mirror of
https://github.com/KevinMidboe/termForecast.git
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138 lines
3.2 KiB
Python
Executable File
138 lines
3.2 KiB
Python
Executable File
#!/usr/bin/env python3.6
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# -*- coding: utf-8 -*-
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# @Author: KevinMidboe
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# @Date: 2017-07-29 11:56:24
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# @Last Modified by: KevinMidboe
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# @Last Modified time: 2017-07-29 18:26:06
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from fuzzywuzzy import process
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# Find the first word, if it is a noun or a adjective.
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# Remove the adjective and split if there is a AND
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# Then match the first noun to list and add that emoji
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# and then match the second to list and add that emoji
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# REGEX this bitch up
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symbol_table = {
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'clear sky': '☀️',
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'fair': '🌤',
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'partly cloudy': '⛅️',
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'cloudy': '☁️',
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'thunder': '⚡️',
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'rain showers': '🌦',
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'rain': '🌧',
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'sleet showers': '🌦 💦',
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'sleet': '🌨 💦',
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'snow showers': '⛅ ❄️',
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'snow': '🌨',
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'rain': '🌧',
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'sleet': '🌧',
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'snow': '🌨',
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'showers': '🌤'
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}
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severity = {
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'rain': ['💧', ' ☂️', ' ☔️'],
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'sleet': [' 💦 ', ' 💧 ', ' 💧 💦 '],
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'snow': [' ❄️ ', ' ❄️ ❄️ ', ' ❄️ ❄️ ❄️ ']
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}
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class EmojiParser(object):
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def __init__(self, condition_text):
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self.condition_expression = condition_text
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self.severity = None
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self.nouns = []
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self.weather_nouns = ['cleary sky', 'fair', 'cloudy', 'rain', 'rain showers', 'sleet',
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'sleet showers', 'snow showers', 'thunder', 'snow']
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self.weather_adjectives = {'light': 0, 'normal': 1, 'heavy': 2}
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def __str__(self):
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return str([self.condition_expression, self.severity, self.nouns])
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# Splits and lowers the condition text for easier parsing
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def splitCondition(self, condition):
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condition = condition.lower()
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return condition.split()
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def findAdjective(self, sentence=None):
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if sentence is None:
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sentence = self.condition_expression
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expression = self.splitCondition(sentence)
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for word in expression:
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if word in self.weather_adjectives:
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return word
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return None
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def severityValue(self):
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adjective = self.findAdjective()
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if adjective:
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self.severity = self.weather_adjectives[adjective]
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else:
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self.severity = self.weather_adjectives['normal']
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def removeAdjective(self):
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adjective = self.findAdjective()
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if adjective:
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expression = self.splitCondition(self.condition_expression)
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expression.remove(adjective)
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return ' '.join(expression)
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else:
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return self.condition_expression
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def findWeatherTokens(self):
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sentence = self.removeAdjective()
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if 'and' in sentence:
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self.nouns = sentence.split(' and ')
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else:
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self.nouns = [sentence]
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def emojify(self, noun):
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return symbol_table[noun]
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def emojifyList(self, noun_list):
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returnList = []
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for noun in noun_list:
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returnList.append(self.emojify(noun))
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return ' '.join(returnList)
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# Trying to analyze the semantics of the condition text
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def emojifyWeatherForecast(self):
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self.findWeatherTokens()
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noun_list = self.nouns
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print(noun_list)
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primary_forcast = noun_list.pop(0)
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primary_severity = severity[primary_forcast][self.severity]
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secondary_forcast = self.emojifyList(noun_list)
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print('%s %s %s' % (self.emojify(primary_forcast), primary_severity, secondary_forcast))
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def convertSematicsToEmoji(self):
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self.severityValue()
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self.emojifyWeatherForecast()
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def main():
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emojiParser = EmojiParser('Light rain')
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emojiParser.convertSematicsToEmoji()
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print(emojiParser)
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if __name__ == '__main__':
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main() |