Moved all runnning scripts to single folder

termWeather/emojiParser.py

@@ -0,0 +1,154 @@
+#!/usr/bin/env python3.6
+# -*- coding: utf-8 -*-
+# @Author: KevinMidboe
+# @Date:   2017-07-29 11:56:24
+# @Last Modified by:   KevinMidboe
+# @Last Modified time: 2017-07-30 13:17:19
+
+from fuzzywuzzy import process
+
+# Find the first word, if it is a noun or a adjective. ✔️
+# Remove the adjective and split if there is a AND ✔️
+# Then match the first noun to list and add that emoji ✔️
+# and then match the second to list and add that emoji ✔️
+# REGEX this bitch up 
+
+symbol_table = {
+	'clear sky': '☀️',
+	'fair': '🌤',
+	'partly cloudy': '⛅️',
+	'cloudy': ' ☁️ ',
+	'thunder': '⚡️',
+	
+	'rain showers': '🌦',
+	'rain': '🌧',
+	'sleet showers': '🌦 💦',
+	'sleet': '🌨 💦',
+	'snow showers': '⛅ ❄️',
+	'snow': '🌨',
+
+	'rain': '🌧',
+	'sleet': '🌧',
+	'snow': '🌨',
+
+	'showers': '🌤'
+	}
+
+severity = {
+		'rain': ['', ' ☂️', ' ☔️'],
+		'sleet': [' 💦 ', ' 💧 ', ' 💧 💦 '],
+		'snow': [' ❄️ ', ' ❄️ ❄️ ', ' ❄️ ❄️ ❄️ ']
+		}
+
+class EmojiParser(object):
+	def __init__(self, condition_text):
+		self.condition_expression = condition_text.lower()
+		self.severity = None
+		self.nouns = []
+
+		self.weather_nouns = ['cleary sky', 'fair', 'cloudy', 'rain', 'rain showers', 'sleet',
+			'sleet showers', 'snow showers', 'thunder', 'snow']
+		self.weather_adjectives = {'light': 0, 'normal': 1, 'heavy': 2}
+
+	def __str__(self):
+	 	return str([self.condition_expression, self.severity, self.nouns])
+
+	# Splits and lowers the condition text for easier parsing
+	def splitCondition(self, condition):
+		return condition.split()
+
+	# Takes a input or uses condition_expression to find adjective in sentence
+	def findAdjective(self, sentence=None):
+		if sentence is None:
+			sentence = self.condition_expression
+
+		# Splits and iterates over each word in sentence
+		expression = self.splitCondition(sentence)
+		for word in expression:
+			if word in self.weather_adjectives:
+				# Return the word if matched with weather_adjectives
+				return word
+
+		return None
+
+	# Removes the first adjective in the a given sentence
+	def removeAdjective(self):
+		adjective = self.findAdjective()
+		if adjective:	# Adjective is not None
+			expression = self.splitCondition(self.condition_expression)
+			expression.remove(adjective)
+			return ' '.join(expression)
+		else:
+			return self.condition_expression
+
+
+	def severityValue(self):
+		adjective = self.findAdjective()
+
+		if adjective:
+			self.severity = self.weather_adjectives[adjective]
+		else:
+			self.severity = self.weather_adjectives['normal']
+
+	def findWeatherTokens(self):
+		# If present removes the leading adjective
+		sentence = self.removeAdjective()
+		
+		# If multiple tokens/weather_nouns split all between the 'and'
+		if 'and' in sentence:
+			self.nouns = sentence.split(' and ')
+		else:
+			self.nouns = [sentence]
+
+
+	# Use the symbol_table to convert the forecast name to emoji
+	def emojify(self, noun):
+		return symbol_table[noun]
+
+	# Does as emojify above, but iterates over a list if multiple elements
+	def emojifyList(self, noun_list):
+		returnList = []
+		
+		# TODO use more like a map function?
+		for noun in noun_list:
+			returnList.append(self.emojify(noun))
+
+		return '  '.join(returnList)
+
+	def findPrimaryForecast(self):
+		# Copies the contents not the refrence to the list
+		noun_list = list(self.nouns)
+		forecast = noun_list.pop(0)
+
+		# Translates to emoji once here instead of twice below
+		forecast_emoji = self.emojify(forecast)
+
+		if forecast in severity:
+			return ('%s %s' % (forecast_emoji, severity[forecast]))
+		else:
+			return forecast_emoji
+
+
+	# Trying to analyze the semantics of the condition text
+	def emojifyWeatherForecast(self):
+		# Finds the tokens/nouns of weather for the given input text and severity value
+		self.findWeatherTokens()
+		self.severityValue()
+
+		primary_forecast = self.findPrimaryForecast()
+		secondary_forecast = self.emojifyList(self.nouns[1:])
+		
+		return ('%s %s' % (primary_forecast, secondary_forecast))
+
+
+	def convertSematicsToEmoji(self):
+		return self.emojifyWeatherForecast()
+
+
+def main():
+	emojiParser = EmojiParser('Cloudy')
+	print(emojiParser.convertSematicsToEmoji())
+
+
+if __name__ == '__main__':
+	main()