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How to Use Optional Return in Python Instead of Raising Exceptions
A Python function returns None for missing dictionary keys instead of raising KeyError, enabling graceful lookup handling with type hints.
from typing import Optional
def find_user(users: dict, user_id: int) -> Optional[dict]:
"""
Look up a user by ID. Returns the user dict if found,
otherwise returns None instead of raising KeyError.
"""
return users.get(user_id)
def main() -> None:
users = {
1: {"name": "Alice", "ema…How to Use the breakpoint() Function for Interactive Debugging in Python
Insert a breakpoint() call into your code to drop into an interactive debugger session where you can inspect variables and step through execution.
def calculate_total(prices, discount=0):
"""Calculates total price with optional discount."""
subtotal = sum(prices)
breakpoint() # Interactive debugging session starts here
final_total = subtotal * (1 - discount)
return final_total
if __name__ == "__main__":
items = [25.50, 13.25, 9.99, 5.7…How to Use try except else finally in Python
Demonstrates the correct order of try/except/else/finally blocks in Python with a safe division function.
def safe_divide(numerator, denominator):
try:
result = numerator / denominator
except ZeroDivisionError:
print("Error: Cannot divide by zero!")
except TypeError:
print("Error: Both arguments must be numbers!")
else:
print(f"Division successful: {numerator} / {denominator…How to Validate Input and Raise TypeError in Python
Define a function that checks its argument type and raises a TypeError early with a clear message when given a non-number.
def validate_number(value):
if not isinstance(value, (int, float)):
raise TypeError(f"Expected a number, got {type(value).__name__}")
return value * 2
if __name__ == "__main__":
try:
print(validate_number(5))
print(validate_number("hello"))
except TypeError as e:
print(…How to Validate JSON in Python and Catch JSONDecodeError
A robust Python function that attempts to parse JSON strings and returns a boolean plus either the parsed data or a descriptive error message when decoding fails.
import json
def validate_json(json_string):
"""Try to parse JSON, return (is_valid, data_or_error)."""
try:
data = json.loads(json_string)
return True, data
except json.JSONDecodeError as e:
return False, f"Invalid JSON: {e}"
if __name__ == "__main__":
test_inputs = [
…How to Validate an Email Address and Raise ValueError in Python
This code defines a validate_email function that checks an email address against a regex pattern and several rules, raising ValueError with a specific reason when invalid.
import re
def validate_email(email: str) -> str:
"""Validate an email address and return it if valid, otherwise raise ValueError."""
if not isinstance(email, str):
raise ValueError("Email must be a string")
if len(email) > 254:
raise ValueError("Email length exceeds 254 characters")
#…How to catch ValueError in Python and print a friendly message
This code defines a function that safely converts text to an integer, catches ValueError, and prints a friendly message instead of crashing.
def parse_number(text):
try:
return int(text)
except ValueError:
print("Oops! That's not a valid number.")
return None
if __name__ == "__main__":
result = parse_number("abc")
if result is None:
print("Parsing failed.")
else:
print(f"Parsed value: {result}")How to check for None and raise helpful errors in Python
A defensive function that explicitly validates data, keys, and values — raising descriptive ValueError and KeyError exceptions before returning a result.
def get_value(data, key):
if data is None:
raise ValueError("data cannot be None")
if key not in data:
raise KeyError(f"key '{key}' not found in data")
result = data[key]
if result is None:
raise ValueError(f"value for key '{key}' is None")
return result
if __name__ == "__…Convert File Data to a Dictionary in Python
This function scans a directory and converts each file's metadata (name, size, extension) into a structured dictionary for easy access.
from pathlib import Path
def convert_files_data(directory: str) -> dict:
data = {}
base = Path(directory)
if not base.exists():
return data
for file in base.iterdir():
if file.is_file():
data[file.name] = {
"size": file.stat().st_size,
"exten…File Data Helper Functions in Python
Read and write text and JSON files, and list files in a directory, using pathlib-based helper functions.
from pathlib import Path
def load_text_file(filepath):
"""Read a text file and return its contents as a string."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not found: {filepath}")
return path.read_text(encoding="utf-8")
def save_text_file(filepath, content):
…How to Decompress a gzip File in Python
This code provides a function to decompress a .gz file, writing the decompressed content to a new file and returning the text, using the gzip standard library module.
import gzip
from pathlib import Path
def decompress_gzip(filepath: str, output_path: str | None = None) -> str:
"""Decompress a .gz file and return the decompressed content."""
input_path = Path(filepath)
if output_path is None:
output_path = str(input_path.with_suffix(""))
with gzip.open…How to Filter CSV Rows by Column Value in Python
Filter CSV rows based on a column value condition using the standard csv module and a lambda function.
