modified definitions class though it should be depracated

BaseUtility.py

@@ -1,54 +1,14 @@
+from etl.epc.settings import DATA_ANOMALY_MATCHES as data_anon_matches
+from etl.epc.settings import DATA_ANOMALY_MATCHES as data_anon_matches
+
+
 class Definitions:
     """
     This class contains some base attributes which are used across multiple other classes
     """
 
     # Anomalies described here: https://epc.opendatacommunities.org/docs/guidance#glossary
-    DATA_ANOMALY_MATCHES = {
-        # Invalid reports are where the value provided is out of bounds, e.g. a negative energy rating of -1199 or a
-        # non-integer, there is no valid energy band for this, so it is marked as INVALID!
-        "INVALID",
-        "INVALID!",
-        # When the energy certificate was first lodged on the register there was no requirement to lodge this data
-        # item, i.e. a non-mandatory item.
-        "NO DATA!",
-        "NODATA!",
-        # When the energy certificate was first lodged on the register there was no requirement to lodge this data item,
-        # i.e.a non - mandatory item.
-        "N/A",
-        # A value generated by the register to account for a data item that was not mandatory when the lodgement of
-        # the energy certificate occurred. When the data item became mandatory the register operator, for backwards
-        # compatibility purposes, populated the data field with a value of ‘not recorded’ to ensure that the energy
-        # certificate retrieval process is successfully completed. Mandatory data items cannot be applied
-        # retrospectively to energy certificates lodged before the date of the change.
-        "Not recorded",
-        # The data also contains DECs with an operational rating of ‘9999’ (a ‘default’ DEC). The production of a
-        # ‘default’ DEC value was allowed to enable building occupiers, with poor quality or no energy data,
-        # the opportunity to comply with the regulations. From April 2011 the ability to lodge a ‘default’ DEC was no
-        # longer allowed.
-        "9999",
-        # The Building Emission Rate (BER) data field for non-domestic buildings may contain a ‘blank’ value. The BER
-        # was only lodged on the register from 7 March 2010.
-        "Blank"
-        # There are currently just over 8,600 records where the local authority identifier is ‘null’. This is due to 
-        # the Register Operator not being able to match the building address in the Markermap Ordinance Survey (GB) 
-        # lookup tables or OS MasterMap Address Layer 2 data. The majority of these addresses have been requested 
-        # manually by energy assessors for inclusion by the Register Operator in the registers (e.g. new builds, 
-        # etc). These records are being published for completeness. An ongoing process to manage these manually added 
-        # addresses will take time to develop to deal with these and future anomalies.
-        #
-        # There are several fields within the lodged data where it is possible to enter multiple entries to cater for 
-        # different data_types of build within a single property, i.e. extensions. This results in multiple entries for 
-        # the description fields for floor, roof and wall. For the purposes of this data release only the information 
-        # contained within the first of these multiple entries is being provided. As there are no restrictions on the 
-        # value in this first field it means that sometimes the first field in a multiple entry description field may 
-        # contain a ‘null’ value. A resolution to correct these anomalies will be considered for future data releases.
-        "NULL",
-        # We sometimes see fields populated with just an empty string.
-        "",
-        # An older value which rarely shows up but has been seen in the data.
-        "UNKNOWN",
-    }
+    DATA_ANOMALY_MATCHES = data_anon_matches
 
     DATA_ANOMALY_SUBSTRINGS = {
         # Where values in a ‘pick’ list that have been superseded by another value. For example, where a value for

etl/epc/DataProcessor.py

@@ -1,7 +1,6 @@
 from pathlib import Path
 import numpy as np
 import pandas as pd
-from BaseUtility import Definitions
 from etl.epc.settings import (
     DATA_PROCESSOR_SETTINGS,
     EARLIEST_EPC_DATE,
@@ -22,6 +21,7 @@ from etl.epc.settings import (
     ENDING_SUFFIX_COMPONENT_COLS,
     POTENTIAL_COLUMNS,
     EFFICIENCY_FEATURES,
+    DATA_ANOMALY_MATCHES
 )
 from recommendations.rdsap_tables import FLOOR_LEVEL_MAP
 
@@ -247,8 +247,7 @@ class EPCDataProcessor:
         # Map all anomaly values to None
         data_anomaly_map = dict(
             zip(
-                Definitions.DATA_ANOMALY_MATCHES,
-                [None] * len(Definitions.DATA_ANOMALY_MATCHES),
+                DATA_ANOMALY_MATCHES, [None] * len(DATA_ANOMALY_MATCHES),
             )
         )
 
@@ -283,7 +282,7 @@ class EPCDataProcessor:
     @staticmethod
     def clean_construction_age_band(x):
         # Firstly, we check if it's an error value
-        if x in Definitions.DATA_ANOMALY_MATCHES or x in [None, np.nan]:
+        if x in DATA_ANOMALY_MATCHES or x in [None, np.nan]:
             return x
 
         # Next, we check if it's a value in our map

etl/epc_clean/epc_attributes/MainheatControlAttributes.py

@@ -128,6 +128,7 @@ class MainheatControlAttributes(Definitions):
     ]
 
     def __init__(self, description: str):
+
         self.description: str = clean_description(description.lower()).strip()
         self.nodata = not self.description or description in self.DATA_ANOMALY_MATCHES or (
             description in self.NO_DATA_DESCRIPTIONS