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Convert All Markdown Files in a Folder to HTML in Python
Batch convert every .md file in a folder to .html using the `markdown` library with the 'extra' extensions.
import os
import markdown
from pathlib import Path
def convert_md_folder_to_html(input_folder="markdown_files", output_folder="html_pages"):
input_path = Path(input_folder)
output_path = Path(output_folder)
output_path.mkdir(exist_ok=True)
for md_file in input_path.glob("*.md"):
with open…How to Compute File SHA256 Hash with hashlib in Python
Compute the SHA256 hash of a file by reading it in chunks with hashlib and Path.open.
import hashlib
from pathlib import Path
def sha256_file(file_path: Path) -> str:
sha256_hash = hashlib.sha256()
with file_path.open("rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
sha256_hash.update(chunk)
return sha256_hash.hexdigest()
if __name__ == "__main__":
demo_fi…Normalize CSV Column Names to snake_case in Python
Convert CSV header names to snake_case using a regular expression and write the updated file in place.
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…Parse Fixed Width Data File by Column Slices in Python
Extract fields from fixed-width text by slicing each line at defined column offsets, with a dictionary describing the boundaries.
from pathlib import Path
def parse_fixed_width(data: str, slices: dict[str, tuple[int, int]]) -> list[dict[str, str]]:
lines = data.strip().splitlines()
records = []
for line in lines:
record = {}
for name, (start, end) in slices.items():
record[name] = line[start:end].strip()…How to Build a Simple argparse CLI in Python
Create a beginner-friendly command-line tool with argparse that reads a file, optionally uppercases its lines, and prints a configurable number of lines.
import argparse
def main():
parser = argparse.ArgumentParser(
description="Automate file processing with a simple CLI tool."
)
parser.add_argument("filename", help="Path to the input file")
parser.add_argument("--uppercase", action="store_true", help="Convert text to uppercase")
parser.add…How to Split PDF Pages into Ranges in Python
Simulates splitting a PDF into page ranges by validating and returning structured range splits for automation workflows.
import os
def split_pdf_ranges(pdf_name, num_pages, ranges):
"""
Simulates splitting a PDF by returning the page ranges that would be split.
Args:
pdf_name (str): Name of the PDF file.
num_pages (int): Total number of pages in the PDF.
ranges (list of tuple): List of (start, end) …How to Watch a Folder and Convert New Images in Python
Watch a folder for new files and mock-convert images by copying and renaming them in an output directory.
import time
import hashlib
from pathlib import Path
from datetime import datetime
def mock_convert_image(source: Path, dest_dir: Path) -> Path:
"""Mock image conversion: copy bytes and add .converted suffix."""
dest = dest_dir / f"{source.stem}.converted{source.suffix}"
dest.write_bytes(source.read_bytes(…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.
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…How to Build Data Processing Functions in Python
Create reusable helper functions to load, filter, transform, and aggregate CSV data in 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…Browse by section
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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.