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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 Validate Function Arguments in Python
Shows how to manually check argument types and values in a Python function, raising clear TypeError and ValueError messages.
def calculate_area(length: float, width: float) -> float:
"""Calculate the area of a rectangle with manual type validation."""
if not isinstance(length, (int, float)) or isinstance(length, bool):
raise TypeError(f"length must be a number, got {type(length).__name__}")
if not isinstance(width, (int,…Catch RecursionError and Fail Gracefully in Python
Wrap a recursive function call in a try-except block to catch RecursionError and print a graceful failure message instead of crashing.
def compute_factorial_recursive(n):
"""Compute factorial recursively, raising RecursionError for deep recursion."""
if n == 0:
return 1
return n * compute_factorial_recursive(n - 1)
if __name__ == "__main__":
try:
result = compute_factorial_recursive(10000)
print(f"Factorial c…Catch ValueError and print friendly message in Python
Wrap an int() call in a try/except block and print a friendly message when ValueError is raised.
try:
number = int("not_a_number")
except ValueError:
print("That's not a valid number. Please enter digits only.")How to Assert Preconditions with Descriptive Messages in Python
Use Python's assert statement with a custom message to validate function preconditions and fail fast with clear diagnostics.
def divide(dividend, divisor):
assert divisor != 0, f"Divisor must be non-zero, got {divisor!r}"
return dividend / divisor
if __name__ == "__main__":
print(divide(10, 2))
try:
divide(10, 0)
except AssertionError as e:
print(f"AssertionError: {e}")How to Catch ValueError in Python (try except)
Handle invalid numeric input by catching ValueError in a try/except block and returning a friendly error message.
def parse_number(text):
try:
number = int(text)
return f"Parsed number: {number}"
except ValueError as error:
return f"Error: '{text}' is not a valid number ({error})"
if __name__ == "__main__":
examples = ["42", "hello", "3.14", "100"]
for item in examples:
print(pars…How to Handle ValueError When Converting Strings to Integers in Python
Convert text to an integer with a try-except block that catches ValueError and prints beginner-friendly error messages.
def parse_number(text):
"""Convert text to an integer, showing beginner-friendly error handling."""
try:
number = int(text)
print(f"Successfully parsed: {number}")
return number
except ValueError as e:
print(f"Error: '{text}' is not a valid number.")
print(f"Debuggin…How to Handle ValueError with try except in Python
Shows a beginner-friendly try/except pattern that catches ValueError when converting text to an integer, prints a helpful message, and returns None instead of crashing.
def parse_number(text):
try:
return int(text)
except ValueError:
print(f"ValueError: '{text}' is not a valid integer.")
return None
if __name__ == "__main__":
user_input = "abc"
result = parse_number(user_input)
print(f"Parsing '{user_input}' returned: {result}")
vali…How to Record Last N Errors with a Ring Buffer in Python
Use collections.deque with maxlen to keep only the most recent N error messages while discarding older entries automatically.
import collections
class ErrorRecorder:
def __init__(self, size):
self.buffer = collections.deque(maxlen=size)
def record_error(self, message):
self.buffer.append(message)
def get_errors(self):
return list(self.buffer)
if __name__ == "__main__":
recorder = ErrorRecorder(3)
…How to Return Success or Error as a Tuple in Python (Result Type Pattern)
Use a (bool, value) tuple as a lightweight Result type to return either a successful result or a descriptive error message from a Python function.
def divide(dividend: float, divisor: float) -> tuple[bool, float | str]:
"""Return (True, result) on success, (False, error_message) on failure."""
if divisor == 0:
return False, "Error: Division by zero"
return True, dividend / divisor
if __name__ == "__main__":
# Success case
success, r…How to Serialize an Exception to a JSON-Safe Dict in Python
Convert any Python exception into a JSON-safe dictionary with type, message, and the last few traceback lines for logging.
import json
import traceback
from typing import Any
def exception_to_dict(exc: Exception) -> dict[str, Any]:
"""Convert an exception into a JSON-safe dictionary."""
return {
"type": type(exc).__name__,
"message": str(exc),
"traceback": traceback.format_exc().strip().split("\n")[-3:],
…How to Test Exceptions in Python with pytest.raises
Learn the pytest.raises pattern to assert that specific exceptions are raised and validate their messages.
