Public recordModerate
Software health reportschema 0.27.0 · metrics 2.3.1 · 2026-07-31 06:59 UTC
codezonediitj / pydatastructs
A python package for data structures and algorithms
codezonediitj/pydatastructs holds a health index of 51 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (78/100) and lowest on Vitality (33/100). It was last updated 281 days ago. 3 contributors account for most of its recent work.
51
overall / 100Software 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.
51
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)
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 57 is calibrated to 60 on the published index scale (record calibration 2026-08-02).
Ownership
CodeZonedOrganization
6 followers6 public repossince Apr 2019
This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.
Package ecosystems
| Registry | Package | Version | Downloads / mo | Versions | Last publish | Tags |
|---|---|---|---|---|---|---|
| PyPI | cz-pydatastructs | 0.0.1 | 102 | 3 | 1719 days ago | — |
| PyPI | pydatastructspoints to another repo — not scored | 1.2.3 | 908 | 6 | 1844 days ago | pythondata-structurescollectionsstackqueuetreebinary-search-treeheaplinked-list |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
33
Development activity
15Critical
Abandonment alert
Work has arrived and nobody has attended to it
no human commit in 284 daysautomated commits excludedissues left unansweredreleases stalledOpenSSF Scorecard reports it unmaintained
Silence alone is never the finding — a small, finished library may need no commits for years. This alert requires both: no human commit for a long time, and obligations the project is visibly not discharging. Automated commits do not count as maintenance.
How abandonment is assessedHow it's scored
| 3.6/36 | Push recency — last push 281 days ago |
| 2.8/36 | Commit cadence — 4/52 weeks with commits |
| 9/18 | Commit volume — 9 commits in the last year |
| 0/10 | OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0 |
Inputs used
| commits_last_year | 9 |
| human_commit_share | 1 |
| days_since_last_push | 281 |
| active_weeks_last_year | 4 |
Release discipline
60Moderate
How it's scored
| 27/27 | Ships releases — 3 releases published |
| 0/36 | Release recency — latest release 1,719 days ago |
| 27/27 | Release cadence — a release every ~10.5 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 3 |
| latest_release_tag | v0.0.1 |
| releases_from_tags | no |
| days_since_latest_release | 1,719 |
| mean_days_between_releases | 10.5 |
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?
58
Popularity & adoption
60Moderate
How it's scored
| 37.7/60 | Stars — 212 stars |
| 20.8/25 | Forks — 316 forks |
| 1.7/15 | Watchers — 3 watchers |
Inputs used
| forks | 316 |
| stars | 212 |
| watchers | 3 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
74Good
How it's scored
| 22.5/22.5 | README |
| 16.9/22.5 | License — license file present, not a recognized license |
| 0/18 | CONTRIBUTING guide |
| 13.5/13.5 | Code of conduct |
| 7.2/7.2 | Issue template |
| 6.3/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| readme_badges | — |
| has_contributing | no |
| has_issue_template | yes |
| has_code_of_conduct | yes |
| readme_badge_services | — |
| has_pull_request_template | yes |
Ecosystem adoption (downloads)
34At Risk
How it's scored
| 26.8/80 | Monthly downloads — 102 downloads/month across pypi |
| 0/20 | Registry dependents — not reported by this ecosystem |
Inputs used
| packages | cz-pydatastructs |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 102 |
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?
65
How it's scored
| 36/54 | Bus factor — 3 contributor(s) cover half of all commits |
| 13.3/22.5 | Commit distribution — top contributor authored 41% of commits |
| 13.5/13.5 | Contributor breadth — 59 contributors |
| 10/10 | OpenSSF Scorecard: Contributors — project has 18 contributing companies or organizations |
Inputs used
| bus_factor | 3 |
| contributors_sampled | 59 |
| top_contributor_share | 0.408 |
How it's scored
| 27/42 | Issue resolution — 64% of issues closed |
| 19/30 | PR acceptance — 230/363 decided PRs merged |
| 0/13 | Newcomer PR acceptance — no first-time contributor's PR decided in 30d |
| 13.5/15 | OpenSSF Scorecard: Code-Review — Found 28/30 approved changesets -- score normalized to 9 |
Inputs used
| merged_prs | 230 |
| open_issues | 98 |
| closed_issues | 177 |
| prs_merged_7d | — |
| prs_decided_7d | — |
| prs_merged_30d | — |
| prs_decided_30d | — |
| issue_closed_ratio | 0.644 |
| closed_unmerged_prs | 133 |
| 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.
