Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 00:09 UTC

ipython / comm

Python Comm implementation for the Jupyter kernel protocol

PythonBSD-3-Clause★ 12 stars⑂ 17 forkssince Aug 2022View on GitHub ↗

ipython/comm holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (78/100) and lowest on Vitality (30/100). It was last updated 234 days ago. 2 contributors account for most of its recent work.

53
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.

53
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 52 is calibrated to 53 on the published index scale (record calibration 2026-08-02).

Ownership

IPythonOrganization
548 followers28 public repossince Mar 2010

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIcomm0.2.3-10356 days agoipykerneljupyterxeus-python

Metrics by category

Vitality

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

30At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 234 days ago
2.1/36Commit cadence3/52 weeks with commits
6.3/18Commit volume4 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year4
human_commit_share
days_since_last_push234
active_weeks_last_year3
How it's scored
27/27Ships releases6 releases published
16.2/36Release recencylatest release 356 days ago
12.6/27Release cadencea release every ~171.2 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count6
latest_release_tagv0.2.3
releases_from_tagsno
days_since_latest_release356
mean_days_between_releases171.2

Community & Adoption

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

40Weak · 17% of overall
How it's scored
16.9/60Stars12 stars
10/25Forks17 forks
3.9/15Watchers6 watchers
Inputs used
forks17
stars12
watchers6
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized 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_badges
has_contributingno
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?

78Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
14.6/22.5Commit distributiontop contributor authored 35% of commits
13.5/13.5Contributor breadth10 contributors
10/10OpenSSF Scorecard: Contributorsproject has 24 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled10
top_contributor_share0.353
How it's scored
35/42Issue resolution83% of issues closed
26.4/30PR acceptance22/25 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 5/20 approved changesets -- score normalized to 2
Inputs used
merged_prs22
open_issues1
closed_issues5
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.833
closed_unmerged_prs3
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 backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
19.7/25Owner reach548 followers of ipython
22.6/25Track record28 public repos, account ~16 yr old
Inputs used
followers548
owner_typeOrganization
is_verified
owner_loginipython
public_repos28
account_age_days5,957
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 356 days ago
20/20Version history10 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagescomm
ecosystemspypi
any_deprecatedno
min_days_since_publish356

Engineering Quality

Are baseline engineering and documentation practices in place?

62Moderate · 19% of overall
How it's scored
24/24CI workflows5 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
2/20OpenSSF Scorecard: CI-Tests2 out of 18 merged PRs checked by a CI test -- score normalized to 1
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics
has_wikino
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

46Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
2.2/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
0.2/2.5CI-Tests2 out of 18 merged PRs checked by a CI test -- score normalized to 1
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 5/20 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 24 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
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
4.5/5Security-Policysecurity policy file detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.6
Excluded from scoring (no data or not applicable): Packaging. 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.

40Weak · 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
11/11Lint / format config
11/11Static type checkingcomm/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno data
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
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_configyes
typecheck_configscomm/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.
How it's scored
27/45Type-checkable codePython with type-check config (comm/py.typed)
55/55Manageable file sizes0/3 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes10,525
source_files_sampled3
oversized_source_files0

Key facts

12GitHub stars
10contributors
4commits, last 12 months
234days since last push
6releases
2bus factor
1open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.6 / 10
4.6aggregate

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 00:08 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
1CI-Tests2 out of 18 merged PRs checked by a CI test -- score normalized to 1
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 5/20 approved changesets -- score normalized to 2
10Contributorsproject has 24 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
9Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 0

Full resolved dependency set from the GitHub dependency graph: 0 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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.