkdocstrings-parser0.0.1indirect
PyPImsgpack1.2.1indirect
PyPImultidict6.7.0indirect
PyPInest-asyncio1.6.0indirect
PyPInodeenv1.10.0indirect
PyPInumba0.63.1indirect
PyPIorjson3.11.6indirect
PyPIpartd1.4.2indirect
PyPIpillow12.3.0indirect
PyPIpip26.1.2indirect
PyPIpip-licenses5.5.0indirect
PyPIplatformdirs4.5.1indirect
PyPIplotly6.5.2indirect
PyPIplotly-resampler0.11.0indirect
PyPIpluggy1.6.0indirect
PyPIpolars1.31.0indirect
PyPIpre-commit4.5.1indirect
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PyPIpropcache0.4.1indirect
PyPIpsutil7.2.1indirect
PyPIpy4j0.10.9.9indirect
PyPIpyarrow23.0.1indirect
PyPIpygments2.20.0indirect
PyPIpyparsing3.3.2indirect
PyPIpyspark4.2.0indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.0.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpytz2025.2indirect
PyPIpyyaml6.0.3indirect
PyPIrequests2.33.0indirect
PyPIretrying1.4.2indirect
PyPIrich14.2.0indirect
PyPIscipy1.15.3indirect
PyPIscipy1.17.0indirect
PyPIsetuptools83.0.0indirect
PyPIsix1.17.0indirect
PyPIsortedcontainers2.4.0indirect
PyPItblib3.2.2indirect
PyPItomli2.4.0indirect
PyPItoolz1.1.0indirect
PyPItornado6.5.7indirect
PyPItqdm4.67.1indirect
PyPItriad1.0.2indirect
PyPItsdownsample0.1.4.1indirect
PyPItyping-extensions4.15.0indirect
PyPItzdata2025.3indirect
PyPIurllib32.7.0indirect
PyPIutilsforecast0.2.16indirect
PyPIvirtualenv20.36.1indirect
PyPIwcwidth0.3.0indirect
PyPIwerkzeug3.1.6indirect
PyPIxlrd2.0.2indirect
PyPIyarl1.22.0indirect
PyPIzict3.0.0indirect
PyPIzipp3.23.0indirect
Dependency advisories 0

Installing pypi:utilsforecast@0.2.16 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.

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 v0.34.0 — full methodology · metrics wiki.

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