Ownership & stewardship
54Moderate
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain |
| 6.1/25 | Owner reach — 6 followers of codezonediitj |
| 18.2/25 | Track record — 6 public repos, account ~7 yr old |
Inputs used
| followers | 6 |
| owner_type | Organization |
| is_verified | — |
| owner_login | codezonediitj |
| public_repos | 6 |
| account_age_days | 2,650 |
Package maintenance
61Moderate
How it's scored
| 25/25 | Published & resolvable — 1 package(s) on pypi |
| 4/35 | Publish recency — latest publish 1,719 days ago |
| 12/20 | Version history — 3 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | cz-pydatastructs |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 1,719 |
Engineering Quality
Are baseline engineering and documentation practices in place?
78
Engineering practices
64Moderate
How it's scored
| 24/24 | CI workflows — 1 workflow(s) |
| 24/24 | Tests present |
| 0/16 | Linter config |
| 0/9.6 | Pre-commit hooks |
| 6.4/6.4 | .editorconfig |
| 10/20 | OpenSSF Scorecard: CI-Tests — 15 out of 30 merged PRs checked by a CI test -- score normalized to 5 |
Inputs used
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | yes |
| has_linter_config | no |
| has_precommit_config | no |
Documentation
100Exceptional
How it's scored
| 30/30 | README |
| 25/25 | Documentation directory |
| 15/15 | Documentation / homepage site — https://pydatastructs.readthedocs.io/en/stable/ |
| 10/10 | Repository description |
| 10/10 | Topics — 8 topics |
| 10/10 | Wiki |
Inputs used
| topics | data-structures, algorithms, algorithms-and-data-structures, sports-programming, computer-science, python3, hacktoberfest, closember |
| has_wiki | yes |
| homepage | https://pydatastructs.readthedocs.io/en/stable/ |
| has_readme | yes |
| has_docs_dir | yes |
| has_description | yes |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
55
Security posture
44Weak
How it's scored
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — no data |
| 1.2/2.5 | CI-Tests — 15 out of 30 merged PRs checked by a CI test -- score normalized to 5 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 6.8/7.5 | Code-Review — Found 28/30 approved changesets -- score normalized to 9 |
| 2.5/2.5 | Contributors — project has 18 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.2/2.5 | License — license file detected |
| 0/7.5 | Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0 |
| 0/5 | Packaging — no data |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — no data |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 15 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 3 |
| scorecard_aggregate | 4.4 |
Excluded from scoring (no data or not applicable): branch_protection, packaging, signed_releases. Remaining weights renormalized.
Dependency advisories
100Exceptional
How it's scored
| 35/35 | Direct dependencies free of known advisories — no direct dependency carries a known advisory |
| 25/25 | Indirect dependencies free of known advisories — no indirect dependency carries a known advisory |
| 0/40 | No advisories left outstanding — no advisory carries a publication date |
Inputs used
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 1 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:pydatastructs@1.2.3 runtime dependency closure — what installing the published package pulls in — 1 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.
42
Agent context & guidance
40Weak
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 40/40 | Legible commit history — 88 of 100 human commits state their intent (structured subject or explanatory body) |
Inputs used
| has_llms_txt | no |
| legible_history_share | 0.88 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
How it's scored
| 18/18 | One-command bootstrap — docs/Makefile |
| 22/22 | Automated tests |
| 0/11 | Lint / format config |
| 0/11 | Static type checking |
| 0/10 | Reproducible environment |
| 0/10 | Demonstrated agent practice — no agent-authored commits among the last 100 |
| 0/8 | Automated maintenance — no automated dependency updates observed |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | docs/Makefile |
| has_devcontainer | no |
| has_linter_config | no |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Code legibility for models
54Moderate
How it's scored
| 0/45 | Type-checkable code — Python without a type-check config |
| 54.5/55 | Manageable file sizes — 1/119 source files over 60KB |
Inputs used
| primary_language | Python |
| largest_source_bytes | 65,049 |
| source_files_sampled | 119 |
| oversized_source_files | 1 |
How it's scored
| 0/40 | API schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP server |
| 40/40 | Runnable examples — notebooks |
Inputs used
| example_dirs | notebooks |
| has_mcp_signal | no |
| api_schema_files | — |
Key facts
212GitHub stars
59contributors
9commits, last 12 months
281days since last push
3releases
3bus factor
98open issues
PyPIpackage ecosystems
Data collection warnings
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- pypi package 'pydatastructs' points at a different repository (https://github.com/yoshiohasegawa/python-data-structures); excluded from ecosystem scoring
More detail
Star and fork history 0 ★ / 316 ⇿
0Stars
316Forks
3Releases
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.
