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Data pipelines & processing

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

3 matches

Build a Python Utility That Detects Duplicate Records Across Multiple Excel Sheets

A Python utility that uses pandas to find overlapping records across different Excel sheets based on specified key columns.

pandas excel data cleaning

Python

import pandas as pd
from pathlib import Path

def find_duplicate_records_across_sheets(file_path: str, key_columns: list, sheet_names: list) -> dict:
    """
    Detect duplicate records across multiple Excel sheets based on specified key columns.
    
    Args:
        file_path: Path to the Excel file
        key_co…

47 0 Open

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 medium

How to Validate Fact Table Grain Row Counts in Python

Validate fact table grain by checking dimension key references, unique grain combinations, duplicate rows, and dimension cardinality from a CSV file.

csv data validation etl

Python

import csv
import hashlib
from pathlib import Path


def validate_fact_grain(fact_file: Path, expected_dim_keys: dict[str, set[str]]) -> dict:
    """
    Validate fact table grain by checking each row's dimension keys exist
    in expected dimension tables and row count consistency.
    """
    dim_references = {}
  …

13 0 Open

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