Files
drc-ners-nlp/core/utils/data_loader.py
T

63 lines
2.1 KiB
Python

import logging
from pathlib import Path
from typing import Optional, Union, Iterator
import pandas as pd
from core.config.pipeline_config import PipelineConfig
class DataLoader:
"""Reusable data loading utilities"""
def __init__(self, config: PipelineConfig):
self.config = config
def load_csv_chunked(
self, filepath: Union[str, Path], chunk_size: Optional[int] = None
) -> Iterator[pd.DataFrame]:
"""Load CSV file in chunks for memory efficiency"""
chunk_size = chunk_size or self.config.processing.chunk_size
encodings = self.config.processing.encoding_options
filepath = Path(filepath)
for encoding in encodings:
try:
logging.info(f"Attempting to read {filepath} with encoding: {encoding}")
chunk_iter = pd.read_csv(
filepath, encoding=encoding, chunksize=chunk_size, on_bad_lines="skip"
)
for i, chunk in enumerate(chunk_iter):
logging.debug(f"Processing chunk {i+1}")
yield chunk
logging.info(f"Successfully read {filepath} with encoding: {encoding}")
return
except Exception as e:
logging.warning(f"Failed with encoding {encoding}: {e}")
continue
raise ValueError(f"Unable to decode {filepath} with any encoding: {encodings}")
def load_csv_complete(self, filepath: Union[str, Path]) -> pd.DataFrame:
"""Load complete CSV file into memory"""
chunks = list(self.load_csv_chunked(filepath))
return pd.concat(chunks, ignore_index=True) if chunks else pd.DataFrame()
@classmethod
def save_csv(
cls, df: pd.DataFrame, filepath: Union[str, Path], create_dirs: bool = True
) -> None:
"""Save DataFrame to CSV with proper handling"""
filepath = Path(filepath)
if create_dirs:
filepath.parent.mkdir(parents=True, exist_ok=True)
df.to_csv(filepath, index=False, encoding="utf-8")
logging.info(f"Saved {len(df)} rows to {filepath}")