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https://github.com/lindera-morphology/lindera

A morphological analysis library.
https://github.com/lindera-morphology/lindera

analyzer hacktoberfest library morphological tokenizer

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A morphological analysis library.

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README 

        
# Lindera



[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Join the chat at https://gitter.im/lindera-morphology/lindera](https://badges.gitter.im/lindera-morphology/lindera.svg)](https://gitter.im/lindera-morphology/lindera?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![Crates.io](https://img.shields.io/crates/v/lindera.svg)](https://crates.io/crates/lindera)



A morphological analysis library in Rust. This project fork from [kuromoji-rs](https://github.com/fulmicoton/kuromoji-rs).



Lindera aims to build a library which is easy to install and provides concise APIs for various Rust applications.



The following products are required to build:



- Rust >= 1.46.0



## Tokenizer Usage



### Basic example



Put the following in Cargo.toml:



```

[dependencies]

lindera-tokenizer = { version = "0.24.0", features = ["ipadic"] }

```



This example covers the basic usage of Lindera.



It will:

- Create a tokenizer in normal mode

- Tokenize the input text

- Output the tokens



```rust

use lindera_core::{mode::Mode, LinderaResult};

use lindera_dictionary::{DictionaryConfig, DictionaryKind};

use lindera_tokenizer::tokenizer::{Tokenizer, TokenizerConfig};



fn main() -> LinderaResult<()> {

    let dictionary = DictionaryConfig {

        kind: Some(DictionaryKind::IPADIC),

        path: None,

    };



    let config = TokenizerConfig {

        dictionary,

        user_dictionary: None,

        mode: Mode::Normal,

    };



    // create tokenizer

    let tokenizer = Tokenizer::from_config(config)?;



    // tokenize the text

    let tokens = tokenizer.tokenize("関西国際空港限定トートバッグ")?;



    // output the tokens

    for token in tokens {

        println!("{}", token.text);

    }



    Ok(())

}

```



The above example can be run as follows:



```shell script

% cargo run --features=ipadic --example=ipadic_basic_example

```



You can see the result as follows:

```text

関西国際空港

限定

トートバッグ

```



### User dictionary example



You can give user dictionary entries along with the default system dictionary. User dictionary should be a CSV with following format.



```

,,

```



For example:

```shell

% cat ./resources/simple_userdic.csv

東京スカイツリー,カスタム名詞,トウキョウスカイツリー

東武スカイツリーライン,カスタム名詞,トウブスカイツリーライン

とうきょうスカイツリー駅,カスタム名詞,トウキョウスカイツリーエキ

```



With an user dictionary, `Tokenizer` will be created as follows:

```rust

use std::path::PathBuf;



use lindera_tokenizer::tokenizer::{Tokenizer, TokenizerConfig};

use lindera_core::viterbi::Mode;

use lindera_core::LinderaResult;



fn main() -> LinderaResult<()> {

    let dictionary = DictionaryConfig {

        kind: Some(DictionaryKind::IPADIC),

        path: None,

    };



    let user_dictionary = Some(UserDictionaryConfig {

        kind: DictionaryKind::IPADIC,

        path: PathBuf::from("./resources/ipadic_simple_userdic.csv"),

    });



    let config = TokenizerConfig {

        dictionary,

        user_dictionary,

        mode: Mode::Normal,

    };



    let tokenizer = Tokenizer::from_config(config)?;



    // tokenize the text

    let tokens = tokenizer.tokenize("東京スカイツリーの最寄り駅はとうきょうスカイツリー駅です")?;



    // output the tokens

    for token in tokens {

        println!("{}", token.text);

    }



    Ok(())

}

```



The above example can be by `cargo run --example`:

```shell

% cargo run --features=ipadic --example=ipadic_userdic_example

東京スカイツリー

の

最寄り駅

は

とうきょうスカイツリー駅

です

```



## Anzalyzer Usage



### Basic example



Put the following in Cargo.toml:



```

[dependencies]

lindera-analyzer = { version = "0.24.0", features = ["ipadic", "ipadic-filter"] }

```



This example covers the basic usage of Lindera Analysis Framework.



It will:

- Apply character filter for Unicode normalization (NFKC)

- Tokenize the input text with IPADIC

- Apply token filters for removing stop tags (Part-of-speech) and Japanese Katakana stem filter



```rust

use std::{fs, path::PathBuf};



use lindera_analyzer::analyzer::Analyzer;

use lindera_core::LinderaResult;



fn main() -> LinderaResult<()> {

    let path = PathBuf::from(env!("CARGO_MANIFEST_DIR"))

        .join("../resources")

        .join("lindera_ipadic_conf.json");



    let config_bytes = fs::read(path).unwrap();



    let analyzer = Analyzer::from_slice(&config_bytes).unwrap();



    let mut text = "Ｌｉｎｄｅｒａは形態素解析ｴﾝｼﾞﾝです。ユーザー辞書も利用可能です。".to_string();

    println!("text: {}", text);



    // tokenize the text

    let tokens = analyzer.analyze(&text)?;



    // output the tokens

    for token in tokens {

        println!(

            "token: {:?}, start: {:?}, end: {:?}, details: {:?}",

            token.text,

            token.byte_start,

            token.byte_end,

            token.details

        );

    }



    Ok(())

}

```



The above example can be run as follows:



```shell script

% cargo run --features=ipadic,ipadic-filter --example=analysis_example

```



You can see the result as follows:

```text

text: Ｌｉｎｄｅｒａは形態素解析ｴﾝｼﾞﾝです。ユーザー辞書も利用可能です。

token: Lindera, start: 0, end: 21, details: Some(["UNK"])

token: 形態素, start: 24, end: 33, details: Some(["名詞", "一般", "*", "*", "*", "*", "形態素", "ケイタイソ", "ケイタイソ"])

token: 解析, start: 33, end: 39, details: Some(["名詞", "サ変接続", "*", "*", "*", "*", "解析", "カイセキ", "カイセキ"])

token: エンジン, start: 39, end: 54, details: Some(["名詞", "一般", "*", "*", "*", "*", "エンジン", "エンジン", "エンジン"])

token: ユーザ, start: 0, end: 26, details: Some(["名詞", "一般", "*", "*", "*", "*", "ユーザー", "ユーザー", "ユーザー"])

token: 辞書, start: 26, end: 32, details: Some(["名詞", "一般", "*", "*", "*", "*", "辞書", "ジショ", "ジショ"])

token: 利用, start: 35, end: 41, details: Some(["名詞", "サ変接続", "*", "*", "*", "*", "利用", "リヨウ", "リヨー"])

token: 可能, start: 41, end: 47, details: Some(["名詞", "形容動詞語幹", "*", "*", "*", "*", "可能", "カノウ", "カノー"])

```



## API reference



The API reference is available. Please see following URL:

- lindera