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Chain Generators with yield from in Python
Combine multiple generators into one seamless sequence using the `yield from` delegation syntax in 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()))How to Compose Two Functions into a Single Callable in Python
Combine two Python functions into a single callable using a compose helper, then apply the chained call.
def add_one(x):
return x + 1
def double(x):
return x * 2
def compose(f, g):
return lambda x: f(g(x))
add_then_double = compose(double, add_one)
double_then_add = compose(add_one, double)
result1 = add_then_double(5)
result2 = double_then_add(5)
print(f"add_one then double(5) = {result1}")
print(f"doub…Collect Multiple Validation Errors in Python Before Raising
A chainable Validator class that accumulates all validation errors and raises them together in a single exception.
class ValidationError(Exception):
pass
class Validator:
def __init__(self):
self.errors = []
def validate_required(self, value, field_name):
if not value:
self.errors.append(f"{field_name} is required")
return self
def validate_email(self, email):
…How to Print an Exception Chain in Python for Debugging
A helper that walks an exception's __cause__ and __context__ chain, printing each level with indentation to make debugging nested errors clearer.
import sys
import traceback
def pretty_exception_chain(exc):
"""Print the full exception chain with cause/context details."""
chain = []
current = exc
seen = set()
while current is not None and id(current) not in seen:
seen.add(id(current))
chain.append(current)
curren…How to Re-raise Exceptions with 'raise from' in Python
Shows how to re-raise an exception with explicit context chaining using the 'raise ... from ...' syntax, so the original cause is preserved for debugging.
def divide_with_chain(a, b):
try:
result = a / b
return result
except ZeroDivisionError as original_error:
# Re-raise with explicit chaining context
raise ValueError("Cannot divide by zero") from original_error
def explain_chain():
try:
divide_with_chain(10, 0)
…How to Wrap a Low Level Error in a Higher Level Exception in Python
Wrap low-level exceptions in a higher-level exception while preserving the original cause with the `from` keyword.
class LowLevelError(Exception):
pass
class HighLevelError(Exception):
pass
def low_level_operation():
raise LowLevelError("storage drive failed to respond")
def high_level_operation():
try:
low_level_operation()
except LowLevelError as e:
raise HighLevelError(f"database operation…How to Use ChainMap for Layered Config Lookup in Python
This code demonstrates using collections.ChainMap to combine multiple dictionaries into a single layered lookup, where earlier maps override later ones.
from collections import ChainMap
defaults = {"theme": "light", "lang": "en", "debug": False}
user = {"lang": "de", "auto_save": True}
runtime = {"debug": True}
config = ChainMap(runtime, user, defaults)
if __name__ == "__main__":
print("theme:", config["theme"])
print("lang:", config["lang"])
print("deb…How to Build a Fluent Interface with the Builder Pattern in Python
Learn to implement a fluent builder pattern in Python by chaining methods that return self, enabling readable object construction.
class Pizza:
def __init__(self):
self.size = None
self.toppings = []
self.crust = None
def set_size(self, size):
self.size = size
return self
def add_topping(self, topping):
self.toppings.append(topping)
return self
def set_crust(self, crust):
…How to Call a Parent Class __init__ with super() in Python
Shows how to chain __init__ calls through a class hierarchy using super(), so each class sets its own attributes while reusing the parent's initialization logic.
class Animal:
def __init__(self, name, species):
self.name = name
self.species = species
print(f"Animal init: {self.name}, {self.species}")
class Mammal(Animal):
def __init__(self, name, species, fur_color):
super().__init__(name, species)
self.fur_color = fur_color
…How to Implement the State Pattern in Python
Implement the State design pattern in Python by delegating behavior to state objects, letting a media player change actions dynamically without if-else chains.
class State:
def play(self, player): pass
def pause(self, player): pass
def stop(self, player): pass
class PlayingState(State):
def play(self, player):
return "Already playing"
def pause(self, player):
player.state = PausedState()
return "Pausing playback"
def stop(self…Build a Generator Pipeline in Python: Filter Then Map
Create a lazy data pipeline by chaining generator functions that read, filter, map, and write data step by step.
def read_data():
return ["a", "bb", "ccc", "dd", "eeeee", "f"]
def filter_short(words):
return (word for word in words if len(word) >= 2)
def map_to_upper(words):
return (word.upper() for word in words)
def write_data(words):
for word in words:
print(word)
if __name__ == "__main__":
…How to Merge Multiple Iterables with a Generator in Python
This code defines a generator function that 'chains' or merges multiple iterables into a single iterator, which is then converted to a list.
