Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-18 00:06 UTC

django-es / django-elasticsearch-dsl

This is a package that allows indexing of django models in elasticsearch with elasticsearch-dsl-py.

PythonCustom license★ 1,056 stars⑂ 269 forkssince Aug 2016View on GitHub ↗

django-es/django-elasticsearch-dsl holds a health index of 31 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (87/100) and lowest on Vitality (18/100). It was last updated 421 days ago. 2 contributors account for most of its recent work.

31
overall / 100
At Risk

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.

31
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

django-esOrganization
1 follower1 public reposince Jun 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdjango-elasticsearch-dslpoints to another repo — not scored9.0-30421 days agodjangoelasticsearchelasticsearch-dsl

Metrics by category

Vitality

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

18Critical · 21% of overall
How it's scored
0/36Push recency — last push 421 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_share0.97
days_since_last_push421
active_weeks_last_year0
How it's scored
27/27Ships releases — 14 releases published
0/36Release recency — latest release 1,082 days ago
12.6/27Release cadence — a release every ~159.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count14
latest_release_tag8.0
releases_from_tagsno
days_since_latest_release1,082
mean_days_between_releases159.3

Community & Adoption

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

71Good · 17% of overall
How it's scored
49/60Stars — 1,056 stars
20.2/25Forks — 269 forks
8.7/15Watchers — 38 watchers
Inputs used
forks269
stars1,056
watchers38
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, codecov.io, github.com, readthedocs.org
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

54Moderate · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
14.9/22.5Commit distribution — top contributor authored 34% of commits
13.5/13.5Contributor breadth — 48 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor2
contributors_sampled48
top_contributor_share0.338
How it's scored
23.9/42Issue resolution — 57% of issues closed
16.6/30PR acceptance — 102/184 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_prs102
open_issues135
closed_issues179
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.57
closed_unmerged_prs82
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
2.2/25Owner reach — 1 followers of django-es
14.2/25Track record — 1 public repos, account ~6 yr old
Inputs used
followers1
owner_typeOrganization
is_verifiedno
owner_logindjango-es
public_repos1
account_age_days2,281

Engineering Quality

Are baseline engineering and documentation practices in place?

87Excellent · 19% of overall
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configno

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 2 topics
10/10Wiki
Inputs used
topicshacktoberfest, elasticsearch
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 lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsexample/requirements.txt, requirements.txt, requirements_dev.txt, requirements_test.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages10
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:django-elasticsearch-dsl@9.0 runtime dependency closure — what installing the published package pulls in — 10 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.

60Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
33.5/40Legible commit history — 61 of 97 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.629
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 3 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.03
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/41 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes19,678
source_files_sampled41
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — example
Inputs used
example_dirsexample
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

1,056GitHub stars
48contributors
0commits, last 12 months
421days since last push
14releases
2bus factor
135open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'django-elasticsearch-dsl' points at a different repository (https://github.com/sabricot/django-elasticsearch-dsl); excluded from ecosystem scoring
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 269 ⇿
0Stars
269Forks
14Releases

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.

05010015020025030025542017-022021-112026-08
Major 1Minor 4Patch 6

Each point covers 9 days.

All dependencies 16

Full resolved dependency set from the GitHub dependency graph: 0 direct and 16 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbumpversion0.6.0indirect
PyPIcelery—indirect
PyPIcoverage—indirect
PyPIdjango—indirect
PyPIdjango4.1.2indirect
PyPIdjango-autofixture0.12.1indirect
PyPIelasticsearch—indirect
PyPIflake8—indirect
PyPImock—indirect
PyPIpillow—indirect
PyPIpillow6.2.2indirect
PyPIsix—indirect
PyPIsphinx—indirect
PyPItox—indirect
PyPItwine—indirect
PyPIwheel0.45.1indirect
Dependency advisories 0

Installing pypi:django-elasticsearch-dsl@9.0 pulls in 10 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 statistics — PyPI.