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Python Code Samples

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

44 matches
Functions & basics easy

Chain Generators with yield from in Python

Combine multiple generators into one seamless sequence using the `yield from` delegation syntax in Python.

generators yield delegation
Python
def numbers():
    yield 1
    yield 2
    yield 3

def letters():
    yield 'a'
    yield 'b'
    yield 'c'

def combined():
    yield from numbers()
    yield from letters()

if __name__ == "__main__":
    print(list(combined()))
16 0 Open
Functions & basics easy

How to Create Generator Functions with yield in Python

Create a memory-efficient generator function using yield to produce a Fibonacci sequence up to a limit.

generator yield fibonacci
Python
def fibonacci_sequence(limit):
    """Generate Fibonacci numbers up to a given limit."""
    a, b = 0, 1
    while a <= limit:
        yield a
        a, b = b, a + b


if __name__ == "__main__":
    fib_gen = fibonacci_sequence(100)
    
    for number in fib_gen:
        print(number, end=" ")
    print()
11 0 Open
Functions & basics easy

How to Create an Iterator Class with Dunder Methods in Python

A minimal Counter class implementing __iter__ and __next__ to act as a self-iterating iterator, yielding numbers from start to end-1.

iterators dunder-methods class
Python
class Counter:
    def __init__(self, start=0, end=5):
        self.current = start
        self.end = end

    def __iter__(self):
        return self

    def __next__(self):
        if self.current >= self.end:
            raise StopIteration
        value = self.current
        self.current += 1
        return val…
13 0 Open
Files & data medium

How to Stream Large CSV Files in Python

Process a large CSV file in memory-efficient chunks using Python's csv module, yielding batches of rows instead of loading everything at once.

csv streaming memory-efficient
Python
import csv
from pathlib import Path

def process_csv_in_chunks(file_path, chunk_size=1000):
    """Yield rows from a large CSV file in chunks without loading all into memory."""
    with open(file_path, 'r', newline='') as f:
        reader = csv.DictReader(f)
        chunk = []
        for row in reader:
            …
12 0 Open
Files & data easy

How to Walk a Directory Tree with os.walk in Python

A generator function that recursively walks a directory tree and yields every file path found using the os.walk generator.

os.walk generators directory-tree
Python
import os


def walk_directory_tree(root_path: str):
    """Walk a directory tree and yield file paths using os.walk generator."""
    for dirpath, dirnames, filenames in os.walk(root_path):
        for filename in filenames:
            yield os.path.join(dirpath, filename)


if __name__ == "__main__":
    # Create a…
12 0 Open
Files & data medium

Read Parquet-Like Columnar CSV Chunks in Python

A Python generator that reads a CSV file column-by-column, yielding dictionary chunks where each key points to a list of values—mirroring how Parquet stores data columnar.

