Hi Jean-Francois - Other than Match, I queried docs and SnapGPT and other options are:
Option 2: Deduplicate Snap (Machine Learning Snap Pack)
The Deduplicate Snap uses the same set of comparators (including Levenshtein) but is intended for deduplication within a single dataset. It can still be leveraged to identify how "different" records are from each other with a configurable threshold, but it's less suited for general-purpose pairwise string comparison.
Option 3: Script Snap (Custom Workaround for Raw Distance)
If you need the raw Levenshtein integer distance (e.g., "kitten" vs "sitting" = 3), you can implement it using a Script Snap with Python or JavaScript:
Example (Python-style pseudologic inside a Script Snap):
import Levenshtein # if available, or implement manually
distance = Levenshtein.distance(input['string1'], input['string2'])
output['levenshtein_distance'] = distance
Note: Library availability depends on your Snaplex configuration. A custom implementation of the algorithm can also be coded directly in the script.
For most use cases involving quantitative string similarity, the Match Snap from the Machine Learning Snap Pack is the recommended starting point due to its built-in support for Levenshtein and many other algorithms.
