Is Arca Safe?
Arca — Nerq Trust Score 58.0/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Arca is a Python package with a Nerq Trust Score of 58.0/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 15/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Arca safe?
Trust Score Breakdown — Arca has a Nerq Trust Score of 58.0/100 (C). Measured across 2 independent trust signals (as of 2026-03-20).
What is Arca's trust score?
Arca has a Nerq Trust Score of 58.0/100, 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 Arca?
Arca's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Arca and who maintains it?
| Author | Mikuláš Poul |
| Category | Python Packages |
| Source | N/A |
Arca Across Platforms
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Safety Guide: Arca
What is Arca?
Arca is a Python package — A library for running Python functions (callables) from git repositories in various states of isolation with integrating caching..
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=arca
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Arca has a Nerq Trust Score of 58/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Arca has a Trust Score of 58/100 (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.