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Add Comprehensive Python Development Skills (#419)
* Add extra python skills covering code style, design patterns, resilience, resource management, testing patterns, and type safety ...etc * fix: correct code examples in Python skills - Clarify Python version requirements for type statement (3.10+ vs 3.12+) - Add missing ValidationError import in configuration example - Add missing httpx import and url parameter in async example --------- Co-authored-by: Seth Hobson <wshobson@gmail.com>
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@@ -618,6 +618,52 @@ def test_sorted_list_properties(lst):
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assert sorted_lst[i] <= sorted_lst[i + 1]
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```
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## Test Design Principles
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### One Behavior Per Test
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Each test should verify exactly one behavior. This makes failures easy to diagnose and tests easy to maintain.
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```python
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# BAD - testing multiple behaviors
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def test_user_service():
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user = service.create_user(data)
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assert user.id is not None
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assert user.email == data["email"]
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updated = service.update_user(user.id, {"name": "New"})
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assert updated.name == "New"
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# GOOD - focused tests
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def test_create_user_assigns_id():
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user = service.create_user(data)
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assert user.id is not None
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def test_create_user_stores_email():
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user = service.create_user(data)
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assert user.email == data["email"]
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def test_update_user_changes_name():
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user = service.create_user(data)
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updated = service.update_user(user.id, {"name": "New"})
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assert updated.name == "New"
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```
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### Test Error Paths
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Always test failure cases, not just happy paths.
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```python
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def test_get_user_raises_not_found():
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with pytest.raises(UserNotFoundError) as exc_info:
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service.get_user("nonexistent-id")
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assert "nonexistent-id" in str(exc_info.value)
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def test_create_user_rejects_invalid_email():
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with pytest.raises(ValueError, match="Invalid email format"):
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service.create_user({"email": "not-an-email"})
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```
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## Testing Best Practices
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### Test Organization
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@@ -636,38 +682,131 @@ def test_sorted_list_properties(lst):
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# test_workflows.py
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```
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### Test Naming
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### Test Naming Convention
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A common pattern: `test_<unit>_<scenario>_<expected_outcome>`. Adapt to your team's preferences.
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```python
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# Good test names
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# Pattern: test_<unit>_<scenario>_<expected>
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def test_create_user_with_valid_data_returns_user():
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...
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def test_create_user_with_duplicate_email_raises_conflict():
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...
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def test_get_user_with_unknown_id_returns_none():
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...
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# Good test names - clear and descriptive
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def test_user_creation_with_valid_data():
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"""Clear name describes what is being tested."""
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pass
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def test_login_fails_with_invalid_password():
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"""Name describes expected behavior."""
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pass
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def test_api_returns_404_for_missing_resource():
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"""Specific about inputs and expected outcomes."""
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pass
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# Bad test names
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# Bad test names - avoid these
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def test_1(): # Not descriptive
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pass
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def test_user(): # Too vague
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pass
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def test_function(): # Doesn't explain what's tested
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pass
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```
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### Testing Retry Behavior
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Verify that retry logic works correctly using mock side effects.
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```python
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from unittest.mock import Mock
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def test_retries_on_transient_error():
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"""Test that service retries on transient failures."""
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client = Mock()
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# Fail twice, then succeed
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client.request.side_effect = [
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ConnectionError("Failed"),
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ConnectionError("Failed"),
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{"status": "ok"},
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]
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service = ServiceWithRetry(client, max_retries=3)
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result = service.fetch()
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assert result == {"status": "ok"}
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assert client.request.call_count == 3
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def test_gives_up_after_max_retries():
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"""Test that service stops retrying after max attempts."""
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client = Mock()
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client.request.side_effect = ConnectionError("Failed")
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service = ServiceWithRetry(client, max_retries=3)
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with pytest.raises(ConnectionError):
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service.fetch()
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assert client.request.call_count == 3
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def test_does_not_retry_on_permanent_error():
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"""Test that permanent errors are not retried."""
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client = Mock()
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client.request.side_effect = ValueError("Invalid input")
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service = ServiceWithRetry(client, max_retries=3)
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with pytest.raises(ValueError):
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service.fetch()
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# Only called once - no retry for ValueError
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assert client.request.call_count == 1
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```
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### Mocking Time with Freezegun
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Use freezegun to control time in tests for predictable time-dependent behavior.
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```python
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from freezegun import freeze_time
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from datetime import datetime, timedelta
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@freeze_time("2026-01-15 10:00:00")
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def test_token_expiry():
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"""Test token expires at correct time."""
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token = create_token(expires_in_seconds=3600)
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assert token.expires_at == datetime(2026, 1, 15, 11, 0, 0)
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@freeze_time("2026-01-15 10:00:00")
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def test_is_expired_returns_false_before_expiry():
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"""Test token is not expired when within validity period."""
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token = create_token(expires_in_seconds=3600)
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assert not token.is_expired()
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@freeze_time("2026-01-15 12:00:00")
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def test_is_expired_returns_true_after_expiry():
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"""Test token is expired after validity period."""
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token = Token(expires_at=datetime(2026, 1, 15, 11, 30, 0))
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assert token.is_expired()
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def test_with_time_travel():
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"""Test behavior across time using freeze_time context."""
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with freeze_time("2026-01-01") as frozen_time:
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item = create_item()
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assert item.created_at == datetime(2026, 1, 1)
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# Move forward in time
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frozen_time.move_to("2026-01-15")
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assert item.age_days == 14
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```
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### Test Markers
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```python
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