Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 04:32 UTC

Unidata / MetPy

MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.

PythonBSD-3-Clause★ 1,435 stars⑂ 449 forkssince Feb 2011View on GitHub ↗

#python #atmospheric-science #meteorology #weather #plotting #scientific-computations #hodograph #skew-t #weather-data #hacktoberfest

Unidata/MetPy holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Community & Adoption (87/100) and lowest on AI Readiness (60/100). It was last updated 1 day ago. 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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

NSF UnidataOrganization

307 followers131 public repossince Feb 2011

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	Tags
PyPI	MetPy	1.7.1	-	43	348 days ago	meteorology weather

Metrics by category

Vitality

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

86Excellent · 21% of overall

Development activity

96Exceptional

How it's scored

36/36	Push recency — last push 1 days ago
32.5/36	Commit cadence — 47/52 weeks with commits
18/18	Commit volume — 347 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	347
human_commit_share	0.55
days_since_last_push	1
active_weeks_last_year	47

Release discipline

70Good

How it's scored

27/27	Ships releases — 43 releases published
16.2/36	Release recency — latest release 348 days ago
19.8/27	Release cadence — a release every ~108.9 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	43
latest_release_tag	v1.7.1
releases_from_tags	no
days_since_latest_release	348
mean_days_between_releases	108.9

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?

87Excellent · 17% of overall

Popularity & adoption

83Excellent

How it's scored

51.2/60	Stars — 1,435 stars
22.1/25	Forks — 449 forks
9.8/15	Watchers — 58 watchers

Inputs used

forks	449
stars	1,435
watchers	58
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

92Excellent

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (BSD-3-Clause)
18/18	CONTRIBUTING guide
13.5/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	10
has_contributing	yes
has_issue_template	no
has_code_of_conduct	yes
readme_badge_services	app.codacy.com, codecov.io, github.com, shields.io
has_pull_request_template	yes

Sustainability & Governance

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

73Good · 23% of overall

Maintainer resilience (bus factor)

40Weak

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
7.8/22.5	Commit distribution — top contributor authored 65% of commits
13.5/13.5	Contributor breadth — 85 contributors
10/10	OpenSSF Scorecard: Contributors — project has 33 contributing companies or organizations

Inputs used

bus_factor	1
contributors_sampled	85
top_contributor_share	0.653

Issue & PR responsiveness

80Excellent

How it's scored

31.1/42	Issue resolution — 74% of issues closed
26.4/30	PR acceptance — 2,262/2,569 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — no data

Inputs used

merged_prs	2,262
open_issues	319
closed_issues	907
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	0.74
closed_unmerged_prs	307
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, OpenSSF Scorecard: Code-Review. Remaining weights renormalized.

Ownership & stewardship

91Excellent

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain — verified-domain status not read for this organization
17.9/25	Owner reach — 307 followers of Unidata
25/25	Track record — 131 public repos, account ~15 yr old

Inputs used

followers	307
owner_type	Organization
is_verified	—
owner_login	Unidata
public_repos	131
account_age_days	5,661

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

Package maintenance

91Excellent

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
26/35	Publish recency — latest publish 348 days ago
20/20	Version history — 43 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	MetPy
ecosystems	pypi
any_deprecated	no
min_days_since_publish	348

Engineering Quality

Are baseline engineering and documentation practices in place?

77Good · 19% of overall

Engineering practices

68Good

How it's scored

24/24	CI workflows — 15 workflow(s)
24/24	Tests present
0/16	Linter config
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 15 out of 15 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	no
has_precommit_config	no

Documentation

90Excellent

How it's scored

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

Inputs used

topics	python, atmospheric-science, meteorology, weather, plotting, scientific-computations, hodograph, skew-t, weather-data, hacktoberfest
has_wiki	no
homepage	https://unidata.github.io/MetPy/
docs_site	https://unidata.github.io/MetPy/
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?

71Good · 16% of overall

Security posture

64Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
1.5/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5	CI-Tests — 15 out of 15 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 — no data
2.5/2.5	Contributors — project has 33 contributing companies or organizations
0/10	Dangerous-Workflow — 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 1 issue activity found in the last 90 days -- score normalized to 10
5/5	Packaging — packaging workflow detected
2.5/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
3.5/5	SAST — SAST tool detected but not run on all commits
5/5	Security-Policy — security policy file detected
0/7.5	Signed-Releases — no data
2.2/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5	Vulnerabilities — 0 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	6.4

Excluded from scoring (no data or not applicable): Code-Review, 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	27
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:MetPy@1.7.1 runtime dependency closure — what installing the published package pulls in — 27 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

Agent context & guidance

40Weak

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 48 of 55 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.873
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

63Moderate

How it's scored

18/18	One-command bootstrap — docs/Makefile, tools/metar_parser/Makefile
22/22	Automated tests
0/11	Lint / format config
0/11	Static type checking
10/10	Reproducible environment — devcontainer, Dockerfile
0/10	Demonstrated agent practice — no agent-authored commits among the last 100
8/8	Automated maintenance — 45 of the last 100 commits are automated dependency updates
5/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5

