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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
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 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__ == "__…Python dict try-except KeyError EAFP vs LBYL
Compare EAFP (try-except) and LBYL (if-in-check) styles for safely accessing dictionary keys, with working examples in Python.
def safe_get_lbyl(d, key):
if key in d:
return d[key]
return "default-lbyl"
def safe_get_eafp(d, key):
try:
return d[key]
except KeyError:
return "default-eafp"
if __name__ == "__main__":
data = {"name": "Alice", "age": 30}
print("LBYL:", safe_get_lbyl(data, "missing")…Automatically Detect Corrupted Files Using SHA-256 Checksums in Python
Compute SHA-256 checksums of files and compare them to detect corruption in Python.
import hashlib
import os
def compute_sha256(filepath: str) -> str:
"""Compute SHA-256 checksum of a file."""
sha256 = hashlib.sha256()
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
sha256.update(chunk)
return sha256.hexdigest()
def validate_file_int…How to Check Disk Free Space in Python with shutil.disk_usage
This Python script uses the standard library shutil.disk_usage to report total, used, and free disk space in bytes, plus a percentage usage figure.
import shutil
def check_disk_free_space(path="/"):
"""Return a tuple of total, used, and free disk space in bytes."""
usage = shutil.disk_usage(path)
return usage.total, usage.used, usage.free
if __name__ == "__main__":
total, used, free = check_disk_free_space()
print(f"Total: {total:,} bytes"…How to Delete a File if it Exists in Python
Delete a file safely in Python using pathlib's Path.unlink, checking existence first to avoid errors.
from pathlib import Path
def delete_file_if_exists(file_path: str) -> bool:
"""Delete a file if it exists. Returns True if deleted, False if not found."""
path = Path(file_path)
if path.exists():
path.unlink()
print(f"Deleted: {path}")
return True
else:
print(f"File not…How to Validate JSON Schema Shape in Python
Validate JSON data against a schema using manual checks for required fields, types, and constraints.
import json
from typing import Any, Dict
def validate_person_schema(data: Dict[str, Any]) -> bool:
"""Validate a person object against expected schema shape."""
if not isinstance(data, dict):
return False
# Required fields check
required_fields = {"name", "age", "email"}
if not requir…How to check file data in Python
Check if a file exists and is a regular file, then return its name, size, line count, and first line.
def check_file_data(file_path):
from pathlib import Path
path = Path(file_path)
if not path.exists():
return f"File '{file_path}' does not exist."
if not path.is_file():
return f"'{file_path}' is not a regular file."
size = path.stat().st_size
lines = path.read_text(encodin…Check Invertible Mapping for Duplicate Values in Python
Detect duplicate values among (key, value) pairs to ensure the mapping is invertible, using a dictionary for O(1) lookups.
def invertible_after_dedup(pairs):
"""
Check whether a set of (key, value) pairs is invertible,
i.e., no duplicate values exist for different keys.
"""
seen = {}
for key, value in pairs:
if value in seen and seen[value] != key:
return False, f"Duplicate value '{value}' for k…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 Check if a Set is a Subset in Python
Check whether one set contains all elements of another set using the issubset method.
def is_subset(allowed_set, check_set):
"""
Check if check_set is a subset of allowed_set.
Returns True if all elements of check_set are in allowed_set, otherwise False.
"""
return check_set.issubset(allowed_set)
if __name__ == "__main__":
# Example usage
allowed = {1, 2, 3, 4, 5}
valid…How to Implement Disjoint Set Union Find in Python
Implement a Disjoint Set Union-Find data structure using a Python dictionary for parent tracking, with path compression and connectivity checks.
class DisjointSet:
def __init__(self):
self.parent = {}
def find(self, x):
# Path compression
if self.parent[x] != x:
self.parent[x] = self.find(self.parent[x])
return self.parent[x]
def union(self, x, y):
# Initialize if not present
if x not in…How to Validate Required Dict Keys in Python
Check whether a dictionary contains all required keys and return the list of missing ones using a simple list comprehension.
def find_missing_keys(data: dict, required_keys: list) -> list:
"""Return a list of required keys that are missing from the dictionary."""
return [key for key in required_keys if key not in data]
if __name__ == "__main__":
user_data = {
"name": "Alice",
"email": "alice@example.com",
…Composable Predicates with the &, |, ~ Operators in Python
Define a reusable Predicate class that combines boolean checks with & (AND), | (OR), and ~ (NOT) operators.
