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How to Process Text in Python
This code processes multiline text by splitting lines, stripping whitespace, counting words and characters, and converting to lowercase.
def process_text(text):
lines = text.split("\n")
clean_lines = []
for line in lines:
stripped = line.strip()
if stripped:
tokens = stripped.split()
title_case = stripped.lower()
clean_lines.append({
"raw": stripped,
"word_c…How to Process Text Lines with Lists and Loops in Python
This code processes a list of text lines by stripping whitespace, converting to uppercase, and reporting character counts per line and totals.
def process_text(lines):
"""Convert a list of text lines to uppercase and report line statistics."""
processed = []
total_chars = 0
for index, line in enumerate(lines, start=1):
cleaned = line.strip().upper()
processed.append(cleaned)
total_chars += len(cleaned)
pri…How to Count Word Frequencies in Python with Counter and Sets
This code processes a text string by lowercasing, splitting into words, counting frequencies with Counter, and extracting unique and sorted word lists using sets.
from collections import Counter
def process_text(text):
words = text.lower().split()
word_counts = Counter(words)
unique_words = set(words)
sorted_words = sorted(unique_words)
return {
"total_words": len(words),
"unique_words": len(unique_words),
"word_frequencies": di…Memory efficient map over large file in Python
A generator-based streaming map that processes a large file line by line without loading the whole file into memory.
import sys
def process_lines(file_path):
"""Memory-efficient map over a large file: yields processed lines."""
with open(file_path, 'r') as f:
for line in f:
# Example mapping: strip whitespace and uppercase
yield line.strip().upper()
if __name__ == "__main__":
# Use a sma…How to Build a CLI with argparse in Python
Create a beginner-friendly command-line tool in Python that processes multiple filenames with optional flags for verbose output and uppercase conversion.
import argparse
def main():
parser = argparse.ArgumentParser(
description="A simple CLI to process files with optional verbose mode."
)
parser.add_argument("filenames", nargs="+", help="Files to process")
parser.add_argument("-v", "--verbose", action="store_true", help="Print extra details")
…How to Kill Zombie Processes Matching a Name in Python
Scans running processes with ps, finds zombies whose command name matches a pattern, and attempts to kill them with SIGKILL.
import subprocess
import re
import signal
def find_zombies(name_pattern):
"""Find PIDs of zombie processes matching the given pattern."""
result = subprocess.run(["ps", "-eo", "pid,stat,comm"], capture_output=True, text=True)
zombies = []
for line in result.stdout.splitlines()[1:]: # Skip header
…How to Send and Receive Messages Between Processes with multiprocessing.Pipe in Python
Use multiprocessing.Pipe to create a two-way connection between two processes, send a message from parent to child, and receive a reply back.
import multiprocessing
def child_process(conn):
"""Receive from parent and send back a response."""
message = conn.recv()
print(f"Child received: {message}")
conn.send("Hello from child!")
if __name__ == "__main__":
parent_conn, child_conn = multiprocessing.Pipe()
process = multiprocessing…How to Use pool.map for CPU-Bound Tasks in Python
Distribute CPU-intensive functions across processes with multiprocessing.Pool.map and measure the performance gain.
from multiprocessing import Pool
import time
def cpu_bound_task(n):
"""Mock CPU-bound work: compute sum of squares."""
total = 0
for i in range(n):
total += i * i
return total
if __name__ == "__main__":
numbers = [10_000_000, 12_000_000, 8_000_000, 15_000_000]
start = time.perf_count…How to spawn multiple worker processes in Python with multiprocessing.Process
Spawns three separate worker processes using multiprocessing.Process, runs them concurrently, and waits for all to finish before printing a completion message.
import multiprocessing
import time
def worker(name):
print(f"Worker {name} started")
time.sleep(1)
print(f"Worker {name} finished")
return name
if __name__ == "__main__":
processes = []
for i in range(3):
p = multiprocessing.Process(target=worker, args=(i,))
processes.append(p…How to implement an idempotency key store in Python
Build an in-memory idempotency key store with TTL that processes a request once and reuses the cached result for duplicate calls.
import hashlib
import time
from typing import Dict, Optional
class IdempotencyStore:
"""Simple in-memory idempotency key store with mock processing."""
def __init__(self, ttl_seconds: int = 3600) -> None:
self.ttl = ttl_seconds
self._store: Dict[str, tuple[str, float]] = {}
def _is_expi…Browse by section
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