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How to Convert Strings to Types in Python Using TypeVar
A beginner-friendly helper that converts a string to int, float, bool, or str with type hints and graceful failure handling.
from typing import TypeVar, Optional
T = TypeVar("T")
def convert_data(value: str, target_type: type[T]) -> Optional[T]:
"""Convert string value to target type; return None on failure."""
try:
if target_type is int:
return int(value)
elif target_type is float:
return f…
How to Filter Data in Python with Type Hints
A reusable filter_data helper uses optional predicates and numeric bounds with modern Python type hints.
from typing import Iterable, TypeVar, Callable, Any
T = TypeVar("T")
def filter_data(
items: Iterable[T],
predicate: Callable[[T], bool] | None = None,
*,
min_value: float | None = None,
max_value: float | None = None,
) -> list[T]:
"""Filter items by predicate and/or numeric bounds."""
r…
How to Group Data by Key in Python with Type Hints
Group a list of dictionaries by a specified key using a typed helper function and print a summary of each group.
from typing import Any, Dict, List, TypeVar, Union
T = TypeVar("T")
def group_by(data: List[Dict[str, Any]], key: str) -> Dict[Any, List[Dict[str, Any]]]:
"""Group a list of dictionaries by a given key."""
grouped: Dict[Any, List[Dict[str, Any]]] = {}
for item in data:
value = item.get(key)
…
How to Merge TypedDicts in Python
Merge two TypedDict dictionaries with type-aware logic using NotRequired, **kwargs unpacking, and safe key updates.
from typing import TypedDict, NotRequired, merge # hypothetical
class User(TypedDict):
name: str
email: NotRequired[str]
age: NotRequired[int]
def merge_users(base: User, **overrides: User) -> User:
"""Merge two user dicts with typing-aware logic."""
result: User = dict(base)
for key, value …
How to Mock open() in Python for Reading File Data
This example shows how to mock Python's built-in open() function using unittest.mock to simulate file reading without touching the disk.
import builtins
from unittest.mock import patch
def read_file_data(filename):
with open(filename, 'r') as f:
return f.read()
def mock_read_data():
fake_data = "This is mocked file content"
class FakeFile:
def __enter__(self):
return self
def __exit__(self, *args):…
How to Mock pathlib Path.read_text with mock_open in Python
Mock pathlib.Path.read_text using patch and mock_open to test file-reading code without touching the filesystem.
import pathlib
from unittest.mock import mock_open, patch
def read_config(filepath: pathlib.Path) -> str:
"""Read file content with pathlib."""
return filepath.read_text()
if __name__ == "__main__":
mock_data = "version: 1.0\nname: demo-app"
with patch("pathlib.Path.open", mock_open(read_data=mo…
How to Mock requests.get in Python
Mock requests.get with unittest.mock to test code that makes HTTP calls without hitting the network.
import requests
from unittest.mock import Mock, patch
def fetch_user_data(user_id):
response = requests.get(f"https://api.example.com/users/{user_id}")
return response.json()
def process_user(user_id):
mock_response = Mock()
mock_response.json.return_value = {"id": user_id, "name": "Alice", "age": 30…
How to Mock return_value with MagicMock in Python unittest
Use unittest.mock.MagicMock to replace a dependency and set return_value to control what a mocked method returns during unit tests.
import unittest
from unittest.mock import MagicMock
class PaymentGateway:
def charge(self, amount):
raise NotImplementedError
class OrderService:
def __init__(self, gateway):
self.gateway = gateway
def process_order(self, amount):
return self.gateway.charge(amount)
class Test…
How to Mock subprocess.run returncode in Python
Simulate subprocess.run return codes in tests with unittest.mock.patch and CompletedProcess.
import subprocess
from unittest.mock import patch
def run_command(cmd):
result = subprocess.run(cmd, capture_output=True, text=True)
return result.returncode
if __name__ == "__main__":
with patch("subprocess.run") as mock_run:
# Simulate a successful command (returncode 0)
mock_run.retu…
How to Parametrize pytest Tests with Multiple Input Cases in Python
This code shows how to use pytest's @pytest.mark.parametrize decorator to run the same test function across multiple input-output combinations, checking that an add function behaves correctly for each case.
import pytest
def add(a, b):
return a + b
@pytest.mark.parametrize("a,b,expected", [
(1, 2, 3),
(5, 5, 10),
(-1, 1, 0),
(0, 0, 0),
(10, -3, 7),
])
def test_add(a, b, expected):
assert add(a, b) == expected
if __name__ == "__main__":
pytest.main([__file__, "-v"])
How to Parse Data with Type Hints in Python
A beginner-friendly helper that parses simple dictionary- or list-like strings into typed Python structures using modern typing annotations.
from typing import Any, Dict, List, Union
def parse_data(raw: str) -> Union[Dict[str, Any], List[Any], str]:
"""Parse a simple string into structured data using type hints."""
cleaned = raw.strip()
if not cleaned:
return {}
if cleaned.startswith("{") and cleaned.endswith("}"):
…
How to Share Fixtures Across Tests with pytest conftest
Learn how to define pytest fixtures in conftest.py and control their scope (function, module, session) so every test in a directory reuses the same setup and teardown.
import pytest
@pytest.fixture
def sample_data():
"""Simple fixture available to all tests in this directory."""
return {"name": "Alice", "age": 30}
@pytest.fixture(scope="session")
def session_data():
"""Fixture created once per test session."""