class Predicate:
def __init__(self, func, name=None):
self.func = func
self.name = name or getattr(func, "__name__", "predicate")
def __call__(self, value):
return self.func(value)
def __and__(self, other):
return Predicate(lambda v: self(v) and other(v), f"({self.name} AN…How to Validate Data Types in Python with a Class
A beginner-friendly Python class that checks if a value is a string, integer, float, list, or empty, using simple methods and isinstance checks.
class DataValidator:
"""A simple data validation helper for beginners."""
def __init__(self, data):
self.data = data
def is_string(self):
return isinstance(self.data, str)
def is_integer(self):
return isinstance(self.data, int) and not isinstance(self.data, bool)
…How to Validate User Input with a Dataclass in Python
A dataclass stores name, age, and email, and a validator class checks each field, returning a dictionary of boolean results.
from dataclasses import dataclass
@dataclass
class UserInput:
name: str
age: int
email: str
def is_valid_name(self) -> bool:
return bool(self.name.strip()) and len(self.name.strip()) >= 2
def is_valid_age(self) -> bool:
return isinstance(self.age, int) and 0 < self.age < 150
…Validate dataclass fields with __post_init__ in Python
Add custom validation to a Python dataclass inside __post_init__, raising ValueError or TypeError for invalid field values.
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class Product:
name: str
price: float
quantity: int = 1
category: Optional[str] = None
def __post_init__(self):
if not self.name or not isinstance(self.name, str):
raise ValueError("name must be a…How to Remove Duplicates in Python Preserving Order
Removes duplicate items from a list while keeping the first occurrence order intact using a set for fast membership checks.
def remove_duplicates_preserving_order(items):
seen = set()
result = []
for item in items:
if item not in seen:
seen.add(item)
result.append(item)
return result
if __name__ == "__main__":
sample = [3, 1, 2, 1, 3, 4, 2, 5]
unique_items = remove_duplicates_preserv…Implement Queue Using Two Stacks in Python
Python class that implements a FIFO queue using two stacks, with enqueue, dequeue, peek, and emptiness checks.
class QueueUsingStacks:
def __init__(self):
self.stack_in = []
self.stack_out = []
def enqueue(self, value):
self.stack_in.append(value)
def dequeue(self):
if not self.stack_out:
while self.stack_in:
self.stack_out.append(self.stack_in.pop())
…Split Array Largest Sum in Python (Minimize Largest Subarray Sum)
Binary search + greedy check to split an array into k subarrays while minimizing the largest subarray sum.
def can_split(nums, k, max_sum):
subarrays = 1
current_sum = 0
for num in nums:
if current_sum + num <= max_sum:
current_sum += num
else:
subarrays += 1
current_sum = num
if subarrays > k:
return False
return True
def spli…Validate Sudoku Board Rows Columns and Boxes in Python
Validate a 9x9 Sudoku board by checking that each row, column, and 3x3 box contains the numbers 1 through 9 exactly once.
def validate_sudoku(board):
def is_valid_group(group):
return sorted(group) == list(range(1, 10))
def get_columns():
return [[board[r][c] for r in range(9)] for c in range(9)]
def get_boxes():
boxes = []
for box_row in range(0, 9, 3):
for box_col in range(0, 9,…How to Use Comprehensions and Generators to Check Data in Python
A beginner-friendly helper that filters numeric values, computes squares and cubes with comprehensions and a generator, and returns a summary dictionary.
def check_data(iterable):
"""Return a summary of numeric data using comprehensions and a generator."""
values = [item for item in iterable if isinstance(item, (int, float))]
squares = [x ** 2 for x in values if x > 0]
cubes = (x ** 3 for x in values if x > 0)
cube_list = list(cubes)
return {
…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 Validate LLM Output in Python
A beginner-friendly DataValidator class that checks required fields and type constraints on LLM-generated or user JSON data.
import json
from typing import Any, Dict, List, Optional
class DataValidator:
"""Simple helper for validating LLM-generated or user data."""
def __init__(self, required_fields: List[str], schema: Optional[Dict[str, str]] = None):
self.required_fields = required_fields
self.schema = schema or…Browse by section
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