Python库 | srec_nlp-0.2.1.tar.gz

import pathlib from typing import Union import attr import paralleldots import requests from aylienapiclient import textapi from srec_nlp.common import _ensure_utf, Query, Score, _parallel class NLP: @_ensure_utf def sentiment(self, text) -> Query: """ Sample class. :param text: Union[IOBase, str, Path, bytes] a file, pathtofile, bytes or string with the text. Function guarantees the value will be converted to text :return: Query """ raise NotImplemented() @attr.s class ParallelDots: """ with ParallelDots(api_key) as nlp: nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) # ParallelDots is still usable at this point. # So reusing it is still valid nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(>>> from math import sqrt >>> from joblib import Parallel, delayed >>> Parallel(n_jobs=2)(delayed(sqrt)(i ** 2) for i in range(10)) [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) """ api_key: str = attr.ib() @api_key.validator def setkey(self, _, value): paralleldots.set_api_key(value) def __enter__(self): return self @_parallel @_ensure_utf def sentiment(self, text) -> Query: """ Produces a sentiment score for query text using ParallelDots API :param text: Union[IOBase, str, Path, bytes] a file, pathtofile, bytes or string with the text. Function guarantees the value will be converted to text :return: Query """ response = paralleldots.sentiment(text) return Query(text, Score.fromtriplet(**response["sentiment"])) def __exit__(self, *exc): pass class TextProcessing: """ with TextProcessing() as nlp: nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) # TextProcessing is still usable at this point. # So reusing it is still valid nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) """ _url = "http://text-processing.com/api/sentiment/" def __enter__(self): return self @_parallel @_ensure_utf def sentiment(self, text) -> Query: """ Produces a sentiment score for query text using TextProcessing API :param text: Union[IOBase, str, Path, bytes] a file, pathtofile, bytes or string with the text. Function guarantees the value will be converted to text :return: Query """ data = dict(text=text) result = requests.post(self._url, data=data).json() result = result["probability"] result['positive'] = result['pos'] result['negative'] = result['neg'] del result['pos'] del result['neg'] q = Query( content=text, score=Score.fromtriplet(**result) ) return q def __exit__(self, *exc): pass try: import fastText class FastText: """ model: str/pathlib.Path the path to the model. # Usage example: with FastText(path/to/model.bin) as nlp: nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) # at this point, nlp.sentiment WILL RAISE AN ERROR because the model has been # dealloc'd, to avoid this, use the following: nlp = FastText(path/to/model.bin) nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) """ def __init__(self, path: Union[str, pathlib.Path]): self.model = FastText._load_model(path) def __enter__(self): return self def __exit__(self, *vargs, **kwargs): del self.model @_ensure_utf def sentiment(self, text) -> Query: """ Produces a sentiment score for query text using FastText API Note that FastText needs to be installed for this to work. :param text: Union[IOBase, str, Path, bytes] a file, pathtofile, bytes or string with the text. Function guarantees the value will be converted to text :return: Query """ labels, scores = self.model.predict(text, 1) label = labels[0] score = scores[0] if label == "__label__1": score = 1 - score score = Score.fromsingle(score) return Query(text, score) @staticmethod def _load_model(path: Union[str, pathlib.Path]): p = pathlib.Path(path).expanduser() if not p.is_file(): raise ValueError(f"{p} is not a file.") try: return fastText.load_model(str(p)) except Exception as e: print(e) raise ValueError(f"{p} is not a valid FastText model") except: pass class Aylien: def __init__(self, appid, appkey): """ :param appid: string Aylien application id :param appkey: string Aylien application key with Aylien(id, key) as nlp: nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) # Aylien is still usable at this point. # So reusing it is still valid nlp.sentiment(text) nlp.sentiment(bytes) nlp.sentiment(open(path/to/text.txt,'r')) nlp.sentiment(pathlib.Path('path/to/text.txt')) """ self.client = textapi.Client(applicationId=appid, applicationKey=appkey) def __enter__(self): return self @_parallel @_ensure_utf def sentiment(self, text: str) -> Query: """ Produces a sentiment score for query text using Aylien API :param text: Union[IOBase, str, Path, bytes] a file, pathtofile, bytes or string with the text. Function guarantees the value will be converted to text :return: Query """ sentiment = self.client.Sentiment(dict(text=text)) confidence = sentiment["polarity_confidence"] klass = sentiment["polarity"] remaining = (1 - confidence) vals = dict(positive=remaining, negative=remaining) vals[klass] = confidence return Query(content=text, score=Score(**vals)) def __exit__(self, *exc): pass