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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Decode a String with Repeated Brackets in Python
Decodes strings with patterns like '3[a]2[bc]' by using a stack to handle nested and repeated bracket groups.
def decode_string(s: str) -> str:
stack = []
current_num = 0
current_str = ""
for ch in s:
if ch.isdigit():
current_num = current_num * 10 + int(ch)
elif ch == "[":
stack.append((current_str, current_num))
current_str = ""
current_num = 0…
How to Map Strings to Uppercase in Python
Loops through a list of strings and builds a new list with each string converted to uppercase.
strings = ["hello", "world", "python", "skillset"]
uppercased = []
for s in strings:
uppercased.append(s.upper())
print(uppercased)
How to compress consecutive numbers into range strings in Python
Convert a sorted list of consecutive integers into compact range strings like '1-3', '5-6', and '15'.
def compress_ranges(nums):
"""Convert a list of sorted consecutive numbers into range strings."""
if not nums:
return []
ranges = []
start = prev = nums[0]
for num in nums[1:]:
if num == prev + 1:
prev = num
else:
if start == prev:
…
Simplify a File Path in Python with a Stack
Uses a stack to normalize an absolute Unix path by handling '.', '..', and duplicate slashes.
from pathlib import PurePosixPath
def simplify_path(path: str) -> str:
tokens = path.split('/')
stack = []
for token in tokens:
if not token or token == '.':
continue
if token == '..':
if stack:
stack.pop()
else:
stack.append…
Split a String into Multiple Lines by Width in Python
Demonstrates a word-wrap algorithm that splits a message into rows without exceeding a maximum width.
def split_message(text, max_width):
words = text.split()
rows = []
current_row = []
for word in words:
if len(" ".join(current_row + [word])) > max_width:
rows.append(" ".join(current_row))
current_row = [word]
else:
current_row.append(word)
if …
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…
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 Accumulate Streamed Tokens into a Final String in Python
Accumulate a stream of tokens into a single final string by concatenating each token in sequence.
def accumulate_tokens(tokens):
"""Accumulate a stream of tokens into a single final string."""
result = ""
for token in tokens:
result += token
return result
if __name__ == "__main__":
token_stream = ["Hello", ", ", "world", "!", " This ", "is ", "accumulated."]
final_string = accumul…
How to Batch Embed a List of Strings in Python
Batch embed a list of strings into deterministic pseudo-random vectors using a mock encoder class.
class MockEncoder:
def __init__(self, dim=8, seed=42):
self.dim = dim
self.seed = seed
def embed(self, text):
# Deterministic pseudo-random embedding based on text content
hash_val = hash(text)
import random
rng = random.Random(hash_val + self.seed)
retu…
How to Build a Prompt Template with Variable Slots in Python
Create a reusable LLM prompt template with named variable slots using Python's string.Template class and fill them with render() calls.
from string import Template
class PromptTemplate:
def __init__(self, template_text):
self.template = Template(template_text)
def render(self, **kwargs):
return self.template.substitute(**kwargs)
if __name__ == "__main__":
template = PromptTemplate(
"You are a helpful assistant …
How to Convert Data to JSON and Back in Python
Convert a Python dict into a JSON string with indentation, then parse it back into a dict, demonstrating a common round-trip conversion for beginners.
import json
from datetime import datetime
def convert_data(data):
"""Convert a dict into a JSON string and back to dict."""
json_str = json.dumps(data, indent=2)
parsed = json.loads(json_str)
return json_str, parsed
def main():
sample_data = {
"user": "alice",
"message": "hello",
…
How to Estimate Token Count in Python
Estimates tokens in a text string using a whitespace and punctuation heuristic without external libraries.
def estimate_tokens(text: str) -> int:
"""Estimate token count using whitespace and punctuation heuristics."""
if not text:
return 0
words = text.split()
total_punctuation = sum(1 for char in text if char in ".,!?;:")
special_tokens = sum(1 for char in text if char in "\n\t")
# Rough …
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.
