Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 22:42 UTC

DeepL / deepl-python

Official Python library for the DeepL language translation API.

PythonMIT★ 1,334 stars⑂ 92 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 83 out of 100, placing it in the Excellent band. It scores highest on Community & Adoption (79/100) and lowest on Sustainability & Governance (56/100). It was last updated 16 days ago. A single contributor accounts for most of its recent work.

83
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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

DeepLOrganization · verified domain
1,526 followers36 public repossince Apr 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdeeplpoints to another repo — not scored1.32.0-4835 days ago

Metrics by category

Vitality

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

78Good · 21% of overall

Development activity

69Good
How it's scored
28.8/36Push recency — last push 16 days ago
14.5/36Commit cadence — 21/52 weeks with commits
15.6/18Commit volume — 53 commits in the last year
10/10OpenSSF Scorecard: Maintained — 10 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year53
human_commit_share1
days_since_last_push16
active_weeks_last_year21

Release discipline

92Excellent
How it's scored
27/27Ships releases — 38 releases published
36/36Release recency — latest release 36 days ago
19.8/27Release cadence — a release every ~52 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count38
latest_release_tagv1.31.0
releases_from_tagsno
days_since_latest_release36
mean_days_between_releases52
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
50.7/60Stars — 1,334 stars
16.3/25Forks — 92 forks
7.5/15Watchers — 23 watchers
Inputs used
forks92
stars1,334
watchers23
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

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

56Moderate · 23% of overall

Maintainer resilience (bus factor)

38Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
9.3/22.5Commit distribution — top contributor authored 58% of commits
13.5/13.5Contributor breadth — 12 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled12
top_contributor_share0.585

Issue & PR responsiveness

40Weak
How it's scored
26/42Issue resolution — 62% of issues closed
14.2/30PR acceptance — 9/19 decided PRs merged
0/13Newcomer PR acceptance — 0/1 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — Found 2/23 approved changesets -- score normalized to 0
Inputs used
merged_prs9
open_issues52
closed_issues84
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d1
issue_closed_ratio0.618
closed_unmerged_prs10
first_time_authors_30d1
first_time_prs_merged_30d0
first_time_prs_decided_30d1

Ownership & stewardship

95Exceptional
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
22.9/25Owner reach — 1,526 followers of DeepL
22.2/25Track record — 36 public repos, account ~5 yr old
Inputs used
followers1,526
owner_typeOrganization
is_verifiedyes
owner_loginDeepL
public_repos36
account_age_days1,969

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.black])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 3 out of 3 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

65Good
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://www.deepl.com
10/10Repository description
10/10Topics — 8 topics
0/10Wiki
Inputs used
topicsdeepl, python, api, official, translation, translator, i18n, language
has_wikino
homepagehttps://www.deepl.com
docs_sitehttps://www.deepl.com
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

63Moderate · 16% of overall

Security posture

54Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 3 out of 3 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
0/7.5Code-Review — Found 2/23 approved changesets -- score normalized to 0
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
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 — 10 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
1.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 51 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.4
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages5
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:deepl@1.32.0 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.

64Moderate · 4% of overall

Agent context & guidance

40Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 93 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.93
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

61Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.black])
11/11Static type checking — deepl/py.typed, examples/basic_usage/mypy.ini
10/10Reproducible environment — lockfile
4/10Demonstrated agent practice — 2 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
3/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock, uv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsdeepl/py.typed, examples/basic_usage/mypy.ini
agent_commit_share0.02
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (deepl/py.typed, examples/basic_usage/mypy.ini)
55/55Manageable file sizes — 0/30 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes57,340
source_files_sampled30
oversized_source_files0

Machine-readable interfaces

100Exceptional
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
Inputs used
example_dirsexamples
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

1,334GitHub stars
12contributors
53commits, last 12 months
16days 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 ★ / 92 ⇿
0Stars
92Forks
38Releases

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.

0204060801009232021-082024-022026-09
Major 0Minor 30Patch 8

Each point covers 5 days.

OpenSSF Scorecard 5.4 / 10
5.4aggregate

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 · 2026-09-17 22:42 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal 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
10CI-Tests3 out of 3 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 2/23 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained10 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
3Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 3
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities51 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPIrequests>=2.32.5pyproject.toml
PyPIkeyring^25.7.0pyproject.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.

RegistryPackageVersionRelation
PyPIkeyring25.7.0direct
PyPIrequests2.32.5direct
PyPIaiohappyeyeballs2.6.1indirect
PyPIaiohttp3.13.2indirect
PyPIaiosignal1.4.0indirect
PyPIattrs25.4.0indirect
PyPIbackports-tarfile1.2.0indirect
PyPIblack25.11.0indirect
PyPIcertifi2025.11.12indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.4indirect
PyPIclick8.1.8indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.10.7indirect
PyPIcryptography43.0.3indirect
PyPIexceptiongroup1.3.1indirect
PyPIflake87.3.0indirect
PyPIfrozenlist1.8.0indirect
PyPIidna3.11indirect
PyPIimportlib-metadata8.7.1indirect
PyPIiniconfig2.1.0indirect
PyPIjaraco-classes3.4.0indirect
PyPIjaraco-context6.0.2indirect
PyPIjaraco-functools4.4.0indirect
PyPIjeepney0.9.0indirect
PyPIlibrt0.7.5indirect
PyPImccabe0.7.0indirect
PyPImore-itertools10.8.0indirect
PyPImultidict6.7.0indirect
PyPImypy1.19.1indirect
PyPImypy-extensions1.1.0indirect
PyPIpackaging25.0indirect
PyPIpathspec0.12.1indirect
PyPIplatformdirs4.4.0indirect
PyPIplatformdirs4.5.0indirect
PyPIpluggy1.6.0indirect
PyPIpropcache0.4.1indirect
PyPIpyaudio0.2.14indirect
PyPIpycodestyle2.14.0indirect
PyPIpycparser2.23indirect
PyPIpydantic1.10.26indirect
PyPIpyflakes3.4.0indirect
PyPIpygments2.19.2indirect
PyPIpytest8.4.2indirect
PyPIpytokens0.3.0indirect
PyPIpywin32-ctypes0.2.3indirect
PyPIsecretstorage3.3.3indirect
PyPItomli2.3.0indirect
PyPItyping-extensions4.15.0indirect
PyPIurllib32.6.2indirect
PyPIwebsockets15.0.1indirect
PyPIyarl1.22.0indirect
PyPIzipp3.23.0indirect
Dependency advisories 0

Installing pypi:deepl@1.32.0 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

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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.