Is Spark Parser Safe?
Spark Parser — Nerq Trust Score 69.5/100 (B- grade). Based on analysis of 2 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-08-01.
Use Spark Parser with some caution. Spark Parser is a Python package with a Nerq Trust Score of 69.5/100 (B-), based on 3 independent data dimensions. Below the recommended threshold of 70. Security: 90/100. Popularity: 75/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-07-22. Machine-readable data (JSON).
Is Spark Parser safe?
CAUTION — Spark Parser has a Nerq Trust Score of 69.5/100 (B-). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
What is Spark Parser's trust score?
Spark Parser has a Nerq Trust Score of 69.5/100, 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 Spark Parser?
Spark Parser's strongest signal is security at 90/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Spark Parser and who maintains it?
| Author | Rocky Bernstein |
| Category | Python Packages |
| Source | N/A |
Spark Parser Across Platforms
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Safety Guide: Spark Parser
What is Spark Parser?
Spark Parser is a Python package — An Earley-Algorithm Context-free grammar Parser Toolkit.
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=spark-parser
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Spark Parser has a Nerq Trust Score of 70/100 (B-) and has not yet reached Nerq trust threshold (70+). This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Spark Parser has a Trust Score of 70/100 (B-).
- Review carefully before use — below trust threshold.
- Always verify independently using the Nerq 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.