Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-02 10:32 UTC

py-econometrics / maketables

Generate publication-ready tables from econometric models

PythonMIT★ 25 stars⑂ 2 forkssince Sep 2025View on GitHub ↗

py-econometrics/maketables holds a health index of 81 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (92/100) and lowest on Community & Adoption (48/100). It was last updated today. A single contributor accounts for most of its recent work.

81
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.

81
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 69 is calibrated to 81 on the published index scale (record calibration 2026-08-02).

Ownership

py-econometricsOrganization
178 followers15 public repossince May 2024

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPImaketables0.1.9140,56060 days agoeconometricslatexpublicationpyfixestregressionstatisticsstatsmodelstables

Metrics by category

Vitality

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

83Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
19.4/36Commit cadence — 28/52 weeks with commits
18/18Commit volume — 208 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year208
human_commit_share0.95
days_since_last_push0
active_weeks_last_year28
How it's scored
27/27Ships releases — 2 releases published
36/36Release recency — latest release 0 days ago
12.6/27Release cadence — a release every ~211 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count2
latest_release_tagv0.1.9
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases211
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?

48Weak · 17% of overall
How it's scored
22.4/60Stars — 25 stars
0/25Forks — 2 forks
0/15Watchers — 1 watchers
Inputs used
forks2
stars25
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
68.6/80Monthly downloads — 140,560 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmaketables
dependents—
ecosystemspypi
total_downloads—
monthly_downloads140,560
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?

60Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6.9/22.5Commit distribution — top contributor authored 69% of commits
6.8/13.5Contributor breadth — 5 contributors
10/10OpenSSF Scorecard: Contributors — project has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled5
top_contributor_share0.694
How it's scored
21.9/42Issue resolution — 52% of issues closed
21.1/30PR acceptance — 31/44 decided PRs merged
11.1/13Newcomer PR acceptance — 6/7 first-time contributors' PRs merged in 30d
4.5/15OpenSSF Scorecard: Code-Review — Found 2/6 approved changesets -- score normalized to 3
Inputs used
merged_prs31
open_issues11
closed_issues12
prs_merged_7d2
prs_decided_7d2
prs_merged_30d6
prs_decided_30d12
issue_closed_ratio0.522
closed_unmerged_prs13
first_time_authors_30d2
first_time_prs_merged_30d6
first_time_prs_decided_30d7
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
16.2/25Owner reach — 178 followers of py-econometrics
13.6/25Track record — 15 public repos, account ~2 yr old
Inputs used
followers178
owner_typeOrganization
is_verifiedno
owner_loginpy-econometrics
public_repos15
account_age_days881

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 6 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmaketables
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall
How it's scored
24/24CI workflows — 3 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

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://py-econometrics.github.io/maketables/
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://py-econometrics.github.io/maketables/
docs_sitehttps://py-econometrics.github.io/maketables/
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
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
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
2.2/7.5Code-Review — Found 2/6 approved changesets -- score normalized to 3
2.5/2.5Contributors — project has 4 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
7.5/7.5Maintained — 30 commit(s) and 2 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
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.6
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

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.

79Good · 4% of overall
How it's scored
45/45Agent instructions — CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://py-econometrics.github.io/pyfixest/llms.txt)
30.9/40Legible commit history — 55 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://py-econometrics.github.io/pyfixest/llms.txt
legible_history_share0.579
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes3,190
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — src/maketables/py.typed
0/10Reproducible environment
10/10Demonstrated agent practice — 15 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 5 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
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configssrc/maketables/py.typed
agent_commit_share0.15
toolchain_manifests—
dependency_bot_commit_share0.05
How it's scored
27/45Type-checkable code — Python with type-check config (src/maketables/py.typed)
52.9/55Manageable file sizes — 1/26 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes87,947
source_files_sampled26
oversized_source_files1
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, notebooks
Inputs used
example_dirsexamples, notebooks
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

25GitHub stars
5contributors
208commits, last 12 months
0days since last push
2releases
1bus factor
11open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:maketables@0.1.9; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 2 ⇿
0Stars
2Forks
1Releases

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.

111222212025-092025-122026-03
Major 0Minor 0Patch 1
OpenSSF Scorecard 5.6 / 10
5.6aggregate

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 · 2026-10-02 10:31 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
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
3Code-ReviewFound 2/6 approved changesets -- score normalized to 3
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 2 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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPInumpy>=1.20.0pyproject.toml
PyPIpandas>=1.3.0pyproject.toml
PyPIgreat-tables>=0.2.0pyproject.toml
PyPItabulate>=0.9.0pyproject.toml
PyPIpython-docx>=0.8.11pyproject.toml
PyPIipython>=7.0.0pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

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.

The message is kept through sign-in.

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.