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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Find Pivot Index in Python
Locate the index where the sum of elements to the left equals the sum to the right, using a single pass with prefix sums.
def find_pivot_index(nums):
total = sum(nums)
left_sum = 0
for i, num in enumerate(nums):
if left_sum == total - left_sum - num:
return i
left_sum += num
return -1
if __name__ == "__main__":
test_cases = [
[1, 7, 3, 6, 5, 6],
[1, 2, 3],
[2, 1, -…
Find the Equilibrium Index of a List in Python
Find every index in a list where the sum of elements to its left equals the sum to its right, using a single pass.
def find_equilibrium_indexes(arr):
total = sum(arr)
left_sum = 0
indexes = []
for i, num in enumerate(arr):
total -= num
if left_sum == total:
indexes.append(i)
left_sum += num
return indexes
if __name__ == "__main__":
test = [1, 2, 3, -1, 2, 3]
result =…
Generate Pascal's Triangle Rows in Python
Builds Pascal's triangle as a list of rows, where each inner value is the sum of the two values above it.
def generate_pascals_triangle(rows):
triangle = []
for row_num in range(rows):
row = [1] * (row_num + 1)
for col in range(1, row_num):
row[col] = triangle[row_num - 1][col - 1] + triangle[row_num - 1][col]
triangle.append(row)
return triangle
if __name__ == "__main__":
…
How to Add Two Lists Elementwise in Python
Add two equal-length lists element by element using a list comprehension with zip, returning a new list of summed values.
def elementwise_add(list1, list2):
return [a + b for a, b in zip(list1, list2)]
if __name__ == "__main__":
list_a = [1, 2, 3, 4]
list_b = [10, 20, 30, 40]
result = elementwise_add(list_a, list_b)
print(result)
How to Compute the Dot Product of Two Lists in Python
Compute the dot product of two equal-length numeric lists using a generator expression with zip and sum.
def dot_product(list1, list2):
"""
Compute the dot product of two numeric lists.
The lists must have the same length.
"""
if len(list1) != len(list2):
raise ValueError("Lists must have the same length")
return sum(a * b for a, b in zip(list1, list2))
if __name__ == "__main__":
…
How to Find Four Sum Quadruplets in Python (Sorted Demo)
Find all unique quadruplets in a sorted array that sum to a target, with duplicate skipping.
def four_sum(nums, target):
nums.sort()
result = []
n = len(nums)
for i in range(n - 3):
if i > 0 and nums[i] == nums[i - 1]:
continue
for j in range(i + 1, n - 2):
if j > i + 1 and nums[j] == nums[j - 1]:
continue
left, right = j + 1…
How to Implement a Moving Average from a Data Stream in Python
Implement a MovingAverage class using a deque and running sum to compute the average of the last k values from a continuous data stream.
from collections import deque
class MovingAverage:
def __init__(self, size):
self.size = size
self.queue = deque()
self.window_sum = 0
def next(self, val):
self.queue.append(val)
self.window_sum += val
if len(self.queue) > self.size:
self.window_su…
Split Array Largest Sum in Python (Minimize Largest Subarray Sum)
Binary search + greedy check to split an array into k subarrays while minimizing the largest subarray sum.
def can_split(nums, k, max_sum):
subarrays = 1
current_sum = 0
for num in nums:
if current_sum + num <= max_sum:
current_sum += num
else:
subarrays += 1
current_sum = num
if subarrays > k:
return False
return True
def spli…
Enumerate a Generator With a Running Total in Python
A generator that yields each element with its index and a cumulative sum, letting you track a running total as you iterate.
def running_total_enum(iterable):
"""Yields (index, item, running_total) for each element."""
total = 0
for index, item in enumerate(iterable):
total += item
yield index, item, total
if __name__ == "__main__":
numbers = [10, 20, 30, 40, 50]
for idx, value, running_sum in running_to…
How to Accumulate Values with a Generator in Python
This generator yields the running total of an iterable's elements, producing a cumulative sum with each step.
def accum(iterable):
total = 0
for item in iterable:
total += item
yield total
# Demo
if __name__ == "__main__":
data = [1, 2, 3, 4, 5]
print(list(accum(data))) # [1, 3, 6, 10, 15]
# Also works with any iterable, e.g., range
print(list(accum(range(1, 6)))) # [1, 3, 6, 10, 15]
How to Build a Backpressure Generator Pause Producer Demo in Python
Demonstrates a producer–consumer pattern with a fixed-size buffer that pauses production when full, simulating backpressure.
import time
import collections
def producer(buffer, max_size, items):
"""Adds items to the buffer until full, then pauses."""
