Jake Pullen
150 lines
7.1 KiB
Python
150 lines
7.1 KiB
Python
import os
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import json
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import logging
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from datetime import datetime
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from typing import List, Dict, Any
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import polars as pl
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class RawToBase:
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def __init__(self, entities: List[str]):
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self.entities = entities
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self.config = {
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'accounts': {'unique_id': 'id'},
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'categories': {'unique_id': 'id'},
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'months': {'unique_id': 'month'},
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'payees': {'unique_id': 'id'},
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'transactions': {'unique_id': 'id'},
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'scheduled_transactions': {'unique_id': 'id'}
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}
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self.raw_data_path = 'data/raw'
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self.base_data_path = 'data/base'
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self.processed_data_path = 'data/processed'
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self.data = {}
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self.base_data = {}
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logging.basicConfig(level=logging.DEBUG)
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self.process_entities()
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def process_entities(self):
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for entity in self.entities:
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# check the file is in the raw data path, if not skip the entity
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folder_path = os.path.join(self.raw_data_path, entity)
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folder_contents = os.listdir(folder_path)
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# Check if the folder is empty
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if not folder_contents:
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logging.warning(f"The folder {folder_path} is empty skipping {entity}.")
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continue
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if not self._load_raw_data(entity):
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logging.warning(f"Skipping processing for entity: {entity} due to empty data.")
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continue
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self._load_existing_base_data(entity)
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self._combine_data(entity)
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self._resolve_duplicates(entity)
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self._save_base_data(entity)
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self._move_raw_to_processed(entity)
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def _load_raw_data(self, entity):
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entity_path = os.path.join(self.raw_data_path, entity)
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self.data[entity] = []
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logging.debug(f"Loading data for entity: {entity} from path: {entity_path}")
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for file_name in os.listdir(entity_path):
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if file_name.endswith('.json'):
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file_path = os.path.join(entity_path, file_name)
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logging.debug(f"Reading file: {file_path}")
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try:
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with open(file_path, 'r') as f:
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data = json.load(f)
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# Check if the data is empty
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if not data.get(entity, []):
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logging.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
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# delete the file as it is empty
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os.remove(file_path)
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return False
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modified_data = []
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if entity == 'categories':
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for group in data.get('category_groups', []):
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for category in group.get('categories', []):
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category['ingestion_date'] = datetime.strptime(file_name.split('.')[0], '%Y%m%d%H%M%S').date()
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modified_data.append(category)
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else:
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for record in data.get(f'{entity}', []):
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if isinstance(record, dict):
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record['ingestion_date'] = datetime.strptime(file_name.split('.')[0], '%Y%m%d%H%M%S').date()
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modified_data.append(record)
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else:
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modified_data.append({'record': record, 'ingestion_date': datetime.strptime(file_name.split('.')[0], '%Y%m%d%H%M%S').date()})
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self.data[entity].append(modified_data)
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logging.debug(f"Successfully loaded data from file: {file_path}")
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except Exception as e:
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logging.error(f"Failed to load data from file: {file_path}, error: {e}")
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exit(1)
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return True
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def _load_existing_base_data(self, entity):
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base_path = os.path.join(self.base_data_path, f'{entity}.parquet')
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if os.path.exists(base_path):
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logging.debug(f"Loading existing base data for entity: {entity} from path: {base_path}")
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self.base_data[entity] = pl.read_parquet(base_path)
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logging.debug(f"Successfully loaded existing base data for entity: {entity}")
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else:
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self.base_data[entity] = pl.DataFrame()
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logging.debug(f"No existing base data found for entity: {entity}, starting with an empty DataFrame")
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def _combine_data(self, entity):
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logging.debug(f"Combining data for entity: {entity}")
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combined_data = []
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if entity == 'categories':
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for data in self.data[entity]:
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for category in data:
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combined_data.append(category)
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else:
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for data in self.data[entity]:
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combined_data.extend(data)
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new_data_df = pl.DataFrame(combined_data)
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#print(new_data_df)
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# Ensure the unique id column is preserved
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unique_id = self.config[entity]['unique_id']
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if unique_id not in new_data_df.columns:
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logging.error(f"Unique ID column '{unique_id}' not found in the combined data for entity: {entity}")
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exit(1)
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self.base_data[entity] = new_data_df
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logging.debug(f"Successfully combined data for entity: {entity}")
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def _resolve_duplicates(self, entity):
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logging.debug(f"Resolving duplicates for entity: {entity}")
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unique_id = self.config[entity]['unique_id']
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self.base_data[entity] = self.base_data[entity].sort(by='ingestion_date').unique(subset=unique_id, keep='first')
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logging.debug(f"Successfully resolved duplicates for entity: {entity}")
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def _save_base_data(self, entity):
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os.makedirs(self.base_data_path, exist_ok=True)
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file_path = os.path.join(self.base_data_path, f'{entity}.parquet')
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self.base_data[entity].write_parquet(file_path)
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logging.debug(f"Saved base data for entity: {entity} to path: {file_path}")
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def _move_raw_to_processed(self, entity):
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raw_entity_path = os.path.join(self.raw_data_path, entity)
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processed_path = os.path.join(self.processed_data_path, entity)
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# logging.debug(f"Raw entity path: {raw_entity_path}")
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# logging.debug(f"Processed path: {processed_path}")
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os.makedirs(processed_path, exist_ok=True)
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for file_name in os.listdir(raw_entity_path):
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if file_name.endswith('.json'):
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raw_file_path = os.path.join(raw_entity_path, file_name)
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processed_file_path = os.path.join(processed_path, file_name)
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logging.debug(f"Moving file: {raw_file_path} to {processed_file_path}")
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if os.path.exists(raw_file_path):
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os.rename(raw_file_path, processed_file_path)
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logging.debug(f"Moved file: {file_name}")
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else:
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logging.error(f"File not found: {raw_file_path}")
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logging.debug(f"Moved processed files for entity: {entity} to path: {processed_path}") |