Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 00:47 UTC

datafold / data-diff

Compare tables within or across databases

PythonMIT★ 2,988 stars⑂ 312 forkssince Mar 2022archivedView on GitHub ↗

KindCommand-line toolLibraryhow this is determined

datafold/data-diff holds a health index of 19 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (84/100) and lowest on Vitality (25/100). The repository is archived, so no further maintenance is expected.

overall / 100

Critical

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 62 is calibrated to 69 on the published index scale (record calibration 2026-08-02).

Ownership

DatafoldOrganization

85 followers41 public repossince Apr 2020

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	data-diff	0.11.2	-	75	817 days ago

Metrics by category

Vitality

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

25At Risk · 21% of overall

Development activity

1Critical

Abandonment alert

Work has arrived and nobody has attended to it

archived on GitHub by its maintainersOverall rating: Critical ceiling

Silence alone is never the finding — a small, finished library may need no commits for years. This alert requires both: no human commit for a long time, and obligations the project is visibly not discharging. Automated commits do not count as maintenance.

How abandonment is assessed

How it's scored

0/36	Push recency — last push 817 days ago
0/36	Commit cadence — 0/52 weeks with commits
0/18	Commit volume — 0 commits in the last year
0/10	OpenSSF Scorecard: Maintained — project is archived

Inputs used

commits_last_year	0
human_commit_share	1
days_since_last_push	817
active_weeks_last_year	0

Release discipline

60Moderate

How it's scored

27/27	Ships releases — 63 releases published
0/36	Release recency — latest release 904 days ago
27/27	Release cadence — a release every ~10.8 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	63
latest_release_tag	v0.11.1
releases_from_tags	no
days_since_latest_release	904
mean_days_between_releases	10.8

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?

82Excellent · 17% of overall

Popularity & adoption

79Good

How it's scored

56.4/60	Stars — 2,988 stars
20.8/25	Forks — 312 forks
1.7/15	Watchers — 3 watchers

Inputs used

forks	312
stars	2,988
watchers	3
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

85Excellent

How it's scored

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

Inputs used

has_readme	yes
has_license	yes
readme_badges	0
has_contributing	yes
has_issue_template	no
has_code_of_conduct	yes
readme_badge_services	—
has_pull_request_template	no

Sustainability & Governance

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

76Good · 23% of overall

Maintainer resilience (bus factor)

61Moderate

How it's scored

25.2/54	Bus factor — 2 contributor(s) cover half of all commits
12.5/22.5	Commit distribution — top contributor authored 44% of commits
13.5/13.5	Contributor breadth — 47 contributors
10/10	OpenSSF Scorecard: Contributors — project has 8 contributing companies or organizations

Inputs used

bus_factor	2
contributors_sampled	47
top_contributor_share	0.444

Issue & PR responsiveness

91Excellent

How it's scored

42/42	Issue resolution — 100% of issues closed
23.9/30	PR acceptance — 459/575 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
13.5/15	OpenSSF Scorecard: Code-Review — Found 15/16 approved changesets -- score normalized to 9

Inputs used

merged_prs	459
open_issues	0
closed_issues	318
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	1
closed_unmerged_prs	116
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

85Excellent

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain — verified-domain status not read for this organization
13.9/25	Owner reach — 85 followers of datafold
23.8/25	Track record — 41 public repos, account ~6 yr old

Inputs used

followers	85
owner_type	Organization
is_verified	—
owner_login	datafold
public_repos	41
account_age_days	2,322

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

69Good

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
4/35	Publish recency — latest publish 817 days ago
20/20	Version history — 75 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	data-diff
ecosystems	pypi
any_deprecated	no
min_days_since_publish	817

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall

Engineering practices

80Excellent

How it's scored

24/24	CI workflows — 7 workflow(s)
24/24	Tests present
16/16	Linter config — ruff.toml
9.6/9.6	Pre-commit hooks
6.4/6.4	.editorconfig
0/20	OpenSSF Scorecard: CI-Tests — 0 out of 16 merged PRs checked by a CI test -- score normalized to 0

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	yes
has_linter_config	yes
has_precommit_config	yes

Documentation

90Excellent

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://docs.datafold.com
10/10	Repository description
10/10	Topics — 20 topics
0/10	Wiki

Inputs used

topics	database, mysql, postgresql, snowflake, rdbms, trino, data-engineering, data-quality, data-science, data-quality-monitoring, databricks-sql, dataengineering, dataquality, oracle-database, postgres, sql, dbt, python, data, data-diffing
has_wiki	no
homepage	https://docs.datafold.com
docs_site	https://docs.datafold.com
has_readme	yes
has_docs_dir	yes
has_description	yes

Security

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

42Weak · 16% of overall

Security posture

34At Risk

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
0/2.5	CI-Tests — 0 out of 16 merged PRs checked by a CI test -- score normalized to 0
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6.8/7.5	Code-Review — Found 15/16 approved changesets -- score normalized to 9
2.5/2.5	Contributors — project has 8 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
0/7.5	Maintained — project is archived
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
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 — 60 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	3.4

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

Dependency advisories

73Good

How it's scored

14/35	Direct dependencies free of known advisories — 1 affected: urllib3 1.26.20 (high 7.5)
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
33.7/40	No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 420 days ago

Inputs used

source	osv
advisories	10
affected_packages	1
assessed_packages	72
unassessed_packages	0
affected_by_severity	high 1
direct_affected_packages	1

Matched the pypi:data-diff@0.11.2 runtime dependency closure — what installing the published package pulls in — 72 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.

