Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-15 07:08 UTC

datalab-to / pdftext

Extract structured text from pdfs quickly

PythonApache-2.0★ 723 stars⑂ 82 forkssince Apr 2024View on GitHub ↗
KindCommand-line toolhow this is determined

datalab-to/pdftext holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Vitality (59/100) and lowest on AI Readiness (43/100). It was last updated 68 days ago. A single contributor accounts for most of its recent work.

53
overall / 100
Moderate

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.

53
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 52 is calibrated to 53 on the published index scale (record calibration 2026-08-02).

Ownership

DatalabOrganization
897 followers12 public repossince Jul 2024

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpdftextpoints to another repo — not scored0.7.1-3668 days agopdftextextraction

Metrics by category

Vitality

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

59Moderate · 21% of overall
How it's scored
18/36Push recencylast push 68 days ago
2.1/36Commit cadence3/52 weeks with commits
12.1/18Commit volume21 commits in the last year
5/10OpenSSF Scorecard: Maintained6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year21
human_commit_share1
days_since_last_push68
active_weeks_last_year3
How it's scored
27/27Ships releases36 releases published
36/36Release recencylatest release 68 days ago
19.8/27Release cadencea release every ~63.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count36
latest_release_tagv0.7.1
releases_from_tagsno
days_since_latest_release68
mean_days_between_releases63.7
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?

59Moderate · 17% of overall
How it's scored
46.4/60Stars723 stars
15.9/25Forks82 forks
4.7/15Watchers8 watchers
Inputs used
forks82
stars723
watchers8
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

46Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
5.4/22.5Commit distributiontop contributor authored 76% of commits
6.8/13.5Contributor breadth5 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled5
top_contributor_share0.762
How it's scored
12.3/42Issue resolution29% of issues closed
28.2/30PR acceptance32/34 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 1/5 approved changesets -- score normalized to 2
Inputs used
merged_prs32
open_issues12
closed_issues5
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.294
closed_unmerged_prs2
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
21.2/25Owner reach897 followers of datalab-to
12.4/25Track record12 public repos, account ~2 yr old
Inputs used
followers897
owner_typeOrganization
is_verifiedno
owner_logindatalab-to
public_repos12
account_age_days781

Engineering Quality

Are baseline engineering and documentation practices in place?

54Moderate · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
8/20OpenSSF Scorecard: CI-Tests2 out of 5 merged PRs checked by a CI test -- score normalized to 4
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

47Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3.8/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
1/2.5CI-Tests2 out of 5 merged PRs checked by a CI test -- score normalized to 4
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 1/5 approved changesets -- score normalized to 2
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
3.8/7.5Maintained6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities74 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.4
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages10
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:pdftext@0.7.1 runtime dependency closure — what installing the published package pulls in — 10 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.

43Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt)llms.txt served by the project website (https://pymupdf.readthedocs.io/llms.txt)
22.4/40Legible commit history42 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://pymupdf.readthedocs.io/llms.txt
legible_history_share0.42
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentlockfile
10/10Demonstrated agent practice16 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0.16
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/18 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes13,966
source_files_sampled18
oversized_source_files0

Key facts

723GitHub stars
5contributors
21commits, last 12 months
68days since last push
36releases
1bus factor
12open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'pdftext' points at a different repository (https://github.com/VikParuchuri/pdftext); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 82 ⇿
0Stars
82Forks
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.

0204060801008252024-042025-072026-09
Major 0Minor 6Patch 28

Each point covers 3 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 · 2026-09-15 07:07 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
4CI-Tests2 out of 5 merged PRs checked by a CI test -- score normalized to 4
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 1/5 approved changesets -- score normalized to 2
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
n/aPackagingpackaging workflow not 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
0Vulnerabilities74 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIpypdfium2=5.10.1pyproject.toml
PyPIpydantic^2.7.1pyproject.toml
PyPIpydantic-settings^2.2.1pyproject.toml
PyPIclick^8.1.8pyproject.toml
PyPInumpy>=1.24pyproject.toml
All dependencies 54

Full resolved dependency set from the GitHub dependency graph: 5 direct and 49 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIclick8.1.8direct
PyPInumpy2.2.3direct
PyPIpydantic2.10.6direct
PyPIpydantic-settings2.7.1direct
PyPIpypdfium25.10.1direct
PyPIaiohappyeyeballs2.4.6indirect
PyPIaiohttp3.11.12indirect
PyPIaiosignal1.3.2indirect
PyPIannotated-types0.7.0indirect
PyPIasync-timeout5.0.1indirect
PyPIattrs25.1.0indirect
PyPIcertifi2025.1.31indirect
PyPIcffi1.17.1indirect
PyPIcharset-normalizer3.4.1indirect
PyPIcolorama0.4.6indirect
PyPIcryptography44.0.1indirect
PyPIdatasets2.21.0indirect
PyPIdill0.3.8indirect
PyPIexceptiongroup1.2.2indirect
PyPIfilelock3.17.0indirect
PyPIfrozenlist1.5.0indirect
PyPIfsspec2024.6.1indirect
PyPIhuggingface-hub0.28.1indirect
PyPIidna3.10indirect
PyPIiniconfig2.0.0indirect
PyPImultidict6.1.0indirect
PyPImultiprocess0.70.16indirect
PyPIpackaging24.2indirect
PyPIpandas2.2.3indirect
PyPIpdfminer-six20231228indirect
PyPIpdfplumber0.11.5indirect
PyPIpillow10.4.0indirect
PyPIpluggy1.5.0indirect
PyPIpropcache0.2.1indirect
PyPIpyarrow19.0.0indirect
PyPIpycparser2.22indirect
PyPIpydantic-core2.27.2indirect
PyPIpymupdf1.25.3indirect
PyPIpytest8.3.4indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-dotenv1.0.1indirect
PyPIpytz2025.1indirect
PyPIpyyaml6.0.2indirect
PyPIrapidfuzz3.12.1indirect
PyPIrequests2.32.3indirect
PyPIsix1.17.0indirect
PyPItabulate0.9.0indirect
PyPItomli2.2.1indirect
PyPItqdm4.67.1indirect
PyPItyping-extensions4.12.2indirect
PyPItzdata2025.1indirect
PyPIurllib32.3.0indirect
PyPIxxhash3.5.0indirect
PyPIyarl1.18.3indirect
Dependency advisories 0

Installing pypi:pdftext@0.7.1 pulls in 10 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.

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 statisticsPyPI.