Major 0Minor 0Patch 1
Each point covers 7 days.
OpenSSF Scorecard 4.4 / 10
4.4aggregate
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| n/a | Branch-Protection | internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md |
| 5 | CI-Tests | 15 out of 30 merged PRs checked by a CI test -- score normalized to 5 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 9 | Code-Review | Found 28/30 approved changesets -- score normalized to 9 |
| 10 | Contributors | project has 18 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 9 | License | license file detected |
| 0 | Maintained | 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0 |
| n/a | Packaging | packaging workflow not detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| n/a | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
All dependencies 9
Full resolved dependency set from the GitHub dependency graph: 0 direct and 9 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | codecov | — | indirect |
| PyPI | llvmlite | — | indirect |
| PyPI | meson | — | indirect |
| PyPI | myst-nb | 0.17.2 | indirect |
| PyPI | pytest | — | indirect |
| PyPI | pytest-cov | — | indirect |
| PyPI | sphinx | 5.0 | indirect |
| PyPI | sphinx-readable-theme | 1.3.0 | indirect |
| PyPI | spin | — | indirect |
Dependency advisories 0
Installing pypi:pydatastructs@1.2.3 pulls in 1 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
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},
{
"key": "tests_present",
"name": "Tests present",
"detail": null,
"points": 24,
"status": "met",
"details": [],
"max_points": 24
},
{
"key": "linter_config",
"name": "Linter config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 16
},
{
"key": "pre_commit_hooks",
"name": "Pre-commit hooks",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 9.6
},
{
"key": "editorconfig",
"name": ".editorconfig",
"detail": null,
"points": 6.4,
"status": "met",
"details": [],
"max_points": 6.4
},
{
"key": "openssf_scorecard_ci_tests",
"name": "OpenSSF Scorecard: CI-Tests",
"detail": "15 out of 30 merged PRs checked by a CI test -- score normalized to 5",
"points": 10,
"status": "partial",
"details": [],
"max_points": 20
}
]
},
{
"key": "documentation",
"band": "exceptional",
"name": "Documentation",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"topics": [
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"algorithms",
"algorithms-and-data-structures",
"sports-programming",
"computer-science",
"python3",
"hacktoberfest",
"closember"
],
"has_wiki": true,
"homepage": "https://pydatastructs.readthedocs.io/en/stable/",
"has_readme": true,
"has_docs_dir": true,
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},
"components": [
{
"key": "readme",
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"detail": null,
"points": 30,
"status": "met",
"details": [],
"max_points": 30
},
{
"key": "documentation_directory",
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"detail": null,
"points": 25,
"status": "met",
"details": [],
"max_points": 25
},
{
"key": "documentation_homepage_site",
"name": "Documentation / homepage site",
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"points": 15,
"status": "met",
"details": [],
"max_points": 15
},
{
"key": "repository_description",
"name": "Repository description",
"detail": null,
"points": 10,
"status": "met",
"details": [],
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},
{
"key": "topics",
"name": "Topics",
"detail": "8 topics",
"points": 10,
"status": "met",
"details": [
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"code": "topics_count",
"params": {
"count": 8
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}
],
"max_points": 10
},
{
"key": "wiki",
"name": "Wiki",
"detail": null,
"points": 10,
"status": "met",
"details": [],
"max_points": 10
}
]
}
],
"description": "Are baseline engineering and documentation practices in place?"
