Data pipelines & processing
ETL-style flows, batch transforms, validation, and moving data between formats.
How to Partition Output Files by Date Key in Python
Group output files into a dictionary partitioned by a YYYYMMDD date key extracted from the filename prefix.
from pathlib import Path
from collections import defaultdict
def partition_files_by_date(directory: str) -> dict:
"""Partition output files by date key extracted from filename (YYYYMMDD prefix)."""
path = Path(directory)
partitions = defaultdict(list)
for file in path.iterdir():
if file.i…Map Partition Over Chunks in Python with Multiprocessing and Mock
Process data in chunks across multiple CPU cores using multiprocessing Pool.map, and mock the chunk function to test partitioning behavior without heavy computation.
from multiprocessing import Pool
from unittest.mock import patch, Mock
def process_chunk(chunk):
return [x * x for x in chunk]
def map_partition_over_chunks(data, chunk_size, process_func=process_chunk):
chunks = [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)]
with Pool() as pool:
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Data pipelines & processing — Python code examples
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