Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 07:27 UTC

misialq / ncbi-datasets-pyclient

PythonBSD-3-Clause★ 2 stars⑂ 0 forkssince Mar 2025View on GitHub ↗
KindLibraryhow this is determined

misialq/ncbi-datasets-pyclient holds a health index of 57 out of 100, placing it in the Moderate band. It scores highest on Vitality (78/100) and lowest on Security (21/100). It was last updated 20 days ago. A single contributor accounts for most of its recent work.

57
overall / 100
Moderate

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.

57
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 55 is calibrated to 57 on the published index scale (record calibration 2026-08-02).

Ownership

Michal ZiemskiPersonal account
24 followers61 public repossince Sep 2016ETH Zürich

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 publishTags
PyPIncbi-datasets-pyclient18.36.05763520 days agoopenapiopenapi-generatorncbi-datasets-api

Metrics by category

Vitality

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

78Good · 21% of overall

Development activity

64Moderate
How it's scored
28.8/36Push recency — last push 20 days ago
15.9/36Commit cadence — 23/52 weeks with commits
13.1/18Commit volume — 28 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year28
human_commit_share1
days_since_last_push20
active_weeks_last_year23

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 37 releases published
36/36Release recency — latest release 20 days ago
27/27Release cadence — a release every ~12.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count37
latest_release_tagv18.36.0
releases_from_tagsno
days_since_latest_release20
mean_days_between_releases12.6

Community & Adoption

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

29At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 2 stars
0/25Forks — 0 forks
0/15Watchers — 1 watchers
Inputs used
forks0
stars2
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (BSD-3-Clause)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

46Weak
How it's scored
36.8/80Monthly downloads — 576 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesncbi-datasets-pyclient
dependents—
ecosystemspypi
total_downloads—
monthly_downloads576
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?

64Moderate · 23% of overall

Maintainer resilience (bus factor)

18Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
4.8/22.5Commit distribution — top contributor authored 79% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.788

Issue & PR responsiveness

100Exceptional
How it's scored
42/42Issue resolution — 100% of issues closed
30/30PR acceptance — 1/1 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs1
open_issues0
closed_issues1
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs0
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

56Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
10.1/25Owner reach — 24 followers of misialq
25/25Track record — 61 public repos, account ~9 yr old
Inputs used
followers24
owner_typeUser
is_verified—
owner_loginmisialq
public_repos61
account_age_days3,645
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 20 days ago
20/20Version history — 35 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesncbi-datasets-pyclient
ecosystemspypi
any_deprecatedno
min_days_since_publish20

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall

Engineering practices

80Excellent
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.pylint]), setup.cfg ([flake8]), tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

65Good
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

21At Risk · 16% of overall

Security posture

1Critical
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestspyproject.toml, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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_packages8
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:ncbi-datasets-pyclient@18.36.0 runtime dependency closure — what installing the published package pulls in — 8 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.

38Weak · 4% of overall

Agent context & guidance

2Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
2.4/40Legible commit history — 2 of 45 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.044
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

49Weak
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.pylint]), setup.cfg ([flake8]), tox.ini
11/11Static type checking — ncbi/datasets/openapi/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 45
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsncbi/datasets/openapi/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (ncbi/datasets/openapi/py.typed)
54.6/55Manageable file sizes — 5/764 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes621,009
source_files_sampled764
oversized_source_files5

Key facts

2GitHub stars
2contributors
28commits, last 12 months
20days since last push
37releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIurllib3(>=2.6.3,<3.0.0)pyproject.toml
PyPIpython-dateutil(>=2.8.2)pyproject.toml
PyPIpydantic(>=2.11)pyproject.toml
PyPItyping-extensions(>=4.7.1)pyproject.toml
All dependencies 48

Full resolved dependency set from the GitHub dependency graph: 8 direct and 40 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIpydantic—direct
PyPIpydantic2.13.4direct
PyPIpython-dateutil—direct
PyPIpython-dateutil2.9.0.post0direct
PyPItyping-extensions—direct
PyPItyping-extensions4.16.0direct
PyPIurllib3—direct
PyPIurllib32.6.3direct
PyPIannotated-types0.7.0indirect
PyPIast-serialize0.8.0indirect
PyPIcachetools6.2.6indirect
PyPIchardet5.2.0indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.10.7indirect
PyPIdistlib0.4.3indirect
PyPIexceptiongroup1.3.1indirect
PyPIfilelock3.19.1indirect
PyPIflake8—indirect
PyPIflake87.3.0indirect
PyPIiniconfig2.1.0indirect
PyPIlibrt0.15.0indirect
PyPImccabe0.7.0indirect
PyPImypy—indirect
PyPImypy1.19.1indirect
PyPImypy-extensions1.1.0indirect
PyPIpackaging26.3indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.4.0indirect
PyPIpluggy1.6.0indirect
PyPIpycodestyle2.14.0indirect
PyPIpydantic-core2.46.4indirect
PyPIpyflakes3.4.0indirect
PyPIpygments2.21.0indirect
PyPIpyproject-api1.9.1indirect
PyPIpytest—indirect
PyPIpytest8.4.2indirect
PyPIpytest-cov—indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-discovery1.5.2indirect
PyPIsix1.17.0indirect
PyPItomli2.4.1indirect
PyPItomli-w1.2.0indirect
PyPItox—indirect
PyPItox4.30.3indirect
PyPItypes-python-dateutil—indirect
PyPItypes-python-dateutil2.9.0.20260124indirect
PyPItyping-inspection0.4.2indirect
PyPIvirtualenv21.7.4indirect
Dependency advisories 0

Installing pypi:ncbi-datasets-pyclient@18.36.0 pulls in 8 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

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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.