Is Py Dactyl Safe?
Py Dactyl — Nerq Trust Score 62.2/100 (C+ grade). Score based on 2 independent trust signals. Last analyzed: 2026-09-01
Py Dactyl is a Python package with a Nerq Trust Score of 62.2/100 (C+), based on 3 independent data dimensions. Last analyzed: 2026-09-01 Security: 90/100. Popularity: 60/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-09-01. Machine-readable data (JSON).
Is Py Dactyl safe?
Trust Score Breakdown — Py Dactyl has a Nerq Trust Score of 62.2/100 (C+). Measured across 2 independent trust signals (as of 2026-09-01).
What is Py Dactyl's trust score?
Py Dactyl has a Nerq Trust Score of 62.2/100, 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 Py Dactyl?
Py Dactyl's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Py Dactyl and who maintains it?
| Author | Ryan Kubiak |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Py Dactyl
What is Py Dactyl?
Py Dactyl is a Python package — An easy to use Python wrapper for the Pterodactyl Panel API..
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=py-dactyl
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Py Dactyl has a Nerq Trust Score of 62/100 (C+). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Py Dactyl has a Trust Score of 62/100 (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.