Reference library

Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

99 matches
Algorithms & data structures easy

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.

pivot array prefix-sum
Python
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, -…
13 0 Open
Algorithms & data structures easy

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.

equilibrium-index prefix-sums arrays
Python
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 =…
13 0 Open
Algorithms & data structures easy

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.

pascal-triangle dynamic-programming algorithms
Python
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__":
…
14 0 Open
Algorithms & data structures easy

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.

list zip list-comprehension
Python
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)
13 0 Open
Algorithms & data structures easy

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.

dot product zip sum
Python
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__":
  …
13 0 Open
Algorithms & data structures medium

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.

two-pointers sorting four-sum
Python
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…
13 0 Open
Algorithms & data structures easy

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.

deque sliding-window streaming
Python
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…
12 0 Open
Algorithms & data structures medium

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.

binary-search greedy array
Python
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…
15 0 Open
Comprehensions & generators easy

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.

generators enumerate running-total
Python
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…
14 0 Open
Comprehensions & generators easy

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.

generator accumulate cumulative-sum
Python
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]
14 0 Open
Comprehensions & generators medium

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.

backpressure producer-consumer deque
Python
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…
14 0 Open
Comprehensions & generators easy

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.

comprehensions generators data-checking
Python
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 {
  …
13 0 Open
Comprehensions & generators easy

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.

comprehensions generators list-comprehension
Python
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…
11 0 Open
Comprehensions & generators easy

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.

generator sum squares
Python
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)}")
14 0 Open
AI & LLM integration patterns easy

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.

jsonl audit llm
Python
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…
15 0 Open
AI & LLM integration patterns easy

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.

llm context compression
Python
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…
14 0 Open
AI & LLM integration patterns easy

How to compute ROUGE recall in Python

Compute ROUGE recall by counting token overlap between a reference and candidate summary with pure Python.

rouge nlp evaluation
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…
12 0 Open
AI & LLM integration patterns easy

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.

llm json prompt-engineering
Python
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…
16 0 Open
Automation & scripting medium

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.

sha256 backup integrity
Python
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…
52 0 Open
Automation & scripting medium

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.

file-system disk-space pathlib
Python
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:
      …
44 0 Open
Automation & scripting medium

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.

ast automation documentation
Python
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…
34 0 Open
Automation & scripting easy

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.

csv logs report
Python
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_…
14 0 Open
Automation & scripting medium

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.

psutil memory monitoring
Python
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…
36 0 Open
Automation & scripting easy

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).

pytest subprocess email
Python
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…
13 0 Open

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Guide: free Python code samples library

Copy-ready Python snippets for learners and developers

PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.

How to use this library

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. Run it in the IDE, tweak values, then take a related quiz or tutorial lesson

Samples vs tutorials and challenges

Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.