Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 15:51 UTC

dgilland / pydash

The kitchen sink of Python utility libraries for doing "stuff" in a functional way. Based on the Lo-Dash Javascript library.

PythonMIT★ 1,448 stars⑂ 101 forkssince May 2013View on GitHub ↗

dgilland/pydash holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (90/100) and lowest on Security (57/100). It was last updated 5 days ago. A single contributor accounts 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

Derrick GillandPersonal account
96 followers30 public repossince Dec 2011

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 publishTags
PyPIpydash8.0.611,822,78479221 days agopydashutilityfunctionallodashunderscore

Metrics by category

Vitality

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

60Moderate · 21% of overall
How it's scored
36/36Push recencylast push 5 days ago
4.2/36Commit cadence6/52 weeks with commits
12.1/18Commit volume21 commits in the last year
10/10OpenSSF Scorecard: Maintained16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year21
human_commit_share1
days_since_last_push5
active_weeks_last_year6
How it's scored
16.2/27Ships releases80 version tags (no GitHub releases)
16.2/36Release recencylatest release 221 days ago
19.8/27Release cadencea release every ~102.9 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count80
latest_release_tagv8.0.6
releases_from_tagsyes
days_since_latest_release221
mean_days_between_releases102.9
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?

80Excellent · 17% of overall
How it's scored
51.3/60Stars1,448 stars
16.7/25Forks101 forks
6.7/15Watchers17 watchers
Inputs used
forks101
stars1,448
watchers17
growth_stateorganic
growth_factor_pct100
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
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
80/80Monthly downloads11,822,784 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagespydash
dependents
ecosystemspypi
total_downloads
monthly_downloads11,822,784
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?

65Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
2.4/22.5Commit distributiontop contributor authored 89% of commits
13.5/13.5Contributor breadth27 contributors
10/10OpenSSF Scorecard: Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled27
top_contributor_share0.892
How it's scored
40.6/42Issue resolution97% of issues closed
26.4/30PR acceptance94/107 decided PRs merged
13/13Newcomer PR acceptance1/1 first-time contributors' PRs merged in 30d
6/15OpenSSF Scorecard: Code-ReviewFound 12/30 approved changesets -- score normalized to 4
Inputs used
merged_prs94
open_issues5
closed_issues141
prs_merged_7d1
prs_decided_7d1
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.966
closed_unmerged_prs13
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d1
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
14.3/25Owner reach96 followers of dgilland
22.9/25Track record30 public repos, account ~14 yr old
Inputs used
followers96
owner_typeUser
is_verified
owner_logindgilland
public_repos30
account_age_days5,375
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 221 days ago
20/20Version history79 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagespydash
ecosystemspypi
any_deprecatedno
min_days_since_publish221

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff]), tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttp://pydash.readthedocs.io
10/10Repository description
10/10Topics5 topics
10/10Wiki
Inputs used
topicslodash, utility, functional, python, python3
has_wikiyes
homepagehttp://pydash.readthedocs.io
docs_sitehttp://pydash.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

57Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
2.5/2.5CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3/7.5Code-ReviewFound 12/30 approved changesets -- score normalized to 4
2.5/2.5Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
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
7.5/7.5Maintained16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
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
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.6
Excluded from scoring (no data or not applicable): 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
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_packages1
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:pydash@8.0.6 runtime dependency closure — what installing the published package pulls in — 1 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)
40/40Legible commit history88 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.88
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdocs/Makefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff]), tox.ini
11/11Static type checkingsrc/pydash/py.typed
0/10Reproducible environment
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/pydash/py.typed
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codePython with type-check config (src/pydash/py.typed)
52.4/55Manageable file sizes2/42 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes72,057
source_files_sampled42
oversized_source_files2

Key facts

1,448GitHub stars
27contributors
21commits, last 12 months
5days since last push
80releases
1bus factor
5open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-07-16: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 1448 stars today.

More detail

Star and fork history 1,446 ★ / 101 ⇿
1,446Stars
101Forks
80Releases

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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

Star history is shown as collected on 2026-07-16. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

02505007501,0001,2501,5001,446101402014-072020-082026-08
Major 9Minor 19Patch 52

Each point covers 12 days.

OpenSSF Scorecard 4.6 / 10
4.6aggregate

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 15:51 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 12/30 approved changesets -- score normalized to 4
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
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
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPItyping-extensions>3.10,!=4.6.0pyproject.toml
All dependencies 2

Full resolved dependency set from the GitHub dependency graph: 1 direct and 1 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPItyping-extensionsdirect
PyPIsetuptoolsindirect
Dependency advisories 0

Installing pypi:pydash@8.0.6 pulls in 1 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.