Is Feedparser Sgmllib Safe?
Feedparser Sgmllib — Nerq Trust Score 61.8/100 (C+ grade). Score based on 2 independent trust signals. Last analyzed: 2026-09-01
Feedparser Sgmllib is a Python package (sgmllib from Python 2) with a Nerq Trust Score of 61.8/100 (C+), based on 3 independent data dimensions. Last analyzed: 2026-09-01 Security: 90/100. Popularity: 90/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-09-01. Machine-readable data (JSON).
Is Feedparser Sgmllib safe?
Trust Score Breakdown — Feedparser Sgmllib has a Nerq Trust Score of 61.8/100 (C+). Measured across 2 independent trust signals (as of 2026-09-01).
What is Feedparser Sgmllib's trust score?
Feedparser Sgmllib has a Nerq Trust Score of 61.8/100, 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 Feedparser Sgmllib?
Feedparser Sgmllib's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Feedparser Sgmllib and who maintains it?
| Author | Kurt McKee |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Feedparser Sgmllib
What is Feedparser Sgmllib?
Feedparser Sgmllib is a Python package — sgmllib from Python 2.7. For feedparser use only..
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=feedparser-sgmllib
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Feedparser Sgmllib 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
- Feedparser Sgmllib 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.
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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.