Python Code
Samples
Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Extract Data from Strings in Python: Beginner's Guide
A beginner-friendly helper that splits a comma-separated string into a list, shows word count, and extracts the first and last words using Python's split() and join() methods.
text = "python,string,extract,beginner"
words = text.split(",")
print("Full text:", text)
print("Word count:", len(words))
print("First word:", words[0])
print("Last word:", words[-1])
joined = " | ".join(words)
print("Joined with separator:", joined)
Find Data From a String in Python: Stats, Clean, Keywords
Three helper functions for beginners: compute character/word/sentence stats, normalize whitespace and case, and extract unique sorted keywords from a string.
def get_text_stats(text):
"""Return basic statistics about a string."""
words = text.split()
sentences = text.replace('!', '.').replace('?', '.').split('.')
sentences = [s for s in sentences if s.strip()]
return {
'characters': len(text),
'words': len(words),
'sentences': le…
How to Convert Data to Strings in Python
Convert common data types like bytes, numbers, containers, and None to readable strings with a safe helper function.
def to_str(value):
"""Convert common types to a readable string, safe for beginners."""
if isinstance(value, bytes):
return value.decode("utf-8")
if isinstance(value, (dict, list, tuple, set)):
return str(value)
if value is None:
return ""
return str(value)
if __name__ == …
How to Detect Expired Domains Using Python
Parse a list of domain registration data and compare expiry dates to today to find expired domains.
import datetime
# List of test domains with fake registration and expiry dates
# Format: (domain, registration_date, expiry_date)
test_domains = [
('example.com', '2020-01-15', '2024-01-15'), # Expired
('google.com', '1997-09-15', '2026-09-15'), # Still active
('test-site.org', '2019-06-01', '2023-06-0…
How to Detect PII in Documents Using Python
Use regex patterns to automatically detect emails, phone numbers, SSNs, and credit card numbers in text documents.
import re
from typing import List, Dict
def detect_pii(text: str) -> Dict[str, List[str]]:
patterns = {
"email": r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}",
"phone": r"\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}",
"ssn": r"\b\d{3}-\d{2}-\d{4}\b",
"credit_card": r"\b\d{4}[- ]?\d{4}[-…
How to Extract Digits Only from a String in Python
This code uses a regular expression to remove all non-digit characters from a mixed string, returning only the digits.
import re
def extract_digits(text):
"""Return only the digits from the given text as a string."""
return re.sub(r'\D', '', text)
if __name__ == "__main__":
mixed = "abc123def456!@#789"
result = extract_digits(mixed)
print(result)
How to Filter Text to Only Letters, Numbers, and Spaces in Python
A beginner-friendly function that filters a string to keep only alphabetic characters, digits, and spaces, removing punctuation and symbols.
def filter_text(text, keep_alpha=True, keep_digits=True, keep_spaces=True):
allowed = set()
if keep_alpha:
allowed.update("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ")
if keep_digits:
allowed.update("0123456789")
if keep_spaces:
allowed.add(" ")
return "".join(ch f…
How to Group Data by Category in Python
Group a list of (category, value) tuples into a dictionary of lists using the setdefault method.
def group_by_category(data):
"""Group list of (category, value) tuples into dictionaries of lists."""
groups = {}
for category, value in data:
groups.setdefault(category, []).append(value)
return groups
if __name__ == "__main__":
items = [
("fruit", "apple"),
("veg", "carro…
How to Slugify a String in Python
Convert any text into a URL-friendly slug using the standard library's unicodedata and re modules.
import re
import unicodedata
def slugify(text):
text = unicodedata.normalize('NFKD', text)
text = text.encode('ascii', 'ignore').decode('ascii')
text = re.sub(r'[^\w\s-]', '', text).strip().lower()
text = re.sub(r'[-\s]+', '-', text)
return text
if __name__ == "__main__":
title = "Hello, Worl…
Normalize unicode accents to ASCII in Python
This code converts accented Unicode characters to ASCII equivalents using the standard library's unicodedata module.
import unicodedata
def normalize_accents(text: str) -> str:
"""Convert accented unicode characters to ASCII equivalents."""
decomposed = unicodedata.normalize('NFD', text)
ascii_text = ''.join(
char for char in decomposed
if unicodedata.category(char) != 'Mn'
)
return unicodedata.n…
Compare Two Lists in Python: Common, Only in First, Only in Second
A beginner-friendly helper that loops over two lists and returns items common to both, items only in the first list, and items only in the second list.
def compare_lists(list1, list2):
common = []
only_in_first = []
only_in_second = []
for item in list1:
if item in list2:
common.append(item)
else:
only_in_first.append(item)
for item in list2:
if item not in list1:
only_in_second…
Extract Data by Type from a List in Python: Numbers and Strings
Loop through a mixed list to filter out numeric and string values into separate lists.
def extract_numbers(items):
"""Extract all numeric values from a mixed list."""
