Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 17:34 UTC

apitally / apitally-py

Simple API monitoring & analytics for Python apps

PythonMIT★ 225 stars⑂ 10 forkssince Jul 2023View on GitHub ↗

#api #monitoring #api-analytics #api-monitoring #api-observability #django-ninja #django-rest-framework #fastapi #flask #python #rest-api #litestar #api-logging #blacksheep #django #starlette

apitally/apitally-py holds a health index of 87 out of 100, placing it in the Excellent band. It scores highest on Vitality (99/100) and lowest on Community & Adoption (55/100). It was last updated today. A single contributor accounts for most of its recent work.

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.

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)

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 73 is calibrated to 87 on the published index scale (record calibration 2026-08-02).

Ownership

ApitallyOrganization · verified domain

35 followers12 public repossince Jul 2023

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	apitally	0.25.1	39,083	73	73 days ago

Metrics by category

Vitality

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

99Exceptional · 21% of overall

Development activity

98Exceptional

How it's scored

36/36	Push recency — last push 0 days ago
33.9/36	Commit cadence — 49/52 weeks with commits
18/18	Commit volume — 191 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	191
human_commit_share	0.12
days_since_last_push	0
active_weeks_last_year	49

Release discipline

100Exceptional

How it's scored

27/27	Ships releases — 69 releases published
36/36	Release recency — latest release 73 days ago
27/27	Release cadence — a release every ~22.7 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	69
latest_release_tag	v0.25.1
releases_from_tags	no
days_since_latest_release	73
mean_days_between_releases	22.7

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?

55Moderate · 17% of overall

Popularity & adoption

46Weak

How it's scored

38.1/60	Stars — 225 stars
8/25	Forks — 10 forks
0/15	Watchers — 1 watchers

Inputs used

forks	10
stars	225
watchers	1
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

50Moderate

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (MIT)
0/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
0/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	3
has_contributing	no
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	codecov.io, github.com, shields.io
has_pull_request_template	no

Ecosystem adoption (downloads)

76Good

How it's scored

61.2/80	Monthly downloads — 39,083 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	apitally
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	39,083
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?

62Moderate · 23% of overall

Maintainer resilience (bus factor)

16Critical

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
0/22.5	Commit distribution — top contributor authored 100% of commits
1.4/13.5	Contributor breadth — 1 contributors
6/10	OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6

Inputs used

bus_factor	1
contributors_sampled	1
top_contributor_share	1

Issue & PR responsiveness

73Good

How it's scored

37.8/42	Issue resolution — 90% of issues closed
26/30	PR acceptance — 283/327 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 0/26 approved changesets -- score normalized to 0

Inputs used

merged_prs	283
open_issues	1
closed_issues	9
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	1
prs_decided_30d	2
issue_closed_ratio	0.9
closed_unmerged_prs	44
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

76Good

How it's scored

30/30	Ownership backing — organization-owned
20/20	Verified domain
11.2/25	Owner reach — 35 followers of apitally
14.5/25	Track record — 12 public repos, account ~3 yr old

Inputs used

followers	35
owner_type	Organization
is_verified	yes
owner_login	apitally
public_repos	12
account_age_days	1,166

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 73 days ago
20/20	Version history — 73 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	apitally
ecosystems	pypi
any_deprecated	no
min_days_since_publish	73

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

100Exceptional

How it's scored

24/24	CI workflows — 3 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
9.6/9.6	Pre-commit hooks
6.4/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	yes
has_linter_config	yes
has_precommit_config	yes

Documentation

65Good

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://apitally.io
10/10	Repository description
10/10	Topics — 16 topics
0/10	Wiki

Inputs used

topics	api, monitoring, api-analytics, api-monitoring, api-observability, django-ninja, django-rest-framework, fastapi, flask, python, rest-api, litestar, api-logging, blacksheep, django, starlette
has_wiki	no
homepage	https://apitally.io
docs_site	https://apitally.io
has_readme	yes
has_docs_dir	no
has_description	yes

Security

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

62Moderate · 16% of overall

Security posture

52Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2.5/2.5	CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 0/26 approved changesets -- score normalized to 0
1.5/2.5	Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
5/5	Pinned-Dependencies — all dependencies are pinned
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 10 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	5.2

Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	6
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:apitally@0.25.1 runtime dependency closure — what installing the published package pulls in — 6 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.

