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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

32 matches
Strings & text easy

Count Characters, Words, and Lines in Python Text

Counts characters, words, lines, and the most common words in a given string using Python's standard library.

text-analysis counter strings
Python
from collections import Counter


def count_data(text):
    """Count characters, words, lines, and most common words in text."""
    char_count = len(text)
    word_count = len(text.split())
    line_count = text.count("\n") + 1
    word_freq = Counter(text.lower().split())
    most_common = word_freq.most_common(3)

…
16 0 Open
Strings & text easy

Find Most Frequent Character in a String in Python

Count character frequencies in a Python string using a dictionary and return the character that appears most often with a max() key function.

string dictionary counting
Python
def most_frequent_char(s: str) -> str:
    if not s:
        return ""
    
    char_count = {}
    for ch in s:
        char_count[ch] = char_count.get(ch, 0) + 1
    
    max_char = max(char_count, key=char_count.get)
    return max_char

if __name__ == "__main__":
    text = "programming"
    result = most_frequent…
12 0 Open
Strings & text easy

How to Count Vowels in a String in Python

Counts uppercase and lowercase vowels in a given string using a set and a generator expression.

strings vowels counting
Python
def count_vowels(text):
    vowels = set("aeiouAEIOU")
    return sum(1 for char in text if char in vowels)

if __name__ == "__main__":
    sample = "Hello, World!"
    result = count_vowels(sample)
    print(f"Vowel count in '{sample}': {result}")
11 0 Open
Strings & text easy

How to Process Text in Python

This code processes multiline text by splitting lines, stripping whitespace, counting words and characters, and converting to lowercase.

text-processing strings beginner
Python
def process_text(text):
    lines = text.split("\n")
    clean_lines = []
    for line in lines:
        stripped = line.strip()
        if stripped:
            tokens = stripped.split()
            title_case = stripped.lower()
            clean_lines.append({
                "raw": stripped,
                "word_c…
12 0 Open
Strings & text easy

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.

string-manipulation text-processing word-count
Python
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."""
 …
11 0 Open
Strings & text easy

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.

text-processing string-methods word-count
Python
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…
13 0 Open
Lists & loops easy

How to Build a Frequency Map from a List in Python

This code builds a dictionary that maps each unique element in a list to its count using the Counter class from the collections module.

counter frequency dictionary
Python
from collections import Counter

def build_frequency_map(values):
    """Return a dictionary mapping each unique value to its frequency."""
    return dict(Counter(values))

if __name__ == "__main__":
    data = ["apple", "banana", "apple", "cherry", "banana", "apple"]
    freq_map = build_frequency_map(data)
    prin…
12 0 Open
Lists & loops easy

How to Build a Text Processor with Lists and Loops in Python

A beginner-friendly Python script that analyzes text by counting sentences, words, and word lengths using lists and for loops, then prints the results.

text-processing loops lists
Python
def process_text(text):
    """Simple text processor for beginners using lists and loops."""
    sentences = text.replace('!', '.').replace('?', '.').split('.')
    words = text.split()
    
    word_counts = []
    for sentence in sentences:
        sentence_word_count = len(sentence.split())
        word_counts.appe…
12 0 Open
Lists & loops easy

How to Count Occurrences of a Value in a Python List

Counts how many times a specific value appears in a list using a simple loop and a counter variable.

counting loops lists
Python
def count_occurrences(data, target):
    count = 0
    for item in data:
        if item == target:
            count += 1
    return count


if __name__ == "__main__":
    numbers = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
    target_value = 5
    result = count_occurrences(numbers, target_value)
    print(f"The value {targ…
12 0 Open
Files & data easy

Count Files by Extension in Python

Count files in a directory grouped by file extension using Python's standard library.

files pathlib directory
Python
from pathlib import Path

def count_files_by_extension(directory: str) -> dict[str, int]:
    """Count files in a directory grouped by file extension."""
    data = {}
    for path in Path(directory).iterdir():
        if path.is_file():
            ext = path.suffix.lower() or "(no extension)"
            data[ext] =…
13 0 Open
Files & data easy

How to Find Files by Extension in Python

This code walks a directory tree with pathlib, collects all file paths, and counts them by extension to summarize a project's contents.

pathlib file-system recursion
Python
from pathlib import Path

def get_project_files(base_path="."):
    """Return a sorted list of all file paths under base_path."""
    base = Path(base_path)
    files = [p for p in base.rglob("*") if p.is_file()]
    return sorted(files)

def count_by_extension(files):
    """Return a dict mapping extension (lowercase…
11 0 Open
Dictionaries & sets easy

Build a defaultdict histogram of categories in Python

Count occurrences of each category in a list using collections.defaultdict(int) for automatic initialization.

defaultdict histogram collections
Python
from collections import defaultdict

def build_category_histogram(items):
    """Count occurrences of each category in a list of items."""
    histogram = defaultdict(int)
    for item in items:
        histogram[item] += 1
    return dict(histogram)

if __name__ == "__main__":
    categories = ["fruit", "vegetable", …
10 0 Open
Dictionaries & sets easy

Count Words in Python with Dictionaries and Sets

Text analysis example that counts total words, finds unique words with a set, and tallies character frequencies with a dictionary.

dictionaries sets text-processing
Python
def analyze_text(text: str) -> dict:
    """Count words, find unique words, and show common characters."""
    words = text.lower().split()
    word_count = len(words)
    unique_words = set(words)
    char_counts = {}
    
    for word in words:
        for char in word:
            if char.isalpha():
               …
12 0 Open
Dictionaries & sets easy

How to Count Elements and Find Duplicates in a Python List

Count occurrences of each element in a list, extract unique values, and identify duplicates using Python dictionaries and sets.

dictionary set counting
Python
def analyze_counts(data):
    """Count elements, return unique values, and find duplicates."""
    
