Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 07:24 UTC

F5Networks / f5-icontrol-rest-python

Generic python library used by the F5 SDK and other F5 projects to communicate with BIG-IP® via the REST API

PythonApache-2.0★ 40 stars⑂ 33 forkssince Oct 2015View on GitHub ↗

F5Networks/f5-icontrol-rest-python holds a health index of 51 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (74/100) and lowest on Security (21/100). It was last updated 156 days ago. 2 contributors account for most of its recent work.

51
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.

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)
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 51 is calibrated to 51 on the published index scale (record calibration 2026-08-02).

Ownership

F5Organization
367 followers80 public repossince Sep 2014

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIf5-icontrol-rest1.3.13214,250232716 days agof5icontrolrestapibigip

Metrics by category

Vitality

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

24At Risk · 21% of overall
How it's scored
9.9/36Push recency — last push 156 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push156
active_weeks_last_year0
How it's scored
27/27Ships releases — 31 releases published
0/36Release recency — latest release 985 days ago
12.6/27Release cadence — a release every ~225.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count31
latest_release_tagv1.3.16
releases_from_tagsno
days_since_latest_release985
mean_days_between_releases225.8

Community & Adoption

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

65Good · 17% of overall
How it's scored
25.8/60Stars — 40 stars
12.5/25Forks — 33 forks
7.8/15Watchers — 26 watchers
Inputs used
forks33
stars40
watchers26
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno
How it's scored
71.1/80Monthly downloads — 214,250 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesf5-icontrol-rest
dependents—
ecosystemspypi
total_downloads—
monthly_downloads214,250
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?

74Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
15.3/22.5Commit distribution — top contributor authored 32% of commits
13.5/13.5Contributor breadth — 17 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor2
contributors_sampled17
top_contributor_share0.322
How it's scored
40.9/42Issue resolution — 97% of issues closed
27/30PR acceptance — 100/111 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs100
open_issues2
closed_issues74
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.974
closed_unmerged_prs11
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 backing — organization-owned
0/20Verified domain
18.4/25Owner reach — 367 followers of F5Networks
25/25Track record — 80 public repos, account ~11 yr old
Inputs used
followers367
owner_typeOrganization
is_verifiedno
owner_loginF5Networks
public_repos80
account_age_days4,373
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 2,716 days ago
20/20Version history — 23 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesf5-icontrol-rest
ecosystemspypi
any_deprecatedno
min_days_since_publish2,716

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://icontrol.readthedocs.org/en/latest/
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttp://icontrol.readthedocs.org/en/latest/
docs_sitehttp://icontrol.readthedocs.org/en/latest/
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 lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsrequirements.docs.txt, requirements.test.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 advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages9
unassessed_packages6
affected_by_severitymoderate 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 9 resolved dependencies against OSV. 6 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

56Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
39.5/40Legible commit history — 74 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.74
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/12 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes28,478
source_files_sampled12
oversized_source_files0

Key facts

40GitHub stars
17contributors
0commits, last 12 months
156days since last push
31releases
2bus factor
2open 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

Star and fork history 0 ★ / 33 ⇿
0Stars
33Forks
30Releases

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.

01325383322016-012020-102025-07
Major 0Minor 3Patch 25

Each point covers 9 days.

All dependencies 15

Full resolved dependency set from the GitHub dependency graph: 0 direct and 15 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIflake82.6.2indirect
PyPImccabe0.5.2indirect
PyPImock1.3.0indirect
PyPIpep81.7.0indirect
PyPIpyflakes1.2.3indirect
PyPIpyopenssl—indirect
PyPIpytest2.9.1indirect
PyPIpytest-cov2.2.1indirect
PyPIpython-coveralls2.7.0indirect
PyPIq—indirect
PyPIrequests—indirect
PyPIrequests-mock1.1.0indirect
PyPIsix—indirect
PyPIsphinx—indirect
PyPItox—indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 9 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 0 are direct. 6 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
pytest2.9.1indirectmoderate29.0.3

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 statistics — PyPI.