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Merge pull request #1102 from PyThaiNLP/add-word2word
Add pythainlp.translate.word_translate
2 parents cf7e780 + 23d49ad commit aad134d

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‎docker_requirements.txt‎

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@@ -39,3 +39,4 @@ transformers==4.51.3
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ufal.chu-liu-edmonds==1.0.3
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wtpsplit==1.3.0
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wunsen==0.0.3
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word2word==1.0.0

‎docs/api/translate.rst‎

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@@ -12,6 +12,9 @@ Modules
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The `Translate` class is the central component of the module, offering a unified interface for various translation tasks. It acts as a coordinator, directing translation requests to specific language pairs and models.
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.. autoclass:: word_translate
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:members:
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.. autofunction:: pythainlp.translate.en_th.download_model_all
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:noindex:
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‎pythainlp/translate/__init__.py‎

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@@ -6,9 +6,9 @@
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Language translation.
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"""
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__all__ = ["Translate", "ThZhTranslator", "ZhThTranslator"]
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__all__ = ["Translate", "ThZhTranslator", "ZhThTranslator", "word_translate"]
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from pythainlp.translate.core import Translate
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from pythainlp.translate.core import Translate, word_translate
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from pythainlp.translate.zh_th import (
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ThZhTranslator,
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ZhThTranslator,

‎pythainlp/translate/core.py‎

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@@ -2,6 +2,8 @@
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# SPDX-FileCopyrightText: 2016-2025 PyThaiNLP Project
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# SPDX-FileType: SOURCE
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# SPDX-License-Identifier: Apache-2.0
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from typing import List, Union
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class Translate:
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"""
@@ -83,7 +85,7 @@ def load_model(self):
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else:
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raise ValueError("Not support language!")
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def translate(self, text) -> str:
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def translate(self, text: str) -> str:
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"""
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Translate text
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@@ -94,3 +96,43 @@ def translate(self, text) -> str:
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if self.engine == "small100":
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return self.model.translate(text, tgt_lang=self.target_lang)
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return self.model.translate(text)
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def word_translate(
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word: str,
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src: str,
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target: str,
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engine: str="word2word"
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) -> Union[List[str], None]:
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"""
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Translate word from source language to target language.
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:param str word: text
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:param str src: src language
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:param str target: target language
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:param str engine: Word translate engine (the default engine is word2word)
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:return: return list word translate or None
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:rtype: Union[List[str], None]
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:Example:
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Translate word from Thai to English::
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from pythainlp.translate import word_translate
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print(word_translate("แมว","th","en"))
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# output: ['cat', 'cats', 'kitty', 'kitten', 'Cat']
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Translate word from English to Thai::
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from pythainlp.translate import word_translate
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print(word_translate("cat","en","th"))
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# output: ['แมว', 'แมวป่า', 'ข่วน', 'เลี้ยง', 'อาหาร']
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"""
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if engine=="word2word":
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from .word2word_translate import translate
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return translate(word=word, src=src, target=target)
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else:
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raise NotImplementedError(
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f"pythainlp.translate.word_translate isn't support {engine}."
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)

‎pythainlp/translate/th_fr.py‎

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@@ -13,7 +13,6 @@
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- Huggingface https://huggingface.co/Helsinki-NLP/opus-mt-th-fr
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"""
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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class ThFrTranslator:
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use_gpu: bool = False,
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pretrained: str = "Helsinki-NLP/opus-mt-th-fr",
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) -> None:
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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self.tokenizer_thzh = AutoTokenizer.from_pretrained(pretrained)
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self.model_thzh = AutoModelForSeq2SeqLM.from_pretrained(pretrained)
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if use_gpu:

‎pythainlp/translate/word2word_translate.py‎

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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: 2016-2025 PyThaiNLP Project
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# SPDX-FileType: SOURCE
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# SPDX-License-Identifier: Apache-2.0
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from typing import List, Union
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from word2word import Word2word
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support_list = set(['zh_tw',
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'el',
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'te',
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'hu',
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'eu',
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'ko',
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'ru',
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'lv',
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'bg',
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'sk',
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'vi',
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'gl',
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'et',
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'ta',
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'fa',
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'it',
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'ms',
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'id',
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'pt',
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'fr',
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'sr',
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'mk',
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'sv',
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'si',
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'en',
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'ka',
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'uk',
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'sl',
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'hi',
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'ca',
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'lt',
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'es',
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'no',
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'de',
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'he',
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'cs',
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'ze_zh',
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'fi',
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'pl',
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'tl',
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'is',
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'ze_en',
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'kk',
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'bn',
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'tr',
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'ur',
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'pt_br',
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'ar',
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'ro',
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'bs',
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'ml',
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'zh_cn',
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'da',
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'hr',
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'sq',
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'af',
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'eo',
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'nl',
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'ja',
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'th'])
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def translate(word: str, src: str, target: str) -> Union[List[str], None]:
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"""
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Word translate
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:param str word: text
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:param str src: src language
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:param str target: target language
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:return: return list word translate or None
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:rtype: Union[List[str], None]
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"""
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if src not in support_list or target not in support_list:
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raise NotImplementedError(
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f"word2word doesn't support {src}-{target}."
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)
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elif src==target:
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return [word]
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_engine = Word2word(src, target)
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return _engine(word)

‎pythainlp/translate/zh_th.py‎

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@@ -10,7 +10,6 @@
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- GitHub: https://github.com/LalitaDeelert/lalita-mt-zhth
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- Facebook post https://web.facebook.com/aibuildersx/posts/166736255494822
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"""
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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class ThZhTranslator:
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use_gpu: bool = False,
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pretrained: str = "Lalita/marianmt-th-zh_cn",
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) -> None:
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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self.tokenizer_thzh = AutoTokenizer.from_pretrained(pretrained)
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self.model_thzh = AutoModelForSeq2SeqLM.from_pretrained(pretrained)
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if use_gpu:

‎setup.py‎

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"sentencepiece>=0.1.91",
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"torch>=1.0.0",
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"transformers>=4.6.0",
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"word2word>=1.0.0"
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],
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"transformers_ud": [
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"transformers>=4.22.1",
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"ufal.chu-liu-edmonds>=1.0.2",
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"wtpsplit>=1.0.1",
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"wunsen>=0.0.3",
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"word2word>=1.0.0",
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],
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}
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‎tests/extra/testx_translate.py‎

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import unittest
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from pythainlp.translate import Translate
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from pythainlp.translate import Translate, word_translate
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from pythainlp.translate.en_th import (
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EnThTranslator,
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ThEnTranslator,
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# )
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with self.assertRaises(ValueError):
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self.th_cat_translator = Translate('th', 'cat', engine="fkfj")
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def test_word_translate(self):
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self.assertIsNone(word_translate("cat", src="en", target="th"))
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self.assertIsNone(word_translate("แมว", src="en", target="th"))
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self.assertIsNone(
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word_translate("cat", src="en", target="th", engine="word2word")
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)
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self.assertIsNone(
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word_translate("แมว", src="en", target="th", engine="word2word")
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)
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self.assertEqual(
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word_translate("แมว", src="th", target="th", engine="word2word"),
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["แมว"]
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)
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with self.assertRaises(NotImplementedError):
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word_translate("cat", src="en", target="th", engine="cat")
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with self.assertRaises(NotImplementedError):
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word_translate("แมว", src="th", target="xxx", engine="word2word")

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