Reference library

Files & data

Read and write files safely; parse JSON, CSV, and common text formats.

3 matches
Files & data easy

Build a File Index by Relative Path Hash Map in Python

Recursively walk a directory and map normalized relative paths to absolute file paths using a defaultdict hash map.

os.walk file-index defaultdict
Python
import os
from collections import defaultdict


def build_file_index(root_dir):
    index = defaultdict(list)

    for dirpath, dirnames, filenames in os.walk(root_dir):
        for filename in filenames:
            full_path = os.path.join(dirpath, filename)
            relative_path = os.path.relpath(full_path, roo…
19 0 Open
Files & data easy

How to Group Files by Extension in Python

Group file names by their file extension using a dictionary and pathlib, producing a simple clear mapping for beginners.

pathlib grouping filesystem
Python
from pathlib import Path


def group_data_by_extension(files: list[Path]) -> dict[str, list[str]]:
    """Group file names by their extension."""
    grouped: dict[str, list[str]] = {}
    for file in files:
        ext = file.suffix.lower()
        grouped.setdefault(ext, []).append(file.name)
    return grouped


if…
14 0 Open
Files & data easy

Read a CSV File with csv.DictReader in Python

Read a CSV file as a list of dictionaries, using csv.DictReader to map each row to column names.

csv csv-dictreader file-reading
Python
import csv
from pathlib import Path

def read_csv_with_dictreader(file_path):
    data = []
    with open(file_path, mode='r', newline='', encoding='utf-8') as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            data.append(row)
    return data

if __name__ == "__main__":
    # Cre…
10 0 Open

Browse by section

Each section groups closely related Python snippets.

Files & data — Python code examples

What you will find here

This page collects files & data 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.