Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 04:25 UTC

DeepL / deepl-python

Official Python library for the DeepL language translation API.

PythonMIT★ 1,330 stars⑂ 89 forkssince Jul 2021View on GitHub ↗

KindCommand-line toolLibraryhow this is determined

#deepl #python #api #official #translation #translator #i18n #language

DeepL/deepl-python holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Vitality (80/100) and lowest on Security (51/100). It was last updated today. A single contributor accounts for most of its recent work.

overall / 100

Good

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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

DeepLOrganization

1,516 followers35 public repossince Apr 2021

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
PyPI	deeplpoints to another repo — not scored	1.31.0	1,421,040	47	1 day ago

Metrics by category

Vitality

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

80Excellent · 21% of overall

Development activity

72Good

How it's scored

36/36	Push recency — last push 0 days ago
14.5/36	Commit cadence — 21/52 weeks with commits
16.4/18	Commit volume — 66 commits in the last year
5/10	OpenSSF Scorecard: Maintained — 5 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 5

Inputs used

commits_last_year	66
human_commit_share	1
days_since_last_push	0
active_weeks_last_year	21

Release discipline

92Excellent

How it's scored

27/27	Ships releases — 38 releases published
36/36	Release recency — latest release 1 days ago
19.8/27	Release cadence — a release every ~52 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	38
latest_release_tag	v1.31.0
releases_from_tags	no
days_since_latest_release	1
mean_days_between_releases	52

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?

79Good · 17% of overall

Popularity & adoption

74Good

How it's scored

50.7/60	Stars — 1,330 stars
16.2/25	Forks — 89 forks
7.5/15	Watchers — 23 watchers

Inputs used

forks	89
stars	1,330
watchers	23
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

85Excellent

How it's scored

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

Inputs used

has_readme	yes
has_license	yes
readme_badges	4
has_contributing	yes
has_issue_template	no
has_code_of_conduct	yes
readme_badge_services	shields.io
has_pull_request_template	no

Sustainability & Governance

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

58Moderate · 23% of overall

Maintainer resilience (bus factor)

38Weak

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
9/22.5	Commit distribution — top contributor authored 60% of commits
13.5/13.5	Contributor breadth — 11 contributors
6/10	OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6

Inputs used

bus_factor	1
contributors_sampled	11
top_contributor_share	0.598

Issue & PR responsiveness

47Weak

How it's scored

25.7/42	Issue resolution — 61% of issues closed
15/30	PR acceptance — 9/18 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 2/23 approved changesets -- score normalized to 0

Inputs used

merged_prs	9
open_issues	52
closed_issues	82
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	0.612
closed_unmerged_prs	9
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

94Exceptional

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain — verified-domain status not read for this organization
22.9/25	Owner reach — 1,516 followers of DeepL
21.9/25	Track record — 35 public repos, account ~5 yr old

Inputs used

followers	1,516
owner_type	Organization
is_verified	—
owner_login	DeepL
public_repos	35
account_age_days	1,933

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

67Good · 19% of overall

Engineering practices

68Good

How it's scored

24/24	CI workflows — 3 workflow(s)
24/24	Tests present
0/16	Linter config
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 3 out of 3 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	no
has_precommit_config	no

Documentation

65Good

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://www.deepl.com
10/10	Repository description
10/10	Topics — 8 topics
0/10	Wiki

Inputs used

topics	deepl, python, api, official, translation, translator, i18n, language
has_wiki	no
homepage	https://www.deepl.com
docs_site	https://www.deepl.com
has_readme	yes
has_docs_dir	no
has_description	yes

Security

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

51Moderate · 16% of overall

Security posture

39Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2.5/2.5	CI-Tests — 3 out of 3 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 2/23 approved changesets -- score normalized to 0
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
3.8/7.5	Maintained — 5 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 5
0/5	Packaging — no data
0.5/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
5/5	Security-Policy — security policy file detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 51 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	3.9

Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	5
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:deepl@1.31.0 runtime dependency closure — what installing the published package pulls in — 5 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.

