Jake Pullen
74 lines
3.6 KiB
Python
74 lines
3.6 KiB
Python
import pandas
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import json
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import os
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import logging
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from datetime import datetime
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from typing import List
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class RawToBase:
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def __init__(self, entities: List[str], raw_data_path: str, base_data_path: str):
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self.entities = entities
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self.raw_data_path = raw_data_path
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self.base_data_path = base_data_path
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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._load_raw_data()
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self._load_existing_base_data()
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self._combine_data()
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self._resolve_duplicates()
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self._save_base_data()
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def _load_raw_data(self):
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for entity in self.entities:
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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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for record in data:
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record['ingestion_date'] = datetime.strptime(file_name.split('.')[0], '%Y%m%d').date()
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self.data[entity].append(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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def _load_existing_base_data(self):
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for entity in self.entities:
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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] = pandas.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] = pandas.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):
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for entity in self.entities:
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logging.debug(f"Combining data for entity: {entity}")
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combined_data = []
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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 = pandas.DataFrame(combined_data)
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self.base_data[entity] = pandas.concat([self.base_data[entity], new_data_df], ignore_index=True)
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logging.debug(f"Successfully combined data for entity: {entity}")
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def _resolve_duplicates(self):
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for entity in self.entities:
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logging.debug(f"Resolving duplicates for entity: {entity}")
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self.base_data[entity] = self.base_data[entity].sort_values('ingestion_date', ascending=False).drop_duplicates('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):
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for entity in self.entities:
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base_path = os.path.join(self.base_data_path, 'base', entity)
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os.makedirs(base_path, exist_ok=True)
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file_path = os.path.join(base_path, f'{entity}.parquet')
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self.base_data[entity].to_parquet(file_path)
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logging.debug(f"Saved base data for entity: {entity} to path: {file_path}") |