What is unicode_names?

48/100
Trust Score (D)
⚠️ Use Caution

unicode_names is a crates that Map characters to and from their name given in the Unicode standard. This goes to great lengths to be as efficient as possible in both time and space, with the full bidirectional tables weighing barel. It has a Nerq Trust Score of 48/100 (D). 0 GitHub stars. Published by Unknown. Last analyzed October 2026.

Why This Score

Trust & Safety Overview

48
TRUST SCORE
D
GRADE
0
STARS
0
DOWNLOADS

What unicode_names Does

unicode_names is a crates in the crates category. Map characters to and from their name given in the Unicode standard. This goes to great lengths to be as efficient as possible in both time and space, with the full bidirectional tables weighing barely 500 KB but still offering O(1)* look-up in both directions. (*more precisely, O(length of name).) . It is published by Unknown and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use unicode_names

unicode_names is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.

Details

AuthorUnknown
Categorycrates
LicenseNot specified
Typecrates
SourceView on GitHub
Security Score0/100
Activity Score0/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=unicode-names

Setup guide · Full safety report · Production review · Is it safe?

Frequently Asked Questions

What is unicode_names used for?
unicode_names is a crates tool. Map characters to and from their name given in the Unicode standard. This goes to great lengths to be as efficient as possible in both time and space, with the full bidirectional tables weighing barel.
Is unicode_names free?
License: Check project page. unicode_names has 0 GitHub stars.
Is unicode_names safe?
unicode_names has a Nerq Trust Score of 48/100 (D). Evaluate carefully.
What are alternatives to unicode_names?
Top alternatives: . See full comparison.

Last updated October 2026. Trust scores based on automated analysis of public data.

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