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How to Close a Generator and Handle GeneratorExit in Python
This Python code demonstrates how to explicitly close a generator using the close() method and handle the GeneratorExit exception through a finally block to run cleanup logic.
def countdown(n):
try:
while n > 0:
yield n
n -= 1
finally:
print(f"Generator closed after countdown completed")
if __name__ == "__main__":
gen = countdown(5)
print(next(gen))
print(next(gen))
gen.close()
print("Generator closed explicitly")
How to Create a Pairwise Generator with zip and tee in Python
Build a memory-efficient generator that yields successive overlapping pairs from any iterable using zip and tee.
from itertools import tee
def pairwise(iterable):
"""Yield successive overlapping pairs from iterable."""
a, b = tee(iterable)
next(b, None)
return zip(a, b)
if __name__ == "__main__":
values = [1, 2, 3, 4, 5]
print(list(pairwise(values)))
print(list(pairwise("hello")))
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…
How to Slice a Generator with islice in Python
Use itertools.islice to take the first n items from any iterable without materializing the whole sequence into a list.
from itertools import islice
def first_n(iterable, n):
"""Return the first n items from an iterable."""
return list(islice(iterable, n))
if __name__ == "__main__":
numbers = range(10, 100) # large iterable
result = first_n(numbers, 5)
print(result) # [10, 11, 12, 13, 14]
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…
Sum of Squares with a Generator Expression in Python
This code computes the sum of squares of integers from 1 to n using a generator expression, demonstrating a memory-efficient and concise way to aggregate a sequence.
def sum_of_squares(n):
return sum(x * x for x in range(1, n + 1))
if __name__ == "__main__":
print(f"Sum of squares from 1 to 5: {sum_of_squares(5)}")
print(f"Sum of squares from 1 to 10: {sum_of_squares(10)}")
Write Data Helpers with Comprehensions and Generators in Python
Demonstrates list, dict, and set comprehensions plus generator expressions and generator functions for building concise data helpers.
# Basic comprehensions and generators demo
# List comprehension: squares of evens
squares = [x * x for x in range(10) if x % 2 == 0]
print("List comp:", squares)
# Dictionary comprehension: char -> count
text = "hello"
char_counts = {c: text.count(c) for c in set(text)}
print("Dict comp:", char_counts)
# Set compre…
Demonstrate Prompt Injection Bypass in Python
Simulate why naive system prompt filters fail against prompt injection with casing and spacing variations.
# Demonstrate why system prompts can be bypassed by simulated user input
# This demo shows a naive filter being ignored via prompt injection
def process_user_message(message, system_rules):
"""Simulate an AI that follows system rules but gets tricked."""
# Claim to check system rules
for rule in system_ru…
How to Compute a Mock BLEU Score with n-gram Overlap in Python
Evaluate text similarity with a simplified BLEU score using word-level n-gram precision and a brevity penalty.
from collections import Counter
def bleu_score(reference, candidate, n=2):
"""
Compute a simplified BLEU score with n-gram precision and brevity penalty.
Mock demo using word-level n-grams.
"""
ref_tokens = reference.lower().split()
cand_tokens = candidate.lower().split()
# Compute n-…
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 Filter Toxic Keywords in Python
Filter toxic keywords from text by replacing each occurrence with asterisks, useful as a basic guardrail for LLM inputs.
TOXIC_KEYWORDS = ["insult", "threat", "hate", "violence", "spam"]
def guardrails_filter(text: str, keywords: list[str] | None = None) -> str:
"""Filter out toxic keywords from the given text.
Args:
text: The input text to filter.
keywords: Optional keyword list. Defaults to TOXIC_KEYWORDS.
…
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…
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 Download a List of URLs to a Directory in Python
This script downloads a list of URLs into a specified directory, creating the folder if needed and keeping original filenames.
import urllib.request
from pathlib import Path
def download_urls(url_list, directory):
"""Download each URL in url_list into directory, keeping original filenames."""
save_dir = Path(directory)
save_dir.mkdir(parents=True, exist_ok=True)
for url in url_list:
filename = url.rstrip('/').spl…
How to Generate an Inventory CSV of Installed pip Packages in Python
This script uses subprocess and csv to list all installed pip packages and write their names and versions into a CSV inventory file.
import subprocess
import csv
def get_installed_packages():
"""Return a list of (name, version) tuples for installed pip packages."""
result = subprocess.run(
["pip", "list", "--format=freeze"],
capture_output=True,
text=True,
check=True
)
packages = []
for line in r…
How to Quarantine Suspicious Files in Python
Move files with suspicious extensions to a quarantine folder using pathlib and shutil for safe isolation.
import shutil
import os
from pathlib import Path
def quarantine_files(source_dir, quarantine_dir, suspicious_extensions):
"""
Move files with suspicious extensions to a quarantine folder.
Returns list of moved files.
"""
source_path = Path(source_dir)
quarantine_path = Path(quarantine_dir)
…
How to Write an IP Block List to hosts.deny in Python
This Python script validates a list of IP addresses and CIDR ranges, then writes them to a hosts.deny file to block connections at the TCP wrapper level.
from ipaddress import ip_network
def write_hosts_deny(ip_list, output_file="hosts.deny"):
with open(output_file, "w") as f:
for ip in ip_list:
try:
ip_network(ip)
f.write(f"ALL: {ip}\n")
except ValueError:
continue
print(f"Written…
Pin Python package versions in requirements.txt
Pin package versions in requirements.txt-style text by adding ==version when no specifier is present, while preserving existing version constraints and comments.
import re
from pathlib import Path
def pin_versions(requirements_text: str) -> str:
"""
Pin package versions in requirements.txt-style text.
Adds ==version if no version specifier is present.
Keeps existing specifiers (>=, <=, ~=, etc.) unchanged.
"""
lines = requirements_text.strip().splitli…
Group Python Events into Sessions with a Gap Timeout
Groups timestamped events into sessions, starting a new session when the time gap exceeds a specified timeout.
from itertools import groupby
from datetime import datetime, timedelta
def session_window_group(events, gap_seconds=300):
"""Group events into sessions where gap > gap_seconds starts a new session."""
if not events:
return []
events = sorted(events, key=lambda x: x[0])
sessions = []
c…
How to Filter Data in Python
Filter a list of dictionaries by exact key-value matches or numerical ranges using concise list comprehensions.
from typing import List, Dict, Any
def filter_data(
data: List[Dict[str, Any]], key: str, value: Any
) -> List[Dict[str, Any]]:
"""Return records where data[key] equals value."""
return [record for record in data if record.get(key) == value]
def filter_by_range(
data: List[Dict[str, Any]], key: str…
How to Group Data by Key in Python
Group a list of dictionaries by a specified key using a defaultdict and compute per-group averages.
from collections import defaultdict
def group_by_key(data, key):
grouped = defaultdict(list)
for item in data:
grouped[item[key]].append(item)
return dict(grouped)
if __name__ == "__main__":
records = [
{"name": "Alice", "dept": "Engineering", "score": 85},
{"name": "Bob", "de…
How to Group Rows by Key into Nested Arrays in Python
This code groups rows in a list of dictionaries by a specified key and returns a dictionary with each key mapped to a list of values from another key.
from collections import defaultdict
def implode_rows(rows, key, value_key):
grouped = defaultdict(list)
for row in rows:
grouped[row[key]].append(row[value_key])
return dict(grouped)
if __name__ == "__main__":
data = [
{"category": "fruit", "item": "apple"},
{"category": "fr…
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