Is Db Dtypes Safe?
Db Dtypes — Nerq Trust Score 68.2/100 (B- grade). Score based on 2 independent trust signals. Last analyzed: 2026-08-11
Db Dtypes is a Python package with a Nerq Trust Score of 68.2/100 (B-), based on 3 independent data dimensions. Last analyzed: 2026-08-11 Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-08-11. Machine-readable data (JSON).
Is Db Dtypes safe?
Trust Score Breakdown — Db Dtypes has a Nerq Trust Score of 68.2/100 (B-). Measured across 2 independent trust signals (as of 2026-08-11).
What is Db Dtypes's trust score?
Db Dtypes has a Nerq Trust Score of 68.2/100, earning a B- grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Db Dtypes?
Db Dtypes's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Db Dtypes and who maintains it?
| Author | The db-dtypes Authors |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Db Dtypes
What is Db Dtypes?
Db Dtypes is a Python package — Pandas Data Types for SQL systems (BigQuery, Spanner).
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=db-dtypes
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Db Dtypes has a Nerq Trust Score of 68/100 (B-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Db Dtypes has a Trust Score of 68/100 (B-).
- The score is a measured composite — it is not a suitability judgment. Evaluate the individual signals against your own requirements.
- Query the current measured values via the Nerq API.
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.