fn_registry/python/functions/datascience/fuzzy_merge_adaptive.md

name, kind, lang, domain, version, purity, signature, description, tags, params, output, uses_functions, uses_types, returns, returns_optional, error_type, imports, tested, tests, test_file_path, file_path, source_repo, source_license, source_file

name	kind	lang	domain	version	purity	signature	description	tags	params	output	uses_functions	uses_types	returns	returns_optional	error_type	imports	tested	tests	test_file_path	file_path	source_repo	source_license	source_file
fuzzy_merge_adaptive	function	py	datascience	1.0.0	pure	def fuzzy_merge_adaptive(left: list[dict], right: list[dict], left_key: str, right_key: str, thresholds: list[int] | None = None, how: str = 'left') -> list[dict]	Fuzzy join adaptativo entre dos listas de dicts usando rapidfuzz.token_sort_ratio. Prueba thresholds de mayor a menor y asigna el mayor cumplido. Soporta how='left' (todos los de left) e how='inner' (solo con match). Campos colisionantes reciben sufijos _left/_right.	fuzzy matching join merge rapidfuzz string-similarity datascience pendiente-usar	name desc left Lista de dicts (lado izquierdo del join). name desc right Lista de dicts (lado derecho del join). name desc left_key Clave en los dicts de left usada para matching de strings. name desc right_key Clave en los dicts de right usada para matching de strings. name desc thresholds Lista de thresholds enteros a probar en orden descendente. Default [90,80,70,60,50]. name desc how 'left' incluye todos los items de left; 'inner' solo los que tienen match.	Lista de dicts mergeados con campos de left + right (sufijos _left/_right si colisionan) + fuzzy_match (str|None), match_score (int), threshold_used (int|None).				false		rapidfuzz	true	left join con typo inner join excluye sin match left join sin match devuelve none threshold adaptativo colision de claves usa sufijos	python/functions/datascience/tests/test_fuzzy_merge_adaptive.py	python/functions/datascience/fuzzy_merge_adaptive.py	internal:footprint_aurgi	internal-aurgi	fuzzy_joins/fuzzy_en_batches.py

Ejemplo

from fuzzy_merge_adaptive import fuzzy_merge_adaptive

left = [{"name": "Madrid"}, {"name": "Barclona"}]
right = [{"name": "Madrid", "cp": "28"}, {"name": "Barcelona", "cp": "08"}]
result = fuzzy_merge_adaptive(left, right, left_key="name", right_key="name")
# result[1]["fuzzy_match"] == "Barcelona", result[1]["match_score"] >= 80

Notas

Migrado de thefuzz a rapidfuzz (API compatible, mayor velocidad). Sin pandas: el merge se implementa manualmente via dict lookup por right_key. Los thresholds se prueban de mayor a menor; el primero cumplido se asigna a threshold_used.