Public recordGood
Software health reportschema 0.17.0 · metrics 1.13.0 · 2026-07-21 03:18 UTC
databricks / databricks-sql-python
Databricks SQL Connector for Python
databricks/databricks-sql-python holds a health index of 80 out of 100, placing it in the Good band. It scores highest on Vitality (93/100) and lowest on AI Readiness (44/100). It was last updated today. 6 contributors account for most of its recent work.
80
overall / 100Software health index
Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.
80
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe 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.
Ownership
DatabricksOrganization
3,894 followers261 public repossince Jul 2013
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 | databricks-sql-connector | 4.3.0 | - | 101 | 35 days ago |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
93
Development activity
88Excellent
How it's scored
| 36/36 | Push recency — last push 0 days ago |
| 24.2/36 | Commit cadence — 35/52 weeks with commits |
| 18/18 | Commit volume — 118 commits in the last year |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
Inputs used
| commits_last_year | 118 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 35 |
Release discipline
100Excellent
How it's scored
| 27/27 | Ships releases — 66 releases published |
| 36/36 | Release recency — latest release 35 days ago |
| 27/27 | Release cadence — a release every ~21.4 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 66 |
| latest_release_tag | v4.3.0 |
| releases_from_tags | no |
| days_since_latest_release | 35 |
| mean_days_between_releases | 21.4 |
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?
70
Popularity & adoption
64Moderate
How it's scored
| 38.3/60 | Stars — 231 stars |
| 18.1/25 | Forks — 148 forks |
| 7.1/15 | Watchers — 20 watchers |
Inputs used
| forks | 148 |
| stars | 231 |
| watchers | 20 |
| growth_state | organic |
| growth_factor_pct | 100 |
Community health
77Good
How it's scored
| 22.5/22.5 | README |
| 22.5/22.5 | License — recognized license (Apache-2.0) |
| 18/18 | CONTRIBUTING guide |
| 0/13.5 | Code of conduct |
| 0/7.2 | Issue template |
| 6.3/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | no |
| has_pull_request_template | yes |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
87
Maintainer resilience (bus factor)
91Excellent
How it's scored
| 48.6/54 | Bus factor — 6 contributor(s) cover half of all commits |
| 18.7/22.5 | Commit distribution — top contributor authored 17% of commits |
| 13.5/13.5 | Contributor breadth — 59 contributors |
| 10/10 | OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10 |
Inputs used
| bus_factor | 6 |
| contributors_sampled | 59 |
| top_contributor_share | 0.17 |
How it's scored
| 33.9/46.8 | Issue resolution — 72% of issues closed |
| 31.3/38.3 | PR acceptance — 438/535 decided PRs merged |
| 12/15 | OpenSSF Scorecard: Code-Review — Found 26/30 approved changesets -- score normalized to 8 |
Inputs used
| merged_prs | 438 |
| open_issues | 75 |
| closed_issues | 198 |
| issue_closed_ratio | 0.725 |
| closed_unmerged_prs | 97 |
Ownership & stewardship
80Good
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain |
| 25/25 | Owner reach — 3,894 followers of databricks |
| 25/25 | Track record — 261 public repos, account ~13 yr old |
Inputs used
| followers | 3,894 |
| owner_type | Organization |
| is_verified | — |
| owner_login | databricks |
| public_repos | 261 |
| account_age_days | 4,756 |
Package maintenance
100Excellent
How it's scored
| 25/25 | Published & resolvable — 1 package(s) on pypi |
| 35/35 | Publish recency — latest publish 35 days ago |
| 20/20 | Version history — 101 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | databricks-sql-connector |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 35 |
Engineering Quality
Are baseline engineering and documentation practices in place?
75
Engineering practices
68Moderate
How it's scored
| 24/24 | CI workflows — 12 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 — 30 out of 30 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
85Excellent
How it's scored
| 30/30 | README |
| 25/25 | Documentation directory |
| 0/15 | Documentation / homepage site |
| 10/10 | Repository description |
| 10/10 | Topics — 4 topics |
| 10/10 | Wiki |
Inputs used
| topics | databricks, dwh, python3, sql |
| has_wiki | yes |
| homepage | — |
| 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?