for item in items:
while len(buffer) >= max_size:
print(f"Buffer full ({len(buffer)}/{max_size}) — producer paused")
time.sleep(0.1)
buffer.appe…
How to Use Comprehensions and Generators to Check Data in Python
A beginner-friendly helper that filters numeric values, computes squares and cubes with comprehensions and a generator, and returns a summary dictionary.
def check_data(iterable):
"""Return a summary of numeric data using comprehensions and a generator."""
values = [item for item in iterable if isinstance(item, (int, float))]
squares = [x ** 2 for x in values if x > 0]
cubes = (x ** 3 for x in values if x > 0)
cube_list = list(cubes)
return {
…
How to Use List Comprehensions and Generators in Python
Analyze a list of numbers using a list comprehension to square evens, a generator for sum, and a generator expression for the maximum squared value.
def analyze_numbers(numbers):
squared = [n ** 2 for n in numbers if n % 2 == 0]
total = sum(n for n in numbers)
max_squared = max((n ** 2 for n in numbers), default=0)
return squared, total, max_squared
if __name__ == "__main__":
data = [1, 2, 3, 4, 5, 6]
evens_squared, total_sum, max_sq = an…
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)}")
How to Log Prompts and Completions as JSONL Audit Files in Python
Read a JSONL file of LLM prompt–completion pairs, compute totals and averages, then write an audit summary with timestamps.
import json
from pathlib import Path
from datetime import datetime
def audit_jsonl(filepath):
logs = []
with open(filepath, encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line:
continue
entry = json.loads(line)
logs.ap…
How to Summarize Old Conversation Turns in Python
Compress old conversation turns into a brief summary while keeping recent turns intact for LLM context management.
from datetime import datetime, timedelta
def summarize_old_turns(conversation, max_turns=5):
"""Compress turns older than max_turns into a brief summary."""
if len(conversation) <= max_turns:
return conversation, ""
old_turns = conversation[:-max_turns]
recent_turns = conversation[-max_turns…
How to compute ROUGE recall in Python
Compute ROUGE recall by counting token overlap between a reference and candidate summary with pure Python.
def rouge_recall(reference, candidate):
ref_tokens = reference.lower().split()
cand_tokens = candidate.lower().split()
ref_counts = {}
for token in ref_tokens:
ref_counts[token] = ref_counts.get(token, 0) + 1
cand_counts = {}
for token in cand_tokens:
cand_counts[token] = cand…
Prepare LLM prompt data with a Python helper class
A beginner-friendly Python class that collects records, converts them to JSON, and produces a quick summary for building LLM prompt context.
import json
from typing import Any, Dict, List
class DataHelper:
"""Simple helper to prepare data for LLM prompts."""
def __init__(self):
self.data = []
def add(self, item: Dict[str, Any]) -> "DataHelper":
self.data.append(item)
return self
def to_json(self) -> s…
Build a Python Utility That Verifies Backup Integrity Automatically
Automatically compute and verify SHA-256 checksums of backup files using a JSON manifest to detect missing or corrupted data.
import hashlib
import os
import json
def compute_checksum(filepath, algorithm='sha256'):
"""Compute checksum for the given file."""
hash_func = hashlib.new(algorithm)
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
hash_func.update(chunk)
return hash_f…
Find the Largest Files Consuming Disk Space with a Beautiful Terminal Report in Python
Scan a directory recursively and print a formatted terminal report of the largest files, with human-readable sizes.
import os
import sys
from pathlib import Path
def get_largest_files(directory: str, count: int = 10) -> list:
"""
Scan the given directory and return the largest files.
Args:
directory: Path to the directory to scan
count: Number of largest files to return
Returns:
…
Generate Beautiful Project Documentation from Python Source Code Automatically
Automatically generate a markdown summary of function docstrings from any Python source file using the AST module.
import ast
import inspect
from pathlib import Path
def extract_docstrings_from_file(filepath):
"""Parse a Python file and collect function docstrings."""
source = Path(filepath).read_text()
tree = ast.parse(source)
docs = []
for node in ast.walk(tree):
if isinstance(node, (ast.FunctionDef…
Generate a Monthly Report CSV from Log Files in Python
Reads a CSV log file, filters events by a given month, aggregates daily event counts and revenue, and writes a summarized monthly report to a new CSV.
import csv
from collections import defaultdict
from datetime import datetime
def generate_monthly_report(log_file: str, month: str, output_file: str) -> None:
events_by_date = defaultdict(int)
revenue_by_date = defaultdict(float)
with open(log_file, 'r') as f:
for line in f:
date_…
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…
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…
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