Is Texttable Safe?
Texttable — Nerq Trust Score 71.8/100 (B grade). Score based on 2 independent trust signals. Last analyzed: 2026-08-11
Texttable is a Python package (module to create simple ASCII tables) with a Nerq Trust Score of 71.8/100 (B), based on 3 independent data dimensions. Last analyzed: 2026-08-11 Security: 90/100. Popularity: 90/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-08-11. Machine-readable data (JSON).
Is Texttable safe?
Trust Score Breakdown — Texttable has a Nerq Trust Score of 71.8/100 (B). Measured across 2 independent trust signals (as of 2026-08-11).
What is Texttable's trust score?
Texttable has a Nerq Trust Score of 71.8/100, 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 Texttable?
Texttable's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Texttable and who maintains it?
| Author | Gerome Fournier |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Texttable
What is Texttable?
Texttable is a Python package — module to create simple ASCII tables.
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=texttable
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Texttable has a Nerq Trust Score of 72/100 (B). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Texttable has a Trust Score of 72/100 (B).
- 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.
Frequently Asked Questions
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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.