Testing & modern typing
pytest basics, mocks, type hints, TypedDict, Protocol, and static-checking patterns.
Characterization Test for Legacy Python Code
Capture the exact output of a legacy Python function for known inputs, creating a characterization test that documents current behavior before refactoring.
def legacy_behavior(value):
"""Legacy function that returns a tuple with unconventional types."""
if value == "special":
return None, "legacy-special"
elif value > 100:
return value, "large"
elif value > 0:
return value * 2, "positive-doubled"
elif value == 0:
…
How to Benchmark Python Code with pytest-benchmark and mocks
Use pytest-benchmark to measure function performance while combining Mock and patch for controlled test scenarios.
import time
from unittest.mock import Mock, patch
import pytest
from pytest_benchmark.fixture import BenchmarkFixture
def heavy_operation(data: list[int]) -> int:
"""Simulates a CPU-bound operation."""
return sum(x * x for x in data)
def test_heavy_operation_benchmark(benchmark: BenchmarkFixture) -> None:…
How to Compare Execution Speed Between Python Functions
Measure and compare the average execution time of multiple Python functions using a reusable benchmark helper with time.perf_counter.
import time
import random
def method_a(values):
"""Sort using built-in sorted."""
return sorted(values)
def method_b(values):
"""Sort using list's sort method."""
values_copy = values[:]
values_copy.sort()
return values_copy
def method_c(values):
"""Sort manually using bubble sort (slow,…
How to Flag Unexpected Diff Changes in Python
Compares two snapshot lists, detects unexpected differences, and returns a flag indicating whether the snapshot should be updated.
import difflib
def snapshot_diff(before, after, intentional_changes=None):
"""Compare snapshots and flag only unexpected differences."""
intentional_changes = intentional_changes or set()
diff = list(difflib.unified_diff(before, after, lineterm=""))
has_unexpected = False
for line in diff:
…
How to Load Test a Local API with Locust in Python
Defines a Locust load test that simulates traffic to local endpoints, enabling manual load testing against a development server.
from locust import HttpUser, task, between
class WebsiteUser(HttpUser):
wait_time = between(1, 3)
@task
def home_page(self):
self.client.get("/")
@task(3)
def about_page(self):
self.client.get("/about")
if __name__ == "__main__":
print("Run with: locust -f this_file.py --h…
How to Mock a Factory Boy Model Instance in Python
Create a factory boy factory, then patch its Meta.model with a Mock to control instance behavior in tests.
import factory
from dataclasses import dataclass
from unittest.mock import Mock, patch
import builtins
@dataclass
class User:
name: str
age: int
class UserFactory(factory.Factory):
class Meta:
model = User
name = "Alice"
age = 30
def get_user_name(user):
return user.name
def ma…
How to Mock an Object Method in Python unittest
Mock a method on an instance or class with @patch.object, set its return value, and assert its call arguments in Python unittest.
import unittest
from unittest.mock import patch
class Calculator:
def add(self, a, b):
return a + b
def multiply(self, a, b):
return a * b
class TestCalculator(unittest.TestCase):
def test_add_normal(self):
calc = Calculator()
result = calc.add(2, 3)
self.asse…
How to Mock and Stub API Calls in Playwright E2E Tests with Python
This code demonstrates how to mock and stub API responses in Playwright end-to-end tests using Python's unittest.mock patch and Playwright's APIRequestContext.
import re
from unittest.mock import patch
from playwright.sync_api import sync_playwright
def verify_api_mock(page, mock_url, mock_response):
with patch("playwright.sync_api.APIRequestContext.get") as mock_get:
mock_get.return_value.json.return_value = mock_response
mock_get.return_value.status_co…
How to Run Test Coverage with pytest-cov in Python
Run pytest with coverage reporting using pytest-cov on a temporary project and see line-by-line coverage output.
import os
import subprocess
import tempfile
from pathlib import Path
def sample_function(x: int) -> int:
"""A simple function to demonstrate coverage."""
if x > 0:
return x * 2
else:
return -x
def run_pytest_with_coverage() -> str:
"""Run pytest with coverage on a temp project and r…
How to Run an Integration Test with Docker Compose Mock in Python
Run a Python integration test against a docker-compose environment, using mocks to simulate service health and business logic responses.
import subprocess
import json
from typing import Dict
def run_integration_test() -> Dict[str, str]:
"""
Simulates an integration test against a docker-compose environment
using a mock service that returns canned responses.
