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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Sort a List of Dictionaries by a Key in Python
Sort a list of dictionaries by a specified key field, optionally in descending order, using Python's built-in sorted() function.
def sort_dicts_by_key(data, key, reverse=False):
return sorted(data, key=lambda item: item.get(key), reverse=reverse)
if __name__ == "__main__":
people = [
{"name": "Alice", "age": 30},
{"name": "Bob", "age": 25},
{"name": "Charlie", "age": 35},
]
sorted_by_age = sort_dicts_b…How to Sort a List of Tuples by the Second Element in Python
Sorts a list of tuples by the second element using the sorted() function with a lambda key, preserving the original list.
def sort_tuples_by_second(tuples_list):
"""Sort a list of tuples by the second element."""
return sorted(tuples_list, key=lambda x: x[1])
if __name__ == "__main__":
data = [(1, 5), (3, 2), (2, 8), (4, 1)]
sorted_data = sort_tuples_by_second(data)
print("Original list:", data)
print("Sorted by…How to Split a List at the First Occurrence of a Value in Python
This function splits a list into two parts at the first occurrence of a given value, returning the left and right portions.
def split_at_first(lst, value):
try:
idx = lst.index(value)
return lst[:idx], lst[idx:]
except ValueError:
return lst, []
if __name__ == "__main__":
sample = [1, 2, 3, 4, 3, 5]
value = 3
left, right = split_at_first(sample, value)
print("Left:", left)
print("Right:"…How to Validate List Data in Python
A beginner-friendly validation helper that checks if data is a list, enforces minimum length, and optionally verifies item types with clear error messages.
def validate_data(data, expected_types=None, min_length=1):
"""Validate that data is a non-empty list and optionally check item types."""
if not isinstance(data, list):
return False, f"Expected a list, got {type(data).__name__}"
if len(data) < min_length:
return False, f"List must have…How to Zip Two Lists into Pairs in Python
Combine two lists element-wise into a list of tuples using Python's built-in zip() function.
def zip_lists_into_pairs(list1, list2):
pairs = list(zip(list1, list2))
return pairs
if __name__ == "__main__":
fruits = ["apple", "banana", "cherry"]
quantities = [3, 5, 2]
result = zip_lists_into_pairs(fruits, quantities)
print(result)How to split a list by condition in Python
Splits a list into two lists based on a condition function, returning matched and unmatched items.
def split_by_condition(items, condition):
"""
Split a list into two lists based on a condition.
The first list contains items where condition(item) is True,
the second list contains the rest.
"""
matched = []
unmatched = []
for item in items:
if condition(item):
matc…How to summarize and transform lists in Python
Compute count, sum, min, max, and average for a list and multiply each element by a factor using simple loops and built-in functions.
def summarize(data):
"""Return a summary of a list: count, sum, min, max, average."""
count = len(data)
total = sum(data)
minimum = min(data)
maximum = max(data)
average = total / count if count else 0
return count, total, minimum, maximum, average
def multiply_elements(data, factor=2):
…Replace Negative Values in a List with Python
This code defines a function that replaces every negative number in a list with a replacement value, defaulting to zero, using a list comprehension.
def replace_if_negative(values, replacement=0):
return [replacement if value < 0 else value for value in values]
if __name__ == "__main__":
numbers = [5, -3, 8, -1, 0, -7, 2]
result = replace_if_negative(numbers)
print(f"Original: {numbers}")
print(f"Replaced: {result}")Symmetric difference between two lists in Python
Find elements present in exactly one of two lists, preserving original order, with a simple Python function.
def symmetric_difference(list1, list2):
"""
Return the symmetric difference of two lists.
Elements present in exactly one of the lists, preserving order.
"""
set1 = set(list1)
set2 = set(list2)
# Elements in list1 but not in list2
diff1 = [x for x in list1 if x not in set2]
# E…Add Type Hints to Function Parameters and Return in Python
Add type hints to function parameters and return values in Python for clearer, more maintainable code using the typing module.
from typing import List, Optional, Dict
def average(numbers: List[float]) -> float:
return sum(numbers) / len(numbers)
def full_name(first: str, last: Optional[str] = "") -> str:
return f"{first} {last}".strip()
def build_user(name: str, age: int, email: Optional[str] = None) -> Dict[str, object]:
us…Build a Progress Callback Function for Loops in Python
Create a reusable progress callback that receives per-step data and lets callers log or update a UI as a loop runs.
def run_with_progress(items, desc="Processing", step_callback=None):
"""Run a loop with progress updates via callback."""
total = len(items)
for idx, item in enumerate(items):
# Process the item (simulated work here)
result = item * 2
# Build progress data dictionary
if ste…Cache expensive function with lru_cache in Python
Use functools.lru_cache to memoize an expensive recursive function and show the dramatic speedup on repeated calls.