import csv
def filter_csv(input_file, output_file, column, condition):
with open(input_file, newline='', encoding='utf-8') as infile, \
open(output_file, 'w', newline='', encoding='utf-8') as outfile:
reader = csv.DictReader(infile)
fieldnames = reader.fieldnames
writer = csv.Dict…How to Parse JSON, TXT, and CSV Files in Python
This code provides simple functions to read and parse JSON, text, and CSV files using Python's standard library, returning native data structures.
import json
from pathlib import Path
def parse_json_file(filepath):
"""Read and parse a JSON file, returning its contents."""
path = Path(filepath)
with path.open('r', encoding='utf-8') as f:
return json.load(f)
def parse_txt_lines(filepath):
"""Read a text file and return non-empty stripped …How to Read a JSON File into a Dictionary in Python
Load a JSON file into a Python dictionary using the json.load() function with proper file handling and UTF-8 encoding.
import json
from pathlib import Path
def read_json_file(filepath: str) -> dict:
"""Read a JSON file and return its contents as a dictionary."""
path = Path(filepath)
with path.open("r", encoding="utf-8") as f:
data = json.load(f)
return data
if __name__ == "__main__":
# Create a sample JS…How to Read and Write Text Files in Python
This code provides simple helper functions to save and load text files using Python's standard pathlib library.
from pathlib import Path
def save_text_data(filename: str, content: str) -> None:
file_path = Path(filename)
file_path.write_text(content, encoding="utf-8")
def load_text_data(filename: str) -> str:
file_path = Path(filename)
return file_path.read_text(encoding="utf-8")
if __name__ == "__main__":…How to Record Audio from Your Microphone in Python
Record audio from your default microphone using PyAudio and save it as a WAV file with a simple reusable function.
import pyaudio
import wave
def record_audio(filename: str, duration: int = 5, sample_rate: int = 44100, chunk: int = 1024):
"""Record audio from default microphone and save as WAV file."""
audio_format = pyaudio.paInt16 # 16-bit resolution
channels = 1 # Mono
p = pyaudio.PyAudio()
stre…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.
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…Convert Lists and Dictionaries to Sets in Python
Convert lists of pairs into dictionaries and lists or dictionaries into sets using simple helper functions.
def convert_to_dict(data):
"""Convert list of tuples or lists into a dictionary."""
return dict(data)
def convert_to_set(data):
"""Convert list or dictionary into a set of its keys/values."""
if isinstance(data, dict):
return set(data.keys())
return set(data)
def convert_collection(data…Convert namedtuple to dict with asdict in Python
Convert a namedtuple instance into an ordinary dictionary using the asdict function from the collections module's namedtuple utility.
from collections import namedtuple, asdict
def main():
# Define a namedtuple for a person
Person = namedtuple("Person", ["name", "age", "city"])
person = Person(name="Alice", age=30, city="New York")
# Convert namedtuple to dict
person_dict = asdict(person)
print("Original namedtuple…Flatten a Nested Dict to Dot Notation Keys in Python
Recursively flatten a nested dictionary into a flat dictionary with dot-separated keys using a small recursive function.
def flatten_dict(nested, parent_key='', sep='.'):
items = {}
for key, value in nested.items():
new_key = f"{parent_key}{sep}{key}" if parent_key else key
if isinstance(value, dict):
items.update(flatten_dict(value, new_key, sep))
else:
items[new_key] = value
…Group Data by Key in Python with Dictionaries and Sets
Group items into a dictionary of sets using a key function, a beginner-friendly pattern for organizing data by categories.
def group_data(items, key_func):
"""Group items into a dictionary of sets based on a key function."""
grouped = {}
for item in items:
key = key_func(item)
if key not in grouped:
grouped[key] = set()
grouped[key].add(item)
return grouped
if __name__ == "__main__":
…How to Check Data Type and Inspect Dictionaries and Sets in Python
Inspect dictionaries and sets by printing their contents, types, and sizes using a small helper function.
def check_data(data):
"""Helper to inspect dictionaries and sets."""
if isinstance(data, dict):
print(f"Dictionary with {len(data)} keys")
for key, value in data.items():
print(f" {key}: {value} ({type(value).__name__})")
elif isinstance(data, set):
print(f"Set with {le…How to Create a Dict from Two Parallel Lists in Python (zip)
Build a dictionary by pairing elements from two parallel lists using Python's built-in zip function and dict constructor.
keys = ["name", "age", "city"]
values = ["Alice", 30, "New York"]
result = dict(zip(keys, values))
print(result)How to Filter a Dictionary by Predicate on Values in Python
This code defines a reusable function that builds a new dictionary containing only the items whose values satisfy a given predicate function.
def filter_dict_by_predicate(d, predicate):
"""Return a new dict with only items whose value passes the predicate."""
return {k: v for k, v in d.items() if predicate(v)}
if __name__ == "__main__":
scores = {"Alice": 85, "Bob": 42, "Charlie": 91, "Diana": 60}
# Keep only values greater than or equal t…Browse by section
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