![]() The full path to this file is YOUR_PROJECT/src/i18n/en.json. Inside the src directory, let’s add an i18n folder with an en.json file. We will use these packages throughout the tutorial, therefore install it by running: pipenv installĪlso, create an empty. Next, create a new folder for your project and add a Pipenv file in it: ] Let’s install Pipenv: pip install -user pipenv I’ll be using Pipenv to manage dependencies and create a virtual environment, but of course you can take advantage of another solution. Now I would like to see these Python translation libraries in action, but first things first: we need to prepare a sample project. Has unresolved issues and does not seem to be actively maintained.Does not allow text language detection.Supports multiple engines, including Google, Microsoft, and DeepL.It is available both as a Python module and as a command-line tool.Translate is a simple command-line tool and a Python module that enables you to perform translations using Google MT and other engines. ![]() Certain additional data no longer seems to be available.The latest stable release has unresolved issues and you’ll have to install release candidate instead.The biggest problem is that this package no longer appears to be actively maintained.The returned data contains extra information like translation confidence score or potential mistakes.It has a text language detection feature.No configuration or authentication needed you can start using the library right away.While it’s still a feasible solution, it does have certain issues. Googletrans is the library that, as the name suggests, enables you to easily translate any text using Google Translate. The package’s community seems to have become less active.Language detection is only possible with a private API key.Allows performance of translations directly from a text file (unfortunately, it has to be in.It has support for multiple translation APIs, including Google, Microsoft, Yandex, Libre, and others.The response contains the translated text without any additional information.ĭeep-translator also seems like a very solid option.Translators does not allow performance of language detection only.It does not provide many customization options.Its package supports around a dozen different translation APIs.It does not have many open issues and appears stable.The translators package is probably one of the best choices out there. There are a few available Python packages that introduce the ability to translate texts by taking advantage of neural networks. If you are interested in learning more about MT in general and the available engines, I would recommend checking out this very detailed blog post on this topic. MT has pros, but of course it has cons, too. Some even say that we don’t really need human translators anymore, but I’d say that’s a little far-fetched. The MT market is growing rapidly: computer-generated translations have come a long way, from absolutely terrible to pretty usable, thanks to the emergence of machine learning and neural networks. Machine translation (MT) is a process involving some kind of algorithm to perform translations automatically rather than hiring a human specialist. What is machine translation and which engine is the best one? We are going to discuss three Python translate libraries: Translators, googletrans, and deep-translator, and see them in action.Ĭheck out how our translation management system can help you translate your Python apps faster. I’ll show you how to work with the Google Translate and DeepL engines using Python, how to detect the language of your texts, and how to automate language translation using a dedicated TMS. In this tutorial, you will learn how to perform Python translation of nearly any type of text.
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