tessl install tessl/pypi-python-levenshtein@0.27.0Python compatibility wrapper for computing string edit distances and similarities using fast Levenshtein algorithms.
Agent Success
Agent success rate when using this tile
88%
Improvement
Agent success rate improvement when using this tile compared to baseline
1.38x
Baseline
Agent success rate without this tile
64%
{
"context": "This criteria evaluates how well the engineer uses the Levenshtein package's edit operation functions to implement a string transformation system. The focus is on proper usage of editops(), apply_edit(), and inverse() functions to record, apply, and reverse string transformations.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Uses editops function",
"description": "Implementation correctly uses Levenshtein.editops() to generate edit operations between source and target strings. The edit operations should be stored for later use.",
"max_score": 30
},
{
"name": "Uses apply_edit function",
"description": "Implementation correctly uses Levenshtein.apply_edit() to apply the stored edit operations to a source string, transforming it to the target string.",
"max_score": 25
},
{
"name": "Uses inverse function",
"description": "Implementation correctly uses Levenshtein.inverse() to create inverse edit operations that reverse the original transformation.",
"max_score": 25
},
{
"name": "Correct operation counting",
"description": "Implementation correctly returns the count of edit operations, typically by using len() on the list returned by editops().",
"max_score": 10
},
{
"name": "Proper initialization",
"description": "TransformTracker class correctly initializes by computing and storing edit operations from source and target strings during construction.",
"max_score": 10
}
]
}