66
Security posture
58Moderate
How it's scored
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 3/7.5 | Branch-Protection — branch protection is not maximal on development and all release branches |
| 2.5/2.5 | CI-Tests — 30 out of 30 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 |
| 6/7.5 | Code-Review — Found 26/30 approved changesets -- score normalized to 8 |
| 2.5/2.5 | Contributors — project has 3 contributing companies or organizations -- score normalized to 10 |
| 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 |
| 7.5/7.5 | Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — no data |
| 4.5/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9 |
| 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 |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 5.8 |
Excluded from scoring (no data or not applicable): packaging, signed_releases. Remaining weights renormalized.
Dependency advisories
100Excellent
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 | 16 |
| 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:databricks-sql-connector@4.3.0 runtime dependency closure — what installing the published package pulls in — 16 packages. Reachability is not analyzed.
AI Readiness
How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.
44
Agent context & guidance
1Critical
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 0/40 | Legible commit history — no data |
Inputs used
| has_llms_txt | no |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
Verify loop (build / test / typecheck)
63Moderate
How it's scored
| 0/18 | One-command bootstrap |
| 22/22 | Automated tests |
| 0/11 | Lint / format config |
| 11/11 | Static type checking — src/databricks/sql/parameters/py.typed, src/databricks/sql/py.typed |
| 10/10 | Reproducible environment — lockfile |
| 0/10 | Demonstrated agent practice — no data |
| 0/8 | Automated maintenance — no data |
| 9/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9 |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | poetry.lock |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | no |
| typecheck_configs | src/databricks/sql/parameters/py.typed, src/databricks/sql/py.typed |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | — |
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
| 27/45 | Type-checkable code — Python with type-check config (src/databricks/sql/parameters/py.typed, src/databricks/sql/py.typed) |
| 53.3/55 | Manageable file sizes — 5/158 source files over 60KB |
Inputs used
| primary_language | Python |
| largest_source_bytes | 1,060,467 |
| source_files_sampled | 158 |
| oversized_source_files | 5 |
Machine-readable interfaces
40At risk
How it's scored
| 0/40 | API schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP server |
| 40/40 | Runnable examples — examples |
Inputs used
| example_dirs | examples |
| has_mcp_signal | no |
| api_schema_files | — |
Key facts
231GitHub stars
59contributors
118commits, last 12 months
0days since last push
66releases
6bus factor
75open issues
PyPIpackage ecosystems
More detail
Star and fork history 231 ★ / 0 ⇿
231Stars
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.
Each point covers 4 days.
OpenSSF Scorecard 5.8 / 10
5.8aggregate
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 4 | Branch-Protection | branch protection is not maximal on development and all release branches |
| 10 | CI-Tests | 30 out of 30 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 |
| 8 | Code-Review | Found 26/30 approved changesets -- score normalized to 8 |
| 10 | Contributors | project has 3 contributing companies or organizations -- score normalized to 10 |
| 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 |
| 10 | Maintained | 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| n/a | Packaging | packaging workflow not detected |
| 9 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 9 |
| 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 |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Direct dependencies 13
| Registry | Package | Version constraint | Manifest |
|---|---|---|---|
| PyPI | thrift | ~=0.24.0 | pyproject.toml |
| PyPI | pandas | — | pyproject.toml |
| PyPI | lz4 | — | pyproject.toml |
| PyPI | requests | ^2.18.1 | pyproject.toml |
