Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-20 10:26 UTC

o-murphy / py-ballisticcalc

LGPL library for small arms ballistic calculations based on point-mass (3 DoF) plus spin drift.

Python · CythonLGPL-3.0★ 64 stars⑂ 21 forkssince Jun 2022View on GitHub ↗
KindLibraryCommand-line toolPluginhow this is determined
#ballistics#cython#python#py-ballisticcalc#balliistic-calculator#ballistic-solver

o-murphy/py-ballisticcalc holds a health index of 88 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (95/100) and lowest on Security (58/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.

88
overall / 100
Excellent

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.

88
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 74 is calibrated to 88 on the published index scale (record calibration 2026-08-02).

Ownership

Dmytro YaroshenkoPersonal account
18 followers54 public repossince Nov 2020

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
PyPIpy_ballisticcalc2.3.13,8709744 days agopy-ballisticcalcballisticscythonballistic-calculatorpythonballistic-solver
PyPIpy_ballisticcalc.exts2.3.112,9178144 days agopy-ballisticcalcballisticscythonballistic-calculatorpythonpython3

Metrics by category

Vitality

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

93Exceptional · 21% of overall

Development activity

89Excellent
How it's scored
36/36Push recency — last push 1 days ago
24.9/36Commit cadence — 36/52 weeks with commits
18/18Commit volume — 125 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year125
human_commit_share0.88
days_since_last_push1
active_weeks_last_year36

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 84 releases published
36/36Release recency — latest release 44 days ago
27/27Release cadence — a release every ~4.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count84
latest_release_tagv2.3.1
releases_from_tagsno
days_since_latest_release44
mean_days_between_releases4.7
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?

62Moderate · 17% of overall

Popularity & adoption

43Weak
How it's scored
29.2/60Stars — 64 stars
10.8/25Forks — 21 forks
2.7/15Watchers — 4 watchers
Inputs used
forks21
stars64
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

77Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (LGPL-3.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges1
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com
has_pull_request_templateyes

Ecosystem adoption (downloads)

70Good
How it's scored
56.3/80Monthly downloads — 16,787 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespy_ballisticcalc, py_ballisticcalc.exts
dependents—
ecosystemspypi
total_downloads—
monthly_downloads16,787
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?

60Moderate · 23% of overall

Maintainer resilience (bus factor)

26At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2.9/22.5Commit distribution — top contributor authored 87% of commits
8.1/13.5Contributor breadth — 6 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.871

Issue & PR responsiveness

74Good
How it's scored
37.5/42Issue resolution — 89% of issues closed
26.8/30PR acceptance — 218/244 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/22 approved changesets -- score normalized to 0
Inputs used
merged_prs218
open_issues10
closed_issues83
prs_merged_7d2
prs_decided_7d3
prs_merged_30d4
prs_decided_30d6
issue_closed_ratio0.892
closed_unmerged_prs26
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

54Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
9.2/25Owner reach — 18 followers of o-murphy
24.4/25Track record — 54 public repos, account ~5 yr old
Inputs used
followers18
owner_typeUser
is_verified—
owner_logino-murphy
public_repos54
account_age_days2,147
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 2 package(s) on pypi
35/35Publish recency — latest publish 44 days ago
20/20Version history — 97 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespy_ballisticcalc, py_ballisticcalc.exts
ecosystemspypi
any_deprecatedno
min_days_since_publish44

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 16 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.pylint])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 19 out of 20 merged PRs checked by a CI test -- score normalized to 9
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://pypi.org/project/py-ballisticcalc
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicsballistics, cython, python, py-ballisticcalc, balliistic-calculator, ballistic-solver
has_wikiyes
homepagehttps://pypi.org/project/py-ballisticcalc
docs_sitehttps://pypi.org/project/py-ballisticcalc
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

58Moderate · 16% of overall

Security posture

47Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.2/2.5CI-Tests — 19 out of 20 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/22 approved changesets -- score normalized to 0
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
0/10Dangerous-Workflow — dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.7
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 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_packages3
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:py_ballisticcalc@2.3.1 runtime dependency closure — what installing the published package pulls in — 3 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.

73Good · 4% of overall

Agent context & guidance

40Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 84 of 88 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.955
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

85Excellent
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.pylint])
11/11Static type checking — py_ballisticcalc.exts/py_ballisticcalc_exts/py.typed, py_ballisticcalc/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 12 of the last 100 commits are automated dependency updates
5/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configspy_ballisticcalc.exts/py_ballisticcalc_exts/py.typed, py_ballisticcalc/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.12

Code legibility for models

80Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (py_ballisticcalc.exts/py_ballisticcalc_exts/py.typed, py_ballisticcalc/py.typed)
52.9/55Manageable file sizes — 5/131 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes629,713
source_files_sampled131
oversized_source_files5

Machine-readable interfaces

100Exceptional
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 — examples, notebooks
Inputs used
example_dirsexamples, 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

64GitHub stars
6contributors
125commits, last 12 months
1days since last push
84releases
1bus factor
10open 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 ★ / 21 ⇿
0Stars
21Forks
79Releases

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.

048121620242122023-072025-012026-08
Major 0Minor 4Patch 18

Each point covers 3 days.

OpenSSF Scorecard 4.7 / 10
4.7aggregate

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 · 2026-09-20 10:26 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
9CI-Tests19 out of 20 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/22 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPItyping_extensions>= 4.15.0pyproject.toml
PyPIDeprecated>=1.3.1pyproject.toml
All dependencies 151

Full resolved dependency set from the GitHub dependency graph: 2 direct and 149 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIbuild1.6.1indirect
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PyPIcffi2.1.1indirect
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PyPIcharset-normalizer3.5.1indirect
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PyPIrequests2.34.2indirect
PyPIrpds-py2026.6.3indirect
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PyPIscipy1.17.1indirect
PyPIscipy1.18.1indirect
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PyPIvirtualenv21.7.14indirect
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PyPIwebencodings0.6.1indirect
PyPIwrapt2.4.1indirect
Dependency advisories 0

Installing pypi:py_ballisticcalc@2.3.1 pulls in 3 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.

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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.