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

# Copyright 2018 Kata.ai

#

# 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 typing import Any, Callable, Container, List, Mapping, Optional, Sequence, Union

import itertools

import re

import string

Word = str

Label = Union[bool, float]

class Sentence(Sequence[Word]):

DELIMITER = '\t\t\t'

def __init__(self,

words: Sequence[Word],

gold_label: Optional[Label] = None,

pred_label: Optional[Label] = None,

) -> None:

self.words = words

self.gold_label = gold_label

self.pred_label = pred_label

@property

def label(self) -> Optional[Label]:

return self.gold_label

@label.setter

def label(self, label):

self.gold_label = label

def __getitem__(self, key):

return self.words[key]

def __len__(self) -> int:

return len(self.words)

def __str__(self) -> str:

words_str = ' '.join(self.words)

if self.label is None:

return words_str

if isinstance(self.label, bool):

label = 1 if self.label else 0

else:

label = self.label

return '{}{}{}'.format(words_str, self.DELIMITER, label)

def filter_words(self, predicate: Callable[[Word], bool]) -> 'Sentence':

return Sentence(

list(filter(predicate, self.words)), gold_label=self.gold_label,

pred_label=self.pred_label)

def map_words(self, func: Callable[[Word], Word]) -> 'Sentence':

return Sentence(

list(map(func, self.words)), gold_label=self.gold_label, pred_label=self.pred_label)

class Paragraph(Sequence[Sentence]):

def __init__(self, sentences: Sequence[Sentence]) -> None:

self.sentences = sentences

@property

def words(self) -> List[Word]:

return [word for sent in self.sentences for word in sent]

@property

def labels(self) -> List[Optional[Label]]:

return [sent.label for sent in self.sentences]

@property

def pred_labels(self) -> List[Optional[Label]]:

return [sent.pred_label for sent in self.sentences]

def __getitem__(self, key):

return self.sentences[key]

def __len__(self) -> int:

return len(self.sentences)

def __str__(self) -> str:

return '\n'.join(str(sent) for sent in self.sentences)

def filter_words(self, predicate: Callable[[Word], bool]) -> 'Paragraph':

filtered_sents = [sent.filter_words(predicate) for sent in self.sentences]

return Paragraph([sent for sent in filtered_sents if sent])

def map_words(self, func: Callable[[Word], Word]) -> 'Paragraph':

return Paragraph([sent.map_words(func) for sent in self.sentences])

@classmethod

def from_sequence(cls,

sents: Sequence[Sequence[Word]],

gold_labels: Optional[Sequence[Label]] = None,

pred_labels: Optional[Sequence[Label]] = None,

) -> 'Paragraph':

gold_labels_ = itertools.repeat(None) if gold_labels is None else gold_labels

pred_labels_ = itertools.repeat(None) if pred_labels is None else pred_labels

sentences = []

for sent, gold, pred in zip(sents, gold_labels_, pred_labels_): # type: ignore

sentences.append(Sentence(sent, gold_label=gold, pred_label=pred))

return cls(sentences)

class Document(Sequence[Paragraph]):

def __init__(self,

paragraphs: Sequence[Paragraph],

summary: Optional[Paragraph] = None,

category: Optional[str] = None,

source: Optional[str] = None,

source_url: Optional[str] = None,

id_: Optional[str] = None,

lower: bool = False,

remove_puncts: bool = False,

replace_digits: bool = False,

stopwords: Optional[Container[Word]] = None,

) -> None:

self.paragraphs = paragraphs

self.summary = summary

self.category = category

self.source = source

self.source_url = source_url

self.id_ = id_

self.lower = lower

self.remove_puncts = remove_puncts

self.replace_digits = replace_digits

self.stopwords = stopwords

self.preprocess()

def preprocess(self) -> None:

if self.lower:

self.paragraphs = [para.map_words(lambda w: w.lower())

for para in self.paragraphs]

if self.remove_puncts:

self.paragraphs = [para.filter_words(lambda w: w not in string.punctuation)

for para in self.paragraphs]

if self.replace_digits:

self.paragraphs = [para.map_words(lambda w: re.sub(r'\d', '0', w))

for para in self.paragraphs]

if self.stopwords is not None:

self.paragraphs = [para.filter_words(lambda w: w not in self.stopwords) # type: ignore

for para in self.paragraphs]

@property

def words(self) -> List[Word]:

return list(itertools.chain(*[para.words for para in self.paragraphs]))

@property

def sentences(self) -> List[Sentence]:

return list(itertools.chain(*self.paragraphs))

def __getitem__(self, key):

return self.paragraphs[key]

def __len__(self) -> int:

return len(self.paragraphs)

def __str__(self) -> str:

return '\n\n'.join(str(para) for para in self.paragraphs)

@classmethod

def from_mapping(cls, obj: Mapping[str, Any], **kwargs) -> 'Document':

paragraphs = cls._get_paragraphs_from_mapping(obj)

summary = obj.get('summary')

if summary is not None:

summary = Paragraph.from_sequence(summary)

return cls(

paragraphs, summary=summary, category=obj.get('category'), source=obj.get('source'),

source_url=obj.get('source_url'), id_=obj.get('id'), **kwargs)

def to_dict(self) -> dict:

paragraphs = [[sent.words for sent in para] for para in self.paragraphs]

res: dict = {'paragraphs': paragraphs}

if self.summary is not None:

res['summary'] = [sent.words for sent in self.summary]

for attr in 'category source source_url'.split():

if getattr(self, attr) is not None:

res[attr] = getattr(self, attr)

if self.id_ is not None:

res['id'] = self.id_

gold_labels = [para.labels for para in self.paragraphs]

if all(lab is not None for lab in itertools.chain.from_iterable(gold_labels)):

res['gold_labels'] = gold_labels

pred_labels = [para.pred_labels for para in self.paragraphs]

if all(lab is not None for lab in itertools.chain.from_iterable(pred_labels)):

res['pred_labels'] = pred_labels

return res

@staticmethod

def _get_paragraphs_from_mapping(obj: Mapping[str, Any]) -> List[Paragraph]:

gold_labels = obj.get('gold_labels', itertools.repeat(None))

pred_labels = obj.get('pred_labels', itertools.repeat(None))

paragraphs = [Paragraph.from_sequence(p, gold_labels=gl, pred_labels=pl)

for p, gl, pl in zip(obj['paragraphs'], gold_labels, pred_labels)]

return paragraphs