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HPR4026: Using NLP to get better answer options for language learning
Code snippets
Install the Levenshtein package.
>>> pip install levenshtein
Use the Levenshtein package to calculate the edit distance.
>>> import Levenshtein
>>> Levenshtein.distance("cat", "dog")
3
>>> Levenshtein.distance("cat", "can")
1
Install the TheFuzz package.
>>> pip install thefuzz
Use TheFuzz to calculate the similarity ratio.
>>> from thefuzz import fuzz
>>> fuzz.ratio("cat", "dog")
0
>>> fuzz.ratio("cat", "can")
67
Use TheFuzz to calculate the similarity ratio for each item in a
list.
>>> from thefuzz import process
>>> options = ["dog", "can"]
>>> process.extract("cat", options, limit=2)
[('can', 67), ('dog', 0)]
>>> process.extract("cat", options, limit=1)
[('can', 67)]
>>> process.extract("cat", options, limit=2, scorer=fuzz.ratio)
[('can', 67), ('dog', 0)]
Other resources
Ethan Nam's Understanding
the Levenshtein Distance Equation for Beginners
Levenstein
package
TheFuzz
View all episodes
By Hacker Public Radio
4.2
3434 ratings
Code snippets
Install the Levenshtein package.
>>> pip install levenshtein
Use the Levenshtein package to calculate the edit distance.
>>> import Levenshtein
>>> Levenshtein.distance("cat", "dog")
3
>>> Levenshtein.distance("cat", "can")
1
Install the TheFuzz package.
>>> pip install thefuzz
Use TheFuzz to calculate the similarity ratio.
>>> from thefuzz import fuzz
>>> fuzz.ratio("cat", "dog")
0
>>> fuzz.ratio("cat", "can")
67
Use TheFuzz to calculate the similarity ratio for each item in a
list.
>>> from thefuzz import process
>>> options = ["dog", "can"]
>>> process.extract("cat", options, limit=2)
[('can', 67), ('dog', 0)]
>>> process.extract("cat", options, limit=1)
[('can', 67)]
>>> process.extract("cat", options, limit=2, scorer=fuzz.ratio)
[('can', 67), ('dog', 0)]
Other resources
Ethan Nam's Understanding
the Levenshtein Distance Equation for Beginners
Levenstein
package
TheFuzz
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