57Moderate · 4% of overall

Agent context & guidance

24At Risk

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
24.5/40	Legible commit history — 46 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.46
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

72Good

How it's scored

18/18	One-command bootstrap — docs/Makefile
22/22	Automated tests
11/11	Lint / format config — ruff.toml
11/11	Static type checking — data_diff/py.typed
10/10	Reproducible environment — Dockerfile, lockfile
0/10	Demonstrated agent practice — no agent-authored commits among the last 100
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	poetry.lock
has_dockerfile	yes
typed_language	no
bootstrap_files	docs/Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	data_diff/py.typed
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

82Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (data_diff/py.typed)
55/55	Manageable file sizes — 0/74 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	48,445
source_files_sampled	74
oversized_source_files	0

Key facts

2,988GitHub stars

47contributors

0commits, last 12 months

817days since last push

63releases

2bus factor

0open 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 ★ / 312 ⇿

0Stars

312Forks

63Releases

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 10Patch 49

Each point covers 4 days.

OpenSSF Scorecard 3.4 / 10

3.4aggregate

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 00:46 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
0	CI-Tests	0 out of 16 merged PRs checked by a CI test -- score normalized to 0
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
9	Code-Review	Found 15/16 approved changesets -- score normalized to 9
10	Contributors	project has 8 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
0	Maintained	project is archived
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
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	60 existing vulnerabilities detected

Direct dependencies 24

Registry	Package	Version constraint	Manifest
PyPI	pydantic	`>=1.10.12`	pyproject.toml
PyPI	dsnparse	`<0.2.0`	pyproject.toml
PyPI	click	`>=8.1`	pyproject.toml
PyPI	rich	`*`	pyproject.toml
PyPI	toml	`>=0.10.2`	pyproject.toml
PyPI	mysql-connector-python	`>=8.0.29`	pyproject.toml
PyPI	psycopg2	`*`	pyproject.toml
PyPI	snowflake-connector-python	`>=3.0.2,<4.0.0`	pyproject.toml
PyPI	cryptography	`*`	pyproject.toml
PyPI	trino	`>=0.314.0`	pyproject.toml
PyPI	presto-python-client	`*`	pyproject.toml
PyPI	clickhouse-driver	`*`	pyproject.toml
PyPI	duckdb	`*`	pyproject.toml
PyPI	dbt-core	`^1.0.0`	pyproject.toml
PyPI	keyring	`*`	pyproject.toml
PyPI	tabulate	`>=0.9.0`	pyproject.toml
PyPI	preql	`>=0.2.19`	pyproject.toml
PyPI	vertica-python	`*`	pyproject.toml
PyPI	urllib3	`<2`	pyproject.toml
PyPI	oracledb	`*`	pyproject.toml
PyPI	pyodbc	`>=4.0.39`	pyproject.toml
PyPI	typing-extensions	`>=4.0.1`	pyproject.toml
PyPI	attrs	`>=23.1.0`	pyproject.toml
PyPI	mashumaro	`>=2.9,<3.11.0`	pyproject.toml