Inputs used

has_nix	no
has_tests	yes
lockfiles	—
has_dockerfile	yes
typed_language	no
bootstrap_files	docs/Makefile, tools/metar_parser/Makefile
has_devcontainer	yes
has_linter_config	no
typecheck_configs	—
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0.45

Code legibility for models

51Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
51.1/55	Manageable file sizes — 13/182 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	228,959
source_files_sampled	182
oversized_source_files	13

Machine-readable interfaces

100Exceptional

How it's scored

0/40	API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20	MCP server — not applicable to this kind of software
40/40	Runnable examples — examples, notebooks

Inputs used

example_dirs	examples, notebooks
has_mcp_signal	no
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

1,435GitHub stars

85contributors

347commits, last 12 months

1days since last push

43releases

1bus factor

319open 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 ★ / 449 ⇿

0Stars

449Forks

43Releases

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 1Minor 19Patch 21

Each point covers 13 days.

OpenSSF Scorecard 6.4 / 10

6.4aggregate

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 04:32 UTC

10	Binary-Artifacts	no binaries found in the repo
2	Branch-Protection	branch protection is not maximal on development and all release branches
10	CI-Tests	15 out of 15 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
n/a	Code-Review	Found no human activity in the last 15 changesets
10	Contributors	project has 33 contributing companies or organizations
0	Dangerous-Workflow	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 1 issue activity found in the last 90 days -- score normalized to 10
10	Packaging	packaging workflow detected
5	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 5
7	SAST	SAST tool detected but not run on all commits
10	Security-Policy	security policy file detected
n/a	Signed-Releases	no releases found
3	Token-Permissions	detected GitHub workflow tokens with excessive permissions
10	Vulnerabilities	0 existing vulnerabilities detected

Direct dependencies 9

Registry	Package	Version constraint	Manifest
PyPI	matplotlib	`>=3.7.0`	pyproject.toml
PyPI	numpy	`>=1.25.0`	pyproject.toml
PyPI	pandas	`>=2.1.0`	pyproject.toml
PyPI	pint	`>=0.22`	pyproject.toml
PyPI	pooch	`>=1.2.0`	pyproject.toml
PyPI	pyproj	`>=3.4.0`	pyproject.toml
PyPI	scipy	`>=1.10.0`	pyproject.toml
PyPI	traitlets	`>=5.1.0`	pyproject.toml
PyPI	xarray	`>=2022.6.0`	pyproject.toml

All dependencies 46

Full resolved dependency set from the GitHub dependency graph: 18 direct and 28 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	matplotlib	`—`	direct
PyPI	matplotlib	`3.10.9`	direct
PyPI	numpy	`—`	direct
PyPI	numpy	`2.4.6`	direct
PyPI	pandas	`—`	direct
PyPI	pandas	`3.0.5`	direct
PyPI	pint	`—`	direct
PyPI	pint	`0.25.3`	direct
PyPI	pooch	`—`	direct
PyPI	pooch	`1.9.0`	direct
PyPI	pyproj	`—`	direct
PyPI	pyproj	`3.7.2`	direct
PyPI	scipy	`—`	direct
PyPI	scipy	`1.17.1`	direct
PyPI	traitlets	`—`	direct
PyPI	traitlets	`5.16.1`	direct
PyPI	xarray	`—`	direct
PyPI	xarray	`2025.10.1`	direct
PyPI	boto3	`1.43.14`	indirect
PyPI	cartopy	`0.25.0`	indirect
PyPI	codespell	`2.4.1`	indirect
PyPI	coverage	`7.15.0`	indirect
PyPI	dask	`2026.7.1`	indirect
PyPI	doc8	`2.0.0`	indirect
PyPI	flake8	`7.3.0`	indirect
PyPI	flake8-broken-line	`1.0.0`	indirect
PyPI	flake8-isort	`7.0.0`	indirect
PyPI	flake8-requirements	`2.3.0`	indirect
PyPI	flake8-rst-docstrings	`0.4.0`	indirect
PyPI	geopandas	`1.1.2`	indirect
PyPI	isort	`8.0.0`	indirect
PyPI	myst-parser	`5.1.0`	indirect
PyPI	netcdf4	`1.7.4`	indirect
PyPI	packaging	`26.3`	indirect
PyPI	pycodestyle	`2.14.0`	indirect
PyPI	pydata-sphinx-theme	`0.16.1`	indirect
PyPI	pyflakes	`3.4.0`	indirect
PyPI	pytest	`9.1.1`	indirect
PyPI	pytest-mpl	`0.19.0`	indirect
PyPI	restructuredtext-lint	`2.0.2`	indirect
PyPI	ruff	`0.16.0`	indirect
PyPI	shapely	`2.1.2`	indirect
PyPI	sphinx	`9.0.4`	indirect
PyPI	sphinx-design	`0.7.0`	indirect
PyPI	sphinx-gallery	`0.21.0`	indirect
PyPI	vcrpy	`8.3.0`	indirect

Dependency advisories 0

Installing pypi:MetPy@1.7.1 pulls in 27 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 v0.31.0 — 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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