import pytest
def divide(a: int, b: int) -> float:
if b == 0:
raise ValueError("Cannot divide by zero")
return a / b
def test_divide_by_zero_raises():
with pytest.raises(ValueError, match="Cannot divide by zero"):
divide(10, 0)
def test_divide_by_zero_raises_exact_match():
with py…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 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 handle ZeroDivisionError in Python
Wrap a division operation in try/except to return None or a friendly message instead of crashing when dividing by zero.
def safe_divide(a, b):
"""Return a/b if possible, else None when dividing by zero."""
try:
return a / b
except ZeroDivisionError:
return None
def safe_divide_with_message(a, b):
"""Return a how-to message on divide-by-zero error."""
try:
return a / b
except ZeroDivisio…Log to stderr with Python logging basicConfig
Configure Python's logging module to send all log messages to standard error (stderr) instead of the default stderr, with a readable timestamped format.
import logging
def main():
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s — %(name)s — %(levelname)s — %(message)s",
stream=__import__("sys").stderr,
)
logger = logging.getLogger("example")
logger.debug("Debug message")
logger.info("Info message")
logger.…Automatically Highlight Data Validation Errors Inside Excel Files in Python
Load an Excel file with openpyxl, iterate over cells, and highlight invalid data (empty, negative) with a red fill and error message.
import openpyxl
from openpyxl.styles import PatternFill
from pathlib import Path
def highlight_validation_errors(filepath: str, output_path: str = None):
wb = openpyxl.load_workbook(filepath)
red_fill = PatternFill(start_color="FF0000", end_color="FF0000", fill_type="solid")
for sheet in wb.worksheet…Split a String into Multiple Lines by Width in Python
Demonstrates a word-wrap algorithm that splits a message into rows without exceeding a maximum width.
def split_message(text, max_width):
words = text.split()
rows = []
current_row = []
for word in words:
if len(" ".join(current_row + [word])) > max_width:
rows.append(" ".join(current_row))
current_row = [word]
else:
current_row.append(word)
if …How to Build a System-User-Assistant Message List in Python
Use dataclasses to model a chat conversation and build the system/user/assistant message list expected by LLM APIs.
from dataclasses import dataclass, field
from typing import List
@dataclass
class Message:
role: str
content: str
@dataclass
class Conversation:
messages: List[Message] = field(default_factory=list)
def add_system(self, content: str) -> None:
self.messages.append(Message(role="system", con…How to Mock OpenAI Tool Call Messages in Python
Create an assistant message with a function tool call in OpenAI's chat format, useful for testing and mocking.
from openai import OpenAI
def mock_tool_call(tool_name: str, arguments: dict) -> dict:
"""Simulate a tool call message in OpenAI style."""
return {
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "call_" + "a1b2c3d4e5f6",
"type…How to Serialize Chat Messages to a JSON File in Python
Writes a list of chat message dicts to a JSON file with metadata like export time and message count.
import json
from pathlib import Path
from datetime import datetime
def serialize_messages(messages, output_path):
data = {
"exported_at": datetime.now().isoformat(),
"count": len(messages),
"messages": messages
}
Path(output_path).write_text(
json.dumps(data, indent=2, ensu…How to Validate JSON Output Against a Dict Schema in Python
Validate JSON-like data against a simple dict schema with type checking and descriptive error messages using only the Python standard library.
from typing import Dict, Any, List, Union
def validate_json(data: Any, schema: Dict[str, str]) -> List[str]:
"""
Validate JSON-like data against a simple dict schema.
Schema format: {field_name: expected_type} where type is one of:
'str', 'int', 'float', 'bool', 'list', 'dict', 'any'
Returns list …How to randomly assign a prompt variant to each key in Python
Randomly pick one variant from a list for each prompt key, useful for A/B testing message variations.
import random
def assign_prompt_variant(prompts: dict[str, list[str]]) -> dict[str, str]:
"""Assign a random prompt variant to each prompt key."""
return {key: random.choice(variants) for key, variants in prompts.items()}
if __name__ == "__main__":
prompt_bank = {
"greeting": ["Hello!", "Hi there…Browse by section
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