Fuzzy Match

Category: Analysis

Status: Registered and callable in the CyberChef 11.3.0 compatibility inventory.

Input / output: string → html

Background: https://wikipedia.org/wiki/Fuzzy_matching_(computer-assisted_translation)

What it does

Conducts a fuzzy search to find a pattern within the input based on weighted criteria. e.g. A search for dpan will match on Don't Panic

Note

Status here means the operation name is implemented and callable. It does not by itself promise byte-for-byte parity for every upstream option. See Compatibility and current status for the verified scope and known boundaries.

Arguments and options

Arguments are positional. Keep their order when using bake() or Pipeline.then().

Index

Name

UI type

PyChef default

Accepted values / format

0

Search

binaryString

''

''

1

Sequential bonus

number

'DEFAULT_WEIGHTS.sequentialBonus'

A Python integer or floating-point value

2

Separator bonus

number

'DEFAULT_WEIGHTS.separatorBonus'

A Python integer or floating-point value

3

Camel bonus

number

'DEFAULT_WEIGHTS.camelBonus'

A Python integer or floating-point value

4

First letter bonus

number

'DEFAULT_WEIGHTS.firstLetterBonus'

A Python integer or floating-point value

5

Leading letter penalty

number

'DEFAULT_WEIGHTS.leadingLetterPenalty'

A Python integer or floating-point value

6

Max leading letter penalty

number

'DEFAULT_WEIGHTS.maxLeadingLetterPenalty'

A Python integer or floating-point value

7

Unmatched letter penalty

number

'DEFAULT_WEIGHTS.unmatchedLetterPenalty'

A Python integer or floating-point value

Recipe template

Important

This is a call template built from the documented defaults. Replace placeholder values such as empty keys, paths, patterns, or lookup data before running it.

from pychef import bake

input_value = "example"
args = ['', 'DEFAULT_WEIGHTS.sequentialBonus', 'DEFAULT_WEIGHTS.separatorBonus', 'DEFAULT_WEIGHTS.camelBonus', 'DEFAULT_WEIGHTS.firstLetterBonus', 'DEFAULT_WEIGHTS.leadingLetterPenalty', 'DEFAULT_WEIGHTS.maxLeadingLetterPenalty', 'DEFAULT_WEIGHTS.unmatchedLetterPenalty']
result = bake(input_value, [{"op": 'Fuzzy Match', "args": args}])
print(result)

Pipeline example

from pychef import Pipeline

args = ['', 'DEFAULT_WEIGHTS.sequentialBonus', 'DEFAULT_WEIGHTS.separatorBonus', 'DEFAULT_WEIGHTS.camelBonus', 'DEFAULT_WEIGHTS.firstLetterBonus', 'DEFAULT_WEIGHTS.leadingLetterPenalty', 'DEFAULT_WEIGHTS.maxLeadingLetterPenalty', 'DEFAULT_WEIGHTS.unmatchedLetterPenalty']
transform = Pipeline().then('Fuzzy Match', *args)
result = transform("example")

Dedicated operation module

The registered entry point lives in pychef.operations.by_operation.fuzzy_match. Direct calls receive the input value and a positional argument tuple:

from pychef.operations.by_operation.fuzzy_match import run

result = run("example", tuple(['', 'DEFAULT_WEIGHTS.sequentialBonus', 'DEFAULT_WEIGHTS.separatorBonus', 'DEFAULT_WEIGHTS.camelBonus', 'DEFAULT_WEIGHTS.firstLetterBonus', 'DEFAULT_WEIGHTS.leadingLetterPenalty', 'DEFAULT_WEIGHTS.maxLeadingLetterPenalty', 'DEFAULT_WEIGHTS.unmatchedLetterPenalty']))
pychef.operations.by_operation.fuzzy_match.run(value, args)

Run this operation using its shared internal implementation.

Parameters:

  • value (str | bytes)

  • args (Sequence[Any])

Return type:

str | bytes