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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Stable merge two lists by custom comparator in Python
Merge two lists into one sorted output using a custom comparator while maintaining the original order of equal elements.
from functools import cmp_to_key
def compare(x, y):
# Custom comparator: sorts by length first, then by original index for stability
if len(x) != len(y):
return len(x) - len(y)
return 0 # Equal keys preserve original order (stable)
def merge_stable(left, right, cmp_func):
result = []
i =…
Build a Generator Pipeline in Python: Filter Then Map
Create a lazy data pipeline by chaining generator functions that read, filter, map, and write data step by step.
def read_data():
return ["a", "bb", "ccc", "dd", "eeeee", "f"]
def filter_short(words):
return (word for word in words if len(word) >= 2)
def map_to_upper(words):
return (word.upper() for word in words)
def write_data(words):
for word in words:
print(word)
if __name__ == "__main__":
…
Cycle an iterable forever in Python
Define a generator that repeatedly yields items from an iterable, cycling back to the beginning infinitely.
def cycle_generator(iterable):
"""Yield items from iterable forever, cycling back to the start."""
items = list(iterable) # Convert to list so it can restart
index = 0
while True:
yield items[index]
index = (index + 1) % len(items)
if __name__ == "__main__":
colors = ["red", "gre…
Drop n items then yield rest generator
A generator that skips the first n items of an iterable and then yields the remaining items one by one.
def drop(n, items):
"""Yield every item except the first n from items."""
it = iter(items)
for _ in range(n):
next(it, None) # skip first n items
yield from it
if __name__ == "__main__":
numbers = [10, 20, 30, 40, 50]
result = list(drop(2, numbers))
print(result)
Generator Function to Yield an Infinite Counter in Python
This code demonstrates a generator function that yields an infinite sequence of integers starting from a given value, allowing lazy, memory-efficient iteration.
def infinite_counter(start=0):
count = start
while True:
yield count
count += 1
if __name__ == "__main__":
counter = infinite_counter(5)
for _ in range(5):
print(next(counter))
How to Create an Infinite Arithmetic Sequence Generator in Python
Build a memory-efficient generator that yields an infinite arithmetic progression and extract the first N values with list comprehension.
"""Count generator infinite arithmetic progression"""
def arithmetic_counter(start=0, step=1):
"""Generate an infinite arithmetic sequence."""
current = start
while True:
yield current
current += step
if __name__ == "__main__":
counter = arithmetic_counter(1, 3)
result = [next(c…
How to Generate Fibonacci Numbers in Python Without Recursion
Build an efficient infinite Fibonacci sequence using a generator function with O(1) memory and no recursion overhead.
def fib(n):
a, b = 0, 1
for _ in range(n):
yield a
a, b = b, a + b
if __name__ == "__main__":
count = 10
result = list(fib(count))
print(result)
How to Reset Python's Random Seed for Deterministic Output
This code shows how to seed Python's random module to generate identical random sequences across runs, ensuring reproducibility.
import random
def seeded_random_sequence(seed, count=5, low=1, high=100):
random.seed(seed)
return [random.randint(low, high) for _ in range(count)]
if __name__ == "__main__":
seed_value = 42
first_run = seeded_random_sequence(seed_value)
print("First run:", first_run)
# Reset seed and gener…
List Comprehension to Filter Even Numbers in Python
Creates a new list containing only the even numbers from an existing list using a list comprehension with a condition.
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers = [n for n in numbers if n % 2 == 0]
print(f"Original: {numbers}")
print(f"Even numbers: {even_numbers}")
Take n items from an infinite Python generator
Uses itertools.islice to lazily take exactly n items from an infinite generator without exhausting it.
from itertools import islice
def count_up_from(start=0):
n = start
while True:
yield n
n += 1
def take_n(generator, count):
return list(islice(generator, count))
if __name__ == "__main__":
gen = count_up_from(10)
result = take_n(gen, 5)
print(result)
How to Batch Embed a List of Strings in Python
Batch embed a list of strings into deterministic pseudo-random vectors using a mock encoder class.
class MockEncoder:
def __init__(self, dim=8, seed=42):
self.dim = dim
self.seed = seed
def embed(self, text):
# Deterministic pseudo-random embedding based on text content
hash_val = hash(text)
import random
rng = random.Random(hash_val + self.seed)
retu…
How to Create a Mock Text Embedding with Hash in Python
Generate deterministic mock text embeddings using SHA-256 hashing and numpy, producing normalized vectors for similarity testing without an LLM.
import hashlib
import numpy as np
def mock_embed(text: str, dim: int = 10, seed: int = 42) -> np.ndarray:
"""Generate a deterministic mock embedding using a hash function.
Args:
text: Input text to embed
dim: Dimension of the output vector
seed: Seed for reproducibility
R…
How to Parse Chat Completion JSON in Python
Parse a mock OpenAI chat completion JSON response into a clean dictionary with content, finish reason, and model.
import json
def parse_chat_response(raw: str) -> dict:
data = json.loads(raw)
choice = data["choices"][0]
return {
"content": choice["message"]["content"],
"finish_reason": choice["finish_reason"],
"model": data["model"],
}
if __name__ == "__main__":
mock_response = '''
…
How to build a mock RAG pipeline in Python
Build a minimal Retrieval-Augmented Generation pipeline that retrieves the best-matching document by keyword overlap and generates a template-based answer.
def simple_rag_pipeline(question, documents):
"""
A minimal mock RAG pipeline: retrieve relevant context, then generate an answer.