58Moderate · 4% of overall

Agent context & guidance

40Weak

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 92 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.92
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

48Weak

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
0/11	Lint / format config
11/11	Static type checking — deepl/py.typed, examples/basic_usage/mypy.ini
10/10	Reproducible environment — lockfile
4/10	Demonstrated agent practice — 2 of the last 100 commits agent-authored or agent-credited
0/8	Automated maintenance — no automated dependency updates observed
1/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1

Inputs used

has_nix	no
has_tests	yes
lockfiles	poetry.lock, uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	no
typecheck_configs	deepl/py.typed, examples/basic_usage/mypy.ini
agent_commit_share	0.02
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

82Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (deepl/py.typed, examples/basic_usage/mypy.ini)
55/55	Manageable file sizes — 0/30 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	57,340
source_files_sampled	30
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

1,330GitHub stars

11contributors

66commits, last 12 months

0days since last push

38releases

1bus factor

52open issues

PyPIpackage ecosystems

Data collection warnings

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

More detail

Star and fork history 0 ★ / 89 ⇿

0Stars

89Forks

37Releases

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 29Patch 8

Each point covers 5 days.

OpenSSF Scorecard 3.9 / 10

3.9aggregate

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 · 2026-08-13 04:24 UTC

10	Binary-Artifacts	no binaries found in the repo
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
10	CI-Tests	3 out of 3 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 2/23 approved changesets -- score normalized to 0
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
5	Maintained	5 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 5
n/a	Packaging	packaging workflow not detected
1	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 1
0	SAST	SAST tool is not run on all commits -- score normalized to 0
10	Security-Policy	security policy file detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	51 existing vulnerabilities detected

Direct dependencies 2

Registry	Package	Version constraint	Manifest
PyPI	requests	`>=2.32.5`	pyproject.toml
PyPI	keyring	`^25.7.0`	pyproject.toml

All dependencies 53

Full resolved dependency set from the GitHub dependency graph: 2 direct and 51 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	keyring	`25.7.0`	direct
PyPI	requests	`2.32.5`	direct
PyPI	aiohappyeyeballs	`2.6.1`	indirect
PyPI	aiohttp	`3.13.2`	indirect
PyPI	aiosignal	`1.4.0`	indirect
PyPI	attrs	`25.4.0`	indirect
PyPI	backports-tarfile	`1.2.0`	indirect
PyPI	black	`25.11.0`	indirect
PyPI	certifi	`2025.11.12`	indirect
PyPI	cffi	`2.0.0`	indirect
PyPI	charset-normalizer	`3.4.4`	indirect
PyPI	click	`8.1.8`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	coverage	`7.10.7`	indirect
PyPI	cryptography	`43.0.3`	indirect
PyPI	exceptiongroup	`1.3.1`	indirect
PyPI	flake8	`7.3.0`	indirect
PyPI	frozenlist	`1.8.0`	indirect
PyPI	idna	`3.11`	indirect
PyPI	importlib-metadata	`8.7.1`	indirect
PyPI	iniconfig	`2.1.0`	indirect
PyPI	jaraco-classes	`3.4.0`	indirect
PyPI	jaraco-context	`6.0.2`	indirect
PyPI	jaraco-functools	`4.4.0`	indirect
PyPI	jeepney	`0.9.0`	indirect
PyPI	librt	`0.7.5`	indirect
PyPI	mccabe	`0.7.0`	indirect
PyPI	more-itertools	`10.8.0`	indirect
PyPI	multidict	`6.7.0`	indirect
PyPI	mypy	`1.19.1`	indirect
PyPI	mypy-extensions	`1.1.0`	indirect
PyPI	packaging	`25.0`	indirect
PyPI	pathspec	`0.12.1`	indirect
PyPI	platformdirs	`4.4.0`	indirect
PyPI	platformdirs	`4.5.0`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	propcache	`0.4.1`	indirect
PyPI	pyaudio	`0.2.14`	indirect
PyPI	pycodestyle	`2.14.0`	indirect
PyPI	pycparser	`2.23`	indirect
PyPI	pydantic	`1.10.26`	indirect
PyPI	pyflakes	`3.4.0`	indirect
PyPI	pygments	`2.19.2`	indirect
PyPI	pytest	`8.4.2`	indirect
PyPI	pytokens	`0.3.0`	indirect
PyPI	pywin32-ctypes	`0.2.3`	indirect
PyPI	secretstorage	`3.3.3`	indirect
PyPI	tomli	`2.3.0`	indirect
PyPI	typing-extensions	`4.15.0`	indirect
PyPI	urllib3	`2.6.2`	indirect
PyPI	websockets	`15.0.1`	indirect
PyPI	yarl	`1.22.0`	indirect
PyPI	zipp	`3.23.0`	indirect

Dependency advisories 0

Installing pypi:deepl@1.31.0 pulls in 5 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.

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 v0.31.0 — 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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