Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:07 UTC

Kludex / mangum

AWS Lambda support for ASGI applications

PythonMIT★ 2,131 stars⑂ 134 forkssince Jan 2019View on GitHub ↗
KindLibraryhow this is determined
#asgi#aws#lambda#serverless#python#asyncio#api-gateway#starlette#fastapi#quart#django#sanic#aws-lambda#python3

Kludex/mangum holds a health index of 77 out of 100, placing it in the Good band. It scores highest on Community & Adoption (74/100) and lowest on AI Readiness (52/100). It was last updated 3 days ago. A single contributor accounts for most of its recent work.

77
overall / 100
Good

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.

77
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 66 is calibrated to 77 on the published index scale (record calibration 2026-08-02).

Ownership

Marcelo TrylesinskiPersonal account
3,217 followers168 public repossince Apr 2014@pydantic

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 publish
PyPImangum0.21.0-74192 days ago

Metrics by category

Vitality

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

60Moderate · 21% of overall

Development activity

59Moderate
How it's scored
36/36Push recency — last push 3 days ago
5.5/36Commit cadence — 8/52 weeks with commits
12.7/18Commit volume — 25 commits in the last year
5/10OpenSSF Scorecard: Maintained — 6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year25
human_commit_share0.87
days_since_last_push3
active_weeks_last_year8

Release discipline

62Moderate
How it's scored
27/27Ships releases — 21 releases published
16.2/36Release recency — latest release 192 days ago
12.6/27Release cadence — a release every ~158.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count21
latest_release_tag0.21.0
releases_from_tagsno
days_since_latest_release192
mean_days_between_releases158.6
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

Popularity & adoption

78Good
How it's scored
54/60Stars — 2,131 stars
17.7/25Forks — 134 forks
6.7/15Watchers — 17 watchers
Inputs used
forks134
stars2,131
watchers17
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

70Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized 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_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, shields.io
has_pull_request_templateno

Sustainability & Governance

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

66Good · 23% of overall

Maintainer resilience (bus factor)

37Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
4.6/22.5Commit distribution — top contributor authored 80% of commits
13.5/13.5Contributor breadth — 31 contributors
10/10OpenSSF Scorecard: Contributors — project has 14 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled31
top_contributor_share0.797

Issue & PR responsiveness

70Good
How it's scored
35.3/42Issue resolution — 84% of issues closed
24.3/30PR acceptance — 135/167 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 3/17 approved changesets -- score normalized to 1
Inputs used
merged_prs135
open_issues29
closed_issues153
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.841
closed_unmerged_prs32
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.

Ownership & stewardship

75Good
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
25/25Owner reach — 3,217 followers of Kludex
25/25Track record — 168 public repos, account ~12 yr old
Inputs used
followers3,217
owner_typeUser
is_verified—
owner_loginKludex
public_repos168
account_age_days4,497
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

91Excellent
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
26/35Publish recency — latest publish 192 days ago
20/20Version history — 74 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmangum
ecosystemspypi
any_deprecatedno
min_days_since_publish192

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall

Engineering practices

64Moderate
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
16/20OpenSSF Scorecard: CI-Tests — 25 out of 29 merged PRs checked by a CI test -- score normalized to 8
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://mangum.fastapiexpert.com/
10/10Repository description
10/10Topics — 14 topics
0/10Wiki
Inputs used
topicsasgi, aws, lambda, serverless, python, asyncio, api-gateway, starlette, fastapi, quart, django, sanic, aws-lambda, python3
has_wikino
homepagehttp://mangum.fastapiexpert.com/
docs_sitehttp://mangum.fastapiexpert.com/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

62Moderate · 16% of overall

Security posture

53Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2/2.5CI-Tests — 25 out of 29 merged PRs checked by a CI test -- score normalized to 8
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-Review — Found 3/17 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 14 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
3.8/7.5Maintained — 6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
1.5/7.5Vulnerabilities — 8 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.3
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 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_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:mangum@0.21.0 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.