from functools import lru_cache
import time
@lru_cache(maxsize=128)
def expensive_operation(n):
"""Simulate an expensive Fibonacci-like calculation."""
if n < 2:
return n
return expensive_operation(n - 1) + expensive_operation(n - 2)
if __name__ == "__main__":
# First call (uncached) - take…Call a Function Dynamically by Name in Python
Use globals() to look up and call a function by its name as a string, with optional arguments.
def greet():
return "Hello from greet!"
def add(a, b):
return a + b
def multiply(a, b):
return a * b
if __name__ == "__main__":
func_name = "add"
args = (3, 5)
# Call function dynamically by name from globals
result = globals()[func_name](*args)
print(f"{func_name}({', '.join(ma…Create a retry decorator with max attempts in Python
A decorator that retries a function up to a specified number of times when it raises an exception, with an optional delay between attempts.
import functools
import time
def retry(max_attempts, delay=0.1):
"""Retry a function up to max_attempts times on exception."""
def decorator(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
for attempt in range(1, max_attempts + 1):
try:
…Format CLI help text in Python
Build a readable usage string for a command-line tool, aligning flags and wrapping descriptions with the textwrap module.
import textwrap
def format_help(command_name: str, description: str, options: list[tuple[str, str]]) -> str:
"""Format CLI help text into a readable usage string."""
header = f"Usage: {command_name} [OPTIONS]"
lines = [header, "", description, "", "Options:"]
for flag, help_text in options:
…How to Build Partial Functions with functools.partial in Python
Create reusable partial functions that pre-fill arguments using functools.partial, like making square and cube functions from a general power function.
```python
from functools import partial
def power(base, exponent):
"""Calculate base raised to the exponent power."""
return base ** exponent
# Create partial functions for common powers
square = partial(power, exponent=2)
cube = partial(power, exponent=3)
if __name__ == "__main__":
squares = [square(x)…How to Build a Simple Decorator That Logs Function Calls in Python
This code shows how to create a reusable decorator that logs each function call, including arguments, return value, and execution time.
import functools
import time
def log_calls(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
print(f"Calling {func.__name__} with args={args}, kwargs={kwargs}")
start = time.time()
result = func(*args, **kwargs)
end = time.time()
print(f"{func.__name__} return…How to Build a Subcommand Parser Tree with argparse in Python
Create a CLI with nested subcommands (like git) using argparse subparsers, where each subcommand maps to its own handler function.
import argparse
def cmd_add(args):
print(f"Adding {args.num1} + {args.num2} = {args.num1 + args.num2}")
def cmd_sub(args):
print(f"Subtracting {args.num1} - {args.num2} = {args.num1 - args.num2}")
def main():
parser = argparse.ArgumentParser(prog="calculator")
subparsers = parser.add_subparsers(d…How to Compare Two Implementations with timeit in Python
Measure and compare the execution time of iterative vs recursive factorial functions using the timeit module.
import timeit
def factorial_iterative(n):
result = 1
for i in range(2, n + 1):
result *= i
return result
def factorial_recursive(n):
if n == 0:
return 1
return n * factorial_recursive(n - 1)
if __name__ == "__main__":
n = 10
iterations = 10000
iterative_time = timeit…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…How to Convert a List to an Iterator in Python with iter()
This code converts a list into an iterator using the built-in iter() function and retrieves items sequentially with next(), handling exhaustion with StopIteration.
def main():
# Original list
fruits = ["apple", "banana", "cherry"]
# Convert the list to an iterator using iter()
fruit_iterator = iter(fruits)
# Retrieve items one at a time with next()
print(next(fruit_iterator)) # apple
print(next(fruit_iterator)) # banana
print(next(fruit_iterat…How to Count Items with Default Parameters in Python
Define a Python function that prints each item with a running counter, using default parameters to allow custom start values and step increments.
def count_items(items, start=0, step=1):
"""Count items in a list with configurable start value and step."""
count = start
for item in items:
print(f"{count}: {item}")
count += step
if __name__ == "__main__":
fruits = ["apple", "banana", "cherry"]
print("Default parameters (start=0…How to Create Functions with Default Parameters in Python
This code defines two Python functions using default parameters to handle missing arguments gracefully, demonstrating how to work with optional inputs and keyword arguments.
def greet(name="Guest", greeting="Hello", punctuation="!"):
"""Generate a greeting message using default parameters."""
return f"{greeting}, {name}{punctuation}"
def create_profile(username="anonymous", age=0, city="Unknown", active=True):
"""Create a user profile dictionary with default values."""
r…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.
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()Browse by section
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