Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-18 23:44 UTC

PyLops / pylops

PyLops – A Linear-Operator Library for Python

PythonLGPL-3.0★ 541 stars⑂ 130 forkssince Nov 2018View on GitHub ↗
KindLibraryhow this is determined
#python#algebra#linear-operators#inverse-problems#optimization

PyLops/pylops holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Security (56/100). It was last updated today. A single contributor accounts for most of its recent work.

91
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.

91
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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).

Ownership

PyLopsOrganization
75 followers17 public repossince Nov 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpylops2.8.016,5123385 days agoalgebrainverse-problemslarge-scale-optimization

Metrics by category

Vitality

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

89Excellent · 21% of overall

Development activity

92Excellent
How it's scored
36/36Push recency — last push 0 days ago
28.4/36Commit cadence — 41/52 weeks with commits
18/18Commit volume — 530 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 11 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year530
human_commit_share1
days_since_last_push0
active_weeks_last_year41

Release discipline

84Excellent
How it's scored
27/27Ships releases — 34 releases published
36/36Release recency — latest release 85 days ago
12.6/27Release cadence — a release every ~153.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count34
latest_release_tagv2.8.0
releases_from_tagsno
days_since_latest_release85
mean_days_between_releases153.6
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

67Good
How it's scored
44.3/60Stars — 541 stars
17.6/25Forks — 130 forks
5.3/15Watchers — 10 watchers
Inputs used
forks130
stars541
watchers10
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (LGPL-3.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges12
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesapp.codacy.com, badge.fury.io, dev.azure.com, github.com, readthedocs.org, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

70Good
How it's scored
56.2/80Monthly downloads — 16,512 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespylops
dependents—
ecosystemspypi
total_downloads—
monthly_downloads16,512
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?

68Good · 23% of overall

Maintainer resilience (bus factor)

37Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
4.7/22.5Commit distribution — top contributor authored 79% of commits
13.5/13.5Contributor breadth — 33 contributors
10/10OpenSSF Scorecard: Contributors — project has 19 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled33
top_contributor_share0.791

Issue & PR responsiveness

82Excellent
How it's scored
35.3/42Issue resolution — 84% of issues closed
27.4/30PR acceptance — 585/641 decided PRs merged
13/13Newcomer PR acceptance — 4/4 first-time contributors' PRs merged in 30d
6/15OpenSSF Scorecard: Code-Review — Found 3/7 approved changesets -- score normalized to 4
Inputs used
merged_prs585
open_issues27
closed_issues143
prs_merged_7d7
prs_decided_7d7
prs_merged_30d17
prs_decided_30d17
issue_closed_ratio0.841
closed_unmerged_prs56
first_time_authors_30d4
first_time_prs_merged_30d4
first_time_prs_decided_30d4

Ownership & stewardship

64Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
13.5/25Owner reach — 75 followers of PyLops
21/25Track record — 17 public repos, account ~5 yr old
Inputs used
followers75
owner_typeOrganization
is_verifiedno
owner_loginPyLops
public_repos17
account_age_days2,167

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 85 days ago
20/20Version history — 33 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespylops
ecosystemspypi
any_deprecatedno
min_days_since_publish85

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 9 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 7 out of 7 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pylops.readthedocs.io
10/10Repository description
10/10Topics — 5 topics
10/10Wiki
Inputs used
topicspython, algebra, linear-operators, inverse-problems, optimization
has_wikiyes
homepagehttps://pylops.readthedocs.io
docs_sitehttps://pylops.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

56Moderate · 16% of overall

Security posture

45Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3/7.5Code-Review — Found 3/7 approved changesets -- score normalized to 4
2.5/2.5Contributors — project has 19 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 11 issue activity found in the last 90 days -- score normalized to 10
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
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 103 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.5
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_packages2
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:pylops@2.8.0 runtime dependency closure — what installing the published package pulls in — 2 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.

77Good · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 94 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.94
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes2,571

Verify loop (build / test / typecheck)

71Good
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile, noxfile.py
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 17 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
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_filesMakefile, docs/Makefile, noxfile.py
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.17
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
54.6/55Manageable file sizes — 2/296 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes126,802
source_files_sampled296
oversized_source_files2

Machine-readable interfaces

100Exceptional
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 — examples
Inputs used
example_dirsexamples
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

541GitHub stars
33contributors
530commits, last 12 months
0days since last push
34releases
1bus factor
27open 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 ★ / 130 ⇿
0Stars
130Forks
34Releases

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.

025507510012515012642018-112022-112026-10
Major 2Minor 25Patch 6

Each point covers 8 days.

OpenSSF Scorecard 4.5 / 10
4.5aggregate

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 · 2026-10-18 23:43 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
10CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 3/7 approved changesets -- score normalized to 4
10Contributorsproject has 19 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 11 issue activity found in the last 90 days -- score normalized to 10
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
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities103 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPInumpy>= 2.0.0pyproject.toml
PyPIscipy>= 1.13.0pyproject.toml
All dependencies 255

Full resolved dependency set from the GitHub dependency graph: 4 direct and 251 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPItriton3.6.0indirect
PyPItyping-extensions4.15.0indirect
PyPItzdata2026.2indirect
PyPIurllib32.6.3indirect
PyPIvirtualenv21.2.4indirect
PyPIwebencodings0.5.1indirect
PyPIxarray2026.4.0indirect
PyPIxarray-einstats0.10.0indirect
PyPIxarray-einstats0.9.1indirect
Dependency advisories 0

Installing pypi:pylops@2.8.0 pulls in 2 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.

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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 v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.