    # Count occurrences using a dictionary
    counts = {}
    for item in data:
        counts[item] = counts.get(item, 0) + 1
    
    # Alternative compact approach with set
    unique_items = set(data)
    
    # Fi…
11 0 Open
Dictionaries & sets easy

How to Count Word Frequencies in Python

Count how often each word appears in a string and list the unique words using Python dictionaries and sets.

dictionaries sets text-processing
Python
def text_processor(text):
    words = text.lower().split()
    word_count = {}
    for word in words:
        word_count[word] = word_count.get(word, 0) + 1
    unique_words = set(words)
    return word_count, unique_words

if __name__ == "__main__":
    sample_text = "The quick brown fox jumps over the lazy dog and t…
13 0 Open
Dictionaries & sets easy

How to Count Word Frequencies in Python with Counter and Sets

This code processes a text string by lowercasing, splitting into words, counting frequencies with Counter, and extracting unique and sorted word lists using sets.

counter sets text-processing
Python
from collections import Counter

def process_text(text):
    words = text.lower().split()
    word_counts = Counter(words)
    unique_words = set(words)
    sorted_words = sorted(unique_words)
    
    return {
        "total_words": len(words),
        "unique_words": len(unique_words),
        "word_frequencies": di…
11 0 Open
Dictionaries & sets easy

How to Use Counter for Most Common Elements in Python

This code demonstrates how to find the most frequent elements in a list using Python's Counter class from the collections module.

collections counter frequency
Python
from collections import Counter

def most_common_elements(items, n=1):
    """Return the n most common elements and their counts."""
    counter = Counter(items)
    return counter.most_common(n)

if __name__ == "__main__":
    data = ["apple", "banana", "apple", "orange", "banana", "apple", "grape"]
    print(most_co…
12 0 Open
Dictionaries & sets easy

Multiset with Counter update and elements in Python

Demonstrates using collections.Counter as a multiset: updating counts with update() and iterating elements() to get repeated items.

counter multiset collections
Python
from collections import Counter

multiset = Counter(['apple', 'banana', 'apple'])

multiset.update(['banana', 'cherry', 'apple'])

print("Elements after update:", sorted(multiset.elements()))
print("Counts:", dict(multiset))
print("Most common:", multiset.most_common(2))
12 0 Open
OOP & classes easy

How to Count Items in a Python Class

A beginner-friendly Inventory class that stores item quantities in a dictionary and provides add, remove, count, and summary methods.

oop classes inventory
Python
class Inventory:
    def __init__(self):
        self.items = {}

    def add(self, item, quantity=1):
        self.items[item] = self.items.get(item, 0) + quantity

    def remove(self, item, quantity=1):
        if item not in self.items:
            raise ValueError(f"{item} not in inventory")
        self.items[it…
12 0 Open
Algorithms & data structures easy

Count Smaller Elements to the Right in Python

Return a list where each index counts how many elements to its right are smaller than that element using a clean O(n²) nested-loop approach.

brute-force nested-loops counting
Python
def count_smaller_elements(arr):
    """
    Return a list where result[i] is the number of elements 
    to the right of arr[i] that are smaller than arr[i].
    """
    result = []
    for i in range(len(arr)):
        count = 0
        for j in range(i + 1, len(arr)):
            if arr[j] < arr[i]:
               …
14 0 Open
Algorithms & data structures easy

Find Elements Appearing More Than n/3 Times in Python

Return all elements that occur more than len(array)/3 times using a simple dictionary counter.

majority-element dictionary counting
Python
def majority_third(arr):
    """Return elements appearing more than len(arr)/3 times."""
    cutoff = len(arr) / 3
    counts = {}
    for x in arr:
        counts[x] = counts.get(x, 0) + 1
    return [x for x, c in counts.items() if c > cutoff]


if __name__ == "__main__":
    test1 = [3, 2, 3]
    test2 = [1, 1, 1, …
11 0 Open
Algorithms & data structures medium

Find Missing Numbers, Duplicates, and Ranges in Python

Analyze a list to identify missing numbers, duplicate values, and contiguous ranges using sets and the Counter class.

algorithms sets counting
Python
def find_missing_duplicates_ranges(numbers):
    """Find missing numbers, duplicates, and ranges in a list."""
    from collections import Counter
    
    if not numbers:
        return {"missing": [], "duplicates": [], "ranges": []}
    
    full_range = set(range(min(numbers), max(numbers) + 1))
    present = set(n…
12 0 Open
Algorithms & data structures medium

Game of Life Next State Grid in Python

Compute the next generation of Conway's Game of Life from a 2D grid using the standard three rules with neighbor counting.

game-of-life grid cellular-automaton
Python
def next_state(grid):
    m, n = len(grid), len(grid[0])
    new = [[0] * n for _ in range(m)]
    for r in range(m):
        for c in range(n):
            total = 0
            for dr in (-1, 0, 1):
                for dc in (-1, 0, 1):
                    if dr == 0 and dc == 0:
                        continue
   …
13 0 Open
Algorithms & data structures easy

How to Count Occurrences of Each Value in Python

Count how many times each value appears in a list using Python's Counter from the collections module.

counter counting collections
Python
from collections import Counter

def count_occurrences(values):
    """Return a dictionary mapping each value to its count."""
    return dict(Counter(values))

if __name__ == "__main__":
    sample_data = ["apple", "banana", "apple", "cherry", "banana", "apple"]
    result = count_occurrences(sample_data)
    print(r…
9 0 Open

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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

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. 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.