Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:44 UTC

Parallels / rq-dashboard

Flask-based web front-end for monitoring RQ queues

Python · JavaScript · HTMLCustom license★ 1,519 stars⑂ 334 forkssince Jan 2012View on GitHub ↗
KindLibraryCommand-line toolhow this is determined

Parallels/rq-dashboard holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Sustainability & Governance (83/100) and lowest on AI Readiness (52/100). It was last updated 35 days ago. 3 contributors account for most of its recent work.

83
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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

Parallels, Inc.Organization
135 followers51 public repossince Dec 2013

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIrq-dashboard0.9.0433,9213541 days ago

Metrics by category

Vitality

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

60Moderate · 21% of overall
How it's scored
18/36Push recencylast push 35 days ago
5.5/36Commit cadence8/52 weeks with commits
10/18Commit volume12 commits in the last year
5/10OpenSSF Scorecard: Maintained5 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year12
human_commit_share0.88
days_since_last_push35
active_weeks_last_year8
How it's scored
27/27Ships releases26 releases published
36/36Release recencylatest release 41 days ago
19.8/27Release cadencea release every ~81.5 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count26
latest_release_tagv0.9.0
releases_from_tagsno
days_since_latest_release41
mean_days_between_releases81.5
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?

74Good · 17% of overall
How it's scored
51.6/60Stars1,519 stars
21/25Forks334 forks
8.8/15Watchers39 watchers
Inputs used
forks334
stars1,519
watchers39
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes
How it's scored
75.2/80Monthly downloads433,921 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesrq-dashboard
dependents
ecosystemspypi
total_downloads
monthly_downloads433,921
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?

83Excellent · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
16.7/22.5Commit distributiontop contributor authored 26% of commits
13.5/13.5Contributor breadth69 contributors
10/10OpenSSF Scorecard: Contributorsproject has 21 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled69
top_contributor_share0.259
How it's scored
31.6/42Issue resolution75% of issues closed
19.1/30PR acceptance190/298 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
12/15OpenSSF Scorecard: Code-ReviewFound 15/17 approved changesets -- score normalized to 8
Inputs used
merged_prs190
open_issues53
closed_issues162
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.753
closed_unmerged_prs108
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
0/20Verified domainverified-domain status not read for this organization
15.3/25Owner reach135 followers of Parallels
24.5/25Track record51 public repos, account ~12 yr old
Inputs used
followers135
owner_typeOrganization
is_verified
owner_loginParallels
public_repos51
account_age_days4,621
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 41 days ago
20/20Version history35 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesrq-dashboard
ecosystemspypi
any_deprecatedno
min_days_since_publish41

Engineering Quality

Are baseline engineering and documentation practices in place?

73Good · 19% of overall
How it's scored
24/24CI workflows3 workflow(s)
24/24Tests present
16/16Linter configtox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
8/20OpenSSF Scorecard: CI-Tests11 out of 25 merged PRs checked by a CI test -- score normalized to 4
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttp://python-rq.org/
10/10Repository description
10/10Topics2 topics
10/10Wiki
Inputs used
topicspython, rq
has_wikiyes
homepagehttp://python-rq.org/
docs_sitehttp://python-rq.org/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

61Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
1/2.5CI-Tests11 out of 25 merged PRs checked by a CI test -- score normalized to 4
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6/7.5Code-ReviewFound 15/17 approved changesets -- score normalized to 8
2.5/2.5Contributorsproject has 21 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
3.8/7.5Maintained5 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 5
5/5Packagingpackaging workflow detected
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
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities17 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.1
Excluded from scoring (no data or not applicable): Branch-Protection, 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
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_packages15
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:rq-dashboard@0.9.0 runtime dependency closure — what installing the published package pulls in — 15 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.

52Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
30.3/40Legible commit history50 of 88 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.568
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format configtox.ini
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance5 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_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.05
How it's scored
0/45Type-checkable codePython without a type-check config
48.1/55Manageable file sizes3/24 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes230,599
source_files_sampled24
oversized_source_files3

Key facts

1,519GitHub stars
69contributors
12commits, last 12 months
35days since last push
26releases
3bus factor
53open 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 ★ / 334 ⇿
0Stars
334Forks
25Releases

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.

012525037532452012-052019-062026-06
Major 0Minor 5Patch 19

Each point covers 13 days.

OpenSSF Scorecard 5.1 / 10
5.1aggregate

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 · 2026-08-13 03:43 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
4CI-Tests11 out of 25 merged PRs checked by a CI test -- score normalized to 4
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 15/17 approved changesets -- score normalized to 8
10Contributorsproject has 21 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
5Maintained5 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 5
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
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
0Vulnerabilities17 existing vulnerabilities detected
All dependencies 20

Full resolved dependency set from the GitHub dependency graph: 0 direct and 20 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIarrowindirect
PyPIarrow1.2.3indirect
PyPIbackports-functools-lru-cache1.5indirect
PyPIblackindirect
PyPIclick8.1.7indirect
PyPIflaskindirect
PyPIflask2.3.2indirect
PyPIisortindirect
PyPIitsdangerous2.1.2indirect
PyPIjinja23.1.2indirect
PyPImarkupsafe2.1.3indirect
PyPIpython-dateutil2.8.2indirect
PyPIredisindirect
PyPIredis5.2.0indirect
PyPIredis-sentinel-urlindirect
PyPIredis-sentinel-url1.0.1indirect
PyPIrqindirect
PyPIrq2.0.0indirect
PyPIsix1.16.0indirect
PyPIwerkzeug2.3.7indirect
Dependency advisories 0

Installing pypi:rq-dashboard@0.9.0 pulls in 15 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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.