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import csv
import io
from typing import List, Dict
from obfuscator.logger import get_logger
# Create the logger
logger = get_logger("CSVReader")
# Putting the CSV reading components into a class may seem like overkill
# for a simple script, but it allows for better organization and scalability.
# @staticmethod is used to define the method without an instance of the class
# being required. The methods could be defined just as functions, and this
# may still be changed.
class CSVReader:
"""
A class to read CSV data from a local file, S3 object, or string. Near
the project completion, support for JSON/Parquet files will be added.
"""
@staticmethod
def read_local(path) -> List[Dict[str, str]]:
"""
A method to read a local CSV file and return the data as a list of
dictionaries.
"""
# Log the path of the file being read for debugging
logger.debug(f"Reading local CSV from: {path}")
# Attempt to read the file and return the data as a list of dictionaries
# However, if the file isn't found or there is a generic exception, log
# the error and raise an exception
try:
with open(path, mode="r", encoding="utf-8") as f:
reader = csv.DictReader(f)
return [dict(row) for row in reader]
except FileNotFoundError:
logger.error(f"File not found: {path}")
raise
except Exception as e:
logger.error(f"Error reading file: {e}")
@staticmethod
def read_s3(path) -> List[Dict[str, str]]:
"""
A method to read an S3 object containing CSV data
and return the data as a list of dictionaries.
"""
# Yet to be implemented.
return []
@staticmethod
def read_string(content: str) -> List[Dict[str, str]]:
"""
A method to read CSV data from a string and return the data as a list
of dictionaries.
"""
# If the content is empty, return an empty list
if not content.strip():
return []
# Treat the string as a file-like object and return as list of dictionaries
f = io.StringIO(content)
reader = csv.DictReader(f)
return [dict(row) for row in reader]
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