Files & data

import openpyxl
from openpyxl.chart import BarChart, Reference
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from openpyxl.utils import get_column_letter

def create_sales_dashboard(workbook_path: str) -> None:
    """Generate a professional sales dashboard in an Excel workbook."""
    wb = op…

import csv

def export_to_csv(data, filename):
    """Export a list of dicts to a CSV file."""
    if not data:
        print("No data to export")
        return
    
    # Get column names from the keys of the first dict
    fieldnames = list(data[0].keys())
    
    with open(filename, 'w', newline='', encoding='utf…

import sqlite3
import csv

def export_query_to_csv(db_path, query, csv_path):
    conn = sqlite3.connect(db_path)
    cursor = conn.cursor()
    cursor.execute(query)

    rows = cursor.fetchall()
    column_names = [description[0] for description in cursor.description]

    with open(csv_path, 'w', newline='', encodi…

from calendar import TextCalendar
from datetime import datetime
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
import os

def generate_monthly_calendar_pdf(year, month, filename="calendar.pdf"):
    cal = TextCalendar()
    days = cal.monthdays2calendar(year, month)
    
    month_name …

import csv
from pathlib import Path
from typing import Any

def read_csv_with_types(filepath: str) -> list[dict[str, Any]]:
    """Read CSV and convert column types based on header suffixes."""
    converters = {
        "int": int,
        "float": float,
        "str": str,
        "bool": lambda v: v.strip().lower(…

import pathlib

def inspect_binary_header(filepath: str, num_bytes: int = 16) -> None:
    """Read the first bytes of a binary file and display them as hex and ASCII."""
    path = pathlib.Path(filepath)
    data = path.read_bytes()[:num_bytes]
    
    hex_str = ' '.join(f"{byte:02x}" for byte in data)
    ascii_str …

import requests
from bs4 import BeautifulSoup

def scrape_headlines(url: str, selector: str) -> list:
    """
    Scrape headlines from a news website using Beautiful Soup.
    
    Args:
        url: The URL of the news website.
        selector: CSS selector for headline elements.
    
    Returns:
        List of h…

import csv
import re
import sys


def to_snake_case(header):
    header = re.sub(r"(?<=[a-z0-9])(?=[A-Z])", "_", header)
    header = re.sub(r"[^a-zA-Z0-9]+", "_", header).strip("_").lower()
    return header


def normalize_csv_headers(input_path, output_path=None):
    with open(input_path, newline="", encoding="utf…

import csv
import os

def split_csv(input_file, chunk_size=1000, output_prefix="chunk"):
    """Split a large CSV file into smaller chunks."""
    with open(input_file, 'r', newline='') as infile:
        reader = csv.reader(infile)
        header = next(reader)
        
        file_count = 1
        row_count = 0
  …

import csv
from pathlib import Path

fieldnames = ["name", "city", "age"]
rows = [
    {"name": "Alice", "city": "New York", "age": 30},
    {"name": "Bob", "city": "Los Angeles", "age": 25},
    {"name": "Charlie", "city": "Chicago", "age": 35},
]

path = Path("people.csv")
with path.open("w", newline="") as csvfile:…