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Define DVC pipeline for data ingestion and training
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import os
from box.exceptions import BoxValueError
import yaml
from cnnClassifier import logger
import json
import joblib
from ensure import ensure_annotations
from box import ConfigBox
from pathlib import Path
from typing import Any
@ensure_annotations
def read_yaml(path_to_yaml: Path) -> ConfigBox:
"""reads yaml file and returns
Args:
path_to_yaml (str): path like input
Raises:
ValueError: if yaml file is empty
e: empty file
Returns:
ConfigBox: ConfigBox type
"""
try:
with open(path_to_yaml) as yaml_file:
content = yaml.safe_load(yaml_file)
logger.info(f"yaml file: {path_to_yaml} loaded successfully")
return ConfigBox(content)
except BoxValueError:
raise ValueError("yaml file is empty")
except Exception as e:
raise e
@ensure_annotations
def create_directories(path_to_directories: list, verbose=True):
"""create list of directories
Args:
path_to_directories (list): list of path of directories
ignore_log (bool, optional): ignore if multiple dirs is to be created. Defaults to False.
"""
for path in path_to_directories:
os.makedirs(path, exist_ok=True)
if verbose:
logger.info(f"created directory at: {path}")