##################

deep-translator

|

=======================

Translation for humans

A flexible FREE and UNLIMITED tool to translate between different languages in a simple way using multiple translators.

• Free software: MIT license
• Documentation: https://deep-translator.readthedocs.io.
• Swagger API: https://deep-translator-api.azurewebsites.net/docs.

|

|

==========

Motivation

I needed to translate a text using python. It was hard to find a simple way to do it. There are other libraries that can be used for this task, but most of them are buggy, not free, limited, not supported anymore or complex to use.

Therefore, I decided to build this simple tool. It is 100% free, unlimited, easy to use and provides support for all languages.

Basically, my goal was to integrate support for multiple famous translators in this tool.

======================

When you should use it

• If you want to translate text using python
• If you want to translate from a file
• If you want to get translations from many sources and not only one
• If you want to automate translations
• If you want to use ChatGpt for translations
• If you want to compare different translations
• If you want to detect language automatically

======================

Why you should use it

• It's the only python tool that integrates many translators
• Multi language support
• Support for ChatGpt (version >= 1.11.0)
• Supports batch translation
• High level of abstraction
• Automatic language detection
• Easy to use and extend
• Support for most famous universal translators
• Stable and maintained regularly
• The API is very easy to use
• Proxy integration is supported

========

Features

• Support for google translate
• Support for the microsoft translator (version >= 1.3.5)
• Support for Pons translator
• Support for the Linguee translator
• Support for the Mymemory translator
• Support for the Yandex translator (version >= 1.2.1)
• Support for the QcriTranslator translator (version >= 1.2.4)
• Support for the DeeplTranslator translator (version >= 1.2.5)
• Support for the Papago translator (version >= 1.4.4)
• Support for the Libre translator
• Support for ChatGpt
• Support for proxy usage
• Automatic single language detection
• Batch language detection
• Translate directly from a text file
• Translate docx files (version >= 1.9.4)
• Translate PDF files (version >= 1.9.4)
• Get multiple translation for a word
• Automate the translation of different paragraphs in different languages
• Translate directly from terminal (version >= 1.1.0)

=============

Installation

Install the stable release:

$ pip install -U deep-translator

$ poetry add deep-translator   # for poetry usage

take a look at the docs if you want to install from source.

Also, you can install extras if you want support for specific use case. For example, translating Docx and PDF files

$ pip install deep-translator[docx]  # add support for docx translation

$ pip install deep-translator[pdf]  # add support for pdf translation

$ pip install deep-translator[ai]   # add support for ChatGpt

$ poetry add deep-translator --extras "docx pdf ai"   # for poetry usage

============

Quick Start

from deep_translator import GoogleTranslator

# Use any translator you like, in this example GoogleTranslator
translated = GoogleTranslator(source='auto', target='de').translate("keep it up, you are awesome")  # output -> Weiter so, du bist großartig

or using proxies:

from deep_translator import GoogleTranslator

proxies_example = {
    "https": "34.195.196.27:8080",
    "http": "34.195.196.27:8080"
}
translated = GoogleTranslator(source='auto', target='de', proxies=proxies_example).translate("keep it up, you are awesome")  # output -> Weiter so, du bist großartig

or even directly from terminal:

$ deep-translator --source "en" --target "de" --text "hello world"

or shorter

$ dt -tg de -txt "hello world"

=====

Usage

In this section, demos on how to use all different integrated translators in this tool are provided.

Imports

from deep_translator import (GoogleTranslator,
                             ChatGptTranslator,
                             MicrosoftTranslator,
                             PonsTranslator,
                             LingueeTranslator,
                             MyMemoryTranslator,
                             YandexTranslator,
                             PapagoTranslator,
                             DeeplTranslator,
                             QcriTranslator,
                             single_detection,
                             batch_detection)

Check Supported Languages

# default return type is a list
langs_list = GoogleTranslator().get_supported_languages()  # output: [arabic, french, english etc...]

