Finished up primary focus of emojiParser. Now it can handle all weather inputs and parses the semantically similar emoji for the given weather condition.

emojiParser.py

@@ -3,21 +3,21 @@
 # @Author: KevinMidboe
 # @Date:   2017-07-29 11:56:24
 # @Last Modified by:   KevinMidboe
-# @Last Modified time: 2017-07-29 18:36:55
+# @Last Modified time: 2017-07-30 10:31:52
 
 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
+# 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': '☁️',
+	'cloudy': ' ☁️ ',
 	'thunder': '⚡️',
 	
 	'rain showers': '🌦',
@@ -35,14 +35,14 @@ symbol_table = {
 	}
 
 severity = {
-		'rain': ['💧', ' ☂️', ' ☔️'],
+		'rain': ['', ' ☂️', ' ☔️'],
 		'sleet': [' 💦 ', ' 💧 ', ' 💧 💦 '],
 		'snow': [' ❄️ ', ' ❄️ ❄️ ', ' ❄️ ❄️ ❄️ ']
 		}
 
 class EmojiParser(object):
 	def __init__(self, condition_text):
-		self.condition_expression = condition_text
+		self.condition_expression = condition_text.lower()
 		self.severity = None
 		self.nouns = []
 
@@ -55,20 +55,33 @@ class EmojiParser(object):
 
 	# Splits and lowers the condition text for easier parsing
 	def splitCondition(self, condition):
-		condition = condition.lower()
 		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()
 
@@ -77,61 +90,64 @@ class EmojiParser(object):
 		else:
 			self.severity = self.weather_adjectives['normal']
 
-
-	def removeAdjective(self):
-		adjective = self.findAdjective()
-		if adjective:
-			expression = self.splitCondition(self.condition_expression)
-			expression.remove(adjective)
-			return ' '.join(expression)
-		else:
-			return self.condition_expression
-
 	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 forcast 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 findPrimaryForcast(self):
+		# Copies the contents not the refrence to the list
+		noun_list = list(self.nouns)
+		forcast = noun_list.pop(0)
+
+		# Translates to emoji once here instead of twice below
+		forcast_emoji = self.emojify(forcast)
+
+		if forcast in severity:
+			return ('%s %s' % (forcast_emoji, severity[forcast]))
+		else:
+			return forcast_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()
-		
-		noun_list = self.nouns
+		self.severityValue()
 
-		primary_forcast = noun_list.pop(0)
-		primary_severity = severity[primary_forcast][self.severity]
-		secondary_forcast = self.emojifyList(noun_list)
+		primary_forcast = self.findPrimaryForcast()
+		secondary_forcast = self.emojifyList(self.nouns[1:])
 		
-		return ('%s %s  %s' % (self.emojify(primary_forcast), primary_severity, secondary_forcast))
+		return ('%s %s' % (primary_forcast, secondary_forcast))
 
 
 	def convertSematicsToEmoji(self):
-		self.severityValue()
-		emojiForcast = self.emojifyWeatherForecast()
-		return emojiForcast
+		return self.emojifyWeatherForecast()
 
 
 def main():
-	emojiParser = EmojiParser('Light rain')
-	emojiParser.convertSematicsToEmoji()
-	print(emojiParser)
+	emojiParser = EmojiParser('Cloudy')
+	print(emojiParser.convertSematicsToEmoji())
 
 
 if __name__ == '__main__':