Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-06 01:16 UTC

andreasvc / disco-dop

Discontinuous Data-Oriented Parsing

Python · CythonGPL-2.0★ 47 stars⑂ 15 forkssince Mar 2011View on GitHub ↗
KindCommand-line toolhow this is determined

andreasvc/disco-dop holds a health index of 19 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (58/100) and lowest on Security (17/100). It was last updated 974 days ago. A single contributor accounts for most of its recent work.

19
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.

19
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 37 is calibrated to 31 on the published index scale (record calibration 2026-08-02).

Ownership

Andreas van CranenburghPersonal account
86 followers63 public repossince May 2010

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdisco-doppoints to another repo — not scored0.5.22073469 days ago

Metrics by category

Vitality

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

17Critical · 21% of overall
How it's scored
0/36Push recencylast push 974 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push974
active_weeks_last_year0
How it's scored
16.2/27Ships releases2 version tags (no GitHub releases)
0/36Release recencylatest release 3,476 days ago
19.8/27Release cadencea release every ~67.1 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count2
latest_release_tagv0.5.2
releases_from_tagsyes
days_since_latest_release3,476
mean_days_between_releases67.1
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?

44Weak · 17% of overall
How it's scored
27/60Stars47 stars
9.6/25Forks15 forks
1.7/15Watchers3 watchers
Inputs used
forks15
stars47
watchers3
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (GPL-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?

45Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0.1/22.5Commit distributiontop contributor authored 100% of commits
4.1/13.5Contributor breadth3 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.996
How it's scored
35.4/42Issue resolution84% of issues closed
23.6/30PR acceptance11/14 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 1/30 approved changesets -- score normalized to 0
Inputs used
merged_prs11
open_issues9
closed_issues48
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.842
closed_unmerged_prs3
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
13.9/25Owner reach86 followers of andreasvc
25/25Track record63 public repos, account ~16 yr old
Inputs used
followers86
owner_typeUser
is_verified
owner_loginandreasvc
public_repos63
account_age_days5,971
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

58Moderate · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigyes
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttp://discodop.readthedocs.io
10/10Repository description
10/10Topics2 topics
10/10Wiki
Inputs used
topicsparsing, nlp
has_wikiyes
homepagehttp://discodop.readthedocs.io
docs_sitehttp://discodop.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

17Critical · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 1/30 approved changesets -- score normalized to 0
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesno data
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-Permissionsno data
2.2/7.5Vulnerabilities7 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate1.8
Excluded from scoring (no data or not applicable): Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. 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.

35Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
14.4/40Legible commit history27 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.27
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
51.9/55Manageable file sizes2/36 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes69,787
source_files_sampled36
oversized_source_files2

Key facts

47GitHub stars
3contributors
0commits, last 12 months
974days since last push
2releases
1bus factor
9open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'disco-dop' points at a different repository (http://discodop.readthedocs.io); excluded from ecosystem scoring
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 15 ⇿
0Stars
15Forks
2Releases

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.

03581013151512013-092018-042022-10
Major 0Minor 0Patch 2

Each point covers 9 days.

OpenSSF Scorecard 1.8 / 10
1.8aggregate

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 · 2026-09-06 01:16 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/30 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
3Vulnerabilities7 existing vulnerabilities detected
All dependencies 13

Full resolved dependency set from the GitHub dependency graph: 0 direct and 13 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcachelibindirect
PyPIcythonindirect
PyPIflaskindirect
PyPIgraphemeindirect
PyPImatplotlibindirect
PyPInumpyindirect
PyPIpandasindirect
PyPIpytestindirect
PyPIreadabilityindirect
PyPIroaringbitmapindirect
PyPIscipyindirect
PyPIseabornindirect
PyPIsphinxindirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

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.