| PyPI | oauthlib | ^3.1.0 | pyproject.toml |
| PyPI | openpyxl | ^3.0.10 | pyproject.toml |
| PyPI | urllib3 | >=1.26 | pyproject.toml |
| PyPI | python-dateutil | ^2.8.0 | pyproject.toml |
| PyPI | pyarrow | — | pyproject.toml |
| PyPI | pyjwt | ^2.0.0 | pyproject.toml |
| PyPI | pybreaker | ^1.0.0 | pyproject.toml |
| PyPI | requests-kerberos | ^0.15.0 | pyproject.toml |
| PyPI | databricks-sql-kernel | ^0.2.0 | pyproject.toml |
All dependencies 58
Full resolved dependency set from the GitHub dependency graph: 13 direct and 45 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | databricks-sql-kernel | 0.2.0 | direct |
| PyPI | lz4 | 4.4.5 | direct |
| PyPI | oauthlib | 3.3.1 | direct |
| PyPI | openpyxl | 3.1.5 | direct |
| PyPI | pandas | 2.3.3 | direct |
| PyPI | pyarrow | 23.0.1 | direct |
| PyPI | pybreaker | 1.4.1 | direct |
| PyPI | pyjwt | 2.13.0 | direct |
| PyPI | python-dateutil | 2.9.0.post0 | direct |
| PyPI | requests | 2.34.2 | direct |
| PyPI | requests-kerberos | 0.15.0 | direct |
| PyPI | thrift | 0.24.0 | direct |
| PyPI | urllib3 | 2.7.0 | direct |
| PyPI | astroid | 4.0.4 | indirect |
| PyPI | black | 26.5.1 | indirect |
| PyPI | certifi | 2026.6.17 | indirect |
| PyPI | cffi | 2.1.0 | indirect |
| PyPI | charset-normalizer | 3.4.9 | indirect |
| PyPI | click | 8.4.2 | indirect |
| PyPI | colorama | 0.4.6 | indirect |
| PyPI | coverage | 7.15.0 | indirect |
| PyPI | cryptography | 49.0.0 | indirect |
| PyPI | decorator | 5.3.1 | indirect |
| PyPI | dill | 0.4.1 | indirect |
| PyPI | et-xmlfile | 2.0.0 | indirect |
| PyPI | exceptiongroup | 1.3.1 | indirect |
| PyPI | execnet | 2.1.2 | indirect |
| PyPI | gssapi | 1.11.1 | indirect |
| PyPI | idna | 3.18 | indirect |
| PyPI | iniconfig | 2.3.0 | indirect |
| PyPI | isort | 8.0.1 | indirect |
| PyPI | krb5 | 0.9.0 | indirect |
| PyPI | librt | 0.13.0 | indirect |
| PyPI | mccabe | 0.7.0 | indirect |
| PyPI | mypy | 1.20.2 | indirect |
| PyPI | mypy-extensions | 1.1.0 | indirect |
| PyPI | numpy | 2.2.6 | indirect |
| PyPI | packaging | 26.2 | indirect |
| PyPI | pathspec | 1.1.1 | indirect |
| PyPI | platformdirs | 4.10.0 | indirect |
| PyPI | pluggy | 1.6.0 | indirect |
| PyPI | pycparser | 3.0 | indirect |
| PyPI | pygments | 2.20.0 | indirect |
| PyPI | pylint | 4.0.6 | indirect |
| PyPI | pyspnego | 0.12.1 | indirect |
| PyPI | pytest | 9.1.1 | indirect |
| PyPI | pytest-cov | 4.1.0 | indirect |
| PyPI | pytest-dotenv | 0.5.2 | indirect |
| PyPI | pytest-xdist | 3.8.0 | indirect |
| PyPI | python-dotenv | 1.2.2 | indirect |
| PyPI | pytokens | 0.4.1 | indirect |
| PyPI | pytz | 2026.2 | indirect |
| PyPI | six | 1.17.0 | indirect |
| PyPI | sspilib | 0.5.0 | indirect |
| PyPI | tomli | 2.4.1 | indirect |
| PyPI | tomlkit | 0.15.0 | indirect |
| PyPI | typing-extensions | 4.16.0 | indirect |
| PyPI | tzdata | 2026.2 | indirect |
Dependency advisories 0
Installing pypi:databricks-sql-connector@4.3.0 pulls in 16 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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{
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"dwh",
"python3",
"sql"
],
"has_wiki": true,
"homepage": null,
"has_readme": true,
"has_docs_dir": true,
"has_description": true
},
"components": [
{
"key": "readme",
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"detail": null,
"points": 30,
"status": "met",
"details": [],
"max_points": 30
},
{
"key": "documentation_directory",
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"detail": null,
"points": 25,
"status": "met",
"details": [],
"max_points": 25
},
{
"key": "documentation_homepage_site",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
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{
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"points": 10,
"status": "met",
"details": [],
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{
"key": "topics",
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{
"key": "wiki",
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"points": 10,
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"details": [],
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]
}
],
"description": "Are baseline engineering and documentation practices in place?"
