Testing with pytest

Introduction

pytest is the de-facto Python test framework — minimal boilerplate, powerful fixtures, parametrization, plugin ecosystem.

Understanding the topic

Core concepts to understand:

• Tests are functions starting with test_.
• assert + rich introspection.
• Fixtures for setup/teardown.
• @pytest.mark.parametrize for table tests.

Syntax reference

Visual flow / code:

# test_math.py
import pytest

def add(a, b): return a + b

@pytest.mark.parametrize("a,b,want", [
    (1, 2, 3),
    (-1, 1, 0),
    (0, 0, 0),
])
def test_add(a, b, want):
    assert add(a, b) == want

@pytest.fixture
def db():
    conn = connect()
    yield conn
    conn.close()

def test_user(db):
    assert db.query("users") is not None

Execution workflow

Real-world use

pytest + pytest-cov + pytest-asyncio covers 95% of test needs. Most Python projects ship with pytest, mypy, and ruff in CI.

Best practices

• Write tests as you write code.
• Use fixtures for shared setup.
• Parametrize over duplicating tests.

Hands-on exercise

Interview preparation — practice these questions:

• unittest vs pytest?
• What's a fixture?
• How do you mock in pytest?

Summary

In summary: pytest = clean, powerful. Fixtures + parametrize = scalable tests.