New TCGA - COAD dataset for demonstration

fractalis/data/etls/demo_tcga_coad/demo_etl_categorical.py

+import os
+
+import pandas as pd
+
+from fractalis.data.etl import ETL
+
+
+class CategoricalETL(ETL):
+
+    name = 'demo_tca_coad_categorical-etl'
+    produces = 'categorical'
+
+    @staticmethod
+    def can_handle(handler: str, descriptor: dict):
+        return handler == 'demo_tcga_coad' and \
+               descriptor['dataType'] == 'categorical'
+
+    def extract(self, server: str, token: str, descriptor: dict):
+        path = '{}/data/{}.tsv'.format(
+            os.path.dirname(os.path.abspath(__file__)), descriptor['field'])
+        raw_data = pd.read_csv(path, sep='\t')
+        return raw_data
+
+    def transform(self, raw_data: pd.DataFrame, descriptor: dict):
+        df = raw_data
+        df[['id']] = df[['id']].astype(str)
+        df[['value']] = df[['value']].astype(str)
+        df[['feature']] = df[['feature']].astype(str)
+        return df

fractalis/data/etls/demo_tcga_coad/demo_etl_numerical.py

+import os
+
+import pandas as pd
+
+from fractalis.data.etl import ETL
+
+
+class NumericalETL(ETL):
+
+    name = 'demo_tcga_coad_numerical-etl'
+    produces = 'numerical'
+
+    @staticmethod
+    def can_handle(handler: str, descriptor: dict):
+        return handler == 'demo_tcga_coad' and \
+               descriptor['dataType'] == 'numerical'
+
+    def extract(self, server: str, token: str, descriptor: dict):
+        print('I am 100% sure that I am a TCGA ETL and NOT a wine quality ETL.')
+        print(__file__)
+        path = '{}/data/{}.tsv'.format(
+            os.path.dirname(os.path.abspath(__file__)), descriptor['field'])
+        raw_data = pd.read_csv(path, sep='\t')
+        return raw_data
+
+    def transform(self, raw_data: pd.DataFrame, descriptor: dict):
+        df = raw_data
+        df[['id']] = df[['id']].astype(str)
+        df['value'] = pd.to_numeric(df['value'], errors='coerce')
+        df['value'] = df[['value']].astype(float)
+        df[['feature']] = df[['feature']].astype(str)
+        return df

fractalis/data/etls/demo_tcga_coad/demo_etl_numerical_array.py

+import os
+
+import pandas as pd
+
+from fractalis.data.etl import ETL
+
+
+class NumericalETL(ETL):
+
+    name = 'demo_tca_coad_numerical-etl'
+    produces = 'numerical_array'
+
+    @staticmethod
+    def can_handle(handler: str, descriptor: dict):
+        return handler == 'demo_tcga_coad' and \
+               descriptor['dataType'] == 'numerical_array'
+
+    def extract(self, server: str, token: str, descriptor: dict):
+        path = '{}/data/{}.tsv'.format(
+            os.path.dirname(os.path.abspath(__file__)), descriptor['field'])
+        raw_data = pd.read_csv(path, sep='\t')
+        return raw_data
+
+    def transform(self, raw_data: pd.DataFrame, descriptor: dict):
+        df = raw_data
+        df[['id']] = df[['id']].astype(str)
+        df[['value']] = df[['value']].astype(float)
+        df[['feature']] = df[['feature']].astype(str)
+        return df

fractalis/data/etls/demo_tcga_coad/demo_handler.py

+from fractalis.data.etlhandler import ETLHandler
+
+
+class TCGADemoHandler(ETLHandler):
+
+    _handler = 'demo_tcga_coad'
+
+    @staticmethod
+    def make_label(descriptor):
+        return descriptor.get('field')
+
+    def _get_token_for_credentials(self, server: str, auth: dict) -> str:
+        return 'foo'
+
+    def _heartbeat(self):
+        pass

fractalis/data/etls/demo/demo_etl_categorical.py → fractalis/data/etls/demo_wine_quality/demo_etl_categorical.py

-"""Provides CategoricalETL for wine quality demo data set."""
+"""Provides CategoricalETL for wine quality demo_wine_quality data set."""
 
 import os
 
@@ -11,12 +11,13 @@ class CategoricalETL(ETL):
     """CategoricalETL implements support for the
     categorical data of the wine quality data set. """
 
-    name = 'demo-wine-quality-categorical-etl'
+    name = 'demo_wine_quality_categorical-etl'
     produces = 'categorical'
 
     @staticmethod
     def can_handle(handler: str, descriptor: dict):
-        return handler == 'demo' and descriptor['dataType'] == 'categorical'
+        return handler == 'demo_wine_quality' \
+               and descriptor['dataType'] == 'categorical'
 
     def extract(self, server: str, token: str, descriptor: dict):
         path = os.path.dirname(os.path.abspath(__file__)) + '/wine_quality.csv'

fractalis/data/etls/demo/demo_etl_numerical.py → fractalis/data/etls/demo_wine_quality/demo_etl_numerical.py

-"""Provides NumericalETL for wine quality demo data set."""
+"""Provides NumericalETL for wine quality data set."""
 
 import os
 
@@ -11,12 +11,13 @@ class NumericalETL(ETL):
     """NumericalETL implements support for the
     numerical data of the wine quality data set. """
 
-    name = 'demo-wine-quality-numerical-etl'
+    name = 'demo_wine_quality_numerical-etl'
     produces = 'numerical'
 
     @staticmethod
     def can_handle(handler: str, descriptor: dict):
-        return handler == 'demo' and descriptor['dataType'] == 'numerical'
+        return handler == 'demo_wine_quality' and \
+               descriptor['dataType'] == 'numerical'
 
     def extract(self, server: str, token: str, descriptor: dict):
         path = os.path.dirname(os.path.abspath(__file__)) + '/wine_quality.csv'

fractalis/data/etls/demo/demo_handler.py → fractalis/data/etls/demo_wine_quality/demo_handler.py

@@ -3,7 +3,7 @@ from fractalis.data.etlhandler import ETLHandler
 
 class DemoHandler(ETLHandler):
 
-    _handler = 'demo'
+    _handler = 'demo_wine_quality'
 
     @staticmethod
     def make_label(descriptor):