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How to Validate Data with a Simple Dict-Based Rules Helper in Python
Validates a dictionary against a set of callable rules, printing pass/fail per field and returning an overall boolean.
import json
from pathlib import Path
from typing import Any, Callable
def validate_data(
data: dict[str, Any],
rules: dict[str, Callable[[Any], bool]],
path: Path | None = None,
) -> bool:
"""Validate a dict against a set of simple rules."""
all_valid = True
for field, validator in rules.item…How to Validate Data with ThreadPoolExecutor in Python
This code shows how to validate a list of numbers concurrently using ThreadPoolExecutor, dramatically speeding up slow validation tasks by running them in parallel threads.
import time
from concurrent.futures import ThreadPoolExecutor
from dataclasses import dataclass
@dataclass
class Result:
is_valid: bool
value: int
def validate(value: int) -> Result:
time.sleep(0.1) # simulate slow validation (API call, DB check)
return Result(is_valid=0 < value < 100, value=value…How to Validate Dataclass Fields with Python Type Hints
A beginner-friendly helper that checks if instance attributes match their declared type hints using dataclasses and get_type_hints.
from typing import Any, TypeVar, get_type_hints
from dataclasses import dataclass
T = TypeVar("T")
@dataclass
class User:
name: str
age: int
email: str
def validate_fields(obj: Any) -> dict[str, bool]:
"""Check if object attributes match declared type hints."""
hints = get_type_hints(obj.__class…How to Validate Data in Python for Beginners
A beginner-friendly Python class for validating required fields, types, ranges, and allowed choices in dict payloads.
import json
from typing import Any, Dict, List, Optional, Union
class Validator:
"""A simple validate data helper designed for beginners."""
def __init__(self, data: Union[Dict[str, Any], List[Any]]):
self.data = data
self.errors: Dict[str, str] = {}
def validate_required(self, field: s…How to Validate JWT Claims (exp, iss, aud) in Python
This code demonstrates how to decode and validate a JWT's essential claims—expiration (exp), issuer (iss), and audience (aud)—using the PyJWT library, returning clear error messages for common validation failures.
import jwt
from datetime import datetime, timezone, timedelta
SECRET = "mock-secret"
def validate_token(token, expected_iss, expected_aud):
try:
decoded = jwt.decode(
token,
SECRET,
algorithms=["HS256"],
options={"require": ["exp", "iss", "aud"]},
…Sort Python list by query param order_by
Sort a list of dataclass objects dynamically by a field name passed as a query param, with asc/desc direction support.
from dataclasses import dataclass
@dataclass
class Item:
name: str
price: int
def sort_items(items, order_by, direction="asc"):
if order_by not in ("name", "price"):
raise ValueError(f"Unsupported sort field: {order_by}")
reverse = direction.lower() == "desc"
return sorted(items, key=l…How to Invalidate a Cache in Python with lru_cache
This code demonstrates how to clear the cache of an @lru_cache decorated function in Python using cache_clear(), showing the effect on cached results.
from functools import lru_cache
import time
@lru_cache(maxsize=None)
def expensive_operation(key):
return f"Computed value for {key} at {time.time():.6f}"
def invalidate_cache():
expensive_operation.cache_clear()
if __name__ == "__main__":
print(expensive_operation("alpha"))
print(expensive_operatio…Rate Limiting with a Simple Python RateLimiter Class
A beginner-friendly Python rate limiter that tracks call timestamps and enforces a maximum number of calls within a rolling time window, with a helper to validate positive integers.
import time
class RateLimiter:
def __init__(self, max_calls, period_seconds):
self.max_calls = max_calls
self.period_seconds = period_seconds
self.calls = []
def is_allowed(self):
now = time.time()
while self.calls and now - self.calls[0] >= self.period_seconds:
…How to Build a Microservice Helper in Python
A beginner-friendly Python helper that validates input, normalizes service responses, and simulates user management—showing clean patterns for microservice development.
import json
from typing import Any, Dict, List
class DataValidator:
"""Simple validator for common data patterns."""
@staticmethod
def is_valid_email(value: str) -> bool:
"""Check if value looks like an email."""
return "@" in value and "." in value.split("@")[-1]
@staticmethod
…Create a Minimal Great Expectations Suite Mock in Python
Build a small Python class that mimics a Great Expectations suite, storing and serializing column expectations as JSON.
import json
class GreatExpectationsSuite:
"""A minimal mock of a Great Expectations suite."""
def __init__(self, suite_name, expectations=None):
self.suite_name = suite_name
self.expectations = expectations or []
def add_expectation(self, expectation_type, column=None, kwargs=None):
…How to Build a Data Validation Schema in Python
Create a lightweight validation schema using dataclasses and lambda validators to check fields in a dictionary.
import re
from dataclasses import dataclass, field
from typing import Any, Callable
@dataclass
class Field:
name: str
validator: Callable[[Any], bool]
required: bool = True
def validate(self, value: Any) -> bool:
if not self.required and value is None:
return True
return …How to create a global control holdout group in Python
This code implements a deterministic global control holdout group, randomly selecting a fraction of users to be excluded from feature rollouts for experiment validation.
import random
class GlobalControl:
def __init__(self, population_size, holdout_fraction=0.2, seed=42):
random.seed(seed)
self.population_size = population_size
self.holdout_fraction = holdout_fraction
self.holdout_size = int(population_size * holdout_fraction)
self.holdout_…How to Validate Data Before Scaling in Python
A reusable Python helper that validates required fields and constraint checks on data rows before entering a database pipeline, improving data quality and throughput.
def validate_data(data, required_fields, constraints=None):
"""
Basic validation helper demonstrating data-quality workflows
before scaling (catches bad rows early, improves throughput).
"""
constraints = constraints or {}
errors = []
for field in required_fields:
if field not in d…How to Enforce a Strict Referrer Policy in Python
Validate HTTP headers to enforce a strict same-origin Referrer policy, accepting only origin-only URLs or absent Referer values.
import re
from unittest.mock import patch
def strict_referrer_policy(headers):
"""Return True if Referer header is absent or strictly same-origin."""
referer = headers.get("Referer")
if referer is None:
return True
# Strict-Origin-When-Cross-Origin allows same-origin full URL
# but here we…How to Revoke Tokens with a Blacklist Set in Python
A minimal TokenBlacklist class using a Python set to revoke, batch-revoke, check, and remove expired tokens for simple token invalidation.
import time
class TokenBlacklist:
def __init__(self):
self.blacklisted_tokens = set()
def revoke(self, token):
self.blacklisted_tokens.add(token)
print(f"Token {token} revoked. Blacklist size: {len(self.blacklisted_tokens)}")
def revoke_batch(self, tokens):
before = len(s…How to mock resource request limits in Python
A Python class that simulates CPU and memory limit checks for resource requests, returning clear acceptance or rejection messages.
class ResourceLimits:
def __init__(self, cpu_limit, memory_limit):
self.cpu_limit = cpu_limit
self.memory_limit = memory_limit
def check_request(self, cpu, memory):
if cpu > self.cpu_limit:
return "CPU limit exceeded: {cpu} > {limit}".format(cpu=cpu, limit=self.cpu_limit)
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