Translators - is a library which aims to bring free, multiple, enjoyable translation to individuals and students in Python

Overview

PyPI - Version PyPI - License PyPI - Python PyPI - Status PyPI - Wheel Downloads


Translators is a library which aims to bring free, multiple, enjoyable translation to individuals and students in Python. It based on the translation interface of Google, Yandex, Microsoft(Bing), Baidu, Alibaba, Tencent, NetEase(Youdao), Sogou, Kingsoft(Iciba), Iflytek, Deepl, Caiyun, Argos, etc.

Installation

From PyPI

# Windows, Mac, Linux
pip install translators --upgrade

# Linux javascript runtime environment:
sudo yum -y install nodejs

From Source

git clone https://github.com/UlionTse/translators.git
cd translators
python setup.py install

Getting Started

import translators as ts

wyw_text = '季姬寂,集鸡,鸡即棘鸡。棘鸡饥叽,季姬及箕稷济鸡。'
chs_text = '季姬感到寂寞,罗集了一些鸡来养,鸡是那种出自荆棘丛中的野鸡。野鸡饿了唧唧叫,季姬就拿竹箕中的谷物喂鸡。'
html_text = '''



	这是标题


这是文章《你的父亲》

''' ## language # input languages print(ts.google(wyw_text)) # default: from_language='auto', to_language='en' # output language_map print(ts._google.language_map) ## professional field print(ts.alibaba(wyw_text, professional_field='general')) # ("general","message","offer") print(ts.baidu(wyw_text, professional_field='common')) # ('common','medicine','electronics','mechanics') print(ts.caiyun(wyw_text, from_language='zh', professional_field=None)) # ("medicine","law","machinery") ## property rs = [ts.tencent(x) for x in [wyw_text, chs_text]] print(ts._tencent.query_count) print(dir(ts._tencent)) ## requests print(ts.youdao(wyw_text, sleep_seconds=5, timeout=None, proxies=None)) ## host # cn print(ts.google(wyw_text, if_use_cn_host=True)) print(ts.bing(wyw_text, if_use_cn_host=False)) # reset host print(ts.google(wyw_text, reset_host_url=None)) print(ts.yandex(wyw_text, reset_host_url=None)) ## detail result print(ts.sogou(wyw_text, is_detail_result=True)) ## translate html print(ts.translate_html(html_text, translator=ts.google, to_language='en', n_jobs=-1)) ## others print(ts._argos.host_pool) print(ts.argos(wyw_text, reset_host_url=None)) ## help help(ts.google)

Issues

Linux Runtime Environment

  1. To support javascript runtime environment, you should sudo yum -y install nodejs .
  2. PS, ts.baidu() does not work on Linux without desktop.

Supported Country and Region Service

  1. If you have requests error, please check whether this service is provided in your country or region.
  2. Check the website about eg: help(ts.google).

HttpError 4xx

  1. Please check whether you made high frequency requests.
  2. Please check whether this service is provided in your country or region.
  3. Detail to solve HttpError itself.
  4. Please issue me, thanks.

RequestsError or ProxyError

  1. Check whether the advanced version of requests you have installed can access the site properly. If not, try lowering the version or otherwise.
  2. Check that agents are enabled on your computer. If it is enabled, try turning it off or otherwise.

More About Translators

Features

Translator Number of Supported Languages Advantage
Iciba 187 support the most languages in the world
Google 109 support more languages in the world
Bing 102 support more languages in the world
Yandex 100 support more languages in the world, support word to emoji
Iflytek 70 support more languages in the world
Sogou 61 support more languages in the world
Baidu 28 support main languages, support professional field
Deepl 24 high quality to translate but response slowly
Tencent 17 support main languages
Argos 17 support main languages , open-source
Youdao 15 support main languages, high quality
Alibaba 12 support main languages, support professional field
Caiyun 6 high quality to translate but response slowly, support professional field

