¿Es Numpy Seguro?
Numpy — Nerq Trust Score 90.0/100 (Grado A+). Basado en el análisis de 2 dimensiones de confianza, se considera seguro de usar. Última actualización: 2026-04-05.
Sí, Numpy es seguro para usar. Numpy es un paquete Python con un Nerq Trust Score de 90.0/100 (A+), basado en 3 dimensiones de datos independientes. It is recomendado para uso en producción. Security: 90/100. Popularity: 100/100. Datos de PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Última actualización: 2026-04-05. Datos legibles por máquina (JSON).
¿Es Numpy Seguro?
YES — Numpy has a Nerq Trust Score of 90.0/100 (A+). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recomendado para uso en producción — review the full report below for specific considerations.
¿Cuál es la puntuación de confianza de Numpy?
Numpy tiene una Puntuación de Confianza Nerq de 90.0/100, obteniendo un grado A+. Esta puntuación se basa en 2 dimensiones medidas independientemente.
¿Cuáles son los hallazgos de seguridad clave de Numpy?
La señal más fuerte de Numpy es popularidad con 100/100. No se han detectado vulnerabilidades conocidas. Cumple con el umbral verificado de Nerq de 70+.
¿Qué es Numpy y quién lo mantiene?
| Autor | Travis E. Oliphant et al. |
| Categoría | pypi |
| Fuente | N/A |
Numpy en Otras Plataformas
Mismo desarrollador/empresa en otros registros:
Similar Pypi por Puntuación de Confianza
Safety Guide: Numpy
What is Numpy?
Numpy is a Python package — Fundamental package for array computing in Python.
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=numpy
Key Safety Concerns for Python packages
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Numpy has a Nerq Trust Score of 76/100 (B+) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Numpy has a Trust Score of 76/100 (B+).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Análisis Detallado de Puntuación
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Privacy | 80/100 |
| Reliability | 90/100 |
| Transparency | 50/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
¿Qué datos recopila Numpy?
Numpy is a Python package maintained by Travis E. Oliphant et al.. It receives approximately 194,984,733 weekly downloads.
As a development package, Numpy does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.
Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.
Análisis completo: Informe de Privacidad de Numpy · Privacy review
¿Es Numpy seguro?
Security score: 90/100. Numpy has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
License information not available. Open-source packages allow independent security review of the source code.
Run your package manager's audit command (`npm audit`, `pip audit`, `cargo audit`) to check for known vulnerabilities in your dependency tree.
Análisis completo: Informe de Seguridad de Numpy
Numpy en Otras Plataformas
Mismo desarrollador/empresa en otros registros:
Cómo calculamos esta puntuación
Numpy's trust score of 90.0/100 (A+) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), privacy (80/100), reliability (90/100), transparency (50/100), maintenance (60/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on April 05, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Preguntas Frecuentes
Is Numpy safe to use?
What is Numpy's trust score?
What are safer alternatives to Numpy?
Does Numpy have known vulnerabilities?
How actively maintained is Numpy?
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Disclaimer: Las puntuaciones de confianza de Nerq son evaluaciones automatizadas basadas en señales disponibles públicamente. No son respaldos ni garantías. Siempre realice su propia diligencia debida.