# alternatively, you can the dictionary containing languages mapped to their abbreviation
langs_dict = GoogleTranslator().get_supported_languages(as_dict=True)  # output: {arabic: ar, french: fr, english:en etc...}

Language Detection

• Single Text Detection

lang = single_detection('bonjour la vie', api_key='your_api_key')
print(lang) # output: fr

• Batch Detection

lang = batch_detection(['bonjour la vie', 'hello world'], api_key='your_api_key')
print(lang) # output: [fr, en]

Google Translate

text = 'happy coding'

• You can use automatic language detection to detect the source language:

translated = GoogleTranslator(source='auto', target='de').translate(text=text)

• You can pass languages by name or by abbreviation:

translated = GoogleTranslator(source='auto', target='german').translate(text=text)

# Alternatively, you can pass languages by their abbreviation:
translated = GoogleTranslator(source='en', target='de').translate(text=text)

• You can also reuse the Translator class and change/update its properties.

(Notice that this is important for performance too, since instantiating new objects is expensive)

# let's say first you need to translate from auto to german
my_translator = GoogleTranslator(source='auto', target='german')
result = my_translator.translate(text=text)
print(f"Translation using source = {my_translator.source} and target = {my_translator.target} -> {result}")

# let's say later you want to reuse the class but your target is french now
# This is the best practice and how you should use deep-translator.
# Please don't over-instantiate translator objects without a good reason, otherwise you will run into performance issues
my_translator.target = 'fr'  # this will override the target 'german' passed previously
result = my_translator.translate(text=text)
print(f"Translation using source = {my_translator.source} and target = {my_translator.target} -> {result}")

# you can also update the source language as well
my_translator.source = 'en'  # this will override the source 'auto' passed previously
result = my_translator.translate(text=text)
print(f"Translation using source = {my_translator.source} and target = {my_translator.target} -> {result}")

• Translate batch of texts

texts = ["hallo welt", "guten morgen"]

# the translate_sentences function is deprecated, use the translate_batch function instead
translated = GoogleTranslator('de', 'en').translate_batch(texts)

• Translate from a file:

translated = GoogleTranslator(source='auto', target='german').translate_file('path/to/file')

Mymemory Translator

• Simple translation

text = 'Keep it up. You are awesome'

translated = MyMemoryTranslator(source='auto', target='french').translate(text)

• Translate batch of texts

texts = ["hallo welt", "guten morgen"]

# the translate_sentences function is deprecated, use the translate_batch function instead
translated = MyMemoryTranslator('de', 'en').translate_batch(texts)

• Translate from file

path = "your_file.txt"

translated = MyMemoryTranslator(source='en', target='fr').translate_file(path)

DeeplTranslator

• Simple translation

text = 'Keep it up. You are awesome'

translated = DeeplTranslator(api_key="your_api_key", source="en", target="en", use_free_api=True).translate(text)

• Translate batch of texts

texts = ["hallo welt", "guten morgen"]

# the translate_sentences function is deprecated, use the translate_batch function instead
translated = DeeplTranslator("your_api_key").translate_batch(texts)

QcriTranslator

• Check languages

# as a property
print("language pairs: ", QcriTranslator("your_api_key").languages)

• Check domains

# as a property
print("domains: ", QcriTranslator("your_api_key").domains)

• Text translation

text = 'Education is great'

translated = QcriTranslator("your_api_key").translate(source='en', target='ar', domain="news", text=text)
# output -> التعليم هو عظيم

# see docs for batch translation and more.

Linguee Translator

word = 'good'

• Simple Translation

translated_word = LingueeTranslator(source='english', target='french').translate(word)

• Return all synonyms or words that match

# set the argument return_all to True if you want to get all synonyms of the word to translate
translated_word = LingueeTranslator(source='english', target='french').translate(word, return_all=True)

• Translate a batch of words

translated_words = LingueeTranslator(source='english', target='french').translate_words(["good", "awesome"])

PONS Translator

word = 'awesome'

• Simple Translation

translated_word = PonsTranslator(source='english', target='french').translate(word)

# pass language by their abbreviation
translated_word = PonsTranslator(source='en', target='fr').translate(word)

• Return all synonyms or words that match

# set the argument return_all to True if you want to get all synonyms of the word to translate
translated_word = PonsTranslator(source='english', target='french').translate(word, return_all=True)

