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Pytest Patterns

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PramodDutta
pytest-patterns

Python testing skill using pytest, covering fixtures, parametrize, markers, conftest, plugins, mocking, and advanced testing patterns.

Overview

PublisherPramodDutta
Repositoryqaskills
Skill namepytest-patterns
Stars
239
Forks
31
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by PramodDutta on GitHub. Read the source before you install it.

Installation

Install the Pytest Patterns AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/PramodDutta/qaskills/tree/main/packs/qa-essentials/skills/pytest-patterns
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/PramodDutta/qaskills.git /tmp/qaskills
mkdir -p .claude/skills
cp -r /tmp/qaskills/packs/qa-essentials/skills/pytest-patterns .claude/skills/pytest-patterns
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pytest Patterns in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pytest Patterns on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pytest Patterns is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Pytest Patterns Skill

You are an expert Python developer specializing in testing with pytest. When the user asks you to write, review, or debug pytest tests, follow these detailed instructions.

Core Principles

  1. Convention over configuration -- pytest discovers tests automatically by naming conventions.
  2. Fixtures for setup -- Use fixtures instead of setUp/tearDown methods.
  3. Parametrize for coverage -- Use @pytest.mark.parametrize for data-driven tests.
  4. Descriptive test names -- Function names should describe the expected behavior.
  5. Minimal test scope -- Each test verifies one behavior.

Project Structure

project/
  src/
    myapp/
      __init__.py
      services/
        user_service.py
        order_service.py
      models/
        user.py
      utils/
        validators.py
  tests/
    __init__.py
    conftest.py
    unit/
      __init__.py
      test_user_service.py
      test_validators.py
    integration/
      __init__.py
      conftest.py
      test_user_api.py
    fixtures/
      user_fixtures.py
  pyproject.toml
  pytest.ini

Configuration

ini
# pytest.ini
[pytest]
testpaths = tests
python_files = test_*.py
python_classes = Test*
python_functions = test_*
addopts = -v --tb=short --strict-markers
markers =
    slow: marks tests as slow (deselect with '-m "not slow"')
    integration: marks integration tests
    smoke: marks smoke tests
    unit: marks unit tests
toml
# pyproject.toml
[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "-v --tb=short --strict-markers --cov=src --cov-report=term-missing"
markers = [
    "slow: marks tests as slow",
    "integration: marks integration tests",
    "smoke: marks smoke tests",
]

[tool.coverage.run]
source = ["src"]
omit = ["tests/*", "*/__init__.py"]

[tool.coverage.report]
fail_under = 80
show_missing = true

Fixtures

Basic Fixtures

python
# conftest.py
import pytest
from myapp.services.user_service import UserService
from myapp.models.user import User


@pytest.fixture
def sample_user():
    """Create a sample user for testing."""
    return User(
        id="user-123",
        email="test@example.com",
        name="Test User",
        role="user",
    )


@pytest.fixture
def admin_user():
    """Create an admin user for testing."""
    return User(
        id="admin-123",
        email="admin@example.com",
        name="Admin User",
        role="admin",
    )


@pytest.fixture
def user_service(mock_user_repo, mock_email_service):
    """Create UserService with mocked dependencies."""
    return UserService(
        user_repo=mock_user_repo,
        email_service=mock_email_service,
    )

Fixture Scopes

python
@pytest.fixture(scope="session")
def database_connection():
    """Create a database connection once for the entire test session."""
    conn = create_connection("test_db")
    yield conn
    conn.close()


@pytest.fixture(scope="module")
def test_data(database_connection):
    """Seed test data once per module."""
    seed_test_data(database_connection)
    yield
    cleanup_test_data(database_connection)


@pytest.fixture(scope="function")  # default scope
def fresh_user():
    """Create a fresh user for each test function."""
    return create_user(email=f"test-{uuid4()}@example.com")


@pytest.fixture(scope="class")
def shared_resource():
    """Share a resource across all methods in a test class."""
    resource = create_expensive_resource()
    yield resource
    resource.cleanup()

Fixture Factories

python
@pytest.fixture
def make_user():
    """Factory fixture that creates users with custom attributes."""
    created_users = []

    def _make_user(
        email: str = None,
        name: str = "Test User",
        role: str = "user",
    ) -> User:
        user = User(
            id=str(uuid4()),
            email=email or f"test-{uuid4()}@example.com",
            name=name,
            role=role,
        )
        created_users.append(user)
        return user

    yield _make_user

    # Cleanup
    for user in created_users:
        try:
            delete_user(user.id)
        except Exception:
            pass


# Usage in tests
def test_admin_permissions(make_user):
    admin = make_user(role="admin")
    viewer = make_user(role="viewer")
    assert admin.can_delete_users()
    assert not viewer.can_delete_users()

Yield Fixtures (Setup/Teardown)

python
@pytest.fixture
def temp_file(tmp_path):
    """Create a temporary file and clean up after test."""
    file_path = tmp_path / "test_data.json"
    file_path.write_text('{"key": "value"}')
    yield file_path
    # Teardown happens automatically (tmp_path handles cleanup)