52Moderate · 4% of overall

Agent context & guidance

35Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
34.9/40Legible commit history — 57 of 87 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.655
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

53Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
11/11Static type checking — mangum/py.typed
10/10Reproducible environment — lockfile
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 13 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configsmangum/py.typed
agent_commit_share0.01
toolchain_manifests—
dependency_bot_commit_share0.13

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (mangum/py.typed)
55/55Manageable file sizes — 0/23 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes23,012
source_files_sampled23
oversized_source_files0

Key facts

2,131GitHub stars
31contributors
25commits, last 12 months
3days since last push
21releases
1bus factor
29open 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 ★ / 134 ⇿
0Stars
134Forks
21Releases

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.

025507510012515013232019-042022-112026-07
Major 0Minor 13Patch 6

Each point covers 7 days.

OpenSSF Scorecard 5.3 / 10
5.3aggregate

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 03:06 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
8CI-Tests25 out of 29 merged PRs checked by a CI test -- score normalized to 8
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 3/17 approved changesets -- score normalized to 1
10Contributorsproject has 14 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained6 commit(s) and 0 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
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
2Vulnerabilities8 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPItyping_extensions—pyproject.toml
All dependencies 63

Full resolved dependency set from the GitHub dependency graph: 1 direct and 62 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPItyping-extensions4.15.0direct
PyPIaiofiles23.2.1indirect
PyPIanyio3.7.1indirect
PyPIbabel2.18.0indirect
PyPIbackrefs6.1indirect
PyPIblinker1.9.0indirect
PyPIbrotli1.2.0indirect
PyPIbrotli-asgi1.6.0indirect
PyPIcertifi2026.1.4indirect
PyPIcharset-normalizer3.4.4indirect
PyPIclick8.1.7indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.2.7indirect
PyPIexceptiongroup1.2.2indirect
PyPIflask3.1.3indirect
PyPIghp-import2.1.0indirect
PyPIh110.16.0indirect
PyPIh24.3.0indirect
PyPIhpack4.1.0indirect
PyPIhypercorn0.17.3indirect
PyPIhyperframe6.1.0indirect
PyPIidna3.15indirect
PyPIimportlib-metadata8.5.0indirect
PyPIiniconfig2.0.0indirect
PyPIitsdangerous2.2.0indirect
PyPIjinja23.1.6indirect
PyPImangum0.21.0indirect
PyPImarkdown3.8.1indirect
PyPImarkupsafe2.1.5indirect
PyPImergedeep1.3.4indirect
PyPImkautodoc0.2.0indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-get-deps0.2.0indirect
PyPImkdocs-material9.7.1indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImypy1.4.1indirect
PyPImypy-extensions1.0.0indirect
PyPIpackaging24.0indirect
PyPIpaginate0.5.7indirect
PyPIpathspec0.11.2indirect
PyPIplatformdirs4.0.0indirect
PyPIpluggy1.6.0indirect
PyPIpriority2.0.0indirect
PyPIpygments2.20.0indirect
PyPIpymdown-extensions11.0.1indirect
PyPIpytest8.4.2indirect
PyPIpytest9.0.2indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpyyaml6.0.1indirect
PyPIpyyaml-env-tag0.1indirect
PyPIquart0.20.0indirect
PyPIrequests2.33.0indirect
PyPIruff0.6.8indirect
PyPIsix1.16.0indirect
PyPIsniffio1.3.1indirect
PyPIstarlette0.49.1indirect
PyPItaskgroup0.0.0a4indirect
PyPItomli2.0.1indirect
PyPIurllib32.7.0indirect
PyPIwatchdog3.0.0indirect
PyPIwerkzeug3.1.6indirect
PyPIwsproto1.2.0indirect
PyPIzipp3.20.2indirect
Dependency advisories 0

Installing pypi:mangum@0.21.0 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

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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 statistics — PyPI.