Python Code
Samples
Easy snippets you can copy, study, and run in the browser editor.
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 Check and Manipulate Strings in Python
Demonstrates core string inspection and transformation methods like case conversion, trimming, splitting, and membership checks on a sample string.
text = " Hello, Python Learners! "
print(f"Original: '{text}'")
print(f"Lowercase: '{text.lower()}'")
print(f"Uppercase: '{text.upper()}'")
print(f"Title case: '{text.title()}'")
print(f"Stripped: '{text.strip()}'")
print(f"Length: {len(text)}")
print(f"Replace: '{text.replace('Python', 'Programming')}'")
print(f"S…
How to Compare Two Strings in Python
Compares two string values and returns a detailed report with equality, case-insensitive comparison, lengths, and uppercase versions.
def compare_data(first_value, second_value):
"""Compare two string values and return a report."""
if first_value == second_value:
status = "MATCH"
else:
status = "DIFFER"
return {
"first_value": first_value,
"second_value": second_value,
"status": status,
…
How to Generate Text Helper Functions in Python
Three simple Python functions that repeat, join, and count characters in strings for beginners.
def repeat_text(text, times):
"""Repeat a string a given number of times."""
return text * times
def join_words(words, separator=" "):
"""Join a list of words into a single string."""
return separator.join(words)
def count_characters(text):
"""Count character occurrences in a string."""
ret…
How to Process Text in Python: Normalize Whitespace and Count Words
A beginner-friendly function that normalizes whitespace in a string and counts total and unique words using Python's standard library.
def process_text(text):
"""Basic text processing: normalize whitespace and count words."""
normalized = " ".join(text.split())
word_count = len(normalized.split())
char_count = len(normalized)
# Count unique words
unique_words = set(normalized.lower().split())
unique_count = len(unique…
How to build a text helper in Python for beginners
This code provides easy-to-use functions for cleaning text, removing punctuation, counting word frequencies, and summarizing strings — perfect for beginners.
def clean_text(text: str) -> str:
"""Clean and normalize a text string."""
text = text.strip()
text = text.replace(" ", " ")
text = text.capitalize()
text = text.replace(".", ".")
return text
def remove_punctuation(text: str) -> str:
"""Remove common punctuation marks from a string."""
…
Python String Helper Functions for Beginners
A set of beginner-friendly Python functions that count words, reverse text, convert to title case, strip punctuation, and compute character frequency from a string.
def count_words(text):
"""Count the number of words in a string."""
return len(text.split())
def reverse_text(text):
"""Reverse the entire string."""
return text[::-1]
def title_case(text):
"""Capitalize the first letter of each word."""
return text.title()
def remove_punctuation(text):
…
Text Processor Functions for Beginners in Python
Demonstrates simple text-processing utilities: word counting, word reversal, whitespace normalization, and lowercase conversion using basic string methods.
def count_words(text):
"""Return the number of words in a string."""
return len(text.split())
def reverse_words(text):
"""Return the text with words in reverse order."""
return ' '.join(text.split()[::-1])
def remove_extra_spaces(text):
"""Return text with extra whitespace collapsed to a single s…
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 Loop Through Lists in Python for Beginners
Transform, filter, sum, and find the maximum in a Python list using basic for loops and conditionals.
def transform_data(numbers):
"""Basic transformation examples using lists and loops."""
doubled = []
for n in numbers:
doubled.append(n * 2)
return doubled
def filter_even(numbers):
"""Keep only even numbers using a loop and condition."""
evens = []
for n in numbers:
if n …
How to Merge Lists in Python with Default Parameters
This Python function merges two lists using the + operator and demonstrates default parameters, allowing the second argument to be omitted.
def merge_lists(list1, list2=["default"]):
"""Merge two lists and return the combined result."""
return list1 + list2
if __name__ == "__main__":
# Example with default parameter
print("With default:", merge_lists([1, 2, 3]))
# Example with both arguments provided
print("With custom:", me…
How to Use Default Parameters with Python's Split Function
Create a reusable Python wrapper around str.split with sensible default parameters for delimiter and maxsplit, showing beginners how default arguments work.
def split_with_defaults(text, delimiter=" ", maxsplit=-1):
"""
Split a string into parts using a delimiter.
Default behavior: split on spaces, unlimited splits.
"""
parts = text.split(delimiter, maxsplit)
return parts
if __name__ == "__main__":
# Example usage with defaults and custom par…
Python Filter Function with Default Parameters for Beginners
Create a reusable filter function with default parameters to keep or exclude numbers above or below a threshold.
def filter_numbers(numbers, threshold=0, reverse=False):
"""Return numbers that pass the threshold filter.