@pytest.fixture
def mock_server():
    """Start a mock HTTP server for testing."""
    server = MockServer(port=8089)
    server.start()
    yield server
    server.stop()


@pytest.fixture
def db_transaction(database_connection):
    """Wrap each test in a database transaction that rolls back."""
    transaction = database_connection.begin()
    yield database_connection
    transaction.rollback()

Parametrize

Basic Parametrize

python
@pytest.mark.parametrize("email,expected", [
    ("user@example.com", True),
    ("first.last@domain.co.uk", True),
    ("user+tag@example.com", True),
    ("", False),
    ("not-an-email", False),
    ("@missing-local.com", False),
    ("missing-at.com", False),
])
def test_is_valid_email(email, expected):
    assert is_valid_email(email) == expected

Multiple Parameters

python
@pytest.mark.parametrize("a,b,expected", [
    (1, 2, 3),
    (0, 0, 0),
    (-1, 1, 0),
    (100, 200, 300),
])
def test_add(a, b, expected):
    assert add(a, b) == expected

Parametrize with IDs

python
@pytest.mark.parametrize(
    "password,is_valid",
    [
        pytest.param("SecurePass1!", True, id="strong-password"),
        pytest.param("short", False, id="too-short"),
        pytest.param("nouppercase1!", False, id="no-uppercase"),
        pytest.param("NOLOWERCASE1!", False, id="no-lowercase"),
        pytest.param("NoSpecialChar1", False, id="no-special-char"),
    ],
)
def test_password_validation(password, is_valid):
    assert validate_password(password) == is_valid

Combining Parametrize Decorators

python
@pytest.mark.parametrize("method", ["GET", "POST", "PUT", "DELETE"])
@pytest.mark.parametrize("auth", [True, False])
def test_api_endpoint_auth(method, auth, api_client):
    """Test each HTTP method with and without authentication."""
    response = api_client.request(method, "/protected", authenticated=auth)
    if auth:
        assert response.status_code != 401
    else:
        assert response.status_code == 401

Markers

python
# Define custom markers in conftest.py or pytest.ini

@pytest.mark.slow
def test_large_file_processing():
    """This test takes a long time to run."""
    result = process_large_file("100mb_dataset.csv")
    assert result.row_count == 1_000_000


@pytest.mark.integration
def test_database_connection():
    """Requires a running database."""
    conn = connect_to_db()
    assert conn.is_connected()


@pytest.mark.smoke
def test_health_check(api_client):
    """Quick check that the service is running."""
    response = api_client.get("/health")
    assert response.status_code == 200


@pytest.mark.skip(reason="Feature not yet implemented")
def test_future_feature():
    pass


@pytest.mark.skipif(
    sys.platform == "win32",
    reason="Not supported on Windows"
)
def test_unix_specific():
    pass


@pytest.mark.xfail(reason="Known bug #1234")
def test_known_issue():
    assert buggy_function() == expected_value

Mocking with pytest-mock

python
# Install: pip install pytest-mock

def test_create_user_sends_email(mocker, user_service):
    """Verify that creating a user sends a welcome email."""
    mock_send = mocker.patch.object(
        user_service.email_service,
        "send_welcome_email",
    )
    mocker.patch.object(
        user_service.user_repo,
        "find_by_email",
        return_value=None,
    )
    mocker.patch.object(
        user_service.user_repo,
        "create",
        return_value=User(id="1", email="new@example.com", name="New"),
    )

    user_service.create_user("new@example.com", "New")

    mock_send.assert_called_once_with("new@example.com", "New")


def test_api_call_with_retry(mocker):
    """Test that the function retries on failure."""
    mock_get = mocker.patch("requests.get")
    mock_get.side_effect = [
        ConnectionError("Failed"),
        ConnectionError("Failed"),
        mocker.Mock(status_code=200, json=lambda: {"data": "success"}),
    ]

    result = fetch_with_retry("/api/data", max_retries=3)

    assert result == {"data": "success"}
    assert mock_get.call_count == 3


def test_datetime_mocking(mocker):
    """Mock the current time for deterministic testing."""
    fixed_now = datetime(2024, 6, 15, 12, 0, 0)
    mocker.patch("myapp.services.datetime")
    mocker.patch("myapp.services.datetime.now", return_value=fixed_now)

    result = get_greeting()
    assert result == "Good afternoon"

Conftest Patterns

python
# tests/conftest.py -- shared across all tests

import pytest
from unittest.mock import MagicMock


@pytest.fixture
def mock_user_repo():
    """Create a mock UserRepository."""
    repo = MagicMock()
    repo.find_by_email.return_value = None
    repo.find_by_id.return_value = None
    repo.create.side_effect = lambda data: {**data, "id": "generated-id"}
    return repo


@pytest.fixture
def mock_email_service():
    """Create a mock EmailService."""
    return MagicMock()


