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Pytest

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prowler-cloud
pytest

Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers). For Prowler-specific API/SDK testing conventions, also use prowler-test-api or prowler-test-sdk.

Overview

Publisherprowler-cloud
Repositoryprowler
Skill namepytest
Stars
14.8K
Forks
2.4K
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by prowler-cloud on GitHub. Read the source before you install it.

Installation

Install the Pytest 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.
  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/prowler-cloud/prowler.git /tmp/prowler
mkdir -p .claude/skills
cp -r /tmp/prowler/skills/pytest .claude/skills/pytest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pytest 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 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 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.

Basic Test Structure

python
import pytest

class TestUserService:
    def test_create_user_success(self):
        user = create_user(name="John", email="john@test.com")
        assert user.name == "John"
        assert user.email == "john@test.com"

    def test_create_user_invalid_email_fails(self):
        with pytest.raises(ValueError, match="Invalid email"):
            create_user(name="John", email="invalid")

Fixtures

python
import pytest

@pytest.fixture
def user():
    """Create a test user."""
    return User(name="Test User", email="test@example.com")

@pytest.fixture
def authenticated_client(client, user):
    """Client with authenticated user."""
    client.force_login(user)
    return client

# Fixture with teardown
@pytest.fixture
def temp_file():
    path = Path("/tmp/test_file.txt")
    path.write_text("test content")
    yield path  # Test runs here
    path.unlink()  # Cleanup after test

# Fixture scopes
@pytest.fixture(scope="module")  # Once per module
@pytest.fixture(scope="class")   # Once per class
@pytest.fixture(scope="session") # Once per test session

conftest.py

python
# tests/conftest.py - Shared fixtures
import pytest

@pytest.fixture
def db_session():
    session = create_session()
    yield session
    session.rollback()

@pytest.fixture
def api_client():
    return TestClient(app)

Mocking

python
from unittest.mock import patch, MagicMock

class TestPaymentService:
    def test_process_payment_success(self):
        with patch("services.payment.stripe_client") as mock_stripe:
            mock_stripe.charge.return_value = {"id": "ch_123", "status": "succeeded"}

            result = process_payment(amount=100)

            assert result["status"] == "succeeded"
            mock_stripe.charge.assert_called_once_with(amount=100)

    def test_process_payment_failure(self):
        with patch("services.payment.stripe_client") as mock_stripe:
            mock_stripe.charge.side_effect = PaymentError("Card declined")

            with pytest.raises(PaymentError):
                process_payment(amount=100)

# MagicMock for complex objects
def test_with_mock_object():
    mock_user = MagicMock()
    mock_user.id = "user-123"
    mock_user.name = "Test User"
    mock_user.is_active = True

    result = get_user_info(mock_user)
    assert result["name"] == "Test User"

Parametrize

python
@pytest.mark.parametrize("input,expected", [
    ("hello", "HELLO"),
    ("world", "WORLD"),
    ("pytest", "PYTEST"),
])
def test_uppercase(input, expected):
    assert input.upper() == expected

@pytest.mark.parametrize("email,is_valid", [
    ("user@example.com", True),
    ("invalid-email", False),
    ("", False),
    ("user@.com", False),
])
def test_email_validation(email, is_valid):
    assert validate_email(email) == is_valid

Markers

python
# pytest.ini or pyproject.toml
[tool.pytest.ini_options]
markers = [
    "slow: marks tests as slow",
    "integration: marks integration tests",
]

# Usage
@pytest.mark.slow
def test_large_data_processing():
    ...

@pytest.mark.integration
def test_database_connection():
    ...

@pytest.mark.skip(reason="Not implemented yet")
def test_future_feature():
    ...

@pytest.mark.skipif(sys.platform == "win32", reason="Unix only")
def test_unix_specific():
    ...

# Run specific markers
# pytest -m "not slow"
# pytest -m "integration"

Async Tests

python
import pytest

@pytest.mark.asyncio
async def test_async_function():
    result = await async_fetch_data()
    assert result is not None

Commands

bash
pytest                          # Run all tests
pytest -v                       # Verbose output
pytest -x                       # Stop on first failure
pytest -k "test_user"           # Filter by name
pytest -m "not slow"            # Filter by marker
pytest --cov=src                # With coverage
pytest -n auto                  # Parallel (pytest-xdist)
pytest --tb=short               # Short traceback

References

For general pytest documentation, see:

For Prowler SDK testing with provider-specific patterns (moto, MagicMock), see:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Pytest AI skill do?

Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers). For Prowler-specific API/SDK testing conventions, also use prowler-test-api or prowler-test-sdk.

Why use Pytest on TypingMind?

Because you install it once and use it with any model. Pytest 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 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/prowler-cloud/prowler/tree/master/skills/pytest. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Pytest?

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?

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

Is the Pytest AI skill free?

Yes. It is published on GitHub by prowler-cloud under the Apache-2.0 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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