},
{
"key": "security",
"band": "moderate",
"name": "Security",
"value": 66,
"weight": 0.16,
"metrics": [
{
"key": "security_posture",
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"notes": [
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"inputs": {
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"components": [
{
"key": "binary_artifacts",
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"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "branch_protection",
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"points": 3,
"status": "partial",
"details": [],
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},
{
"key": "ci_tests",
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"points": 2.5,
"status": "met",
"details": [],
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},
{
"key": "cii_best_practices",
"name": "CII-Best-Practices",
"detail": "no effort to earn an OpenSSF best practices badge detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 2.5
},
{
"key": "code_review",
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"detail": "Found 26/30 approved changesets -- score normalized to 8",
"points": 6,
"status": "partial",
"details": [],
"max_points": 7.5
},
{
"key": "contributors",
"name": "Contributors",
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"points": 2.5,
"status": "met",
"details": [],
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},
{
"key": "dangerous_workflow",
"name": "Dangerous-Workflow",
"detail": "no dangerous workflow patterns detected",
"points": 10,
"status": "met",
"details": [],
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},
{
"key": "dependency_update_tool",
"name": "Dependency-Update-Tool",
"detail": "no update tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.5,
"status": "met",
"details": [],
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},
{
"key": "maintained",
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"detail": "30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
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"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
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],
"max_points": 5
},
{
"key": "pinned_dependencies",
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"points": 4.5,
"status": "partial",
"details": [],
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},
{
"key": "sast",
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"points": 0,
"status": "missed",
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},
{
"key": "security_policy",
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "signed_releases",
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"points": 0,
"status": "excluded",
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"code": "no_data",
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}
],
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{
"key": "token_permissions",
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
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"points": 7.5,
"status": "met",
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"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
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"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:databricks-sql-connector@4.3.0 runtime dependency closure — what installing the published package pulls in — 16 packages. Reachability is not analyzed.",
"notes": [
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"params": {
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},
{
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}
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"direct_affected_packages": 0
},
"components": [
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"points": 35,
"status": "met",
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}
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{
"key": "indirect_dependencies_free_of_known_advisories",
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"points": 25,
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"code": "no_indirect_advisories",
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{
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"points": 0,
"status": "excluded",
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"code": "advisories_no_publication_date",
"params": {}
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],
"max_points": 40
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]
},
{
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"note": null,
"notes": [],
"value": 100,
"inputs": {
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"packages": [],
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"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
},
"components": [
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{
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"notes": [
{
"code": "jurisdiction_evidence_limits",
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}
],
"value": 100,
"inputs": {
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"North Korea"
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"review_only_matches": 0,
"assessed_self_published_locations": 5
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
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]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 44,
"weight": 0,
"metrics": [
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"key": "ai_agent_context",
"band": "critical",
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"note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
"notes": [
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"code": "excluded_no_data",
"params": {
"components": [
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{
"code": "weights_renormalized",
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"value": 1,
"inputs": {
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"legible_history_share": null,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
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"components": [
{
"key": "agent_instructions",
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"points": 0,
"status": "missed",
"details": [
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"code": "no_agent_instructions",
"params": {}
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"max_points": 45
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{
"key": "machine_readable_docs_llms_txt",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
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{
"key": "legible_commit_history",
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"points": 0,
"status": "excluded",
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{
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"code": "excluded_no_data",
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"components": [
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"points": 0,
"status": "missed",
"details": [],
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{
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"points": 22,
"status": "met",
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{
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"points": 0,
"status": "missed",
"details": [],
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{
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"status": "met",
"details": [
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{
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"points": 10,
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"details": [
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"code": "file_list",
"params": {
"files": "lockfile"
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"max_points": 10
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{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
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"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 8
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{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
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"points": 9,
"status": "partial",
"details": [],
"max_points": 10
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]
},
{
"key": "ai_code_legibility",
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"note": null,
"notes": [],
"value": 80,
"inputs": {
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"source_files_sampled": 158,
"oversized_source_files": 5
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"components": [
{
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"points": 27,
"status": "partial",
"details": [
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"code": "typecheck_config_language",
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],
"max_points": 45
},
{
"key": "manageable_file_sizes",
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"points": 53.3,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
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"oversized": 5
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],
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]
},
{
"key": "ai_interfaces",
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"note": null,
"notes": [],
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"has_mcp_signal": false,
"api_schema_files": []
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"components": [
{
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"points": 0,
"status": "missed",
"details": [],
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{
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{
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"points": 40,
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"code": "file_list",
"params": {
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],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [],
"report_type": "repository",
"generated_at": "2026-07-21T03:18:18.753665Z",
"schema_version": "0.17.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/databricks/databricks-sql-python.svg",
"full_name": "databricks/databricks-sql-python",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}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 v1.13.0, schema v0.17.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics — PyPI.