Strings & text
Format, split, join, parse, and clean text — everyday Python string patterns.
Convert Natural Language Dates to Datetime in Python
Parse common natural language date phrases like 'tomorrow' or 'in 3 days' into Python datetime objects using regex and timedelta.
from datetime import datetime, timedelta
import re
def parse_natural_date(text: str) -> datetime:
"""Convert common natural language date expressions to datetime objects."""
now = datetime.now()
text = text.lower().strip()
# Handle relative dates
patterns = {
r"today": now,
r"…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 Generate Initials from a Full Name in Python
Extract and uppercase the first letter of each word in a full name to produce initials using standard string methods.
def generate_initials(full_name):
parts = full_name.strip().split()
initials = ''.join(part[0].upper() for part in parts if part)
return initials
if __name__ == "__main__":
name = "john f. kennedy"
print(generate_initials(name))How to Parse and Clean Text in Python
This code defines three helper functions to parse text into lowercase words, count unique word frequencies, and clean text by removing punctuation and extra whitespace.
def extract_words(text: str) -> list[str]:
"""Return a list of lowercase words from the given text."""
return [word.lower() for word in text.split() if word.isalpha()]
def count_unique_words(text: str) -> dict[str, int]:
"""Return a dictionary with unique words and their frequencies."""
words = extra…How to Split Strings in Python (Beginner-Friendly)
Split Python strings by a delimiter into lists, plus a cleanup variant that strips whitespace and filters empty parts.
def split_text(text, delimiter=" "):
"""Split a string by a delimiter and return a list of parts."""
return text.split(delimiter)
def split_text_with_cleanup(text, delimiter=" "):
"""Split a string, stripping whitespace and filtering empty parts."""
parts = text.split(delimiter)
cleaned = [part.s…How to parse key=value pairs in Python
Parse a single line of key=value pairs separated by a delimiter into a Python dictionary.
def parse_key_value_pairs(line: str, delimiter: str = "&") -> dict:
"""Parse a single line of key=value pairs into a dictionary."""
pairs = {}
for token in line.split(delimiter):
if not token.strip():
continue
key, _, value = token.partition("=")
pairs[key.strip()] = val…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.
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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.