mirror of
https://github.com/gsi-upm/senpy
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76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
import requests
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import json
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from senpy.plugins import SentimentPlugin
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from senpy.models import Sentiment
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ENDPOINT = 'http://www.sentiment140.com/api/bulkClassifyJson'
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class Sentiment140(SentimentPlugin):
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'''Connects to the sentiment140 free API: http://sentiment140.com'''
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author = "@balkian"
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version = '0.2'
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url = "https://github.com/gsi-upm/senpy-plugins-community"
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extra_params = {
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'language': {
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"@id": 'lang_sentiment140',
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'aliases': ['language', 'l'],
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'required': False,
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'default': 'auto',
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'options': ['es', 'en', 'auto']
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}
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}
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maxPolarityValue = 1
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minPolarityValue = 0
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def analyse_entry(self, entry, params):
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lang = params["language"]
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res = requests.post(ENDPOINT,
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json.dumps({
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"language": lang,
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"data": [{
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"text": entry['nif:isString']
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}]
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}))
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p = params.get("prefix", None)
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polarity_value = self.maxPolarityValue * int(
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res.json()["data"][0]["polarity"]) * 0.25
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polarity = "marl:Neutral"
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neutral_value = self.maxPolarityValue / 2.0
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if polarity_value > neutral_value:
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polarity = "marl:Positive"
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elif polarity_value < neutral_value:
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polarity = "marl:Negative"
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sentiment = Sentiment(
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prefix=p,
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marl__hasPolarity=polarity,
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marl__polarityValue=polarity_value)
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sentiment.prov__wasGeneratedBy = self.id
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entry.sentiments.append(sentiment)
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entry.language = lang
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yield entry
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test_cases = [
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{
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'entry': {
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'nif:isString': 'I love Titanic'
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},
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'params': {},
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'expected': {
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"nif:isString": "I love Titanic",
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'sentiments': [
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{
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'marl:hasPolarity': 'marl:Positive',
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}
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]
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},
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'responses': [{'url': ENDPOINT,
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'method': 'POST',
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'json': {'data': [{'polarity': 4}]}}]
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}
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]
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