Modern tooling
uv, ruff, pyproject.toml, packaging, and current Python project workflows.
How to Define Nox Sessions in Python
Automate repetitive tasks like testing and linting with reusable Nox sessions.
import nox
@nox.session(python=["3.9", "3.10"])
def tests(session):
session.install("pytest")
session.run("pytest")
@nox.session(python="3.9")
def lint(session):
session.install("ruff")
session.run("ruff", "check", ".")
if __name__ == "__main__":
print("Nox sessions defined: tests, lint")
…How to Parametrize Tests in Python with pytest
This code demonstrates how to use pytest's @pytest.mark.parametrize decorator to run a single test function against multiple input sets, ensuring comprehensive coverage with minimal code duplication.
import pytest
def multiply(a, b):
return a * b
@pytest.mark.parametrize("x, y, expected", [
(2, 3, 6),
(4, 5, 20),
(0, 10, 0),
(7, 1, 7),
])
def test_multiply(x, y, expected):
result = multiply(x, y)
assert result == expected, f"multiply({x}, {y}) = {result}, expected {expected}"
if _…How to Use pytest Fixtures and conftest.py for Shared Setup in Python
Learn how to define reusable pytest fixtures for shared setup and use them to keep tests clean and maintainable.
import pytest
class Calculator:
def add(self, a, b):
return a + b
def multiply(self, a, b):
return a * b
@pytest.fixture
def calc():
return Calculator()
@pytest.fixture
def sample_numbers():
return (3, 5)
def test_add(calc, sample_numbers):
a, b = sample_numbers
assert c…pytest mark slow skip integration
Uses pytest markers to select fast tests, skip unfinished ones, and run integration checks with verbose output.
import pytest
def test_fast():
assert 1 + 1 == 2
@pytest.mark.slow
def test_slow():
import time
time.sleep(1)
assert 5 * 5 == 25
@pytest.mark.skip(reason="Not ready for production")
def test_skipped():
assert 2 + 2 == 5
@pytest.mark.integration
def test_integration():
database = {"users": […Browse by section
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Modern tooling — Python code examples
What you will find here
This page collects modern tooling snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.