Reference library

Files & data

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

4 matches
Files & data medium

Calculate Working Hours Between Two Dates in Python

Compute total business hours (Mon-Fri, 09:00-17:00) between two datetime objects, excluding weekends and non-working hours.

datetime working hours business hours
Python
from datetime import datetime, timedelta

def work_hours_between(start: datetime, end: datetime) -> float:
    """Calculate total working hours between two datetimes (Mon-Fri, 09:00-17:00)."""
    def is_workday(d: datetime) -> bool:
        return d.weekday() < 5
    
    total_hours = 0.0
    current = start
    whi…
49 0 Open
Files & data medium

Find Duplicate Web Pages by Content Similarity in Python

Compute SHA-256 hashes of file contents to detect and report duplicate HTML pages or any files in a directory.

duplicate-detection hashing sha256
Python
import hashlib
import os
from collections import defaultdict

def get_file_hash(filepath):
    """Compute SHA-256 hash of file contents."""
    sha256 = hashlib.sha256()
    with open(filepath, 'rb') as f:
        for chunk in iter(lambda: f.read(4096), b''):
            sha256.update(chunk)
    return sha256.hexdiges…
46 0 Open
Files & data medium

How to Merge Sorted Chunk Files in Python

Merge multiple sorted text files into one sorted output file using a heap for efficient k-way merging.

heapq merge-sort external-sort
Python
import heapq


def merge_sorted_chunks(chunks, output_path):
    """Merge multiple sorted iterables into single sorted output file."""
    with open(output_path, "w") as out_f:
        # Open all chunk files
        handles = [open(chunk, "r") for chunk in chunks]
        try:
            # Heap of (value, index) tupl…
14 0 Open
Files & data medium

Join two CSV files on shared key column in Python

Merge rows from two CSV files by a common key column, outputting combined records to a new file.

csv join dictreader
Python
import csv

def join_csv(file1, file2, key, output="joined.csv"):
    # Read first CSV into dict keyed by the join column
    with open(file1, newline="") as f1:
        reader1 = csv.DictReader(f1)
        data1 = {row[key]: row for row in reader1}

    # Read second CSV and merge matching rows
    with open(file2, n…
15 0 Open

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