csv columnar generator
Python
```python
import csv
from pathlib import Path
from typing import Iterator, List

def read_parquet_like_columnar(csv_path: str, column_names: List[str], chunk_size: int = 2) -> Iterator[dict]:
    """Read CSV data in columnar chunks, similar to how parquet stores columns."""
    csv_file = Path(csv_path)
    with csv_f…
13 0 Open
Dictionaries & sets medium

Find All Leaf Paths in a Nested Dict in Python

Recursively traverse a nested dictionary and yield every leaf path as a list of keys, including paths to empty dictionaries.

dictionary recursion nested-data
Python
def find_leaf_paths(data, path=None):
    if path is None:
        path = []
    
    if not isinstance(data, dict) or not data:
        yield path
        return
    
    for key, value in data.items():
        yield from find_leaf_paths(value, path + [key])

if __name__ == "__main__":
    nested = {
        "a": 1,
…
13 0 Open
Dictionaries & sets medium

Traverse Nested Dict Paths Depth-First in Python

Recursively walk a nested dictionary depth-first and yield each full path from root to leaf as lists.

recursion generators nested-dicts
Python
def depth_first_paths(node, path=None):
    if path is None:
        path = []
    
    if not isinstance(node, dict):
        yield path + [node]
        return
    
    for key, value in node.items():
        new_path = path + [key]
        if isinstance(value, dict):
            yield from depth_first_paths(value, …
13 0 Open
OOP & classes easy

How to Create an Iterable Class with __iter__ and __next__ in Python

Build custom iterable classes in Python by implementing the __iter__ and __next__ dunder methods to yield items on demand.

iterable iterator dunder-methods
Python
class EvenNumbers:
    def __init__(self, limit):
        self.limit = limit
        self.current = 0

    def __iter__(self):
        return self

    def __next__(self):
        if self.current >= self.limit:
            raise StopIteration
        result = self.current
        self.current += 2
        return resul…
14 0 Open
Algorithms & data structures easy

Drop Elements From Start While Condition Is True in Python

This generator function drops elements from the beginning of an iterable while a predicate returns true, then yields the rest.

generator iteration filtering
Python
def drop_while(predicate, iterable):
    """Drop elements from the start while predicate is true."""
    it = iter(iterable)
    for item in it:
        if not predicate(item):
            yield item
            break
    yield from it

if __name__ == "__main__":
    numbers = [1, 2, 3, 4, 1, 2, 5]
    result = list(d…
12 0 Open
Comprehensions & generators easy

Batch Rows in Chunks with a Generator in Python

Group a list of row dicts into fixed-size chunks using a generator that yields one slice per call.

generators chunking database
Python
from typing import Iterator, List


def batch_rows(rows: List[dict], batch_size: int) -> Iterator[List[dict]]:
    for i in range(0, len(rows), batch_size):
        yield rows[i:i + batch_size]


if __name__ == "__main__":
    sample_rows = [
        {"id": 1, "name": "Alice"},
        {"id": 2, "name": "Bob"},
      …
15 0 Open
Comprehensions & generators easy

Build a lazy generator to read file lines in Python

Create a generator function that yields file lines one at a time, avoiding loading the entire file into memory, and demonstrate its lazy processing.

generator file-io lazy
Python
def lazy_lines(filepath):
    """Yield lines from a file one at a time without loading the whole file into memory."""
    with open(filepath, 'r', encoding='utf-8') as file:
        for line in file:
            yield line.rstrip('\n')


if __name__ == "__main__":
    # Create a sample file to demonstrate
    sample_c…
14 0 Open
Comprehensions & generators easy

Chunk an Iterable into Batches with a Generator in Python

Yield fixed-size batches from any iterable lazily using itertools.islice inside a generator function.

generators iterators itertools
Python
from itertools import islice

def chunked(iterable, size):
    iterator = iter(iterable)
    while True:
        batch = list(islice(iterator, size))
        if not batch:
            break
        yield batch

if __name__ == "__main__":
    data = range(10)
    for batch in chunked(data, 3):
        print(batch)
14 0 Open
Comprehensions & generators easy

Cycle an iterable forever in Python

Define a generator that repeatedly yields items from an iterable, cycling back to the beginning infinitely.

generators cycle iteration
Python
def cycle_generator(iterable):
    """Yield items from iterable forever, cycling back to the start."""
    items = list(iterable)  # Convert to list so it can restart
    index = 0
    while True:
        yield items[index]
        index = (index + 1) % len(items)


if __name__ == "__main__":
    colors = ["red", "gre…
14 0 Open
Comprehensions & generators easy

Drop n items then yield rest generator

A generator that skips the first n items of an iterable and then yields the remaining items one by one.

generators iterators drop
Python
def drop(n, items):
    """Yield every item except the first n from items."""
    it = iter(items)
