Python Code
Samples
Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Redact secrets from log message formatter in Python
Build a custom logging.Formatter that masks passwords, API keys, and credit card numbers in log output.
import re
import logging
class RedactingFormatter(logging.Formatter):
"""Formatter that masks sensitive data in log messages."""
SENSITIVE_PATTERNS = [
(re.compile(r'password[=:]\s*\S+', re.IGNORECASE), 'password=[REDACTED]'),
(re.compile(r'api[_-]?key[=:]\s*\S+', re.IGNORECASE), 'api_key…Create a Python Tool That Generates Professional Excel Dashboards
Generate a professional sales dashboard in an Excel workbook with styled headers, a bar chart, and formatted number cells using the openpyxl library.
import openpyxl
from openpyxl.chart import BarChart, Reference
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from openpyxl.utils import get_column_letter
def create_sales_dashboard(workbook_path: str) -> None:
"""Generate a professional sales dashboard in an Excel workbook."""
wb = op…Generate Timesheet Reports from Daily Logs in Python
Aggregate daily log entries by project and produce a formatted timesheet report using Python's standard library.
import json
from pathlib import Path
from collections import defaultdict
def generate_timesheet_report(daily_logs: list[dict]) -> str:
"""
Generate a timesheet report from daily log entries.
Args:
daily_logs: List of dicts with 'date', 'project', 'hours', 'task' keys
Returns:
…How to Automatically Merge Hundreds of Excel Files Without Losing Formatting in Python
Merge all .xlsx files in a folder into a single Excel workbook, preserving individual sheet structures with sheet name prefixes.
import pandas as pd
from pathlib import Path
def merge_excel_files(folder_path: str, output_path: str) -> None:
"""
Merge all .xlsx files in a folder into a single Excel file,
preserving individual sheet structures.
"""
folder = Path(folder_path)
excel_files = list(folder.glob("*.xlsx"))
…How to Convert Images Between Formats in Python
Use the Pillow library to open an image from one file format and save it to another, with error handling for missing files or conversion issues.
from PIL import Image
import sys
def convert_image_format(input_path, output_path):
try:
img = Image.open(input_path)
img.save(output_path)
print(f"Converted {input_path} to {output_path}")
except FileNotFoundError:
print(f"Error: File {input_path} not found")
sys.exit(…How to List File Information in a Directory with Python
A helper that walks a directory and returns each file's name, size, and extension as a list of dictionaries.
from pathlib import Path
def get_files_data(directory: str) -> list[dict]:
"""Return basic info about all files in a directory."""
files = []
for path in Path(directory).iterdir():
if path.is_file():
files.append({
"name": path.name,
"size": path.stat()…How to Load and Save JSON Files in Python
Load and save JSON files with pretty formatting using Python's standard library json module and pathlib.
import json
from pathlib import Path
def load_json(filepath: str) -> dict:
"""Load JSON data from a file."""
path = Path(filepath)
with path.open("r", encoding="utf-8") as f:
return json.load(f)
def save_json(filepath: str, data: dict) -> None:
"""Save data to a JSON file with pretty format…How to Parse Apache Log Files in Python
Parse Apache common log format lines into structured dictionaries using Python's standard library.
import re
from pathlib import Path
def parse_apache_line(line):
pattern = r'^(\S+) (\S+) (\S+) \[([^\]]+)\] "(\S+) (\S+) (\S+)" (\d{3}) (\S+)'
match = re.match(pattern, line)
if not match:
return None
ip, ident, user, timestamp, method, path, protocol, status, size = match.groups()
return …How to Map Dictionary Values with a Transformation Function in Python
Create a reusable function that applies a transformation to every value in a dictionary and returns a new dict.
def transform_dict_values(d, func):
"""Apply a transformation function to every value in a dictionary."""
return {key: func(value) for key, value in d.items()}
if __name__ == "__main__":
original = {"a": 1, "b": 2, "c": 3}
doubled = transform_dict_values(original, lambda x: x * 2)
print(doubled)
…Group Data Helper Class in Python
A simple Python class that stores items under named groups, retrieves groups, items, and counts, and formats them as a readable summary.
class GroupData:
"""A simple helper class to store and group data for beginners."""
def __init__(self):
self.items = []
def add(self, item, group):
"""Add an item under a given group name."""
self.items.append({"item": item, "group": group})
def get_groups(self):
"""R…How to Create a Data Formatter Class in Python
A beginner-friendly helper class to format lists, dictionaries, and stored records into readable strings.
class DataFormatter:
"""Helper class for beginners to format common data types."""
def __init__(self, name="data"):
self.name = name
self.records = []
def add_record(self, key, value):
"""Add a key-value record to the formatter."""
self.records.append({"key": key, …Python Adapter Class: Wrap Legacy Interface
Convert a legacy system's interface into a modern one using the Adapter pattern in Python, translating method calls and data formats.
