@yofriadi/pi-fuzzy-match

Install from git URL

pi install git:github.com/yofriadi/pi-extensions@fuzzy-match-v<version>

To load only this extension from the monorepo package source, use package filtering in settings:

{
  "packages": [
    {
      "source": "git:github.com/yofriadi/pi-extensions@fuzzy-match-v<version>",
      "extensions": ["packages/fuzzy-match/src/index.ts"]
    }
  ]
}

Fuzzy matching utilities for pi — progressive matching strategies for finding text in files.

Overview

Provides both character-level and line-level fuzzy matching with progressive fallback strategies for edit tool operations.

Usage

import {
  findMatch,
  seekSequence,
  findContextLine,
  similarity,
  DEFAULT_FUZZY_THRESHOLD,
} from "@yofriadi/pi-fuzzy-match";

// Find text with fuzzy matching
const result = findMatch(fileContent, searchText, {
  allowFuzzy: true,
  threshold: 0.95,
});

// Find line sequences with progressive fallback
const seqResult = seekSequence(
  lines,
  patternLines,
  0,     // start index
  false, // eof mode
  { allowFuzzy: true }
);

// Find a context line
const contextResult = findContextLine(lines, "function hello()", 0);

// Compute string similarity (0-1)
const score = similarity("hello world", "hello  world"); // ~0.95

Matching Strategies

The fuzzy matching uses progressive fallback strategies:

1. Exact match - Identical content
2. Trailing whitespace stripped - Ignores trailing spaces
3. Trimmed match - Ignores leading/trailing whitespace
4. Comment-prefix normalized - Ignores comment markers
5. Unicode normalized - Normalizes fancy quotes/dashes to ASCII
6. Prefix match - Pattern is prefix of line
7. Substring match - Pattern is substring of line
8. Fuzzy similarity - Levenshtein-based similarity scoring

API

Function	Description
findMatch(content, target, options)	Find text with optional fuzzy matching
seekSequence(lines, pattern, start, eof, options?)	Find line sequence with progressive strategies
findContextLine(lines, context, startFrom, options?)	Find a context line with fallbacks
findClosestSequenceMatch(lines, pattern, options?)	Find best fuzzy sequence match
levenshteinDistance(a, b)	Compute edit distance
similarity(a, b)	Compute similarity score (0-1)
normalizeForFuzzy(line)	Normalize for fuzzy comparison
normalizeUnicode(s)	Normalize Unicode to ASCII equivalents

Constants

Constant	Value	Description
DEFAULT_FUZZY_THRESHOLD	0.95	Default similarity threshold

License

MIT