    for _ in range(n):
        next(it, None)  # skip first n items
    yield from it


if __name__ == "__main__":
    numbers = [10, 20, 30, 40, 50]
    result = list(drop(2, numbers))
    print(result)
11 0 Open
Comprehensions & generators easy

Enumerate a Generator With a Running Total in Python

A generator that yields each element with its index and a cumulative sum, letting you track a running total as you iterate.

generators enumerate running-total
Python
def running_total_enum(iterable):
    """Yields (index, item, running_total) for each element."""
    total = 0
    for index, item in enumerate(iterable):
        total += item
        yield index, item, total

if __name__ == "__main__":
    numbers = [10, 20, 30, 40, 50]
    for idx, value, running_sum in running_to…
14 0 Open
Comprehensions & generators easy

Flatten a Nested List in Python (Recursive Generator)

Recursively flatten arbitrarily nested lists into a single-level list using both a function and a generator with `yield from`.

recursion generators flatten
Python
def flatten(nested_list):
    """Recursively flatten a nested list into a single-level list."""
    result = []
    for item in nested_list:
        if isinstance(item, list):
            result.extend(flatten(item))
        else:
            result.append(item)
    return result


def flatten_generator(nested_list):
…
14 0 Open
Comprehensions & generators easy

Generate Data with Python Comprehensions and Generators

Shows list, dict compregensions and generator expressions plus a Fibonacci generator to produce data lazily.

comprehensions generators lazy-evaluation
Python
# Data generation helpers using comprehensions and generators
from itertools import islice


def fibonacci(limit):
    """Generate Fibonacci numbers up to a limit."""
    a, b = 0, 1
    while a <= limit:
        yield a
        a, b = b, a + b


def main():
    # List comprehension: squares of even numbers
    square…
15 0 Open
Comprehensions & generators easy

Generate UUID4 Values with a Python Generator

This code defines a generator function that yields mock UUID4 values, allowing you to stream unique identifiers one at a time.

uuid generators streaming
Python
import uuid

def generate_uuids(count=5):
    """Generate a stream of mock UUID4 values."""
    for _ in range(count):
        yield uuid.uuid4()

if __name__ == "__main__":
    # Generate and print 5 UUIDs
    for uid in generate_uuids(5):
        print(uid)
15 0 Open
Comprehensions & generators easy

Generator Function to Yield an Infinite Counter in Python

This code demonstrates a generator function that yields an infinite sequence of integers starting from a given value, allowing lazy, memory-efficient iteration.

generators infinite sequences yield
Python
def infinite_counter(start=0):
    count = start
    while True:
        yield count
        count += 1

if __name__ == "__main__":
    counter = infinite_counter(5)
    for _ in range(5):
        print(next(counter))
14 0 Open
Comprehensions & generators easy

How to Accumulate Values with a Generator in Python

This generator yields the running total of an iterable's elements, producing a cumulative sum with each step.

generator accumulate cumulative-sum
Python
def accum(iterable):
    total = 0
    for item in iterable:
        total += item
        yield total

# Demo
if __name__ == "__main__":
    data = [1, 2, 3, 4, 5]
    print(list(accum(data)))  # [1, 3, 6, 10, 15]

    # Also works with any iterable, e.g., range
    print(list(accum(range(1, 6))))  # [1, 3, 6, 10, 15]
14 0 Open
Comprehensions & generators easy

How to Build a Sliding Window Generator in Python

Create a generator that yields fixed-size overlapping slices of a sequence, useful for efficient windowed iteration.

generators sliding-window iteration
Python
def sliding_window(sequence, size):
    for i in range(len(sequence) - size + 1):
        yield sequence[i:i + size]

if __name__ == "__main__":
    data = [1, 2, 3, 4, 5]
    n = 3
    for window in sliding_window(data, n):
        print(window)
12 0 Open
Comprehensions & generators easy

How to Compress a Generator with a Boolean Mask in Python

Filters items from a generator based on a parallel boolean mask, yielding only the items where the mask is True.

generators zip filter
Python
def compress(generator, mask):
    for item, keep in zip(generator, mask):
        if keep:
            yield item


if __name__ == "__main__":
    data = [1, 2, 3, 4, 5]
    mask = [True, False, True, False, True]
    result = list(compress(iter(data), mask))
    print(result)
14 0 Open
Comprehensions & generators easy

How to Create a Line-Numbered Generator with enumerate start in Python

This Python code defines a generator that yields lines prefixed with their index, using enumerate's start parameter to offset numbering.

enumerate generator yield
Python
def line_numbered_lines(lines, start=1):
    for idx, line in enumerate(lines, start):
        yield f"{idx:3} {line}"


if __name__ == "__main__":
    sample = ["first line", "second", "third"]
    for numbered in line_numbered_lines(sample, start=10):
        print(numbered)
14 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.