Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-19 05:39 UTC

ispras / dedoc

Dedoc is a library (service) for automate documents parsing and bringing to a uniform format. It automatically extracts content, logical structure, tables, and meta information from textual electronic documents. (Parse document; Document content extraction; Logical structure extraction; PDF parser; Scanned document parser; DOCX parser; HTML parser

Python · HTMLApache-2.0★ 737 stars⑂ 65 forkssince Dec 2020View on GitHub ↗

KindCommand-line toolLibraryhow this is determined

#doc #docx #odt #documents #excel #pdf #txt #ocr #scanned-documents #document-content-extraction #table-of-contents #table-recognition #html #docx-parser #html-parser #pdf-parser #document-analysis #logical-structure-extraction

ispras/dedoc holds a health index of 12 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (86/100) and lowest on Security (13/100). It was last updated 19 days ago. A single contributor accounts for most of its recent work.

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.

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 58 is calibrated to 62 on the published index scale (record calibration 2026-08-02). High-Risk Jurisdiction Policy applies a 20% multiplier to weighted overall health and gives it an At Risk ceiling of 34.

Ownership

Ivannikov Institute for System Programming of the Russian Academy of SciencesOrganization

149 followers126 public repossince Sep 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	dedoc	2.8	509	35	26 days ago	document-analysis logical-structure-extraction ocr deep-learning computer-vision

Metrics by category

Vitality

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

61Moderate · 21% of overall

Development activity

41Weak

How it's scored

28.8/36	Push recency — last push 19 days ago
2.8/36	Commit cadence — 4/52 weeks with commits
6.3/18	Commit volume — 4 commits in the last year
3/10	OpenSSF Scorecard: Maintained — 2 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 3

Inputs used

commits_last_year	4
human_commit_share	1
days_since_last_push	19
active_weeks_last_year	4

Release discipline

92Excellent

How it's scored

27/27	Ships releases — 31 releases published
36/36	Release recency — latest release 26 days ago
19.8/27	Release cadence — a release every ~85.2 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	31
latest_release_tag	v2.8
releases_from_tags	no
days_since_latest_release	26
mean_days_between_releases	85.2

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?

56Moderate · 17% of overall

Popularity & adoption

67Good

How it's scored

46.5/60	Stars — 737 stars
15.1/25	Forks — 65 forks
5.3/15	Watchers — 10 watchers

Inputs used

forks	65
stars	737
watchers	10
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

50Moderate

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
0/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
0/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	9
has_contributing	no
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	badge.fury.io, github.com, readthedocs.org, shields.io
has_pull_request_template	no

Ecosystem adoption (downloads)

45Weak

How it's scored

36.1/80	Monthly downloads — 509 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	dedoc
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	509
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?

66Good · 23% of overall

Maintainer resilience (bus factor)

34At Risk

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
10.5/22.5	Commit distribution — top contributor authored 53% of commits
8.1/13.5	Contributor breadth — 6 contributors
6/10	OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6

Inputs used

bus_factor	1
contributors_sampled	6
top_contributor_share	0.532

Issue & PR responsiveness

74Good

How it's scored

30.9/42	Issue resolution — 74% of issues closed
27.4/30	PR acceptance — 479/525 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
6/15	OpenSSF Scorecard: Code-Review — Found 14/30 approved changesets -- score normalized to 4

Inputs used

merged_prs	479
open_issues	9
closed_issues	25
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	3
prs_decided_30d	3
issue_closed_ratio	0.735
closed_unmerged_prs	46
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. Remaining weights renormalized.

Ownership & stewardship

71Good

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
15.6/25	Owner reach — 149 followers of ispras
25/25	Track record — 126 public repos, account ~15 yr old

Inputs used

followers	149
owner_type	Organization
is_verified	no
owner_login	ispras
public_repos	126
account_age_days	5,521

Package maintenance

100Exceptional

How it's scored

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

Inputs used

packages	dedoc
ecosystems	pypi
any_deprecated	no
min_days_since_publish	26

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

76Good

How it's scored

24/24	CI workflows — 5 workflow(s)
24/24	Tests present
16/16	Linter config — .flake8
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
2/20	OpenSSF Scorecard: CI-Tests — 5 out of 27 merged PRs checked by a CI test -- score normalized to 1

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://dedoc.readthedocs.io
10/10	Repository description
10/10	Topics — 18 topics
10/10	Wiki

Inputs used

topics	doc, docx, odt, documents, excel, pdf, txt, ocr, scanned-documents, document-content-extraction, table-of-contents, table-recognition, html, docx-parser, html-parser, pdf-parser, document-analysis, logical-structure-extraction
has_wiki	yes
homepage	—
docs_site	https://dedoc.readthedocs.io
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?