"""
# Mock docker-compose environment check
env_ready = subprocess.run(…
How to Snapshot Test JSON with Mock in Python
Use pytest-snapshot to capture the exact output of a JSON-loading function, with and without mocking json.loads, so future changes are automatically detected.
import json
from unittest.mock import Mock, patch
import pytest
def load_config(data):
config = json.loads(data)
return {"host": config["host"], "port": config["port"]}
def test_load_config_snapshot(snapshot):
mock_data = json.dumps({"host": "localhost", "port": 8080, "extra": "ignored"})
result = …
How to Test Properties with Random Inputs in Python
Write a simple property-based test in Python using random string generation to verify that string invariants like reverse-twice identity and uppercase idempotence always hold.
import random
import string
def generate_random_string(length: int) -> str:
"""Generate a random alphanumeric string of given length."""
chars = string.ascii_letters + string.digits
return "".join(random.choice(chars) for _ in range(length))
def reverse_twice_is_identity(s: str) -> bool:
"""Propert…
How to Use Hypothesis Strategies for Lists of Text in Python
Generate random lists of non-empty strings with Hypothesis and verify that joining them with a comma-and-space separator meets expected length and containment invariants.
from hypothesis import given, strategies as st
from hypothesis import example
@given(st.lists(st.text(min_size=1, max_size=10), min_size=1, max_size=5))
def test_joined_string_length(items):
"""Each text is non-empty; a joined string should be at least as long
as the number of items (separator adds character…
How to Use Mock Flip Mutation Testing in Python
Demonstrates how mutation testing tools flip Boolean literals (mock flip) in Python source to verify test suite effectiveness in catching logic changes.
import random
# In mutation testing, a "mock flip" intentionally changes a Boolean
# constant to False (or True) to see if the test suite catches it.
# This is a common "constant mutation" applied to a source file's literals.
def is_even(n: int) -> bool:
"""Return True if n is even. Contains a Boolean literal us…
How to Use Stubs, Fakes, Spies, and Mocks in Python Testing
Implement four types of test doubles — stubs, fakes, spies, and mocks — as subclasses of a PaymentGateway interface to replace real dependencies during testing.
class PaymentGateway:
def charge(self, amount):
raise NotImplementedError
class StubPaymentGateway(PaymentGateway):
"""Returns a fixed response without any logic."""
def charge(self, amount):
return {"success": True, "transaction_id": "stub-12345"}
class FakePaymentGateway(PaymentGatewa…
How to Use TypedDict for Data Validation in Python
Define a TypedDict schema and validate raw dictionary input with type hints for safer, more readable data handling.
from typing import Any, Dict, List, Optional, Union, TypedDict, Literal
class Product(TypedDict):
product_id: int
name: str
price: Union[int, float]
in_stock: bool
tags: Optional[List[str]]
def validate_product(data: Dict[str, Any]) -> Product:
product_id: int = int(data["product_id"])
na…
How to Validate Data in Python with Typing Hints
Build a runtime validation helper that checks values against Python type hints like Optional, list, and basic types.
from typing import Any, Optional, Union, TypeVar, get_origin, get_args
T = TypeVar("T")
def validate(value: Any, expected_type: type) -> Optional[str]:
"""Returns an error message if value doesn't match expected_type, else None."""
# Handle Optional[...] types
origin = get_origin(expected_type)
if or…
Use pytest fixture to mock a database connection in Python
This code shows how to use a pytest fixture and unittest.mock to replace a database connection with a Mock, enabling isolated tests without a real database.
import pytest
import sqlite3
from unittest.mock import Mock
class Database:
def __init__(self, connection):
self.connection = connection
def get_user(self, user_id):
cursor = self.connection.cursor()
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
return cursor.…
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