enderecobr_rs

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MIT licensed

enderecobr_rs é uma biblioteca em Rust que disponibiliza diversas funções para padronizar endereços brasileiros, corrigindo erros comuns, expandindo abreviações etc, afim de facilitar processamentos posteriores. Ela usa majoritariamente expressões regulares nas padronizações, com exceção do módulo experimental de separação de endereços, que utiliza um modelo probabilístico de Conditional Random Field já embutido na bilioteca.

Obs. Esta biblioteca é uma adaptação e expansão para Rust da versão original em R do enderecobr visando ganho de eficiência e expandir a implementação do pacote endereçobr em diferentes linguagens usando a versão em Rust como base.

Bindings

Este é o repositório do enderecobr em Rust e em Python. A versão em Python é feita no subdiretório bindings/python deste projeto. O repositório da versão em R se mantém em enderecobr, utilizando internamente as funções desta lib. Algumas funções ou classes/structs da implementação em Rust podem não estar expostas em outras linguagens. Vide documentação do Rust para identificar tais situações. Para solicitar esse tipo de mudança ou bindings em outras linguagens de programação, por favor abrir uma Issue ou Pull request neste repositório.

Documentação:

Instalação

A última versão pode ser baixada do crates com o comando:

cargo add enderecobr_rs

Ou adicionando em no seu Cargo.toml:

[dependencies]
enderecobr_rs = { version = "0.0.3" }

Exemplo de uso

Rust:

use enderecobr_rs::{padronizar_complementos, padronizar_logradouros};
assert_eq!(padronizar_logradouros("r. gen.. glicério"), "RUA GENERAL GLICERIO");
assert_eq!(padronizar_complementos("QD1 LT2 CS3"), "QUADRA 1 LOTE 2 CASA 3");

Python:

import enderecobr
assert enderecobr.padronizar_logradouros("r. gen.. glicério") == "RUA GENERAL GLICERIO"
assert enderecobr.padronizar_logradouros("QD1 LT2 CS3") == "QUADRA 1 LOTE 2 CASA 3"

Nota Ipea

enderecobr é desenvolvido por uma equipe de pesquisadores do Instituto de Pesquisa Econômica Aplicada (Ipea).

Project links

Key dates

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  • Released:
Latest release

1 maintainer

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Avatar for ggalmeida from gravatar.com ggalmeida

Credits

Author: Daniel Herszenhut Meirelles Santos

License

MIT License

Requires

Python >=3.9

Provides Extra

doc

Tags

address brazil brasil regex geocoding

Classifiers

Report project as malware

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This release

0.2.0 This release

31 files

0.0.6

29 files

0.0.5

29 files

0.0.4

29 files

0.0.3

29 files

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