13Critical · 16% of overall

Security posture

5Critical

Jurisdiction risk alert

High-risk jurisdiction exposure detected

1 software.redFlag.role.ownerRussia2 top contributor profilesRussia

Based on self-published public profile locations. This governance signal does not determine nationality, citizenship, intent, sanctions status, or individual trustworthiness.

How jurisdiction exposure is assessed

How it's scored

0/7.5	Binary-Artifacts — binaries present in source code
0/7.5	Branch-Protection — no data
0.2/2.5	CI-Tests — 5 out of 27 merged PRs checked by a CI test -- score normalized to 1
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3/7.5	Code-Review — Found 14/30 approved changesets -- score normalized to 4
1.5/2.5	Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
2.2/7.5	Maintained — 2 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 3
5/5	Packaging — packaging workflow detected
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 16 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	2.7
high_risk_jurisdiction_cap	34
high_risk_jurisdiction_multiplier	20
security_posture_after_multiplier	5
security_posture_before_jurisdiction	27

Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized. High-Risk Jurisdiction Policy applies a 20% multiplier and gives Security posture an At risk ceiling of 34.

Dependency advisories

44Weak

How it's scored

5.1/35	Direct dependencies free of known advisories — 8 affected: fastapi 0.106.0 (high 7.5), opencv-python 4.5.5.64 (high 8.8), pdfminer-six 20231228.0.0 (high 8.6), +5 more
19/25	Indirect dependencies free of known advisories — 1 affected: anyio 3.7.1 (unknown)
19.8/40	No advisories left outstanding — 5 advisory-carrying package(s) unaddressed past 90 days; oldest published 1,115 days ago

Inputs used

source	osv
advisories	150
affected_packages	9
assessed_packages	89
unassessed_packages	0
affected_by_severity	high 5, unknown 4
direct_affected_packages	8

Matched the pypi:dedoc@2.8 runtime dependency closure — what installing the published package pulls in — 89 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.

48Weak · 4% of overall

Agent context & guidance

24At Risk

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
24.5/40	Legible commit history — 46 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.46
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

43Weak

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config — .flake8
0/11	Static type checking
10/10	Reproducible environment — Dockerfile
0/10	Demonstrated agent practice — no agent-authored commits among the last 100
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	—
has_dockerfile	yes
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

55Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
55/55	Manageable file sizes — 0/514 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	37,457
source_files_sampled	514
oversized_source_files	0

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

Inputs used

example_dirs	examples
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

737GitHub stars

6contributors

4commits, last 12 months

19days since last push

31releases

1bus factor

9open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Advisory severity resolved for 120 of 150 advisories (lookup cap); the remainder are reported as unknown severity

More detail

Star and fork history 0 ★ / 65 ⇿

0Stars

65Forks

31Releases

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 0Minor 3Patch 16

Each point covers 6 days.

OpenSSF Scorecard 2.7 / 10

2.7aggregate

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 · 2026-10-19 05:39 UTC

0	Binary-Artifacts	binaries present in source code
n/a	Branch-Protection	internal 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
1	CI-Tests	5 out of 27 merged PRs checked by a CI test -- score normalized to 1
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
4	Code-Review	Found 14/30 approved changesets -- score normalized to 4
6	Contributors	project has 2 contributing companies or organizations -- score normalized to 6
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
3	Maintained	2 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 3
10	Packaging	packaging workflow detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	16 existing vulnerabilities detected

