#
#    Copyright 2014 Grupo de Sistemas Inteligentes (GSI) DIT, UPM
#
#    Licensed under the Apache License, Version 2.0 (the "License");
#    you may not use this file except in compliance with the License.
#    You may obtain a copy of the License at
#
#        http://www.apache.org/licenses/LICENSE-2.0
#
#    Unless required by applicable law or agreed to in writing, software
#    distributed under the License is distributed on an "AS IS" BASIS,
#    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#    See the License for the specific language governing permissions and
#    limitations under the License.
#

from senpy.plugins import Transformation
from senpy.models import Entry
from nltk.tokenize.punkt import PunktSentenceTokenizer
from nltk.tokenize.simple import LineTokenizer


class Split(Transformation):
    '''
    A plugin that chunks input text, into paragraphs or sentences.

    It does not provide any sort of annotation, and it is meant to precede
    other annotation plugins, when the annotation of individual sentences
    (or paragraphs) is required.
    '''

    author = ["@militarpancho", '@balkian']
    version = '0.3'
    url = "https://github.com/gsi-upm/senpy"
    nltk_resources = ['punkt']

    extra_params = {
        'delimiter': {
            'description': 'Split text into paragraphs or sentences.',
            'aliases': ['type', 't'],
            'required': False,
            'default': 'sentence',
            'options': ['sentence', 'paragraph']
        },
    }

    def analyse_entry(self, entry, activity):
        yield entry
        chunker_type = activity.params["delimiter"]
        original_text = entry['nif:isString']
        if chunker_type == "sentence":
            tokenizer = PunktSentenceTokenizer()
        if chunker_type == "paragraph":
            tokenizer = LineTokenizer()
        chars = list(tokenizer.span_tokenize(original_text))
        if len(chars) == 1:
            # This sentence was already split
            return
        for i, chunk in enumerate(chars):
            start, end = chunk
            e = Entry()
            e['nif:isString'] = original_text[start:end]
            if entry.id:
                e.id = entry.id + "#char={},{}".format(start, end)
            yield e

    test_cases = [
        {
            'entry': {
                'nif:isString': 'Hello. World.'
            },
            'params': {
                'delimiter': 'sentence',
            },
            'expected': [
                {
                    'nif:isString': 'Hello.'
                },
                {
                    'nif:isString': 'World.'
                }
            ]
        },
        {
            'entry': {
                "@id": ":test",
                'nif:isString': 'Hello\nWorld'
            },
            'params': {
                'delimiter': 'paragraph',
            },
            'expected': [
                {
                    "@id": ":test#char=0,5",
                    'nif:isString': 'Hello'
                },
                {
                    "@id": ":test#char=6,11",
                    'nif:isString': 'World'
                }
            ]
        }
    ]