Jake Pullen
106 lines
4.8 KiB
Python
106 lines
4.8 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': 'accounts_id'},
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'categories': {'unique_id': 'categories_id'},
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'months': {'unique_id': 'months_month'},
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'payees': {'unique_id': 'payees_id'},
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'transactions': {'unique_id': 'transactions_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.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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self._load_raw_data(entity)
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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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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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modified_data = []
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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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def _load_existing_base_data(self, entity):
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base_path = os.path.join(self.base_data_path, 'base', entity, 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 group in data:
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if 'category_groups' in group:
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for category_group in group['category_groups']:
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for category in category_group['categories']:
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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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# 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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