Data pipelines & processing
ETL-style flows, batch transforms, validation, and moving data between formats.
How to Compress Pipeline Output Gzip Per Partition in Python
Compress each partition of pipeline output into a separate gzip file and verify the compressed data by reading it back.
import gzip
import io
import random
from pathlib import Path
def compress_partition(partition_data: list[str], output_path: Path) -> int:
"""Compress a partition of data to a gzip file, returns bytes written."""
with gzip.open(output_path, 'wt', encoding='utf-8') as f:
f.writelines(partition_data)
…
How to Convert Data Types in a Python Data Pipeline
Demonstrates a simple Python data pipeline that converts string values to proper types (bool, int, float, datetime) and outputs structured JSON.
import json
from datetime import datetime
def convert_value(value):
"""Convert string values to appropriate Python types."""
if value.lower() == "true":
return True
if value.lower() == "false":
return False
if value.isdigit():
return int(value)
try:
return float(val…
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…
How to route late-arriving data to a side output in Python
Separate late-arriving events from a streaming data batch into a dead-letter side output list using a timestamp threshold.
from collections import defaultdict
def late_arriving_side_output(events, late_threshold_ts):
"""
Mock a streaming pipeline that separates late-arriving data events
into a side output list (e.g., for dead-letter analysis).
events: list of (timestamp, data) tuples, timestamps as ints.
late_thresho…
How to shard output by primary key hash mod N in Python
This code computes a consistent shard index for any primary key string using an MD5 hash mod the number of shards, enabling stable key-based data distribution.
import hashlib
def shard_id(primary_key: str, num_shards: int) -> int:
"""Return the shard index for a primary key using MD5 hash mod N."""
digest = hashlib.md5(primary_key.encode("utf-8")).hexdigest()
hash_int = int(digest, 16)
return hash_int % num_shards
if __name__ == "__main__":
keys = ["use…
Pipeline stage compose functions left to right in Python
Compose multiple functions into a left-to-right pipeline so each stage receives the output of the previous one.
def compose(*funcs):
"""Compose functions left to right: compose(f, g, h)(x) == h(g(f(x)))"""
def composed(arg):
result = arg
for func in funcs:
result = func(result)
return result
return composed
if __name__ == "__main__":
def add_one(x):
return x + 1
…
Browse by section
Each section groups closely related Python snippets.
Data pipelines & processing — Python code examples
What you will find here
This page collects data pipelines & processing snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.