9bdcbe0447
Major integrations and fixes: - Added BACKBEAT SDK integration for P2P operation timing - Implemented beat-aware status tracking for distributed operations - Added Docker secrets support for secure license management - Resolved KACHING license validation via HTTPS/TLS - Updated docker-compose configuration for clean stack deployment - Disabled rollback policies to prevent deployment failures - Added license credential storage (CHORUS-DEV-MULTI-001) Technical improvements: - BACKBEAT P2P operation tracking with phase management - Enhanced configuration system with file-based secrets - Improved error handling for license validation - Clean separation of KACHING and CHORUS deployment stacks 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
119 lines
3.8 KiB
Markdown
119 lines
3.8 KiB
Markdown
# This fork...
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I'm maintaining this fork because the original author was not replying to issues or pull requests. For now I plan on maintaining this fork as necessary.
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## Status
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[](https://travis-ci.org/blevesearch/go-porterstemmer)
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[](https://coveralls.io/r/blevesearch/go-porterstemmer?branch=HEAD)
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# Go Porter Stemmer
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A native Go clean room implementation of the Porter Stemming Algorithm.
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This algorithm is of interest to people doing Machine Learning or
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Natural Language Processing (NLP).
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This is NOT a port. This is a native Go implementation from the human-readable
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description of the algorithm.
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I've tried to make it (more) efficient by NOT internally using string's, but
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instead internally using []rune's and using the same (array) buffer used by
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the []rune slice (and sub-slices) at all steps of the algorithm.
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For Porter Stemmer algorithm, see:
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http://tartarus.org/martin/PorterStemmer/def.txt (URL #1)
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http://tartarus.org/martin/PorterStemmer/ (URL #2)
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# Departures
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Also, since when I initially implemented it, it failed the tests at...
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http://tartarus.org/martin/PorterStemmer/voc.txt (URL #3)
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http://tartarus.org/martin/PorterStemmer/output.txt (URL #4)
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... after reading the human-readble text over and over again to try to figure out
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what the error I made was (and doing all sorts of things to debug it) I came to the
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conclusion that the some of these tests were wrong according to the human-readable
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description of the algorithm.
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This led me to wonder if maybe other people's code that was passing these tests had
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rules that were not in the human-readable description. Which led me to look at the source
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code here...
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http://tartarus.org/martin/PorterStemmer/c.txt (URL #5)
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... When I looked there I noticed that there are some items marked as a "DEPARTURE",
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which differ from the original algorithm. (There are 2 of these.)
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I implemented these departures, and the tests at URL #3 and URL #4 all passed.
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## Usage
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To use this Golang library, use with something like:
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package main
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import (
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"fmt"
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"github.com/reiver/go-porterstemmer"
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)
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func main() {
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word := "Waxes"
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stem := porterstemmer.StemString(word)
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fmt.Printf("The word [%s] has the stem [%s].\n", word, stem)
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}
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Alternatively, if you want to be a bit more efficient, use []rune slices instead, with code like:
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package main
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import (
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"fmt"
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"github.com/reiver/go-porterstemmer"
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)
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func main() {
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word := []rune("Waxes")
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stem := porterstemmer.Stem(word)
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fmt.Printf("The word [%s] has the stem [%s].\n", string(word), string(stem))
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}
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Although NOTE that the above code may modify original slice (named "word" in the example) as a side
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effect, for efficiency reasons. And that the slice named "stem" in the example above may be a
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sub-slice of the slice named "word".
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Also alternatively, if you already know that your word is already lowercase (and you don't need
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this library to lowercase your word for you) you can instead use code like:
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package main
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import (
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"fmt"
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"github.com/reiver/go-porterstemmer"
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)
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func main() {
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word := []rune("waxes")
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stem := porterstemmer.StemWithoutLowerCasing(word)
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fmt.Printf("The word [%s] has the stem [%s].\n", string(word), string(stem))
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}
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Again NOTE (like with the previous example) that the above code may modify original slice (named
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"word" in the example) as a side effect, for efficiency reasons. And that the slice named "stem"
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in the example above may be a sub-slice of the slice named "word".
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