numbers = []
for item in items:
if isinstance(item, (int, float)) and not isinstance(item, bool):
numbers.append(item)
return numbers
def extract_strings(items):
"""Extract all string values from a…
Generate Data Helper for Beginners in Python
Define two functions that create a random list of integers and then compute basic summary statistics like count, total, average, maximum, and minimum using simple loops.
from random import randint
def build_dataset(size: int, max_val: int) -> list[int]:
data = []
for _ in range(size):
data.append(randint(1, max_val))
return data
def summarize(data: list[int]) -> dict[str, float]:
total = 0
maximum = data[0]
minimum = data[0]
for value in data:
…
How to Convert Data Types in Python Lists
Convert a mixed list of values to integers, floats, or strings based on their content, with graceful fallback for unparseable strings.
def convert_data(data):
"""Convert a mixed list of values to strings, ints, and floats."""
result = []
for item in data:
if isinstance(item, (int, float)):
result.append(str(item))
elif isinstance(item, str):
try:
if '.' in item:
r…
How to Filter None Values from a Mixed List in Python
Filter None values from a mixed Python list using a list comprehension with the `is not None` condition.
mixed_list = [1, None, "hello", None, 3.14, None, [1, 2], None]
filtered_list = [item for item in mixed_list if item is not None]
print(f"Original list: {mixed_list}")
print(f"Filtered list: {filtered_list}")
print(f"Original length: {len(mixed_list)}, Filtered length: {len(filtered_list)}")
How to Normalize a List of Numbers in Python
This Python function normalizes a list of numeric values to the range [0, 1] using min-max scaling, returning a new list and leaving the original unchanged.
def normalize(data):
"""
Normalize a list of numeric values to the range [0, 1].
Returns a new list, leaving the original unchanged.
"""
if not data:
return []
min_val = min(data)
max_val = max(data)
# Handle the edge case where all values are identical
if min_val …
How to Normalize a List of Numbers to the 0-1 Range in Python
Scale a list of numbers so the minimum becomes 0 and the maximum becomes 1 using min-max normalization.
def min_max_normalize(values):
"""Normalize a list of numbers to the [0, 1] range."""
if not values:
return []
min_val = min(values)
max_val = max(values)
if min_val == max_val:
return [0.0] * len(values)
return [(x - min_val) / (max_val - min_val) for x in values]
if __name__…
How to Parse Delimited Data into a Python List
Splits a pipe-delimited string, strips whitespace, filters empty items, and returns a clean list with a loop.
def parse_data(raw_data):
"""Parse a pipe-delimited string into a list of cleaned items."""
items = raw_data.split("|")
parsed = []
for item in items:
cleaned = item.strip()
if cleaned:
parsed.append(cleaned)
return parsed
if __name__ == "__main__":
data = " apple…
How to Standardize a List with Z-Score Normalization in Python
This code computes the z-score for each number in a list, standardizing the data to have zero mean and unit variance using the statistics module.
import statistics
def z_score_normalize(values):
"""Standardize a list of numbers using z-score normalization."""
if not values or len(values) < 2:
raise ValueError("Need at least 2 values for meaningful z-score normalization")
mean = statistics.mean(values)
std_dev = statistics.stdev(val…
How to Validate List Data in Python
A beginner-friendly validation helper that checks if data is a list, enforces minimum length, and optionally verifies item types with clear error messages.
def validate_data(data, expected_types=None, min_length=1):
"""Validate that data is a non-empty list and optionally check item types."""
if not isinstance(data, list):
return False, f"Expected a list, got {type(data).__name__}"
if len(data) < min_length:
return False, f"List must have…
How to check list items by type and emptiness in Python
Loop through a list with enumerate(), classify each item as empty, number, or text, and print a formatted status for each element.
def check_data(data):
"""Check each item in a list and print whether it's valid."""
for i, item in enumerate(data):
if item is None or item == "":
status = "empty"
elif isinstance(item, (int, float)):
status = "number"
else:
status = "text"
pr…
Replace Negative Values in a List with Python
This code defines a function that replaces every negative number in a list with a replacement value, defaulting to zero, using a list comprehension.
def replace_if_negative(values, replacement=0):
return [replacement if value < 0 else value for value in values]
if __name__ == "__main__":
numbers = [5, -3, 8, -1, 0, -7, 2]
result = replace_if_negative(numbers)
print(f"Original: {numbers}")
print(f"Replaced: {result}")
Build a Progress Callback Function for Loops in Python
Create a reusable progress callback that receives per-step data and lets callers log or update a UI as a loop runs.
def run_with_progress(items, desc="Processing", step_callback=None):
"""Run a loop with progress updates via callback."""
total = len(items)
for idx, item in enumerate(items):
# Process the item (simulated work here)
result = item * 2
# Build progress data dictionary
if ste…
How to Parse Function Signatures in Python with inspect
Extract a function's parameter names, kinds, defaults, annotations, and return type using Python's built-in inspect module.
import inspect
def example_function(a: int, b: str = "default", *args, c: float = 1.5, **kwargs) -> bool:
"""An example function with various parameter types."""
return True
def parse_signature(func):
"""Parse a function's signature using the inspect module."""
sig = inspect.signature(func)
param…
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.