Is Bqsensorgen Safe?
Bqsensorgen — Nerq Trust Score 53.2/100 (C- grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25
Bqsensorgen is a Python package with a Nerq Trust Score of 53.2/100 (C-), based on 3 independent data dimensions. Last analyzed: 2026-03-25 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).
Is Bqsensorgen safe?
Trust Score Breakdown — Bqsensorgen has a Nerq Trust Score of 53.2/100 (C-). Measured across 2 independent trust signals (as of 2026-03-25).
What is Bqsensorgen's trust score?
Bqsensorgen has a Nerq Trust Score of 53.2/100, earning a C- grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Bqsensorgen?
Bqsensorgen's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Bqsensorgen and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Bqsensorgen
What is Bqsensorgen?
Bqsensorgen is a Python package — Generate sensor queries from your BigQuery queries..
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=bqsensorgen
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Bqsensorgen has a Nerq Trust Score of 53/100 (C-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Bqsensorgen has a Trust Score of 53/100 (C-).
- 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.