• Translate a batch of words

translated_words = PonsTranslator(source='english', target='french').translate_words(["good", "awesome"])

Yandex Translator

• Language detection

lang = YandexTranslator('your_api_key').detect('Hallo, Welt')
print(f"language detected: {lang}")  # output -> language detected: 'de'

• Text translation

# with auto detection | meaning provide only the target language and let yandex detect the source
translated = YandexTranslator('your_api_key').translate(source="auto", target="en", text='Hallo, Welt')
print(f"translated text: {translated}")  # output -> translated text: Hello world

# provide source and target language explicitly
translated = YandexTranslator('your_api_key').translate(source="de", target="en", text='Hallo, Welt')
print(f"translated text: {translated}")  # output -> translated text: Hello world

• File translation

translated = YandexTranslator('your_api_key').translate_file(source="auto", target="en", path="path_to_your_file")

• Batch translation

translated = YandexTranslator('your_api_key').translate_batch(source="auto", target="de", batch=["hello world", "happy coding"])

Microsoft Translator

• Required and optional attributes

There are two required attributes, namely "api_key" (string) and "target" (string or list). Attribute "source" is optional. Also, Microsoft API accepts a number of other optional attributes, you can find them here: https://docs.microsoft.com/azure/cognitive-services/translator/reference/v3-0-translate You can simply add them after the required attributes, see the example.

text = 'happy coding'
translated = MicrosoftTranslator(api_key='some-key', target='de').translate(text=text)
translated_two_targets = MicrosoftTranslator(api_key='some-key', target=['de', 'ru']).translate(text=text)
translated_with_optional_attr = MicrosoftTranslator(api_key='some-key', target='de', textType='html']).translate(text=text)

• You can pass languages by name or by abbreviation:

translated = MicrosoftTranslator(api_key='some-key', target='german').translate(text=text)

# Alternatively, you can pass languages by their abbreviation:
translated = MicrosoftTranslator(api_key='some-key', target='de').translate(text=text)

• Translate batch of texts

texts = ["hallo welt", "guten morgen"]
translated = MicrosoftTranslator(api_key='some-key', target='english').translate_batch(texts)

• Translate from a file:

translated = MicrosoftTranslator(api_key='some-key', target='german').translate_file('path/to/file')

ChatGpt Translator

• Required and optional attributes

There are two required attributes, namely "api_key" (string) and "target" (string or list). Attribute "source" is optional.

You can provide your api key as an argument or you can export it as an env var e.g. export OPENAI_API_KEY="your_key"

text = 'happy coding'
translated = ChatGptTranslator(api_key='your_key', target='german').translate(text=text)

• Translate batch of texts

texts = ["hallo welt", "guten morgen"]
translated = ChatGptTranslator(api_key='some-key', target='english').translate_batch(texts)

• Translate from a file:

translated = ChatGptTranslator(api_key='some-key', target='german').translate_file('path/to/file')

Papago Translator

text = 'happy coding'
translated = PapagoTranslator(client_id='your_client_id', secret_key='your_secret_key', source='en', target='ko').translate(text=text)  # output: 행복한 부호화

Libre Translator

text = 'laufen'
translated = LibreTranslator(source='auto', target='en', base_url = 'https://libretranslate.com/', api_key = 'your_api_key').translate(text=text)  # output: run

• You can pass languages by name or by abbreviation:

translated = LibreTranslator(source='german', target='english').translate(text=text)

# Alternatively, you can pass languages by their abbreviation:
translated = LibreTranslator(source='de', target='en').translate(text=text)

• Translate batch of texts

texts = ["hallo welt", "guten morgen"]
translated = LibreTranslator(source='auto', target='en').translate_batch(texts)

• Translate from a file:

translated = LibreTranslator(source='auto', target='en').translate_file('path/to/file')

BaiduTranslator

• Simple translation

text = 'Hello world'
translated = BaiduTranslator(appid="your-appid", appkey="your-appkey" source="en", target="zh").translate(text)

