Metadata-Version: 1.1
Name: spacy-langdetect
Version: 0.1.1
Summary: Fully customizable language detection pipeline for spaCy
Home-page: https://github.com/Abhijit-2592/spacy-langdetect
Author: Abhijit Balaji
Author-email: balaabhijit5@gmail.com
License: UNKNOWN
Description-Content-Type: text/markdown
Description: # spacy_langdetect
        Fully customizable language detection pipeline for [spaCy](https://github.com/explosion/spaCy)
        
        ## Installation
        `pip3 install spacy-langdetect`
        
        ## NOTE:
        Requires spaCy >= 2.0. This dependency is removed in `pip install spacy-langdetect`
        
        ## 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.
        
        ```python
        import spacy
        from spacy_langdetect import LanguageDetector
        nlp = spacy.load("en")
        nlp.add_pipe(LanguageDetector(), name="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."
        doc = nlp(text)
        # document level language detection. Think of it like average language of document!
        print(doc._.language)
        # sentence level language detection
        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 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_langdetect 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
            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}
        
        nlp.add_pipe(LanguageDetector(language_detection_function=custom_detection_function), name="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."
        doc = nlp(text)
        # document level language detection. Think of it like average language of document!
        print(doc._.language)
        # sentence level language detection
        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
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
