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Split strings into (character-based) k-shingles
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There could be multiple matches. Select the matched pattern with lowest number of wildcards
typo encode_multi_match_test
Offset is required
ensure that len(s)>=k-1 before shingling
numpy warning
doesn't split consecutive wildcards
re.error: missing ), unterminated subpattern at position 6
add ks.metrics.jaccard to README.md
Docstring missing
add containment similarity metric
Rename VOCAB to TOKENLIST
add 1 wildcard for n letters
add single-chars to memo automatically
Check `if snew not in memo:` before calling `select_most_frequent_shingles`
Set `memo` dictionary with start values
Delete commented code lines
centered padding for shingle sequences
Selection Algorithm for k-shingles
Rename `shingling_k` to `shingleseqs_k`
add code quality checks
Actually store the README.rst file in the repo before uploading to pypi
v0.6.2 seems broken
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