Is Astral Safe?
Astral — Nerq Trust Score 75.8/100 (B+ grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Astral is a Python package with a Nerq Trust Score of 75.8/100 (B+), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 75/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Astral safe?
Trust Score Breakdown — Astral has a Nerq Trust Score of 75.8/100 (B+). Measured across 2 independent trust signals (as of 2026-03-20).
What is Astral's trust score?
Astral has a Nerq Trust Score of 75.8/100, 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 Astral?
Astral's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Astral and who maintains it?
| Author | Simon Kennedy |
| Category | Python Packages |
| Source | N/A |
Astral Across Platforms
Same developer/company in other registries:
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Safety Guide: Astral
What is Astral?
Astral is a Python package — Calculations for the position of the sun and moon..
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=astral
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Astral has a Nerq Trust Score of 76/100 (B+). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Astral has a Trust Score of 76/100 (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.