Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 13:11 UTC

redis / hiredis-py

Python wrapper for hiredis

C · PythonMIT★ 522 stars⑂ 104 forkssince Jan 2011View on GitHub ↗

redis/hiredis-py holds a health index of 84 out of 100, placing it in the Excellent band. It scores highest on Sustainability & Governance (87/100) and lowest on AI Readiness (58/100). It was last updated 17 days ago. 3 contributors account for most of its recent work.

84
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.

84
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 71 is calibrated to 84 on the published index scale (record calibration 2026-08-02).

Ownership

RedisOrganization · verified domain
2,908 followers78 public repossince Mar 2012

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIhiredis3.4.132,591,8493620 days agoredis

Metrics by category

Vitality

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

65Good · 21% of overall
How it's scored
28.8/36Push recencylast push 17 days ago
4.2/36Commit cadence6/52 weeks with commits
10.8/18Commit volume15 commits in the last year
3/10OpenSSF Scorecard: Maintained4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
Inputs used
commits_last_year15
human_commit_share0.98
days_since_last_push17
active_weeks_last_year6
How it's scored
27/27Ships releases18 releases published
36/36Release recencylatest release 20 days ago
19.8/27Release cadencea release every ~83.2 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count18
latest_release_tagv3.4.1
releases_from_tagsno
days_since_latest_release20
mean_days_between_releases83.2
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?

70Good · 17% of overall
How it's scored
44.1/60Stars522 stars
16.8/25Forks104 forks
7.4/15Watchers22 watchers
Inputs used
forks104
stars522
watchers22
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_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, github.com, shields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads32,591,849 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packageshiredis
dependents
ecosystemspypi
total_downloads
monthly_downloads32,591,849
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?

87Excellent · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
14.8/22.5Commit distributiontop contributor authored 34% of commits
13.5/13.5Contributor breadth40 contributors
10/10OpenSSF Scorecard: Contributorsproject has 16 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled40
top_contributor_share0.341
How it's scored
39.8/42Issue resolution95% of issues closed
24/30PR acceptance113/141 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-ReviewFound 9/29 approved changesets -- score normalized to 3
Inputs used
merged_prs113
open_issues5
closed_issues89
prs_merged_7d0
prs_decided_7d0
prs_merged_30d3
prs_decided_30d3
issue_closed_ratio0.947
closed_unmerged_prs28
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
24.9/25Owner reach2,908 followers of redis
25/25Track record78 public repos, account ~14 yr old
Inputs used
followers2,908
owner_typeOrganization
is_verifiedyes
owner_loginredis
public_repos78
account_age_days5,280

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 20 days ago
20/20Version history36 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packageshiredis
ecosystemspypi
any_deprecatedno
min_days_since_publish20

Engineering Quality

Are baseline engineering and documentation practices in place?

64Moderate · 19% of overall
How it's scored
24/24CI workflows7 workflow(s)
24/24Tests present
16/16Linter configtox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
10/20OpenSSF Scorecard: CI-Tests14 out of 28 merged PRs checked by a CI test -- score normalized to 5
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

67Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
1.2/2.5CI-Tests14 out of 28 merged PRs checked by a CI test -- score normalized to 5
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-ReviewFound 9/29 approved changesets -- score normalized to 3
2.5/2.5Contributorsproject has 16 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
5/5Fuzzingproject is fuzzed
2.5/2.5Licenselicense file detected
2.2/7.5Maintained4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
4.5/7.5Vulnerabilities4 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.9
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories3
affected_packages1
assessed_packages6
unassessed_packages4
affected_by_severitycritical 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 6 resolved dependencies against OSV. 4 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.

58Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history79 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.806
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configtox.ini
11/11Static type checkinghiredis/py.typed
0/10Reproducible environment
4/10Demonstrated agent practice2 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance2 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageyes
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configshiredis/py.typed
agent_commit_share0.02
toolchain_manifests
dependency_bot_commit_share0.02
How it's scored
45/45Type-checkable codeC (statically typed)
55/55Manageable file sizes0/13 source files over 60KB
Inputs used
primary_languageC
largest_source_bytes17,402
source_files_sampled13
oversized_source_files0

Key facts

522GitHub stars
40contributors
15commits, last 12 months
17days since last push
18releases
3bus factor
5open 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 ★ / 104 ⇿
0Stars
104Forks
17Releases

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.

02040608010012010332012-012019-042026-08
Major 1Minor 7Patch 9

Each point covers 14 days.

OpenSSF Scorecard 5.9 / 10
5.9aggregate

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 · 2026-08-27 13:10 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal 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
5CI-Tests14 out of 28 merged PRs checked by a CI test -- score normalized to 5
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 9/29 approved changesets -- score normalized to 3
10Contributorsproject has 16 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
10Fuzzingproject is fuzzed
10Licenselicense file detected
3Maintained4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
6Vulnerabilities4 existing vulnerabilities detected
All dependencies 10

Full resolved dependency set from the GitHub dependency graph: 0 direct and 10 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIblack24.3.0indirect
PyPIflake84.0.1indirect
PyPIisort5.10.1indirect
PyPImemray1.19.2indirect
PyPIpytestindirect
PyPIpytest-memray1.7.0indirect
PyPIsetuptoolsindirect
PyPItox3.24.4indirect
PyPIvultureindirect
PyPIwheelindirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 6 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 0 are direct. 4 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
black24.3.0indirectcritical326.3.1

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.