Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-20 00:46 UTC

opalsecurity / opal-python

Opal Python SDK

PythonNo license detected★ 3 stars⑂ 0 forkssince Nov 2021View on GitHub ↗

opalsecurity/opal-python holds a health index of 59 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (78/100) and lowest on Security (21/100). It was last updated 6 days ago. A single contributor accounts for most of its recent work.

59
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.

59
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 56 is calibrated to 59 on the published index scale (record calibration 2026-08-02).

Ownership

OpalOrganization · verified domain
11 followers16 public repossince Mar 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIopal_security1.0.81,351951 days agoopenapiopenapi-generatoropal-api

Metrics by category

Vitality

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

72Good · 21% of overall
How it's scored
36/36Push recencylast push 6 days ago
4.2/36Commit cadence6/52 weeks with commits
11.7/18Commit volume19 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year19
human_commit_share0.873
days_since_last_push6
active_weeks_last_year6
How it's scored
27/27Ships releases7 releases published
36/36Release recencylatest release 51 days ago
19.8/27Release cadencea release every ~101.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count7
latest_release_tagv1.0.8
releases_from_tagsno
days_since_latest_release51
mean_days_between_releases101.7

Community & Adoption

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

24At Risk · 17% of overall
How it's scored
4.9/60Stars3 stars
0/25Forks0 forks
0/15Watchers1 watchers
Inputs used
forks0
stars3
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
0/22.5Licenseno license file detected
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseno
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
41.7/80Monthly downloads1,351 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesopal_security
dependents
ecosystemspypi
total_downloads
monthly_downloads1,351
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?

72Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
10.9/22.5Commit distributiontop contributor authored 52% of commits
12.2/13.5Contributor breadth9 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor1
contributors_sampled9
top_contributor_share0.516
How it's scored
42/42Issue resolution100% of issues closed
20.2/30PR acceptance29/43 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs29
open_issues0
closed_issues2
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs14
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.
How it's scored
30/30Ownership backingorganization-owned
20/20Verified domain
7.8/25Owner reach11 followers of opalsecurity
21/25Track record16 public repos, account ~6 yr old
Inputs used
followers11
owner_typeOrganization
is_verifiedyes
owner_loginopalsecurity
public_repos16
account_age_days2,364

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 51 days ago
20/20Version history9 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesopal_security
ecosystemspypi
any_deprecatedno
min_days_since_publish51

Engineering Quality

Are baseline engineering and documentation practices in place?

78Good · 19% of overall
How it's scored
24/24CI workflows3 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.pylint]), setup.cfg ([flake8]), tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

21At Risk · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestspyproject.toml, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages8
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:opal_security@1.0.8 runtime dependency closure — what installing the published package pulls in — 8 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.

58Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
26.7/40Legible commit history31 of 62 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.5
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.pylint]), setup.cfg ([flake8]), tox.ini
11/11Static type checkingopal_security/py.typed
0/10Reproducible environment
5.6/10Demonstrated agent practice2 of the last 71 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configsopal_security/py.typed
agent_commit_share0.028
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codePython with type-check config (opal_security/py.typed)
54.5/55Manageable file sizes6/656 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes321,487
source_files_sampled656
oversized_source_files6
How it's scored
40/40API schema (OpenAPI/GraphQL/proto)api/openapi.yaml
0/20MCP servernot applicable to this kind of software
0/40Runnable examples
Inputs used
example_dirs
has_mcp_signalno
api_schema_filesapi/openapi.yaml
interfaces_expected_of
Excluded from scoring (no data or not applicable): MCP server. Remaining weights renormalized.

Key facts

3GitHub stars
9contributors
19commits, last 12 months
6days since last push
7releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIurllib3(>=2.1.0,<3.0.0)pyproject.toml
PyPIpython-dateutil(>=2.8.2)pyproject.toml
PyPIpydantic(>=2)pyproject.toml
PyPItyping-extensions(>=4.7.1)pyproject.toml
All dependencies 11

Full resolved dependency set from the GitHub dependency graph: 4 direct and 7 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIpydanticdirect
PyPIpython-dateutildirect
PyPItyping-extensionsdirect
PyPIurllib3direct
PyPIflake8indirect
PyPImypyindirect
PyPIpytestindirect
PyPIpytest-covindirect
PyPIsetuptools-scmindirect
PyPItoxindirect
PyPItypes-python-dateutilindirect
Dependency advisories 0

Installing pypi:opal_security@1.0.8 pulls in 8 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 statisticsPyPI.