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Data pipelines & processing

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

6 matches

Add a UUID Surrogate Key to Each Row in a CSV with Python

Generate a unique UUID string for every row in a CSV file using the standard-library uuid and csv modules.

import uuid
import csv

def add_surrogate_key(filename):
    with open(filename, newline='') as f_in:
        reader = csv.DictReader(f_in)
        rows = list(reader)

    for row in rows:
        row['surrogate_key'] = str(uuid.uuid4())

    with open(filename, 'w', newline='') as f_out:
        writer = csv.DictWri…

14 0 Open

Data pipelines & processing easy

ETL in Python: Extract CSV, Transform Dict, Load JSON

Build a simple ETL pipeline in Python that reads a CSV file, transforms each row (stripping whitespace and converting numeric fields), and writes the result to JSON.

etl csv json

Python

import csv
import json
from pathlib import Path

def extract_csv(file_path):
    """Read CSV file and return list of row dictionaries."""
    with Path(file_path).open('r', newline='', encoding='utf-8') as f:
        reader = csv.DictReader(f)
        return list(reader)

def transform_dicts(rows):
    """Transform ro…

13 0 Open

Data pipelines & processing easy

ETL in Python: Extract CSV, Transform Dicts, Load JSON

Build a simple ETL pipeline that reads a CSV, normalizes keys and converts price to float, then writes structured JSON.

etl csv json

Python

import csv
import json
from pathlib import Path

def etl_csv_to_json(csv_path: str, json_path: str) -> None:
    """Extract CSV, transform rows to dicts, load to JSON."""
    with open(csv_path, mode='r', newline='', encoding='utf-8') as f:
        reader = csv.DictReader(f)
        records = list(reader)

    # Trans…

12 0 Open

Data pipelines & processing easy

How to Build Data Processing Functions in Python

Create reusable helper functions to load, filter, transform, and aggregate CSV data in Python.

csv pipeline etl

Python

import csv
from pathlib import Path


def load_data(filepath):
    """Load CSV data into a list of dicts."""
    with open(filepath, "r", newline="", encoding="utf-8") as f:
        return list(csv.DictReader(f))


def filter_rows(rows, column, value):
    """Keep rows where column equals value."""
    return [row for…

11 0 Open

Data pipelines & processing easy

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.

data-pipeline type-conversion json

Python

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…

11 0 Open

Data pipelines & processing easy

How to Process CSV Data in Python with a Data Helper

Build a beginner-friendly data helper in Python that loads a CSV file, filters rows by a condition, and summarizes numeric fields.

csv data-processing pathlib

Python

import csv
from pathlib import Path

DATA = [
    {"name": "Alice", "score": 88, "passed": True},
    {"name": "Bob", "score": 42, "passed": False},
    {"name": "Carol", "score": 95, "passed": True},
]


def load_csv(file_path: Path) -> list[dict]:
    with file_path.open(newline="", encoding="utf-8") as f:
        r…

13 0 Open

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