…
How to Parse an LLM Response in Python
This code parses a JSON string from an LLM response, stripping code fences and handling common issues like whitespace, returning a Python dictionary.
import json
from typing import Any, Dict, List
def parse_llm_response(response: str) -> Dict[str, Any]:
"""Parse a JSON string from an LLM response, handling common edge cases."""
# Remove code fences if present
cleaned = response.strip()
if cleaned.startswith("
How to Render a Jinja-like Template from a Dict in Python
Replace {{placeholders}} in a string using values from a Python dict with a simple regex-based template renderer.
import re
def render_template(template, context):
pattern = re.compile(r"\{\{\s*(\w+)\s*\}\}")
def replace(match):
key = match.group(1)
return str(context.get(key, ""))
return pattern.sub(replace, template)
if __name__ == "__main__":
template = "Hello {{name}}, you have {{count}} new …
How to Truncate Text to a Token Budget in Python
Truncate a string to a maximum token budget for LLM context using the tiktoken library and OpenAI's tokenizer.
import tiktoken
def truncate_to_token_budget(text, max_tokens, model="gpt-3.5-turbo"):
enc = tiktoken.encoding_for_model(model)
tokens = enc.encode(text)
if len(tokens) <= max_tokens:
return text
truncated_tokens = tokens[:max_tokens]
return enc.decode(truncated_tokens)
if __name__ == "__…
How to hash a prompt with SHA-256 in Python
Create a SHA-256 hex fingerprint of a prompt string, with a short-prefix variant for quick references.
import hashlib
def prompt_hash_fingerprint(prompt: str) -> str:
"""Return the full SHA-256 hex digest of the prompt."""
return hashlib.sha256(prompt.encode("utf-8")).hexdigest()
def short_fingerprint(prompt: str, length: int = 12) -> str:
"""Return a short prefix of the SHA-256 digest for quick reference…
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)
…
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…
How to Generate a QR Code in Python
Generate a QR code image from a URL string using the qrcode library and save it as a PNG file.
import qrcode
# Data to encode
data = "https://www.example.com"
# Create QR code instance
qr = qrcode.QRCode(
version=1,
error_correction=qrcode.constants.ERROR_CORRECT_L,
box_size=10,
border=4,
)
# Add data to QR code
qr.add_data(data)
qr.make(fit=True)
# Create an image from the QR code
img = qr.…
Add a UUID Surrogate Key to Each Row in a CSV with Python
Generate a unique UUID string for every row in a CSV file using the standard-library uuid and csv modules.
import uuid
import csv
def add_surrogate_key(filename):
with open(filename, newline='') as f_in:
reader = csv.DictReader(f_in)
rows = list(reader)
for row in rows:
row['surrogate_key'] = str(uuid.uuid4())
with open(filename, 'w', newline='') as f_out:
writer = csv.DictWri…
How to Convert Data Types in a Python Data Pipeline
Demonstrates a simple Python data pipeline that converts string values to proper types (bool, int, float, datetime) and outputs structured JSON.
import json
from datetime import datetime
def convert_value(value):
"""Convert string values to appropriate Python types."""
if value.lower() == "true":
return True
if value.lower() == "false":
return False
if value.isdigit():
return int(value)
try:
return float(val…
How to Hash Email Addresses in a PII Masking Pipeline in Python
Replaces every email address in a text string with its SHA-256 hash to protect personally identifiable information (PII).
import hashlib
import re
def hash_email(email: str) -> str:
"""Mask an email address by hashing it with SHA-256."""
normalized = email.strip().lower()
return hashlib.sha256(normalized.encode("utf-8")).hexdigest()
def mask_pii_emails(text: str) -> str:
"""Replace all email addresses in text with their…
How to Safely Coerce Strings to Numbers in Python
A safe conversion function that turns strings into integers or floats, returning a fallback value when conversion fails.
import math
def to_number(value, fallback=None):
"""Safely coerce a string to int or float, returning fallback on failure."""
if isinstance(value, (int, float)):
return value
try:
# Try int first for clean whole numbers
return int(value)
except (ValueError, TypeError):
…
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- 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.