Files & data
Read and write files safely; parse JSON, CSV, and common text formats.
Create a ZIP Archive of a Folder in Python
Recursively zip all files in a folder into a single archive using the standard library zipfile and pathlib modules.
import zipfile
from pathlib import Path
def zip_folder(source_dir: str, archive_path: str) -> None:
"""Zip all files in source_dir recursively into archive_path."""
source = Path(source_dir)
with zipfile.ZipFile(archive_path, "w", zipfile.ZIP_DEFLATED) as archive:
for file_path in source.rglob("*"…Download Files from Internet with Progress Bar in Python
Download a file from the internet while displaying a text progress bar in the terminal.
import urllib.request
import sys
def download_with_progress(url, filename):
"""Download a file with a simple text progress bar."""
def report_hook(block_count, block_size, total_size):
downloaded = block_count * block_size
if total_size > 0:
percent = min(100, int(downloaded * 100 …How to Automatically Extract Every Archive in a Folder with Python
Walk through a folder and extract all ZIP, RAR, and 7Z archives into separate subdirectories using Python.
import zipfile
import rarfile
import py7zr
import pathlib
def extract_archives(folder: str):
"""Extract every ZIP, RAR, and 7Z archive in the given folder."""
folder_path = pathlib.Path(folder)
for archive_file in folder_path.iterdir():
suffix = archive_file.suffix.lower()
try:
…How to Automatically Merge Hundreds of Excel Files Without Losing Formatting in Python
Merge all .xlsx files in a folder into a single Excel workbook, preserving individual sheet structures with sheet name prefixes.
import pandas as pd
from pathlib import Path
def merge_excel_files(folder_path: str, output_path: str) -> None:
"""
Merge all .xlsx files in a folder into a single Excel file,
preserving individual sheet structures.
"""
folder = Path(folder_path)
excel_files = list(folder.glob("*.xlsx"))
…How to Memory Map Large Files Read-Only in Python
This code demonstrates reading only the tail of a large file using a read-only memory map (mmap) to avoid loading the entire file into memory.
import mmap
import os
def read_tail_with_mmap(filepath, bytes_from_end=64):
"""Read the last bytes of a large file using a read-only mmap."""
file_size = os.path.getsize(filepath)
start = max(0, file_size - bytes_from_end)
with open(filepath, "rb") as f:
with mmap.mmap(f.fileno(), length=0, a…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.
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…How to Parse Apache Log Files in Python
Parse Apache common log format lines into structured dictionaries using Python's standard library.
import re
from pathlib import Path
def parse_apache_line(line):
pattern = r'^(\S+) (\S+) (\S+) \[([^\]]+)\] "(\S+) (\S+) (\S+)" (\d{3}) (\S+)'
match = re.match(pattern, line)
if not match:
return None
ip, ident, user, timestamp, method, path, protocol, status, size = match.groups()
return …Read Parquet-Like Columnar CSV Chunks in Python
A Python generator that reads a CSV file column-by-column, yielding dictionary chunks where each key points to a list of values—mirroring how Parquet stores data columnar.
```python
import csv
from pathlib import Path
from typing import Iterator, List
def read_parquet_like_columnar(csv_path: str, column_names: List[str], chunk_size: int = 2) -> Iterator[dict]:
"""Read CSV data in columnar chunks, similar to how parquet stores columns."""
csv_file = Path(csv_path)
with csv_f…Tail last N lines of growing log file in Python
Prints the last n lines of a log file and follows new content appended to it, polling for size changes.
import time
from pathlib import Path
def tail_log(file_path, n=10, poll_interval=1.0, timeout=10):
"""
Print the last n lines and follow new lines appended to a growing log file.
"""
path = Path(file_path)
# Read the last n lines from the current file
with path.open("r", encoding="utf-8") as f…Browse by section
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