mirror of
https://github.com/KevinMidboe/termForecast.git
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43 lines
1.2 KiB
Python
Executable File
43 lines
1.2 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 12:34:58
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from fuzzywuzzy import process
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weather_nouns = ['cleary sky', 'fair', 'cloudy', 'rain showers', 'rain', 'sleet',
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'sleet showers', 'snow showers', 'thunder', 'sleet', 'snow']
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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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# Splits and lowers the condition text for easier parsing
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def splitCondition(condition):
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condition = condition.lower()
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return condition.split()
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# Trying to analyze the semantics of the condition text
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def findConditionContext(condition_text):
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condition_expression = splitCondition(condition_text)
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# Iterate over each word and find what matches 100%
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for expression_value in condition_expression:
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noun_matches = process.extract(expression_value, weather_nouns)
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print(expression_value + ': ' + str(noun_matches))
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def emojiParser(condition_text):
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findConditionContext(condition_text)
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def main():
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emojiParser('Rain showers')
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if __name__ == '__main__':
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main() |