All dependencies 105

Full resolved dependency set from the GitHub dependency graph: 24 direct and 81 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	attrs	`23.1.0`	direct
PyPI	click	`8.1.7`	direct
PyPI	clickhouse-driver	`0.2.6`	direct
PyPI	cryptography	`41.0.7`	direct
PyPI	dbt-core	`1.7.4`	direct
PyPI	dsnparse	`0.1.15`	direct
PyPI	duckdb	`0.9.2`	direct
PyPI	keyring	`24.3.0`	direct
PyPI	mashumaro	`3.10`	direct
PyPI	mysql-connector-python	`8.0.29`	direct
PyPI	oracledb	`1.4.2`	direct
PyPI	preql	`0.2.19`	direct
PyPI	presto-python-client	`0.8.3`	direct
PyPI	psycopg2	`2.9.9`	direct
PyPI	pydantic	`1.10.12`	direct
PyPI	pyodbc	`4.0.39`	direct
PyPI	rich	`13.7.0`	direct
PyPI	snowflake-connector-python	`3.6.0`	direct
PyPI	tabulate	`0.9.0`	direct
PyPI	toml	`0.10.2`	direct
PyPI	trino	`0.314.0`	direct
PyPI	typing-extensions	`4.9.0`	direct
PyPI	urllib3	`1.26.18`	direct
PyPI	vertica-python	`1.3.7`	direct
PyPI	agate	`1.7.1`	indirect
PyPI	arrow	`1.3.0`	indirect
PyPI	asn1crypto	`1.5.1`	indirect
PyPI	babel	`2.14.0`	indirect
PyPI	backports-zoneinfo	`0.2.1`	indirect
PyPI	certifi	`2023.11.17`	indirect
PyPI	cffi	`1.16.0`	indirect
PyPI	cfgv	`3.4.0`	indirect
PyPI	charset-normalizer	`3.3.2`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	coverage	`7.3.3`	indirect
PyPI	data-diff	`—`	indirect
PyPI	dbt-extractor	`0.5.1`	indirect
PyPI	dbt-semantic-interfaces	`0.4.2`	indirect
PyPI	distlib	`0.3.8`	indirect
PyPI	enum-tools	`—`	indirect
PyPI	filelock	`3.13.1`	indirect
PyPI	identify	`2.5.33`	indirect
PyPI	idna	`3.6`	indirect
PyPI	importlib-metadata	`6.11.0`	indirect
PyPI	importlib-resources	`6.1.1`	indirect
PyPI	isodate	`0.6.1`	indirect
PyPI	jaraco-classes	`3.3.0`	indirect
PyPI	jeepney	`0.8.0`	indirect
PyPI	jinja2	`3.1.2`	indirect
PyPI	jsonschema	`4.20.0`	indirect
PyPI	jsonschema-specifications	`2023.11.2`	indirect
PyPI	lark-parser	`0.11.3`	indirect
PyPI	leather	`0.3.4`	indirect
PyPI	logbook	`1.5.3`	indirect
PyPI	markdown-it-py	`3.0.0`	indirect
PyPI	markupsafe	`2.1.3`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	minimal-snowplow-tracker	`0.0.2`	indirect
PyPI	more-itertools	`10.1.0`	indirect
PyPI	msgpack	`1.0.7`	indirect
PyPI	networkx	`3.1`	indirect
PyPI	nodeenv	`1.8.0`	indirect
PyPI	packaging	`23.2`	indirect
PyPI	parameterized	`0.9.0`	indirect
PyPI	parsedatetime	`2.6`	indirect
PyPI	pathspec	`0.11.2`	indirect
PyPI	pkgutil-resolve-name	`1.3.10`	indirect
PyPI	platformdirs	`3.11.0`	indirect
PyPI	pre-commit	`3.5.0`	indirect
PyPI	prompt-toolkit	`3.0.43`	indirect
PyPI	protobuf	`4.25.1`	indirect
PyPI	pycparser	`2.21`	indirect
PyPI	pygments	`2.17.2`	indirect
PyPI	pyjwt	`2.8.0`	indirect
PyPI	pyopenssl	`23.3.0`	indirect
PyPI	python-dateutil	`2.8.2`	indirect
PyPI	python-slugify	`8.0.1`	indirect
PyPI	pytimeparse	`1.1.8`	indirect
PyPI	pytz	`2023.3.post1`	indirect
PyPI	pywin32-ctypes	`0.2.2`	indirect
PyPI	pyyaml	`6.0.1`	indirect
PyPI	recommonmark	`—`	indirect
PyPI	referencing	`0.32.0`	indirect
PyPI	requests	`2.31.0`	indirect
PyPI	rpds-py	`0.15.2`	indirect
PyPI	ruff	`0.1.8`	indirect
PyPI	runtype	`0.2.7`	indirect
PyPI	secretstorage	`3.3.3`	indirect
PyPI	setuptools	`69.0.3`	indirect
PyPI	six	`1.16.0`	indirect
PyPI	sortedcontainers	`2.4.0`	indirect
PyPI	sphinx-copybutton	`—`	indirect
PyPI	sphinx-gallery	`—`	indirect
PyPI	sphinx-markdown-tables	`—`	indirect
PyPI	sphinx-rtd-theme	`—`	indirect
PyPI	sqlparse	`0.4.4`	indirect
PyPI	text-unidecode	`1.3`	indirect
PyPI	tomlkit	`0.12.3`	indirect
PyPI	types-python-dateutil	`2.8.19.14`	indirect
PyPI	tzdata	`2023.3`	indirect
PyPI	tzlocal	`5.2`	indirect
PyPI	unittest-parallel	`1.6.1`	indirect
PyPI	virtualenv	`20.25.0`	indirect
PyPI	wcwidth	`0.2.12`	indirect
PyPI	zipp	`3.17.0`	indirect

Dependency advisories 1

Installing pypi:data-diff@0.11.2 pulls in 72 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

Package	Version	Relation	Severity	Advisories	Fixed in
urllib3	`1.26.20`	direct	high	10	`2.7.0`

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 v0.31.0 — 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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