},
{
"key": "security",
"band": "moderate",
"name": "Security",
"value": 55,
"weight": 0.16,
"metrics": [
{
"key": "security_posture",
"band": "weak",
"name": "Security posture",
"note": "Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
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}
},
{
"code": "weights_renormalized",
"params": {}
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],
"value": 44,
"inputs": {
"source": "openssf_scorecard",
"checks_evaluated": 15,
"scorecard_version": "v5.5.0",
"checks_inconclusive": 3,
"scorecard_aggregate": 4.4
},
"components": [
{
"key": "binary_artifacts",
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"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "branch_protection",
"name": "Branch-Protection",
"detail": "internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "ci_tests",
"name": "CI-Tests",
"detail": "15 out of 30 merged PRs checked by a CI test -- score normalized to 5",
"points": 1.2,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "cii_best_practices",
"name": "CII-Best-Practices",
"detail": "no effort to earn an OpenSSF best practices badge detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 2.5
},
{
"key": "code_review",
"name": "Code-Review",
"detail": "Found 28/30 approved changesets -- score normalized to 9",
"points": 6.8,
"status": "partial",
"details": [],
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},
{
"key": "contributors",
"name": "Contributors",
"detail": "project has 18 contributing companies or organizations",
"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
},
{
"key": "dangerous_workflow",
"name": "Dangerous-Workflow",
"detail": "no dangerous workflow patterns detected",
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "dependency_update_tool",
"name": "Dependency-Update-Tool",
"detail": "no update tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.2,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
"detail": "0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
"name": "Packaging",
"detail": "packaging workflow not detected",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "sast",
"name": "SAST",
"detail": "SAST tool is not run on all commits -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "security_policy",
"name": "Security-Policy",
"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "0 existing vulnerabilities detected",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
"band": "exceptional",
"name": "Dependency advisories",
"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:pydatastructs@1.2.3 runtime dependency closure — what installing the published package pulls in — 1 packages. Reachability is not analyzed.",
"notes": [
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"code": "excluded_no_data",
"params": {
"components": [
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}
},
{
"code": "weights_renormalized",
"params": {}
},
{
"code": "advisories_scope_published",
"params": {
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"assessed": 1
}
},
{
"code": "advisories_reachability",
"params": {}
}
],
"value": 100,
"inputs": {
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"advisories": 0,
"affected_packages": 0,
"assessed_packages": 1,
"unassessed_packages": 0,
"affected_by_severity": "none",
"direct_affected_packages": 0
},
"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
{
"code": "no_direct_advisories",
"params": {}
}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
"name": "Indirect dependencies free of known advisories",
"detail": "no indirect dependency carries a known advisory",
"points": 25,
"status": "met",
"details": [
{
"code": "no_indirect_advisories",
"params": {}
}
],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
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"points": 0,
"status": "excluded",
"details": [
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"code": "advisories_no_publication_date",
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}
],
"max_points": 40
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]
},
{
"key": "malicious_dependencies",
"band": "exceptional",
"name": "Malicious dependencies",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"source": "osv",
"meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
"packages": [],
"red_flag": false,
"assessed_packages": 1,
"malicious_packages": 0,
"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
},
"components": [
{
"key": "no_dependency_reported_as_a_malicious_package",
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"detail": "no dependency is reported as a malicious package",
"points": 100,
"status": "met",
"details": [
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"code": "no_malicious_dependencies",
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}
],
"max_points": 100
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]
},
{
"key": "high_risk_jurisdiction_exposure",
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"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
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"commit_weight_rule": {
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"min_commit_share": 0.1
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"review_only_matches": 0,
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"assessed_self_published_locations": 20
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "weak",
"name": "AI Readiness",
"value": 42,
"weight": 0.04,
"metrics": [
{
"key": "ai_agent_context",
"band": "weak",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 40,
"inputs": {
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"legible_history_share": 0.88,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
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"points": 40,
"status": "met",
"details": [
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"code": "legible_history",
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}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
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"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 40,
"inputs": {
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"lockfiles": [],
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"agent_commit_share": 0,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "docs/Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "docs/Makefile"
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}
],
"max_points": 18
},
{
"key": "automated_tests",
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"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no agent-authored commits among the last 100",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_authored_commits",
"params": {
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no automated dependency updates observed",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 54,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 65049,
"source_files_sampled": 119,
"oversized_source_files": 1
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "1/119 source files over 60KB",
"points": 54.5,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 119,
"oversized": 1
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "weak",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"notebooks"
],
"has_mcp_signal": false,
"api_schema_files": []
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 40
},
{
"key": "mcp_server",
"name": "MCP server",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": "notebooks",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "notebooks"
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}
],
"max_points": 40
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
}
],
"classification": {
"labels": [
"library"
],
"scores": {
"library": 6
},
"primary": "library",
"evidence": [
{
"tier": "distribution",
"label": "library",
"source": "registry:pypi",
"weight": 6
}
],
"artifacts": [],
"confidence": "medium",
"host_extension": false,
"runs_as_process": false,
"consumed_by_code": true
},
"metrics_version": "2.3.1"
},
"warnings": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
"pypi package 'pydatastructs' points at a different repository (https://github.com/yoshiohasegawa/python-data-structures); excluded from ecosystem scoring"
],
"report_type": "repository",
"generated_at": "2026-07-31T06:59:53.182507Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/c/codezonediitj/pydatastructs.svg",
"full_name": "codezonediitj/pydatastructs",
"license_state": "custom",
"license_spdx": null
}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 v2.3.1, schema v0.27.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics — PyPI.