All dependencies 69

Full resolved dependency set from the GitHub dependency graph: 0 direct and 69 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	apted	`1.0.3`	indirect
PyPI	beautifulsoup4	`—`	indirect
PyPI	charset-normalizer	`—`	indirect
PyPI	cython	`—`	indirect
PyPI	dedoc-utils	`0.3.11`	indirect
PyPI	distance	`0.1.3`	indirect
PyPI	docutils	`0.18.1`	indirect
PyPI	fastapi	`—`	indirect
PyPI	flake8	`5.0.4`	indirect
PyPI	flake8-absolute-import	`1.0.0.1`	indirect
PyPI	flake8-annotations	`2.9.1`	indirect
PyPI	flake8-bugbear	`23.3.12`	indirect
PyPI	flake8-builtins	`2.1.0`	indirect
PyPI	flake8-fill-one-line	`—`	indirect
PyPI	flake8-import-order	`0.18.2`	indirect
PyPI	flake8-multiline-containers	`0.0.19`	indirect
PyPI	flake8-print	`5.0.0`	indirect
PyPI	flake8-quotes	`3.3.2`	indirect
PyPI	flake8-tidy-imports	`4.10.0`	indirect
PyPI	flake8-use-fstring	`1.4`	indirect
PyPI	fonttools	`—`	indirect
PyPI	html2text	`2024.2.26`	indirect
PyPI	huggingface-hub	`—`	indirect
PyPI	imutils	`0.5.4`	indirect
PyPI	itsdangerous	`—`	indirect
PyPI	levenshtein	`—`	indirect
PyPI	linuxdoc	`20230506`	indirect
PyPI	olefile	`—`	indirect
PyPI	opencv-python	`—`	indirect
PyPI	orjson	`—`	indirect
PyPI	pandas	`—`	indirect
PyPI	pdf-tocgen	`—`	indirect
PyPI	pdf2image	`1.10.0`	indirect
PyPI	pdfminer-six	`—`	indirect
PyPI	pep8-naming	`0.13.3`	indirect
PyPI	piexif	`1.1.3`	indirect
PyPI	puremagic	`—`	indirect
PyPI	py7zr	`—`	indirect
PyPI	pycodestyle	`2.9.0`	indirect
PyPI	pypdf	`—`	indirect
PyPI	pypdfium2	`—`	indirect
PyPI	pytesseract	`0.3.10`	indirect
PyPI	python-docx	`0.8.11`	indirect
PyPI	python-magic	`—`	indirect
PyPI	python-multipart	`0.0.6`	indirect
PyPI	rarfile	`4.0`	indirect
PyPI	requests	`—`	indirect
PyPI	roman	`—`	indirect
PyPI	rtree	`—`	indirect
PyPI	scikit-image	`—`	indirect
PyPI	scikit-learn	`—`	indirect
PyPI	scipy	`—`	indirect
PyPI	six	`—`	indirect
PyPI	sphinx	`6.2.1`	indirect
PyPI	sphinx-copybutton	`0.5.2`	indirect
PyPI	sphinx-rtd-theme	`1.2.0`	indirect
PyPI	sphinx-togglebutton	`0.3.2`	indirect
PyPI	starlette	`—`	indirect
PyPI	tabula-py	`2.8.1`	indirect
PyPI	texttable	`—`	indirect
PyPI	torch	`—`	indirect
PyPI	torchvision	`—`	indirect
PyPI	transformers	`—`	indirect
PyPI	ujson	`—`	indirect
PyPI	uvicorn	`—`	indirect
PyPI	wget	`3.2`	indirect
PyPI	xgbfir	`—`	indirect
PyPI	xgboost	`—`	indirect
PyPI	xlrd	`—`	indirect

Dependency advisories 9

Installing pypi:dedoc@2.8 pulls in 89 packages, direct and transitive: 9 carry known advisories, of which 8 are direct dependencies.

Package	Version	Relation	Severity	Advisories	Fixed in
fastapi	`0.106.0`	direct	high	1	`0.109.1`
opencv-python	`4.5.5.64`	direct	high	2	`4.8.1.78`
pdfminer-six	`20231228.0.0`	direct	high	4	`20251230`
pypdf	`5.9.0`	direct	high	97	`6.19.0`
python-multipart	`0.0.6`	direct	high	18	`0.0.31`
scikit-learn	`1.2.2`	direct	unknown	2	—
starlette	`0.27.0`	direct	unknown	14	—
ujson	`5.8.0`	direct	unknown	8	—
anyio	`3.7.1`	indirect	unknown	4	—

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 v0.34.0 — 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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