added transformation class that contains each step transformations

Author: stantaneous

models.py

@@ -21,5 +21,6 @@ def __init__(self, table, type='user_table'):
 									 'B': ['B0', 'B1', 'B2'],
 									 'id': ['K0', 'K1', 'K3']
 									 }))
+
 }
 

transformation_functions.py

@@ -1,5 +1,5 @@
 import pandas as pd
-from models import loaded_table_dict as table_dict
+from models import loaded_table_dict as table_dict, TableObj
 import nlp_helpers
 from models import join_types
 
@@ -25,7 +25,7 @@ def join(table_a, table_b):
 
 
 	joined_table = pd.merge(table_a.table, table_b.table, how=TypeofJoin, left_on=matched_keys_left, right_on=matched_keys_right)
-	return joined_table
+	return TableObj(joined_table, 'tx_table')
 
 
 def union(table_a, table_b):

transformations.py

@@ -3,17 +3,36 @@
 from transformation_functions import transformations_dict
 
 
-
-
 # Class to contain a step and the transformation associated with that step
 class TransformData:
 	def __init__(self, query):
 		language_token = helpers.ProcessLanguageTokens(query=query)
-		table_list = models.loaded_table_dict.keys()
-		transformation_list = transformations_dict.keys()
+		table_list = list(models.loaded_table_dict.keys())
+		transformation_list = list(transformations_dict.keys())
 		self.matched_table = language_token.get_matches(table_list, threshold=94)
 		self.matched_transformation = language_token.get_matches(transformation_list, threshold=90)[0]
 		tx_fn = transformations_dict.get(self.matched_transformation)
 		if not tx_fn:
 			raise NotImplemented('This Transformation is not implemented yet!')
-		self.transformation_function = tx_fn
+		self.transformation_function = tx_fn
+
+	def load_table(self, table_name):
+		table_a = models.loaded_table_dict.get(self.matched_table[0])
+		table_b = models.loaded_table_dict.get(self.matched_table[1])
+		if not table_a or not table_b:
+			raise ValueError('Could Not Find Tables in loaded table list')
+		models.loaded_table_dict[table_name] = self.transformation_function(table_a, table_b)
+
+
+# ----------------------- DEBUGGING -----------------------------------------
+
+if __name__ == '__main__':
+	i = 0
+	query = ""
+	list_of_transformations = []
+	while query != 'end!':
+		i += 1
+		query = input('Enter Query. end! to stop\n-->')
+		transformation = TransformData(query)
+		transformation.load_table('step' + str(i))
+		list_of_transformations.append(transformation)