Is Analytics Python Safe?
Analytics Python — Nerq Trust Score 75.0/100 (B+ grade). Based on analysis of 2 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-06-01.
Yes, Analytics Python is safe to use. Analytics Python is a Python package with a Nerq Trust Score of 75.0/100 (B+), based on 3 independent data dimensions. Recommended for production use. 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 Analytics Python safe?
YES — Analytics Python has a Nerq Trust Score of 75.0/100 (B+). 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.
What is Analytics Python's trust score?
Analytics Python has a Nerq Trust Score of 75.0/100, 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 Analytics Python?
Analytics Python's strongest signal is security at 90/100. No known vulnerabilities have been detected. It meets the Nerq Verified threshold of 70+.
What is Analytics Python and who maintains it?
| Author | Segment |
| Category | Python Packages |
| Source | N/A |
Analytics Python Across Platforms
Same developer/company in other registries:
Similar Pypi by Trust Score
Safety Guide: Analytics Python
What is Analytics Python?
Analytics Python is a Python package — The hassle-free way to integrate analytics into any python application..
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=analytics-python
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Analytics Python has a Nerq Trust Score of 75/100 (B+) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Analytics Python has a Trust Score of 75/100 (B+).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 92/100 |
| Popularity | 75/100 |
| Quality | 65/100 |
| Community | 35/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Analytics Python collect?
Privacy assessment for Analytics Python is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Analytics Python secure?
Security score: 90/100. Analytics Python has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under MIT License, allowing code inspection. 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.
Full analysis: Analytics Python Security Report
Analytics Python Across Platforms
Same developer/company in other registries:
How we calculated this score
Analytics Python's trust score of 75.0/100 (B+) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (92/100), popularity (75/100), quality (65/100), community (35/100). 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 June 01, 2026. Data version: 0.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.