• Translate batch of texts

texts = ["Hello world", "How are you?"]
translated = BaiduTranslator(appid="your-appid", appkey="your-appkey" source="en", target="zh").translate_batch(texts)

• Translate from a file:

translated = BaiduTranslator(appid="your-appid", appkey="your-appkey" source="en", target="zh").translate_file('path/to/file')

BaiduTranslator

• Simple translation

text = 'Hello world'
translated = BaiduTranslator(appid="your-appid", appkey="your-appkey" source="en", target="zh").translate(text)

• Translate batch of texts

texts = ["Hello world", "How are you?"]
translated = BaiduTranslator(appid="your-appid", appkey="your-appkey" source="en", target="zh").translate_batch(texts)

• Translate from a file:

translated = BaiduTranslator(appid="your-appid", appkey="your-appkey" source="en", target="zh").translate_file('path/to/file')

Proxy usage

deep-translator provides out of the box usage of proxies. Just define your proxies config as a dictionary and pass it to the corresponding translator. Below is an example using the GoogleTranslator, but this feature can be used with all supported translators.

from deep_translator import GoogleTranslator

# define your proxy configs:
proxies_example = {
    "https": "your https proxy",  # example: 34.195.196.27:8080
    "http": "your http proxy if available"
}
translated = GoogleTranslator(source='auto', target='de', proxies=proxies_example).translate("this package is awesome")

File Translation

Deep-translator (version >= 1.9.4) supports not only text file translation, but docx and PDF files too. However, you need to install deep-translator using the specific extras.

For docx translation:

pip install deep-translator[docx]

For PDF translation:

pip install deep-translator[pdf]

Usage from Terminal

Deep-translator supports a series of command line arguments for quick and simple access to the translators directly in your console.

For a list of available translators:

$ deep-translator list

To translate a string or line of text:

$ deep_translator google --source "english" --target "german" --text "happy coding"

Alternate short option names, along with using language abbreviations:

$ deep_translator google -src "en" -tgt "de" -txt "happy coding"

Finally, to retrieve a list of available languages for a given translator:

$ deep-translator languages google

======

Tests

Developers can install the development version of deep-translator and execute unit tests to verify functionality. For more information on doing this, see the contribution guidelines

========

Links

Check this article on medium to know why you should use the deep-translator package and how to translate text using python. https://medium.com/@nidhalbacc/how-to-translate-text-with-python-9d203139dcf5

======

Help

If you are facing any problems, please feel free to open an issue. Additionally, you can make contact with the author for further information/questions.

Do you like deep-translator? You can always help the development of this project by:

• Following on github and/or twitter
• Promote the project (ex: by giving it a star on github)
• Watch the github repo for new releases
• Tweet about the package
• Help others with issues on github
• Create issues and pull requests
• Sponsor the project

===========

Next Steps

Take a look in the examples folder for more :) Contributions are always welcome. Read the Contribution guidelines Here

==========

Credits

Many thanks to @KirillSklyarenko for his work on integrating the microsoft translator

==========

License

MIT license

Copyright (c) 2020-present, Nidhal Baccouri

===========

Swagger UI

deep-translator offers an api server for easy integration with other applications. Non python applications can communicate with the api directly and leverage the features of deep-translator

Access the api here: https://deep-translator-api.azurewebsites.net/docs

===========================

The Translator++ mobile app

You can download and try the app on play store https://play.google.com/store/apps/details?id=org.translator.translator&hl=en_US&gl=US

After developing the deep-translator, I realized how cool this would be if I can use it as an app on my mobile phone. Sure, there is google translate, pons and linguee apps etc.. but isn't it cooler to make an app where all these translators are integrated?

Long story short, I started working on the app. I decided to use the kivy framework since I wanted to code in python and to develop a cross platform app. I open sourced the Translator++ app on my github too. Feel free to take a look at the code or make a pull request ;)

I published the first release on google play store on 02-08-2020

Here are some screenshots:

• Phone

• Tablet:

===========================

Website & Desktop app

Currently, there are propositions for a website and/or desktop app based on deep-translator. You can follow the issue here: https://github.com/nidhaloff/deep-translator/issues/144