return {"session_id": 12345}
@pytest.fixture(scope="mo…
How to Skip Slow Tests with pytest.mark in Python
Use pytest.mark.skip and custom marks like @pytest.mark.slow to skip or deselect slow tests during test runs.
import pytest
import time
def test_fast():
assert 1 + 1 == 2
@pytest.mark.skip(reason="slow test skipped by default")
def test_slow():
time.sleep(5)
assert True
@pytest.mark.slow
def test_marked_slow():
time.sleep(5)
assert True
if __name__ == "__main__":
pytest.main([__file__, "-v", "-…
How to Sort Data in Python
Sort sequences with type-safe helpers that handle mixed data with a string fallback.
from typing import Any, TypeVar, Protocol, Sequence, Iterable
T = TypeVar("T")
Comparable = TypeVar("Comparable", bound="Comparable")
class Sortable(Protocol):
def __lt__(self, other: Any) -> bool: ...
S = TypeVar("S", bound=Sortable)
def sort_data(data: Sequence[S], *, reverse: bool = False) -> list[S]:
"…
How to Test Environment Variables with pytest monkeypatch in Python
Shows how to use pytest's monkeypatch fixture to set and delete environment variables for isolated tests.
import os
import pytest
def get_database_url():
return os.getenv("DATABASE_URL", "postgres://default")
def test_database_url_with_env(monkeypatch):
monkeypatch.setenv("DATABASE_URL", "postgres://test-db")
assert get_database_url() == "postgres://test-db"
def test_database_url_default(monkeypatch):
m…
How to Test Hypotheses with Property-Based Check in Python
A Python search that checks an integer property (palindrome divisible by digit sum) and returns the first counterexample within a range, with exactly reproduced output from the code.
def is_property_satisfied(n):
"""
Demonstrates a mathematically inspired property:
checks whether n is both a palindrome and divisible by its digit sum.
"""
s = str(n)
if s != s[::-1]:
return False
digit_sum = sum(int(d) for d in s)
return digit_sum != 0 and n % digit_sum == 0
…
How to Use Basic Type Hints (int, str) for Return Values in Python
Declare a simple function with int and str type hints and a typed return value in Python.
def greet(name: str, age: int) -> str:
return f"{name} is {age} years old."
if __name__ == "__main__":
print(greet("Alice", 30))
How to Use Literal Type Hints in Python
Use typing.Literal to restrict a function parameter to specific allowed string values and get static type checking.
from typing import Literal
def get_status_message(status: Literal["active", "inactive", "pending"]) -> str:
"""Return a message based on the status value."""
if status == "active":
return "Account is active"
elif status == "inactive":
return "Account is inactive"
else:
return "…
How to Use Python Type Hints for Beginners
Build a data helper module with basic type hints — Union, Optional, List, Dict, Any, and TypeVar — to make your code clearer and safer.
from typing import Any, Union, Optional, List, Dict, Tuple, Callable, TypeVar
T = TypeVar("T")
def describe(value: Any) -> str:
"""Return a human-readable description of the value's type."""
if isinstance(value, list):
return f"list of {len(value)} items"
elif isinstance(value, dict):
ret…
How to Use TypedDict and Dataclasses in Python
Create typed data structures with TypedDict and dataclasses, then use them as helper functions for describing objects in a type-safe way.
from typing import TypedDict, NotRequired, Optional
from dataclasses import dataclass
class User(TypedDict):
name: str
age: NotRequired[int]
email: Optional[str]
@dataclass
class Product:
id: int
title: str
price: float = 0.0
def describe_user(user: User) -> str:
age = user.get("age",…
How to Use TypedDict for Structured Dict Typing in Python
Define and use TypedDict to add type hints to dictionaries, improving code clarity and enabling static type checking in your Python projects.
from typing import TypedDict
class User(TypedDict):
name: str
age: int
email: str
def greet(user: User) -> str:
return f"Hello {user['name']}, age {user['age']}, contact {user['email']}"
if __name__ == "__main__":
alice: User = {"name": "Alice", "age": 30, "email": "alice@example.com"}
pr…
How to Use Union Type Hints in Python
This code demonstrates how to use Union type hints to specify that a parameter can accept multiple types (int, float, str) and handle them accordingly.
from typing import Union
def process_value(value: Union[int, float, str]) -> str:
if isinstance(value, (int, float)):
return f"Number: {value * 2}"
return f"String: {value.upper()}"
if __name__ == "__main__":
print(process_value(10))
print(process_value(3.14))
print(process_value("hello"))
How to Use mock.assert_called_with in Python
Verify that a MagicMock received a call with specific positional and keyword arguments using assert_called_with in unittest.
import unittest
from unittest.mock import MagicMock
class TestMockAssertions(unittest.TestCase):
def test_assert_called_with(self):
# Create a mock object
mock = MagicMock()
# Call the mock with specific arguments
mock.send_email("alice@example.com", subject="Greetings", body="Hel…
How to Use setUp and tearDown in Python unittest TestCase
Demonstrates how to structure unit tests with setUp and tearDown methods in Python's unittest framework for reusable test fixtures.
import unittest
class ExampleTest(unittest.TestCase):
def setUp(self):
self.data = [1, 2, 3]
def tearDown(self):
self.data = None
def test_length(self):
self.assertEqual(len(self.data), 3)
def test_contains(self):
self.assertIn(2, self.data)
if __name__ == "__main…
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