Безопасен ли Numpy?
Numpy — Nerq Trust Score 90.0/100 (Оценка A+). На основе анализа 2 измерений доверия, считается безопасным для использования. Последнее обновление: 2026-04-05.
Да, Numpy безопасен для использования. Numpy — это Python package with a Nerq Trust Score of 90.0/100 (A+), based on 3 independent data dimensions. It is recommended for production use. Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-05. Машинночитаемые данные (JSON).
Безопасен ли Numpy?
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. Recommended for production use — review the full report below for specific considerations.
Каков рейтинг доверия Numpy?
Numpy имеет Nerq Trust Score 90.0/100 с оценкой A+. Этот балл основан на 2 независимо измеренных параметрах, включая безопасность, обслуживание и принятие сообществом.
Каковы основные выводы по безопасности Numpy?
Самый сильный сигнал Numpy — популярность на уровне 100/100. Известных уязвимостей не обнаружено. It meets the Nerq Verified threshold of 70+.
Что такое Numpy и кто его поддерживает?
| Разработчик | Travis E. Oliphant et al. |
| Категория | pypi |
| Источник | N/A |
Numpy на других платформах
Тот же разработчик/компания в других реестрах:
Похожие Pypi по рейтингу доверия
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.
Подробный анализ рейтинга
| 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.
Какие данные собирает 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.
Полный анализ: Отчёт о конфиденциальности Numpy · Privacy review
Безопасен ли Numpy?
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.
Полный анализ: Отчёт о безопасности Numpy
Numpy на других платформах
Тот же разработчик/компания в других реестрах:
Как мы рассчитали этот рейтинг
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)
Часто задаваемые вопросы
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?
Popular in pypi
Browse Categories
Disclaimer: Рейтинги доверия Nerq — это автоматические оценки, основанные на публично доступных сигналах. Они не являются рекомендацией или гарантией. Всегда проводите собственную проверку.