Support Language

Language Language of Translator Google Yandex Bing Baidu Alibaba Tencent Youdao Sogou Deepl Caiyun Argos Iciba Iflytek
english en Y Y Y Y Y Y Y Y Y Y Y ... ...
chinese zh Y Y Y Y Y Y Y Y Y Y Y
arabic ar Y Y Y Y(ara) Y Y Y Y Y
russian ru Y Y Y Y Y Y Y Y Y Y Y
french fr Y Y Y Y(fra) Y Y Y Y Y Y Y
german de Y Y Y Y Y Y Y Y Y
spanish es Y Y Y Y(spa) Y Y Y Y Y Y Y
portuguese pt Y Y Y(pt/pt-pt) Y Y Y Y Y Y Y
italian it Y Y Y Y Y Y Y Y Y Y
japanese ja Y Y Y Y(jp) Y Y Y Y Y Y
korean ko Y Y Y Y(kor) Y Y Y Y
greek el Y Y Y Y Y Y
dutch nl Y Y Y Y Y Y Y
hindi hi Y Y Y Y Y Y
turkish tr Y Y Y Y Y Y Y
malay ms Y Y Y Y Y
thai th Y Y Y Y Y Y Y
vietnamese vi Y Y Y Y(vie) Y Y Y Y Y
indonesian id Y Y Y Y Y Y Y Y
hebrew he Y(iw) Y Y Y
polish pl Y Y Y Y Y Y Y
mongolian mn Y Y Y(nm)
czech cs Y Y Y Y Y Y
hungarian hu Y Y Y Y Y Y
estonian et Y Y Y Y(est) Y Y
bulgarian bg Y Y Y Y(bul) Y Y
danish da Y Y Y Y(dan) Y Y
finnish fi Y Y Y Y(fin) Y Y
romanian ro Y Y Y Y(rom) Y Y
swedish sv Y Y Y Y(swe) Y Y
slovenian sl Y Y Y Y(slo) Y Y
persian/farsi fa Y Y Y Y
bosnian bs Y Y Y(bs-Latn) Y(bs-Latn)
serbian sr Y Y Y(sr-Latn/sr-Cyrl) Y(sr-Latn/sr-Cyrl)
fijian fj Y Y
filipino tl Y Y Y(fil) Y(fil)
haitiancreole ht Y Y Y Y
catalan ca Y Y Y Y
croatian hr Y Y Y Y
latvian lv Y Y Y Y Y
lithuanian lt Y Y Y Y Y
urdu ur Y Y Y Y
ukrainian uk Y Y Y Y
welsh cy Y Y Y Y
tahiti ty Y Y
tongan to Y Y
swahili sw Y Y Y Y
samoan sm Y Y Y
slovak sk Y Y Y Y Y
afrikaans af Y Y Y Y
norwegian no Y Y Y Y
bengali bn Y Y Y(bn-BD) Y
malagasy mg Y Y Y Y
maltese mt Y Y Y Y
queretaro otomi otq Y Y
klingon/tlhingan hol tlh Y Y
gujarati gu Y Y Y
tamil ta Y Y Y
telugu te Y Y Y
punjabi pa Y Y Y
amharic am Y Y
azerbaijani az Y Y
bashkir ba Y
belarusian be Y Y
cebuano ceb Y Y
chuvash cv Y
esperanto eo Y Y
basque eu Y Y
irish ga Y Y Y
emoji emj Y
... ...

More supported language, eg:

# request once first, then:
print(ts._google.language_map)

About Chinese Language

Language Language of Translator Google Yandex Bing Baidu Alibaba Tencent Youdao Sogou Iciba Iflytek Caiyun Deepl Argos
Chinese(简体) zh-CHS Y(zh-CN) Y(zh) Y(zh-Hans) Y(zh) Y(zh) Y(zh) Y Y Y(zh) Y(zh) Y(zh) Y(zh) Y(zh)
Chinese(繁体) zh-CHT Y(zh-TW) Y(zh-Hant) Y(cht) Y(zh-TW) Y Y(cnt)
Chinese(文言文) wyw Y
Chinese(粤语) yue Y Y Y Y Y
Chinese(内蒙语) mn N[外蒙] N[外蒙] Y[内蒙]
Chinese(维吾尔语) uy Y
Chinese(藏语) ti Y
Chinese(白苗文) mww Y Y Y
Chinese(彝语) ii Y

License

MIT Llicense

Toy example of an applied ML pipeline for me to experiment with MLOps tools.

Toy Machine Learning Pipeline Table of Contents About Getting Started ML task description and evaluation procedure Dataset description Repository stru

Shreya Shankar 190 Dec 21, 2022
Takes a string and puts it through different languages in Google Translate a requested amount of times, returning nonsense.

