Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 03:10 UTC

samberry19 / bioviper

Enhancements to Biopython for working with biological data

Jupyter Notebook · PythonMIT★ 7 stars⑂ 1 forksince Feb 2022View on GitHub ↗

samberry19/bioviper holds a health index of 28 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (42/100) and lowest on Vitality (23/100). It was last updated 318 days ago. A single contributor accounts for most of its recent work.

28
overall / 100
At Risk

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.

28
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 34 is calibrated to 28 on the published index scale (record calibration 2026-08-02).

Ownership

Sam BerryPersonal account
5 followers16 public repossince Mar 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 publish
PyPIbioviper0.2.12646816 days ago

Metrics by category

Vitality

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

23At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 318 days ago
0.7/36Commit cadence1/52 weeks with commits
4.3/18Commit volume2 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_year2
human_commit_share
days_since_last_push318
active_weeks_last_year1
How it's scored
27/27Ships releases2 releases published
0/36Release recencylatest release 750 days ago
12.6/27Release cadencea release every ~349.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count2
latest_release_tagv0.30
releases_from_tagsno
days_since_latest_release750
mean_days_between_releases349.8
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?

33At Risk · 17% of overall
How it's scored
12.6/60Stars7 stars
0/25Forks1 forks
0/15Watchers1 watchers
Inputs used
forks1
stars7
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
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
How it's scored
32.3/80Monthly downloads264 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesbioviper
dependents
ecosystemspypi
total_downloads
monthly_downloads264
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?

37Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0.5/22.5Commit distributiontop contributor authored 98% of commits
2.7/13.5Contributor breadth2 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.98
How it's scored
14/42Issue resolution33% of issues closed
15/30PR acceptance1/2 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs1
open_issues2
closed_issues1
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.333
closed_unmerged_prs1
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
5.6/25Owner reach5 followers of samberry19
21/25Track record16 public repos, account ~6 yr old
Inputs used
followers5
owner_typeUser
is_verified
owner_loginsamberry19
public_repos16
account_age_days2,323
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
4/35Publish recencylatest publish 816 days ago
20/20Version history6 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesbioviper
ecosystemspypi
any_deprecatedno
min_days_since_publish816

Engineering Quality

Are baseline engineering and documentation practices in place?

42Weak · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics3 topics
10/10Wiki
Inputs used
topicsbiological-data-analysis, multiple-sequence-alignment, protein-structure
has_wikiyes
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?

39Weak · 16% of overall
How it's scored
6.8/7.5Binary-Artifactsbinaries present in source code
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Testsno data
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update 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
1/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
0/5SASTno SAST tool detected
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3.9
Excluded from scoring (no data or not applicable): CI-Tests, Packaging, Signed-Releases. 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.

24At Risk · 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
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
2/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
0/45Type-checkable codeJupyter Notebook without a type-check config
55/55Manageable file sizes0/9 source files over 60KB
Inputs used
primary_languageJupyter Notebook
largest_source_bytes42,149
source_files_sampled9
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesnotebooks
Inputs used
example_dirsnotebooks
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

7GitHub stars
2contributors
2commits, last 12 months
318days since last push
2releases
1bus factor
2open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 3.9 / 10
3.9aggregate

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 03:10 UTC

9Binary-Artifactsbinaries present in source code
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update 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
2Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPInumpypyproject.toml
PyPIpandaspyproject.toml
PyPImatplotlibpyproject.toml
PyPIbiopythonpyproject.toml
PyPItqdmpyproject.toml
PyPIete4pyproject.toml
All dependencies 8

Full resolved dependency set from the GitHub dependency graph: 6 direct and 2 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbiopythondirect
PyPIete4direct
PyPImatplotlibdirect
PyPInumpydirect
PyPIpandasdirect
PyPItqdmdirect
PyPIete3indirect
PyPIsubprocessindirect
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.