StringDistances.jl
diff-match-patch
| StringDistances.jl | diff-match-patch | |
|---|---|---|
| 2 | 8 | |
| 135 | 7,115 | |
| - | 1.2% | |
| 2.3 | 0.0 | |
| 26 days ago | about 2 months ago | |
| Julia | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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StringDistances.jl
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How to do a fuzzy join of two datafrmaes in Julia ?
You'll need: * StringDistances.jl to calculate the distance between the strings. * FlexiJoins.jl to join the dataframes based on a predicate. * A custom function that you write that takes two strings as arguments and returns a boolean for if the strings are "close enough" based on their distance.
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Getting the difference of two strings
If you need to know exactly what the diff is, you might want to use something like github.com/google/diff-match-patch. Otherwise, a simple Levenshtein distance would suffice. This library seems to have a whole bunch of string distances implemented. Hope this helps!
diff-match-patch
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Ideas for approaching pattern matching/distance problem
I also came across this diff match algorithms: https://github.com/google/diff-match-patch
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Form editing, changelogs, and progressive diffing - am I reinventing the wheel?
Outside of that, to get the diffs there is a library called diff-match-patch that has implementations in most languages. Your data model / state tracking sounds like it matches the internal constraints.
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Here’s my ~600 byte (minified, gzipped) package for diffing two strings.
So I'll just leave you with this question - why, as a developer, would I ever advise using this, when fast diff is an industry standard tool that does exactly this, but better, using well tested methods that are being implemented in JS and further optimized by one of the largest global tech companies. Mind you, this is the same company which has developed its own proprietary monolithic VCS, managing versioning for 2billion+ lines of code.
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Show HN: Character-Based Git Conflict Resolution
Hello HN!
I was always annoyed by conflicts that can be solved automatically, but still need human intervention. E.g. two people changing the same line, but at different, non-conflicting positions. So I searched for a character based patching library and found this nice article https://neil.fraser.name/writing/patch/ and its corresponding library https://github.com/google/diff-match-patch.
Parsing git conflicts, applying patches and showing some useful diffs in the UI helps me to solve 80% of my conflicts automatically. I hope it can help you too.
Happy Hacking!
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Keeping track of changes made to xml file.
A bit late to the party but have you checked this? google/diff-match-patch
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Ask HN: What are the best the publicly available FAMANG code repos?
Found this, simple and seems interesting: https://github.com/google/diff-match-patch
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Getting the difference of two strings
If you need to know exactly what the diff is, you might want to use something like github.com/google/diff-match-patch. Otherwise, a simple Levenshtein distance would suffice. This library seems to have a whole bunch of string distances implemented. Hope this helps!
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Get Diff and Patch Html
Photo by Markus Spiske on Diff.Match.Patch based on Google library.
What are some alternatives?
Cadmium - Natural Language Processing (NLP) library for Crystal
esbuild - An extremely fast bundler for the web
Quickenshtein - Making the quickest and most memory efficient implementation of Levenshtein Distance with SIMD and Threading support
webdiff - Two-column web-based git difftool
Java String Similarity - Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity ...
tmatch - Super fast token matcher
mudderjs - Lexicographically-subdivide the “space” between strings, by defining an alternate non-base-ten number system using a pre-defined dictionary of symbol↔︎number mappings. Handy for ordering NoSQL keys.
Eureka - AWS Service registry for resilient mid-tier load balancing and failover.
NLP-Model-for-Corpus-Similarity - A NLP algorithm I developed to determine the similarity or relation between two documents/Wikipedia articles. Inspired by the cosine similarity algorithm and built from WordNet.
haproxy - HAProxy Load Balancer's development branch (mirror of git.haproxy.org)
go-edlib - 📚 String comparison and edit distance algorithms library, featuring : Levenshtein, LCS, Hamming, Damerau levenshtein (OSA and Adjacent transpositions algorithms), Jaro-Winkler, Cosine, etc...
Pawky - The Python version of awk