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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Transform a List of Dictionaries with Sets in Python
Normalize a list of dict records — cleaning names, extracting unique tags with sets, and building a standardized result.
def transform_data(raw_records):
"""Transform a list of dict records into normalized data with sets for unique values."""
normalized = []
unique_names = set()
all_tags = set()
for record in raw_records:
# Normalize name to lowercase and strip whitespace
name = record.get("name"…
Extract n largest elements from a large list using heapq
Uses heapq.nlargest to efficiently extract the top n largest numbers from a large list, even with millions of elements.
import heapq
import random
def n_largest(numbers, n):
"""Return the n largest numbers from a list using heapq."""
if n <= 0:
return []
return heapq.nlargest(n, numbers)
if __name__ == "__main__":
# Create a large list with 1,000,000 random numbers
large_list = [random.randint(1, 1_000_000…
How to Find the n Smallest Items in a Large List with heapq in Python
This code demonstrates how to efficiently extract the n smallest items from a large list using Python's heapq module and a manual max-heap approach.
import heapq
def n_smallest_iterable(data, n):
"""Return the n smallest items without loading the whole list."""
if n <= 0:
return []
return heapq.nsmallest(n, data)
def n_smallest_manual(data, n):
"""Return the n smallest using a heap, O(n log k) time."""
if n <= 0:
return []
…
Convert Data in Python with Comprehensions and Generators
Convert mixed data to integers, filter and transform numbers, and extract fields from dicts using list comprehensions and generator expressions.
def convert_numbers(data):
"""Convert a list of mixed values into integers using a comprehension."""
return [int(item) for item in data if item is not None]
def double_even_numbers(numbers):
"""Double only even numbers using a generator expression."""
return (n * 2 for n in numbers if n % 2 == 0)
d…
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 Sort Data with Comprehensions and Generators in Python
Sort a list of tuples by a key, then use a list comprehension to extract names and a generator to square high ranks.
data = [("Anna", 3), ("Ben", 1), ("Clara", 2), ("Dan", 5), ("Eve", 4)]
# Comprehension: list of tuples (name, rank) sorted ascending by rank
sorted_by_rank = sorted(data, key=lambda x: x[1])
# Comprehension: extract just the names in rank order
names_in_rank_order = [name for name, rank in sorted_by_rank]
# Generat…
Set Comprehension for Unique Word Lengths in Python
Use a set comprehension to extract unique word lengths from a string, then sort and print the result.
text = "hello world hello python programming"
word_lengths = {len(word) for word in text.split()}
print("Unique word lengths:", word_lengths)
print("Sorted:", sorted(word_lengths))
How to Parse JSON from LLM Model Output Fence in Python
Extract and parse a JSON object from a language model's output that may be wrapped in triple-backtick fences with an optional language tag.
import json
import re
def parse_json_from_fence(text):
"""
Extract JSON object from a model output that may be wrapped in
triple-backtick fences with optional language tag.
"""
# Match content inside
JSON Mode Prompt Schema Output in Python
Extract a user object to JSON with explicit schema keys, ready for LLM JSON-mode prompts.
import json
from typing import Any, Dict
def extract_user_as_json(user: Dict[str, Any]) -> str:
"""Extract a user object and return it as JSON using explicit schema keys."""
schema_fields = ("id", "name", "email", "is_active")
user_subset = {key: user[key] for key in schema_fields if key in user}
ret…
Automatically Generate Charts from CSV Files with One Command
Read a CSV file with headers, extract the first two numeric columns, and save a matplotlib line chart as a PNG image.
import csv
import sys
from pathlib import Path
import matplotlib.pyplot as plt
def generate_chart(csv_path: str) -> None:
"""Read a CSV file with headers and plot the first two numeric columns."""
data = []
with open(csv_path, 'r', newline='') as f:
reader = csv.reader(f)
headers = next(re…
Build an RSS feed from markdown blog posts in Python
Scans a folder of markdown files, extracts titles, dates, and excerpts, and generates a valid RSS 2.0 XML feed.
import re
from pathlib import Path
from xml.etree.ElementTree import Element, SubElement, tostring
from datetime import datetime, timezone
from xml.dom import minidom
def build_rss(blog_dir, site_url="https://example.com"):
feed = Element("rss", version="2.0")
channel = SubElement(feed, "channel")
SubElem…
Convert DOCX to Text by Unzipping XML in Python
Extract plain text from a .docx file by unzipping the container and parsing word/document.xml with regex, using only Python's standard library.
import zipfile
import re
from pathlib import Path
def docx_to_text_unzip_xml(docx_path: str) -> str:
"""Extract plain text from a .docx file by unzipping and parsing document.xml."""