def chain(*iterables):
for iterable in iterables:
yield from iterable
def main():
list1 = [1, 2, 3]
tuple1 = (4, 5)
set1 = {6, 7}
string1 = "89"
result = list(chain(list1, tuple1, set1, string1))
print(result)
if __name__ == "__main__":
main()Chain of Thought Prompting in Python: Step-by-Step Reasoning Demo
This demo shows how to structure a function that explains its own reasoning step-by-step, mimicking chain-of-thought prompting for AI systems.
def solve_math_step_by_step(expression: str) -> str:
"""Solves a simple expression, showing each reasoning step."""
# Step 1: Parse the expression (assume "a + b" or "a - b")
parts = expression.split()
a = int(parts[0])
op = parts[1]
b = int(parts[2])
steps = []
steps.append(f"Step…Detect Circular Imports Across Python Projects Automatically
This script walks through all .py files in a directory, builds an import graph, and uses depth-first search to find cycles—printing each circular dependency chain.
import ast
import sys
from pathlib import Path
from collections import defaultdict, deque
def find_imports(filepath):
"""Return set of module names imported by a Python file."""
imports = set()
try:
with open(filepath) as f:
tree = ast.parse(f.read())
except (SyntaxError, UnicodeDe…Cross Account Role Chaining Mock Credentials in Python
Simulate AWS STS AssumeRole with mock credentials for cross-account role chaining in Python.
import json
class CredentialChain:
def __init__(self, account_id, role_name):
self.account_id = account_id
self.role_name = role_name
self.credentials = {}
def assume_role(self, session_name="mock_session"):
"""Simulate STS AssumeRole, returning mock credentials with expiry.""…How to Build a Chainable Filter Helper in Python
A beginner-friendly dataclass helper that chains filters, uniqueness, and slicing on any sequence, returning a plain list at the end.
from dataclasses import dataclass
from typing import Callable, Iterator, Sequence, TypeVar
T = TypeVar("T")
@dataclass
class FilterAssistant:
"""Beginner-friendly helper to filter any collection."""
data: Sequence[T]
def where(self, predicate: Callable[[T], bool]) -> "FilterAssistant":
return …How to Build a Pipe and Filter Text Processing Chain in Python
A functional pipe-and-filter chain that transforms text through uppercase, whitespace normalization, number removal, stopword filtering, and file export.
import re
import sys
def pipe_filter_chain(stream):
def uppercase(text):
return text.upper()
def strip_whitespace(text):
return " ".join(text.split())
def remove_numbers(text):
return re.sub(r"\d+", "", text)
def remove_stopwords(text, stopwords={"the", "and", "of", "in"}):…How to Build an sklearn Pipeline with ColumnTransformer in Python
A mock example showing how to chain preprocessing and a regression model into a single sklearn Pipeline, scaling numeric features and one-hot encoding categorical features with ColumnTransformer.
import numpy as np
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LinearRegression
# Mock dataset
X = np.array([[1, 'red'], [2, 'blue'], [3, 'red'], [4, 'green'], [5, 'blue']], dtype=o…How to Define Dagster ML Assets in Python
Define a chain of Dagster software-defined assets that compute raw features, normalized features, and predictions for an ML pipeline.
from dagster import asset
@asset
def raw_features():
return {"sepal_length": [5.1, 4.9, 6.2], "sepal_width": [3.5, 3.0, 3.4]}
@asset
def normalized_features(raw_features):
values = raw_features["sepal_length"]
mean = sum(values) / len(values)
std = (sum((x - mean) ** 2 for x in values) / len(values…How to Mock a Kubeflow Pipeline in Python
Build a minimal in-memory mock of a Kubeflow pipeline DAG using dataclasses and OrderedDict to chain component functions.
from typing import Dict, Any
from dataclasses import dataclass, field
from collections import OrderedDict
@dataclass
class KubeflowPipelineMock:
"""A minimal mock of a Kubeflow pipeline DAG."""
name: str
components: OrderedDict[str, callable] = field(default_factory=OrderedDict)
def add_component(se…Browse by section
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Guide: free Python code samples library
Copy-ready Python snippets for learners and developers
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- 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.