Q: Does agnivade/levenshtein support non-English text like Chinese or Arabic?

Yes, it fully supports Unicode and handles various languages, but you must ensure strings are properly normalized if needed, as the library doesn't automatically handle composed vs. decomposed forms for accurate distance calculations.

Q: Are there any Go libraries with more string distance algorithms than agnivade/levenshtein?

Yes, libraries like github.com/tebeka/snowball for stemming or other packages may offer additional metrics. Agnivade/levenshtein is focused only on Levenshtein distance, so for a multi-algorithm approach, you might need to combine it with other libraries.

Question 1

How do I handle Unicode normalization with agnivade/levenshtein?

Accepted Answer

The library doesn't normalize strings internally. You need to pre-process strings using Go's normalization package (golang.org/x/text/unicode/norm) before passing them to ComputeDistance to ensure accurate comparisons for accented or composed characters.

Question 2

Agnivade levenshtein vs dgryski/trifles for Go string distance?

Accepted Answer

Agnivade/levenshtein is significantly faster and more memory-efficient, with benchmarks showing about 55-60% better performance and zero allocations in many cases. It's the better choice for high-throughput applications, though it has a string length limit that dgryski/trifles might not.

Question 3

What's the maximum string length agnivade/levenshtein can handle?

Accepted Answer

The library is optimized for strings up to 65,536 characters (runes). For longer strings, you must use version 1.0.3, which supports larger inputs but may require pinning to an older version and could have other limitations.

Question 4

How to implement fuzzy search using agnivade/levenshtein?

Accepted Answer

Use the ComputeDistance function to calculate similarity scores between query and target strings, then set a threshold (e.g., distance <= 2) to filter results. Note that performance degrades with longer strings due to the algorithm's O(n*m) complexity.

Question 5

Does agnivade/levenshtein support non-English text like Chinese or Arabic?

Accepted Answer

Yes, it fully supports Unicode and handles various languages, but you must ensure strings are properly normalized if needed, as the library doesn't automatically handle composed vs. decomposed forms for accurate distance calculations.

Question 6

Are there any Go libraries with more string distance algorithms than agnivade/levenshtein?

Accepted Answer

Yes, libraries like github.com/tebeka/snowball for stemming or other packages may offer additional metrics. Agnivade/levenshtein is focused only on Levenshtein distance, so for a multi-algorithm approach, you might need to combine it with other libraries.

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