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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
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…How to Use Python's next() Builtin with a Default Sentinel Value
A wrapper function that returns the next item from an iterator, or a default sentinel value when the iterator is exhausted.
def get_next_or_default(iterator, default=None):
"""Return the next item from an iterator, or default if exhausted."""
return next(iterator, default)
if __name__ == "__main__":
fruits = iter(["apple", "banana", "cherry"])
print(get_next_or_default(fruits)) # apple
print(get_next_or…Build a Case-Insensitive Dict with a Wrapper Class in Python
Create a custom dict subclass that treats keys as case-insensitive by normalizing them to lowercase, with a full set of common dict methods.
class CaseInsensitiveDict:
def __init__(self, data=None):
self._data = {}
if data:
self.update(data)
def __setitem__(self, key, value):
self._data[str(key).lower()] = value
def __getitem__(self, key):
return self._data[str(key).lower()]
def __delitem__(sel…Python Adapter Class: Wrap Legacy Interface
Convert a legacy system's interface into a modern one using the Adapter pattern in Python, translating method calls and data formats.
class LegacySystem:
"""Legacy interface - old method names and parameter format."""
def query_employee_info(self, emp_id, emp_name):
return f"Legacy: {emp_id} - {emp_name}"
def update_employee_department(self, emp_id, department_code):
return f"Legacy: Updated {emp_id} to dept {department_…How to Write an IP Block List to hosts.deny in Python
This Python script validates a list of IP addresses and CIDR ranges, then writes them to a hosts.deny file to block connections at the TCP wrapper level.
from ipaddress import ip_network
def write_hosts_deny(ip_list, output_file="hosts.deny"):
with open(output_file, "w") as f:
for ip in ip_list:
try:
ip_network(ip)
f.write(f"ALL: {ip}\n")
except ValueError:
continue
print(f"Written…Mock systemctl Wrapper in Python for Service Testing
A Python class-based mock of systemctl that simulates start, stop, restart, and status operations for a service, useful for testing automation scripts.
import subprocess
import sys
class ServiceManager:
def __init__(self, service_name):
self.service_name = service_name
self.status = "inactive"
def start(self):
self.status = "active"
print(f"Starting {self.service_name}... OK")
def stop(self):
self.status …How to mock boto3 S3 upload file wrapper in Python
Wrap an S3 put_object call in a testable function that returns metadata, and mock boto3 to verify the upload without touching AWS.
import boto3
import io
def upload_file_to_s3(file_obj, bucket, key, object_metadata=None):
"""Upload a file-like object to S3 and return a metadata dict."""
s3 = boto3.client("s3")
content = file_obj.read()
s3.put_object(
Bucket=bucket,
Key=key,
Body=content,
Metadata=…How to Mock a Timeout per Dependency Call in Python
This code demonstrates how to simulate and test per-call timeouts for external dependencies using Python's unittest.mock and a simple timing wrapper.
```python
import time
from unittest.mock import Mock, patch
def call_dependency(dependency, timeout):
start = time.time()
result = dependency.call()
elapsed = time.time() - start
if elapsed > timeout:
raise TimeoutError(f"Dependency call took {elapsed:.2f}s, exceeding timeout {timeout}s")
…How to implement stale-while-revalidate caching in Python
A Python cache wrapper that returns a stale cached value with a fallback flag when the upstream fetch fails, using TTL-based freshness checks.
import time
from functools import lru_cache
class CachedService:
def __init__(self, fetch_func, ttl=5):
self.fetch_func = fetch_func
self.ttl = ttl
self._cache = {}
self._timestamp = {}
def get(self, key):
now = time.time()
if key in self._cache and now - self…How to Cache Data in Redis with Python
Build a simple Redis cache wrapper that stores and retrieves JSON data with automatic TTL and serialization.
import redis
import json
import time
class Cache:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db)
self.default_ttl = default_ttl
def get(self, key):
value = self.client.get(key)
if value is None:
…How to Implement Namespaced Cache Keys for Tenant Isolation in Python
Build a tenant-aware cache wrapper that prefixes keys with tenant and namespace, and test it with mocks.
from keyvaluestore import SimpleCache
from unittest.mock import patch
class TenantCache(SimpleCache):
def __init__(self, tenant_id, namespace="default"):
super().__init__()
self.tenant_id = tenant_id
self.namespace = namespace
def _key(self, key):
return f"tenant:{self.tenant_…Retry with Exponential Backoff and Jitter in Python
A decorator-style retry wrapper that retries a flaky function with exponential backoff plus random jitter, then raises after the last attempt fails.
import random
import time
def retry_with_backoff(func, max_retries=3, base_delay=0.5, max_jitter=0.1):
for attempt in range(max_retries + 1):
try:
return func()
except Exception as e:
if attempt == max_retries:
raise
delay = base_delay * (2 ** at…Lazy Evaluation Transform Lineage Mock in Python
Build a mock lineage tracker for data transforms using lazy evaluation and function wrappers in Python.
import functools
def lazy_transform(pipeline):
"""Build a mock lineage tracker using lazy evaluation."""
lineage = []
def wrap(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
result = func(*args, **kwargs)
lineage.append({"transform": func.__name__, "a…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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