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https://github.com/davebulaval/spacy-language-detection

Fully customizable language detection for spaCy pipeline
https://github.com/davebulaval/spacy-language-detection

language-detection nlp spacy spacy-extension

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Fully customizable language detection for spaCy pipeline

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# Here is spacy_language_detection



Spacy_language_detection is a fully customizable language detection for [spaCy](https://github.com/explosion/spaCy)

pipeline forked from

[spacy-langdetect](https://github.com/Abhijit-2592/spacy-langdetect) in order to fix the seed problem (see [this issue](https://github.com/Abhijit-2592/spacy-langdetect/issues/3)) and to update it with spaCy 3.0.



Use spacy_language_detection to



- Detect the language of a document,

- Detect the language of the sentences of a document.



## Installation



`pip install spacy-language-detection`



## Basic Usage



Out of the box, under the hood, it uses [langdetect](https://github.com/Mimino666/langdetect) to detect languages on

spaCy's Doc and Span objects.



Here is how to use it for spaCy 3.0

see [here](https://github.com/davebulaval/spacy-language-detection/blob/master/examples/detect_text_language_spacy2.py)

for an example with spaCy 2.0.



```python

import spacy

from spacy.language import Language



from spacy_language_detection import LanguageDetector



def get_lang_detector(nlp, name):

    return LanguageDetector(seed=42)  # We use the seed 42



nlp_model = spacy.load("en_core_web_sm")

Language.factory("language_detector", func=get_lang_detector)

nlp_model.add_pipe('language_detector', last=True)



# Document level language detection

job_title = "Senior NLP Research Engineer"

doc = nlp_model(job_title)

language = doc._.language

print(language)



# Sentence level language detection

text = "This is English text. Er lebt mit seinen Eltern und seiner Schwester in Berlin. Yo me divierto todos los días en el parque. Je m'appelle Angélica Summer, j'ai 12 ans et je suis canadienne."

doc = nlp_model(text)

for i, sent in enumerate(doc.sents):

    print(sent, sent._.language)

```



## Using your own language detector



Suppose you are not happy with the accuracy of the out-of-the-box language detector, or you have your own language

detector, which you want to use with a spaCy pipeline. How do you do it? That's where the `language_detection_function`

argument comes in. The function takes in a spaCy Doc or Span object and can return any Python object which is stored

in `doc._.language` and `span._.language`. For example, let's say you want to

use [googletrans](https://pypi.org/project/googletrans/) as your language detection module:



```python

import spacy

from spacy.tokens import Doc, Span

from spacy_language_detection import LanguageDetector

# install using pip install googletrans

from googletrans import Translator



nlp = spacy.load("en")



def custom_detection_function(spacy_object):

    # Custom detection function should take a spaCy Doc or a Span

    assert isinstance(spacy_object, Doc) or isinstance(

        spacy_object, Span), "spacy_object must be a spacy Doc or Span object but it is a {}".format(type(spacy_object))

    detection = Translator().detect(spacy_object.text)

    return {'language': detection.lang, 'score': detection.confidence}



def get_lang_detector(nlp, name):

    return LanguageDetector(language_detection_function=custom_detection_function, seed=42)  # We use the seed 42



nlp_model = spacy.load("en_core_web_sm")

Language.factory("language_detector", func=get_lang_detector)

nlp_model.add_pipe('language_detector', last=True)



text = "This is English text. Er lebt mit seinen Eltern und seiner Schwester in Berlin. Yo me divierto todos los días en el parque. Je m'appelle Angélica Summer, j'ai 12 ans et je suis canadienne."



# Document level language detection

doc = nlp_model(text)

language = doc._.language

print(language)



# Sentence level language detection

text = "This is English text. Er lebt mit seinen Eltern und seiner Schwester in Berlin. Yo me divierto todos los días en el parque. Je m'appelle Angélica Summer, j'ai 12 ans et je suis canadienne."

doc = nlp_model(text)

for i, sent in enumerate(doc.sents):

    print(sent, sent._.language)

```



Similarly, you can also use [pycld2](https://pypi.org/project/pycld2/) and other language detectors with spaCy.