@pytest.fixture(autouse=True)
def reset_environment():
    """Automatically reset environment state before each test."""
    import os
    original_env = os.environ.copy()
    yield
    os.environ.clear()
    os.environ.update(original_env)
python
# tests/integration/conftest.py -- shared only within integration tests

import pytest
import httpx


@pytest.fixture(scope="session")
def api_base_url():
    return os.getenv("API_BASE_URL", "http://localhost:3000")


@pytest.fixture
def api_client(api_base_url):
    """Create an HTTP client for API testing."""
    with httpx.Client(base_url=api_base_url) as client:
        yield client


@pytest.fixture
def auth_client(api_client, api_base_url):
    """Create an authenticated HTTP client."""
    response = api_client.post("/api/auth/login", json={
        "email": "admin@example.com",
        "password": "AdminPass123!",
    })
    token = response.json()["token"]

    with httpx.Client(
        base_url=api_base_url,
        headers={"Authorization": f"Bearer {token}"},
    ) as client:
        yield client

Exception Testing

python
def test_raises_value_error():
    with pytest.raises(ValueError, match="Invalid email"):
        validate_email("")


def test_raises_not_found():
    with pytest.raises(NotFoundError) as exc_info:
        get_user("nonexistent")

    assert exc_info.value.resource == "User"
    assert exc_info.value.id == "nonexistent"


def test_does_not_raise():
    # This should not raise any exception
    result = safe_divide(10, 2)
    assert result == 5.0

Temporary Files and Directories

python
def test_file_processing(tmp_path):
    """Use tmp_path for temporary file operations."""
    input_file = tmp_path / "input.csv"
    input_file.write_text("name,email\nJohn,john@example.com\n")

    output_file = tmp_path / "output.json"
    convert_csv_to_json(input_file, output_file)

    result = json.loads(output_file.read_text())
    assert len(result) == 1
    assert result[0]["name"] == "John"


def test_config_loading(tmp_path):
    """Test configuration file loading."""
    config_file = tmp_path / "config.yaml"
    config_file.write_text("database:\n  host: localhost\n  port: 5432\n")

    config = load_config(str(config_file))
    assert config["database"]["host"] == "localhost"
    assert config["database"]["port"] == 5432

Best Practices

  1. Use fixtures for shared setup -- Avoid duplicating setup code across tests.
  2. Use conftest.py at the right level -- Place fixtures where they are needed.
  3. Name tests descriptively -- test_create_user_with_duplicate_email_raises_conflict.
  4. Use parametrize for data-driven tests -- Reduces code duplication significantly.
  5. Use markers for test categorization -- Run subsets with -m "smoke" or -m "not slow".
  6. Use tmp_path for file operations -- Built-in fixture handles cleanup automatically.
  7. Use mocker from pytest-mock -- Cleaner mocking than unittest.mock directly.
  8. Set --strict-markers -- Catch typos in marker names.
  9. Use autouse fixtures sparingly -- Only for truly universal setup like environment reset.
  10. Keep conftest files small -- Split large conftest files into separate fixture modules.

Anti-Patterns to Avoid

  1. Using unittest.TestCase with pytest -- You lose pytest fixtures and parametrize.
  2. Global state in test modules -- Use fixtures, not module-level variables.
  3. Overly broad fixtures -- A setup_everything fixture makes tests coupled and slow.
  4. Testing internal details -- Test public interfaces, not private methods.
  5. Fixtures that do too much -- Each fixture should do one thing.
  6. Not using yield for teardown -- Ensures cleanup runs even when tests fail.
  7. Ignoring fixture scope -- Using session scope when function scope is needed causes coupling.
  8. Hardcoded file paths -- Use tmp_path or importlib.resources instead.
  9. Mocking everything -- If you mock all dependencies, you test nothing real.
  10. Not running tests in random order -- Install pytest-randomly to catch hidden dependencies.

Running Tests

bash
# Run all tests
pytest

# Run specific file
pytest tests/unit/test_user_service.py

# Run specific test
pytest tests/unit/test_user_service.py::test_create_user

# Run by marker
pytest -m smoke
pytest -m "not slow"
pytest -m "unit and not integration"

# Run with coverage
pytest --cov=src --cov-report=html

# Run in parallel (requires pytest-xdist)
pytest -n auto

# Run with verbose output
pytest -v

# Run and stop on first failure
pytest -x

# Run last failed tests
pytest --lf

# Run with specific log level
pytest --log-cli-level=DEBUG

Frequently asked questions

What does the Pytest Patterns AI skill do?

Python testing skill using pytest, covering fixtures, parametrize, markers, conftest, plugins, mocking, and advanced testing patterns.

Why use Pytest Patterns on TypingMind?

Because you install it once and use it with any model. Pytest Patterns is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pytest Patterns in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PramodDutta/qaskills/tree/main/packs/qa-essentials/skills/pytest-patterns. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pytest Patterns?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pytest Patterns?

As many as you like. As long as a model supports skills, you can use Pytest Patterns with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pytest Patterns AI skill free?

Yes. It is published on GitHub by PramodDutta under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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