Is Pytest Env Safe?
Pytest Env — Nerq Trust Score 72.2/100 (B grade). Score based on 2 independent trust signals. Last analyzed: 2026-08-11
Pytest Env is a Python package with a Nerq Trust Score of 72.2/100 (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 Pytest Env safe?
Trust Score Breakdown — Pytest Env has a Nerq Trust Score of 72.2/100 (B). Measured across 2 independent trust signals (as of 2026-08-11).
What is Pytest Env's trust score?
Pytest Env has a Nerq Trust Score of 72.2/100, 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 Pytest Env?
Pytest Env's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Pytest Env and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Pytest Env
What is Pytest Env?
Pytest Env is a Python package — pytest plugin that allows you to add environment variables..
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=pytest-env
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Pytest Env has a Nerq Trust Score of 72/100 (B). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Pytest Env has a Trust Score of 72/100 (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.