Strings & text
Format, split, join, parse, and clean text — everyday Python string patterns.
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…Browse by section
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Strings & text — Python code examples
What you will find here
This page collects strings & text snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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.