docx_path = Path(docx_path)
if not docx_path.exists():
raise FileNotFoundError(f"File not found: {docx_path}")
…
Extract All Links from Any Website in Python
Scrape a webpage and extract all absolute HTTP/HTTPS links using requests and regex.
import requests
import re
from urllib.parse import urljoin
def extract_links(url):
try:
response = requests.get(url)
response.raise_for_status()
html = response.text
# Find all href attributes in anchor tags
pattern = r'href=["\'](.*?)["\']'
raw_links = re.findall(p…
Extract Attachments from mbox Mailbox Files in Python
Extract file attachments from an mbox mailbox format using Python's standard library email and mailbox modules.
import email
import mailbox
from email.policy import default
from pathlib import Path
def extract_attachments(mbox_path, output_dir):
output_dir = Path(output_dir)
output_dir.mkdir(exist_ok=True)
mbox = mailbox.mbox(mbox_path)
for msg in mbox:
if msg.is_multipart():
for part i…
Extract Every Open Graph and Social Media Meta Tag from Web Pages in Python
A Python script that fetches a webpage and extracts all Open Graph, Twitter Card, Facebook, and Article meta tags using the standard library HTML parser.
from html.parser import HTMLParser
import re
from urllib.request import urlopen
from urllib.parse import urlparse
class MetaExtractor(HTMLParser):
def __init__(self):
super().__init__()
self.meta_tags = []
def handle_starttag(self, tag, attrs):
if tag == 'meta':
attrs_…
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 Run Tesseract OCR from Python with subprocess
This script uses Python's subprocess module to invoke the Tesseract OCR engine from the command line and return the extracted text.
import subprocess
def ocr_image(image_path):
command = ["tesseract", image_path, "stdout"]
result = subprocess.run(command, capture_output=True, text=True)
return result.stdout.strip()
if __name__ == "__main__":
# Stub: call the actual tesseract (must be installed)
text = ocr_image("sample.png")
…
How to rename music files by ID3 tags in Python
Renames MP3 files in a folder using artist and title extracted from ID3 tags, with a mock fallback that parses filenames.
import os
import re
from pathlib import Path
def sanitize_filename(name: str) -> str:
return re.sub(r'[<>:"/\\|?*]', '_', name).strip()
def rename_mp3_from_id3(path: Path) -> None:
for f in path.glob("*.mp3"):
# Mock ID3 extraction: derive artist/title from filename
stem = f.stem
if "…
Parse WHOIS Data with Python Regex
Extract domain registration fields from a mock WHOIS record using regex and compute days until expiration.
import re
from datetime import datetime
def parse_whois(whois_text: str) -> dict:
"""Extract key registration fields from a mock WHOIS record."""
patterns = {
"domain": r"Domain Name:\s*(.+)",
"registrar": r"Registrar:\s*(.+)",
"creation_date": r"Creation Date:\s*(.+)",
"expir…
Parse nginx access log top IPs in Python
Reads an nginx access log line by line, extracts the client IP, and returns the most frequent IPs using a regex and Counter.
import re
from collections import Counter
def top_ips(log_file, n=10):
ip_pattern = re.compile(r'^(\S+)')
ip_counts = Counter()
with open(log_file, 'r') as f:
for line in f:
match = ip_pattern.match(line)
if match:
ip_counts[match.group(1)] += 1
return…
Run pytest and email summary in Python
Runs pytest via subprocess, extracts the test summary line, and sends it in an email (mocked for demonstration).
import smtplib
import subprocess
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
def run_tests():
"""Run pytest and capture the summary output."""
result = subprocess.run(
["pytest", "-q"],
capture_output=True,
text=True
)
return result.stdo…
Scrape HTML Tables in Python with html.parser
Extract data from HTML tables using Python's built-in html.parser module, without third-party dependencies, by overriding callback methods to track table, row, and cell states.
import html.parser
from urllib.request import urlopen
class TableParser(html.parser.HTMLParser):
def __init__(self):
super().__init__()
self.in_table = False
self.in_row = False
self.in_cell = False
self.current_cell = []
self.rows = []
self.row = []
d…
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…
ETL in Python: Extract CSV, Transform Dicts, Load JSON
Build a simple ETL pipeline that reads a CSV, normalizes keys and converts price to float, then writes structured JSON.
import csv
import json
from pathlib import Path
def etl_csv_to_json(csv_path: str, json_path: str) -> None:
"""Extract CSV, transform rows to dicts, load to JSON."""
with open(csv_path, mode='r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
records = list(reader)
# Trans…
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