Args:
numbers: list of numbers to filter
threshold: minimum value to keep (default 0)
reverse: if True, keep numbers below threshold (default False)
"""
if reverse:
…
How to Catch ValueError in Python
Shows how to handle a ValueError with try-except so a bad int() conversion doesn't crash the script.
try:
number = int("not_a_number")
print(f"Parsed successfully: {number}")
except ValueError as e:
print(f"Error: {e}")
print("Please provide a valid integer.")
print("Program continues running.")
How to Handle ValueError Exceptions in Python
A beginner-friendly example showing how to catch ValueError and related exceptions with try-except blocks in Python.
def divide_numbers(a, b):
try:
result = a / b
return f"{a} / {b} = {result}"
except ZeroDivisionError:
return "Error: Cannot divide by zero."
except TypeError:
return "Error: Please provide numbers, not strings."
except ValueError:
return "Error: Invalid value de…
How to Handle ValueError and Multiple Exceptions in Python
This code demonstrates try/except blocks for beginners, handling ZeroDivisionError, TypeError, and ValueError with two practical functions: dividing numbers and parsing strings to floats.
def divide_numbers(a, b):
"""Divide two numbers with error handling for beginners."""
try:
result = a / b
print(f"{a} / {b} = {result}")
return result
except ZeroDivisionError:
print(f"Error: Cannot divide {a} by zero!")
except TypeError:
print(f"Error: Both argu…
How to Handle ValueError with try except in Python
Shows a beginner-friendly try/except pattern that catches ValueError when converting text to an integer, prints a helpful message, and returns None instead of crashing.
def parse_number(text):
try:
return int(text)
except ValueError:
print(f"ValueError: '{text}' is not a valid integer.")
return None
if __name__ == "__main__":
user_input = "abc"
result = parse_number(user_input)
print(f"Parsing '{user_input}' returned: {result}")
vali…
How to Use try except ValueError in Python to Parse Numbers
Convert strings to integers safely with try/except ValueError and TypeError, returning a value-or-error tuple.
def parse_number(text):
"""Safely convert a string to an integer, handling errors gracefully."""
try:
value = int(text)
return value, None
except ValueError as error:
return None, f"Conversion failed: {error}"
except TypeError as error:
return None, f"Wrong type provided…
Split try except ValueError handler for beginners in Python
Demonstrates how to handle ValueError and ZeroDivisionError separately using try/except blocks, with beginner-friendly examples for parsing and division.
def parse_number(text):
try:
number = int(text)
return f"Parsed successfully: {number}"
except ValueError as error:
return f"Conversion failed: {error}"
def divide_numbers(dividend, divisor):
try:
result = dividend / divisor
return f"Division result: {result}"
e…
Try Except ValueError in Python: Handle Conversion Errors
Catch ValueError exceptions when converting strings to integers or performing arithmetic, returning None on failure instead of crashing.
def convert_to_int(value):
try:
return int(value)
except ValueError as error:
print(f"Conversion failed: {error}")
print(f"Problem value was: {repr(value)}")
return None
def divide_numbers(numerator, denominator):
try:
result = numerator / denominator
retur…
Validate try except ValueError handler for beginners — errors debugging
Learn how to validate user input and handle division errors safely using try/except with ValueError and ZeroDivisionError in Python.
def divide_numbers(a, b):
"""Divide two numbers, catching division by zero and value errors."""
try:
result = a / b
except ZeroDivisionError:
print("Error: Cannot divide by zero!")
return None
except TypeError:
print("Error: Both arguments must be numbers!")
retu…
How to Group Files by Extension in Python
Group file names by their file extension using a dictionary and pathlib, producing a simple clear mapping for beginners.
from pathlib import Path
def group_data_by_extension(files: list[Path]) -> dict[str, list[str]]:
"""Group file names by their extension."""
grouped: dict[str, list[str]] = {}
for file in files:
ext = file.suffix.lower()
grouped.setdefault(ext, []).append(file.name)
return grouped
if…
How to Use Dictionaries and Sets in Python for Beginners
Demonstrates Python dictionary operations and set operations with examples, including access, modification, defaults, and set algebra.
def demonstrate_collections():
# Dictionary basics
student = {
"name": "Alice",
"age": 20,
"courses": ["Math", "Physics"]
}
print("Dictionary:", student)
# Access and modify
student["age"] = 21
student["grade"] = "A"
print("Modified:", student)
# Get with d…
How to Use Dictionaries and Sets in Python for Beginners
Introduces Python dictionaries and sets with practical examples including creating, modifying, and performing set operations, plus a word-frequency counter.
def demonstrate_dict_sets():
# Create a dictionary with basic info
person = {
"name": "Alice",
"age": 30,
"city": "New York"
}
print("Dictionary:", person)
# Access and modify dictionary values
person["age"] = 31
person["email"] = "alice@example.com"
print("Afte…
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.