PythonTextObfuscator Takes a string and puts it through different languages in Google Translate a requested amount of times, returning nonsense. Requi

2 Aug 29, 2022
Finally, some decent sample sentences

tts-dataset-prompts This repository aims to be a decent set of sentences for people looking to clone their own voices (e.g. using Tacotron 2). Each se

hecko 19 Dec 13, 2022
ChatterBot is a machine learning, conversational dialog engine for creating chat bots

ChatterBot ChatterBot is a machine-learning based conversational dialog engine build in Python which makes it possible to generate responses based on

Gunther Cox 12.8k Jan 03, 2023
This Project is based on NLTK It generates a RANDOM WORD from a predefined list of words, From that random word it read out the word, its meaning with parts of speech , its antonyms, its synonyms

This Project is based on NLTK(Natural Language Toolkit) It generates a RANDOM WORD from a predefined list of words, From that random word it read out the word, its meaning with parts of speech , its

SaiVenkatDhulipudi 2 Nov 17, 2021
Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers

beyond masking Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers The code is coming Figure 1: Pipeline of token-based pre-

Yunjie Tian 23 Sep 27, 2022
New Modeling The Background CodeBase

Modeling the Background for Incremental Learning in Semantic Segmentation This is the updated official PyTorch implementation of our work: "Modeling t

Fabio Cermelli 9 Dec 28, 2022
End-to-end image captioning with EfficientNet-b3 + LSTM with Attention

Image captioning End-to-end image captioning with EfficientNet-b3 + LSTM with Attention Model is seq2seq model. In the encoder pretrained EfficientNet

2 Feb 10, 2022
Training code of Spatial Time Memory Network. Semi-supervised video object segmentation.

Training-code-of-STM This repository fully reproduces Space-Time Memory Networks Performance on Davis17 val set&Weights backbone training stage traini

haochen wang 128 Dec 11, 2022
fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.

fastNLP fastNLP是一款轻量级的自然语言处理(NLP)工具包,目标是快速实现NLP任务以及构建复杂模型。 fastNLP具有如下的特性: 统一的Tabular式数据容器,简化数据预处理过程; 内置多种数据集的Loader和Pipe,省去预处理代码; 各种方便的NLP工具,例如Embedd

fastNLP 2.8k Jan 01, 2023
Natural Language Processing Tasks and Examples.

Natural Language Processing Tasks and Examples With the advancement of A.I. technology in recent years, natural language processing technology has bee

Soohwan Kim 53 Dec 20, 2022
Source code for the paper "TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations"

TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations Created by Jiahao Pang, Duanshun Li, and Dong Tian from InterDigital In

InterDigital 21 Dec 29, 2022
Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021

efficient-task-transfer This repository contains code for the experiments in our paper "What to Pre-Train on? Efficient Intermediate Task Selection".

AdapterHub 26 Dec 24, 2022
🏆 • 5050 most frequent words in 109 languages

🏆 Most Common Words Multilingual 5000 most frequent words in 109 languages. Uses wordfrequency.info as a source. 🔗 License source code license data

14 Nov 24, 2022
InferSent sentence embeddings

InferSent InferSent is a sentence embeddings method that provides semantic representations for English sentences. It is trained on natural language in

Facebook Research 2.2k Dec 27, 2022
MEDIALpy: MEDIcal Abbreviations Lookup in Python

A small python package that allows the user to look up common medical abbreviations.

Aberystwyth Systems Biology 7 Nov 09, 2022
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

Ryuichi Yamamoto 1.8k Dec 30, 2022
A Python/Pytorch app for easily synthesising human voices

Voice Cloning App A Python/Pytorch app for easily synthesising human voices Documentation Discord Server Video guide Voice Sharing Hub FAQ's System Re

Ben Andrew 840 Jan 04, 2023
📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation

Well-formed Limericks and Haikus with GPT2 📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation In collaboration with Matthew Korahais &

Bardia Shahrestani 2 May 26, 2022
A fast and easy implementation of Transformer with PyTorch.

FasySeq FasySeq is a shorthand as a Fast and easy sequential modeling toolkit. It aims to provide a seq2seq model to researchers and developers, which

宁羽 7 Jul 18, 2022