class LegacySystem:
"""Legacy interface - old method names and parameter format."""
def query_employee_info(self, emp_id, emp_name):
return f"Legacy: {emp_id} - {emp_name}"
def update_employee_department(self, emp_id, department_code):
return f"Legacy: Updated {emp_id} to dept {department_…How to Use List Comprehensions and Generators to Format Data in Python
A beginner-friendly helper that formats dictionaries into strings using a list comprehension and generates squared numbers lazily with a generator.
def format_data(items):
"""Format a list of dictionaries into readable strings."""
formatted = [
f"{item.get('name', 'Unknown')}: {item.get('value', 0)} units"
for item in items
if item.get('value', 0) > 0
]
return formatted if formatted else ["No positive values found"]
def g…How to Use List Comprehensions and Generators to Transform Data in Python
Transform a list of integers by squaring even numbers with a list comprehension and cubing odd numbers with a generator.
def transform_data(data):
"""
Transform a list of integers:
- squares of even numbers using a list comprehension
- cubes of odd numbers using a generator
"""
squares = [num ** 2 for num in data if num % 2 == 0]
cubes = (num ** 3 for num in data if num % 2 != 0)
return squares, cubes
i…How to Append Few-Shot Examples to a Prompt in Python
This code builds a complete LLM prompt by appending few-shot examples in alternating user/assistant format using a simple loop.
def append_few_shot_examples(prompt: str, examples: list[tuple[str, str]], separator: str = "\n\n") -> str:
"""Append few-shot examples to a prompt in alternating user/assistant format."""
full_prompt = prompt
for user_input, assistant_output in examples:
full_prompt = f"{full_prompt}{separator}Use…How to Build a Data Helper for LLM Prompts in Python
A beginner-friendly helper class that flattens nested dictionaries, formats prompt templates, and safely parses JSON for AI/LLM pipelines.
import json
from typing import Any, Dict, List, Optional
class DataHelper:
"""Simple helper class for working with data in AI/LLM pipelines."""
def __init__(self, data: Optional[Dict[str, Any]] = None) -> None:
self.data = data or {}
def flatten(self, prefix: str = "") -> Dict[str, Any]…How to Mock OpenAI Tool Call Messages in Python
Create an assistant message with a function tool call in OpenAI's chat format, useful for testing and mocking.
from openai import OpenAI
def mock_tool_call(tool_name: str, arguments: dict) -> dict:
"""Simulate a tool call message in OpenAI style."""
return {
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "call_" + "a1b2c3d4e5f6",
"type…Serialize and Format Data for LLM Prompts in Python
Use dataclasses and the json module to convert Python objects to JSON strings, parse them back, and format structured data into prompt-friendly text for LLM calls.
import json
from dataclasses import dataclass, asdict
@dataclass
class Recipe:
"""Simple data model to represent a recipe."""
name: str
cuisine: str
prep_minutes: int
def to_json(recipe: Recipe) -> str:
"""Serialize a Recipe to a JSON string."""
return json.dumps(asdict(recipe), indent=2)
…Convert HTML Tables to Excel Reports in Python
Convert HTML tables into formatted Excel reports using BeautifulSoup and Pandas with auto-adjusted column widths.
import pandas as pd
from bs4 import BeautifulSoup
from pathlib import Path
def html_table_to_excel(html_file: str, excel_file: str) -> None:
"""Convert HTML table to formatted Excel report."""
with open(html_file, 'r', encoding='utf-8') as f:
html_content = f.read()
soup = BeautifulSoup(html_…Create ICS Calendar Invites in Python
This script generates a batch of calendar invites in the ICS format using the ics library.
import ics
from datetime import datetime, timedelta
def create_invites(batch):
calendar = ics.Calendar()
for event_data in batch:
event = ics.Event()
event.name = event_data["name"]
event.begin = event_data["start"]
event.end = event_data["end"]
event.description = even…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…Fill PDF Form Fields from a Mock Template in Python
Fills a PDF-style form template dictionary with user data, preserving template fields and formatting output as JSON.
import json
template = {
"first_name": "",
"last_name": "",
"email": "",
"phone": "",
"date_of_birth": "",
"address": "",
"city": "",
"state": "",
"zip_code": "",
"agree_to_terms": False
}
def fill_pdf_form(template: dict, data: dict) -> dict:
for key, value in data.items…Find Sensitive Information in Log Files with Python
Scan log files for emails, IP addresses, API keys, and passwords using regular expressions in Python.
import re
import os
from pathlib import Path
def find_sensitive_info(log_path):
"""Scans log files for patterns like emails, IPs, API keys, and passwords."""
patterns = {
'Email': r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}',
'IP Address': r'\b(?:\d{1,3}\.){3}\d{1,3}\b',
'API Key'…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:
…Browse by section
Each section groups closely related Python snippets.
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
- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- 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.