68Good · 4% of overall

Agent context & guidance

25At Risk

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15	Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.apitally.io/llms.txt)
0/40	Legible commit history — no data

Inputs used

has_llms_txt	yes
llms_txt_url	https://docs.apitally.io/llms.txt
legible_history_share	—
agent_instruction_files	—
agent_instruction_max_bytes	—

Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

96Exceptional

How it's scored

18/18	One-command bootstrap — Makefile
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
11/11	Static type checking — apitally/py.typed
10/10	Reproducible environment — lockfile
6/10	Demonstrated agent practice — 3 of the last 100 commits agent-authored or agent-credited
8/8	Automated maintenance — 88 of the last 100 commits are automated dependency updates
10/10	OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned

Inputs used

has_nix	no
has_tests	yes
lockfiles	uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	apitally/py.typed
agent_commit_share	0.03
toolchain_manifests	—
dependency_bot_commit_share	0.88

Code legibility for models

82Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (apitally/py.typed)
55/55	Manageable file sizes — 0/52 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	22,492
source_files_sampled	52
oversized_source_files	0

Key facts

225GitHub stars

1contributors

191commits, last 12 months

0days since last push

69releases

1bus factor

1open 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 ★ / 10 ⇿

0Stars

10Forks

40Releases

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.

Major 0Minor 13Patch 27

Each point covers 2 days.

OpenSSF Scorecard 5.2 / 10

5.2aggregate

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 · 2026-09-10 17:33 UTC

10	Binary-Artifacts	no binaries found in the repo
n/a	Branch-Protection	internal 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
10	CI-Tests	30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 0/26 approved changesets -- score normalized to 0
6	Contributors	project has 2 contributing companies or organizations -- score normalized to 6
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
10	Pinned-Dependencies	all dependencies are pinned
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	10 existing vulnerabilities detected

Direct dependencies 4

Registry	Package	Version constraint	Manifest
PyPI	backoff	`>=2.0.0`	pyproject.toml
PyPI	opentelemetry-sdk	`>=1.39.1,<2.0.0`	pyproject.toml
PyPI	psutil	`>=5.9.6`	pyproject.toml
PyPI	typing-extensions	`>=4.0.0`	pyproject.toml

