Reference library

Data pipelines & processing

ETL-style flows, batch transforms, validation, and moving data between formats.

5 matches
Data pipelines & processing medium

Deduplicate events by ID within a window in Python

Deduplicate event streams by ID within sliding time windows, keeping the newest occurrence per window using heaps and sets.

deduplication events heapq
Python
import heapq
from collections import defaultdict

def deduplicate_events(events, window_size):
    """Return events deduplicated by id, keeping newest within each sliding window."""
    # Index events by (timestamp, id) for deterministic ordering
    events_by_id = defaultdict(list)
    for ts, eid, *payload in events…
14 0 Open
Data pipelines & processing easy

Fan Out Records to Multiple Sinks in Python

Distribute the same records across multiple target sinks (database, API, queue, etc.) using a defaultdict-based fan-out pattern.

fan-out defaultdict records
Python
import json
from collections import defaultdict

SINKS = ["database", "api", "message_queue", "data_lake", "monitoring"]

def fan_out(records, *sinks):
    dist = defaultdict(list)
    for record in records:
        for sink in sinks:
            dist[sink].append(record)
    return dict(dist)

if __name__ == "__main_…
12 0 Open
Data pipelines & processing easy

How to Group Data by Key in Python

Group a list of dictionaries by a specified key using a defaultdict and compute per-group averages.

grouping defaultdict data-pipelines
Python
from collections import defaultdict

def group_by_key(data, key):
    grouped = defaultdict(list)
    for item in data:
        grouped[item[key]].append(item)
    return dict(grouped)

if __name__ == "__main__":
    records = [
        {"name": "Alice", "dept": "Engineering", "score": 85},
        {"name": "Bob", "de…
15 0 Open
Data pipelines & processing easy

How to Group Rows by Key into Nested Arrays in Python

This code groups rows in a list of dictionaries by a specified key and returns a dictionary with each key mapped to a list of values from another key.

grouping defaultdict data-aggregation
Python
from collections import defaultdict


def implode_rows(rows, key, value_key):
    grouped = defaultdict(list)
    for row in rows:
        grouped[row[key]].append(row[value_key])
    return dict(grouped)


if __name__ == "__main__":
    data = [
        {"category": "fruit", "item": "apple"},
        {"category": "fr…
14 0 Open
Data pipelines & processing easy

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.

file-partitioning date-key pathlib
Python
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…
14 0 Open

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Data pipelines & processing — Python code examples

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