"""
# Step 1: Retrieve — mock retrieval by simple keyword scoring
scores = []
for doc in documents:
doc_words = set(doc.lower().split())
question_wo…
Find Zombie Processes on Linux with Python
Parse the output of `ps -eo pid,stat,comm` to detect processes in zombie state (Z) on a Linux system and report their PIDs and commands.
#!/usr/bin/env python3
import os
import subprocess
def find_zombie_processes():
"""Find zombie processes (state 'Z') running on Linux."""
try:
result = subprocess.run(['ps', '-eo', 'pid,stat,comm'], capture_output=True, text=True, check=True)
zombies = []
for line in result.stdout.stri…
How to Check SSL Certificate Expiry in Python
Connect to a host over TLS, extract the certificate's expiry date, and report days remaining using only the Python standard library.
import socket
import ssl
from datetime import datetime
def check_cert_expiry(hostname, port=443):
context = ssl.create_default_context()
with socket.create_connection((hostname, port), timeout=10) as sock:
with context.wrap_socket(sock, server_hostname=hostname) as tls_sock:
cert = tls_soc…
How to Compress a Folder in Python While Preserving Directory Structure
A Python function that uses zipfile to recursively compress a folder, maintaining the original directory hierarchy inside the zip archive.
import os
import zipfile
from pathlib import Path
def compress_folder(source_dir: str, output_zip: str):
"""
Compress a folder into a zip file, preserving the directory structure.
Args:
source_dir: Path to the source directory to compress
output_zip: Path for the output zip file
"…
How to Create a Mock Headless Browser Screenshot Stub in Python
This code provides a deterministic stub that simulates capturing webpage screenshots with a headless browser, returning formatted output without real browser dependencies.
import subprocess
import sys
def mock_screenshot_webpage(url: str, width: int = 1280, height: int = 800) -> str:
"""Stub that simulates taking a screenshot of a webpage using headless browser."""
# In real implementation, you would use playwright/selenium/headless chrome
result = {
"url": url,
…
How to Detect Applications Consuming Excessive Memory in Python
Use psutil to list the top memory-using processes by RSS and print their names, PIDs, and memory usage in MB.
import psutil
def find_top_memory_processes(limit=5):
"""Return top `limit` processes by memory usage (RSS)."""
processes = []
for proc in psutil.process_iter(['pid', 'name', 'memory_info']):
try:
info = proc.info
mem = info['memory_info'].rss if info['memory_info'] else 0…
How to Generate Thumbnails While Maintaining Aspect Ratio in Python
Resize images to fit within maximum dimensions while preserving the original aspect ratio using Pillow (PIL).
from PIL import Image
def thumbnail_with_aspect_ratio(image_path, output_path, max_width, max_height):
with Image.open(image_path) as img:
# Get original dimensions
width, height = img.size
# Calculate scaling ratio to fit within max dimensions
ratio = min(max_width / width, max_h…
How to Generate a cloud-init User Data Mock in Python
Generate a cloud-init user data mock for a VM using a dataclass and JSON in Python.
import json
from dataclasses import dataclass, asdict
@dataclass
class VMConfig:
hostname: str
cpus: int
memory_mb: int
ssh_key: str
def generate_cloud_init_mock(config: VMConfig) -> str:
"""Build a cloud-init user-data mock for a VM."""
user_data = {
"hostname": config.hostname,
…
How to Monitor Laptop Battery Health Over Time in Python
Log battery percentage, power status, and remaining time every N seconds to a JSON file using psutil for ongoing health monitoring.
import time
import json
from pathlib import Path
from datetime import datetime
try:
import psutil
except ImportError:
print("psutil required: pip install psutil")
exit(1)
LOG_FILE = Path("battery_health_log.json")
def monitor_battery(log_interval=60, duration=300):
"""Log battery percentage and rema…
Generate a Deterministic Hash for Deduplication in Python
Create a stable SHA-256 fingerprint from nested data and file contents to deduplicate records in a data pipeline.
import hashlib
import json
from pathlib import Path
def natural_key_hash(data, salt=""):
"""
Generate a deterministic fingerprint from raw data (dict/list/str).
Uses JSON canonical-ish serialization with sorted keys and SHA-256.
"""
canonical = json.dumps(data, sort_keys=True, separators=(",", ":"…
How to create a dated snapshot path for a dataset in Python
Generate a versioned directory path combining a base directory, dataset name, and today's date, ready for creating snapshots in data pipelines.
import datetime
import os
from pathlib import Path
def snapshot_path(base_dir: str, dataset_name: str) -> Path:
"""Return a dated snapshot path for a dataset under a base directory."""
today = datetime.date.today().isoformat()
return Path(base_dir) / dataset_name / today
if __name__ == "__main__":
…
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