Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-18 00:23 UTC

neuronsimulator / nrn

NEURON Simulator

C++ · PythonCustom license★ 559 stars⑂ 155 forkssince Oct 2016View on GitHub ↗

neuronsimulator/nrn holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Security (66/100). It was last updated today. 3 contributors account 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

95 followers98 public repossince Apr 2018

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIneuron9.0.217,6633168 days ago

Metrics by category

Vitality

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

87Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
24.9/36Commit cadence — 36/52 weeks with commits
18/18Commit volume — 156 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year156
human_commit_share0.98
days_since_last_push0
active_weeks_last_year36
How it's scored
27/27Ships releases — 31 releases published
36/36Release recency — latest release 11 days ago
19.8/27Release cadence — a release every ~55.9 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count31
latest_release_tag9.0.2a1
releases_from_tagsno
days_since_latest_release11
mean_days_between_releases55.9

Community & Adoption

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

68Good · 17% of overall
How it's scored
44.6/60Stars — 559 stars
18.2/25Forks — 155 forks
7.4/15Watchers — 22 watchers
Inputs used
forks155
stars559
watchers22
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, dev.azure.com, github.com, readthedocs.org
has_pull_request_templateno
How it's scored
56.6/80Monthly downloads — 17,663 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesneuron
dependents—
ecosystemspypi
total_downloads—
monthly_downloads17,663
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?

80Excellent · 23% of overall
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
14.3/22.5Commit distribution — top contributor authored 36% of commits
13.5/13.5Contributor breadth — 78 contributors
10/10OpenSSF Scorecard: Contributors — project has 24 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled78
top_contributor_share0.364
How it's scored
30.3/42Issue resolution — 72% of issues closed
25.2/30PR acceptance — 2,133/2,536 decided PRs merged
13/13Newcomer PR acceptance — 2/2 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs2,133
open_issues343
closed_issues888
prs_merged_7d9
prs_decided_7d14
prs_merged_30d21
prs_decided_30d29
issue_closed_ratio0.721
closed_unmerged_prs403
first_time_authors_30d2
first_time_prs_merged_30d2
first_time_prs_decided_30d2
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
14.3/25Owner reach — 95 followers of neuronsimulator
25/25Track record — 98 public repos, account ~8 yr old
Inputs used
followers95
owner_typeOrganization
is_verifiedno
owner_loginneuronsimulator
public_repos98
account_age_days3,102

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 68 days ago
20/20Version history — 31 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesneuron
ecosystemspypi
any_deprecatedno
min_days_since_publish68

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows — 13 workflow(s)
24/24Tests present
16/16Linter config — .flake8
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://www.neuronsimulator.org
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsneuron, neuroscience, high-performance-computing, simulation
has_wikiyes
homepagehttps://www.neuronsimulator.org
docs_sitehttps://www.neuronsimulator.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

66Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 24 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
7.5/7.5Maintained — 30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 39 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5.7

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_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:neuron@9.0.2 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.

67Good · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 98 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — .flake8
11/11Static type checking — C++ (statically typed)
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 2 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_languageyes
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.02
How it's scored
45/45Type-checkable code — C++ (statically typed)
53.7/55Manageable file sizes — 34/1,452 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes1,413,790
source_files_sampled1,452
oversized_source_files34
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — example, examples, notebooks
Inputs used
example_dirsexample, examples, notebooks
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

559GitHub stars
78contributors
156commits, last 12 months
0days since last push
31releases
3bus factor
343open 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 ★ / 155 ⇿
0Stars
155Forks
31Releases

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.

025507510012515014932016-112021-102026-10
Major 2Minor 2Patch 14

Each point covers 10 days.

OpenSSF Scorecard 5.7 / 10
5.7aggregate

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 · 2026-10-18 00:23 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-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 24 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities39 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIfind-libpython—pyproject.toml
PyPInumpy>=1.9.3pyproject.toml
PyPIpackaging>=22.0pyproject.toml
PyPIsetuptools—pyproject.toml
PyPIsympy>=1.3pyproject.toml
All dependencies 193

Full resolved dependency set from the GitHub dependency graph: 16 direct and 177 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIfind-libpython—direct
PyPIfind-libpython0.5.1direct
PyPInumpy—direct
PyPInumpy1.20.3direct
PyPInumpy1.21.6direct
PyPInumpy1.23.5direct
PyPInumpy1.26.4direct
PyPInumpy2.1.0direct
PyPInumpy2.3.2direct
PyPInumpy2.3.3direct
PyPIpackaging—direct
PyPIpackaging26.3direct
PyPIsetuptools—direct
PyPIsetuptools84.0.0direct
PyPIsympy—direct
PyPIsympy1.14.0direct
PyPIalabaster1.0.0indirect
PyPIanyio4.15.1indirect
PyPIanywidget—indirect
PyPIanywidget0.11.0indirect
PyPIappnope1.0.0indirect
PyPIargon2-cffi25.1.0indirect
PyPIargon2-cffi-bindings26.1.0indirect
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PyPIasync-lru2.3.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbeautifulsoup44.15.0indirect
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PyPIbokeh—indirect
PyPIbokeh3.9.2indirect
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PyPIcharset-normalizer3.5.1indirect
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PyPIcomm0.2.3indirect
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PyPIcycler0.12.1indirect
PyPIcython—indirect
PyPIcython3.3.0indirect
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PyPIdecorator5.3.1indirect
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PyPIdocutils—indirect
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PyPIexecuting2.2.1indirect
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PyPIh110.16.0indirect
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PyPIjinja2—indirect
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PyPIjsonschema4.26.0indirect
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PyPIjupyter-client—indirect
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PyPIjupyterlab-server2.28.1indirect
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PyPImarkdown-it-py3.0.0indirect
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PyPImatplotlib—indirect
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PyPImpi4py—indirect
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PyPImyst-parser—indirect
PyPImyst-parser4.0.1indirect
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PyPInbconvert—indirect
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PyPInbsphinx—indirect
PyPInbsphinx0.9.8indirect
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PyPIplatformdirs4.12.2indirect
PyPIplotly—indirect
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PyPIpygments2.21.0indirect
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PyPIpytest—indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov—indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-json-logger4.2.0indirect
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PyPIrequests2.34.2indirect
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PyPIrfc3986-validator0.1.1indirect
PyPIrfc3987-syntax1.1.0indirect
PyPIscikit-build-core—indirect
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PyPIsphinxcontrib-applehelp—indirect
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PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp—indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jquery4.1indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-mermaid—indirect
PyPIsphinxcontrib-mermaid2.1.1indirect
PyPIsphinxcontrib-moderncmakedomain—indirect
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PyPItenacity—indirect
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PyPIuv—indirect
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PyPIwidgetsnbextension4.0.16indirect
PyPIxyzservices2026.9.1indirect
Dependency advisories 0

Installing pypi:neuron@9.0.2 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 statistics — PyPI.