All dependencies 126

Full resolved dependency set from the GitHub dependency graph: 4 direct and 122 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	backoff	`2.2.1`	direct
PyPI	opentelemetry-sdk	`1.44.0`	direct
PyPI	psutil	`7.2.2`	direct
PyPI	typing-extensions	`4.16.0`	direct
PyPI	annotated-doc	`0.0.5`	indirect
PyPI	annotated-types	`0.8.0`	indirect
PyPI	anyio	`4.15.0`	indirect
PyPI	asgiref	`3.12.1`	indirect
PyPI	async-timeout	`5.0.1`	indirect
PyPI	blacksheep	`2.6.3`	indirect
PyPI	blinker	`1.9.0`	indirect
PyPI	certifi	`2026.7.22`	indirect
PyPI	cffi	`2.1.1`	indirect
PyPI	cfgv	`3.5.0`	indirect
PyPI	charset-normalizer	`3.5.1`	indirect
PyPI	click	`8.5.0`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	coverage	`7.16.0`	indirect
PyPI	cryptography	`46.0.7`	indirect
PyPI	defusedxml	`0.7.1`	indirect
PyPI	distlib	`0.4.3`	indirect
PyPI	django	`5.2.17`	indirect
PyPI	django	`6.1.1`	indirect
PyPI	django-ninja	`1.7.0`	indirect
PyPI	django-types	`0.24.0`	indirect
PyPI	djangorestframework	`3.18.0`	indirect
PyPI	djangorestframework-types	`0.9.0`	indirect
PyPI	essentials	`1.1.9`	indirect
PyPI	essentials-openapi	`1.4.0`	indirect
PyPI	exceptiongroup	`1.3.1`	indirect
PyPI	faker	`40.38.0`	indirect
PyPI	fastapi	`0.141.1`	indirect
PyPI	filelock	`3.32.5`	indirect
PyPI	flask	`3.1.3`	indirect
PyPI	guardpost	`1.1.0`	indirect
PyPI	h11	`0.16.0`	indirect
PyPI	h2	`4.4.1`	indirect
PyPI	hpack	`4.2.0`	indirect
PyPI	httpcore	`1.0.9`	indirect
PyPI	httptools	`0.8.0`	indirect
PyPI	httpx	`0.27.2`	indirect
PyPI	hyperframe	`6.1.0`	indirect
PyPI	identify	`2.6.19`	indirect
PyPI	idna	`3.19`	indirect
PyPI	inflection	`0.5.1`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	itsdangerous	`2.2.0`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	litestar	`2.24.0`	indirect
PyPI	litestar-htmx	`0.5.0`	indirect
PyPI	loguru	`0.7.3`	indirect
PyPI	markdown-it-py	`4.2.0`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	msgspec	`0.21.1`	indirect
PyPI	multidict	`6.7.1`	indirect
PyPI	multipart	`2.0.0`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	opentelemetry-api	`1.44.0`	indirect
PyPI	opentelemetry-instrumentation	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-asyncpg	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-botocore	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-dbapi	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-httpx	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-mysql	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-psycopg	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-psycopg2	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-pymongo	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-redis	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-requests	`0.65b0`	indirect
PyPI	opentelemetry-instrumentation-sqlalchemy	`0.65b0`	indirect
PyPI	opentelemetry-propagator-aws-xray	`1.0.2`	indirect
PyPI	opentelemetry-semantic-conventions	`0.65b0`	indirect
PyPI	opentelemetry-util-http	`0.65b0`	indirect
PyPI	packaging	`26.3`	indirect
PyPI	platformdirs	`4.11.7`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	polyfactory	`3.3.0`	indirect
PyPI	pre-commit	`4.6.2`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pydantic	`2.13.5`	indirect
PyPI	pydantic-core	`2.46.5`	indirect
PyPI	pygments	`2.21.0`	indirect
PyPI	pyjwt	`2.12.1`	indirect
PyPI	pytest	`8.4.2`	indirect
PyPI	pytest-asyncio	`0.21.2`	indirect
PyPI	pytest-cov	`7.1.0`	indirect
PyPI	pytest-httpx	`0.33.0`	indirect
PyPI	pytest-mock	`3.15.1`	indirect
PyPI	python-discovery	`1.6.0`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	requests	`2.34.2`	indirect
PyPI	requests-mock	`1.12.1`	indirect
PyPI	rich	`15.0.0`	indirect
PyPI	rich-click	`1.9.8`	indirect
PyPI	rodi	`2.0.8`	indirect
PyPI	ruff	`0.15.22`	indirect
PyPI	sentry-sdk	`2.68.1`	indirect
PyPI	sniffio	`1.3.1`	indirect
PyPI	sqlparse	`0.6.0`	indirect
PyPI	starlette	`1.6.0`	indirect
PyPI	tomli	`2.4.1`	indirect
PyPI	ty	`0.0.78`	indirect
PyPI	types-colorama	`0.4.15.20260508`	indirect
PyPI	types-docutils	`0.23.0.20260827`	indirect
PyPI	types-gevent	`26.8.0.20260811`	indirect
PyPI	types-greenlet	`3.5.0.20260518`	indirect
PyPI	types-pexpect	`4.9.0.20260518`	indirect
PyPI	types-psutil	`7.2.2.20260827`	indirect
PyPI	types-psycopg2	`2.9.21.20260724`	indirect
PyPI	types-pygments	`2.21.0.20260819`	indirect
PyPI	types-pysocks	`1.7.1.20260518`	indirect
PyPI	types-pyyaml	`6.0.12.20260815`	indirect
PyPI	types-requests	`2.33.0.20260712`	indirect
PyPI	types-setuptools	`84.0.0.20260812`	indirect
PyPI	types-six	`1.17.0.20260724`	indirect
PyPI	types-ujson	`5.10.0.20250822`	indirect
PyPI	typing-inspection	`0.4.4`	indirect
PyPI	tzdata	`2026.3`	indirect
PyPI	uritemplate	`4.2.0`	indirect
PyPI	urllib3	`2.7.0`	indirect
PyPI	virtualenv	`21.7.8`	indirect
PyPI	websockets	`15.0.1`	indirect
PyPI	werkzeug	`3.1.8`	indirect
PyPI	win32-setctime	`1.2.0`	indirect
PyPI	wrapt	`2.4.0`	indirect

Dependency advisories 0

Installing pypi:apitally@0.25.1 pulls in 6 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.

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.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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