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write-tests
Guide for writing unit tests. Use this when creating tests to verify Python logic.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Guide for writing unit tests. Use this when creating tests to verify Python logic.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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Guide for running code style linters and formatters. Use this when asked to check code style, run linters, or fix formatting issues.
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Guide for adding new functions to the library. Use this when implementing new API wrappers or utility functions.
Guide for working with Direct Lake semantic models. Use this when implementing Direct Lake-related features or troubleshooting.
| name | write-tests |
| description | Guide for writing unit tests. Use this when creating tests to verify Python logic. |
This skill covers how to write tests for the Semantic Link Labs project.
Use this skill when you need to:
| Component | Details |
|---|---|
| Framework | pytest |
| Location | tests/ directory |
| Assertions | Standard pytest assertions |
tests/
├── __init__.py
├── test_helper_functions.py
├── test_workspaces.py
├── test_admin.py
└── ...
test_*.py or *_test.pytest_<function_name>_<scenario>Test<ClassName>import pytest
import pandas as pd
def test_my_function_returns_dataframe():
"""Test that my_function returns a DataFrame."""
from sempy_labs import my_function
result = my_function()
assert isinstance(result, pd.DataFrame)
def test_my_function_has_expected_columns():
"""Test that result has expected columns."""
from sempy_labs import my_function
result = my_function()
expected_columns = ["Id", "Name", "Type"]
for col in expected_columns:
assert col in result.columns
def test_my_function_filters_by_type():
"""Test that my_function filters by item_type."""
from sempy_labs import my_function
result = my_function(item_type="Report")
assert all(result["Type"] == "Report")
def test_my_function_raises_on_invalid_workspace():
"""Test that invalid workspace raises ValueError."""
from sempy_labs import my_function
with pytest.raises(ValueError, match="Invalid workspace"):
my_function(workspace="NonExistent")
def test_my_function_raises_on_missing_parameter():
"""Test that missing required parameter raises error."""
from sempy_labs import my_function
with pytest.raises(TypeError):
my_function() # Missing required parameter
def test_error_message_is_descriptive():
"""Test that error message contains helpful information."""
from sempy_labs import my_function
with pytest.raises(ValueError) as exc_info:
my_function(invalid_param="bad")
assert "invalid_param" in str(exc_info.value)
assert "bad" in str(exc_info.value)
import pytest
import pandas as pd
@pytest.fixture
def sample_dataframe():
"""Create a sample DataFrame for testing."""
return pd.DataFrame({
"Id": ["1", "2", "3"],
"Name": ["Item A", "Item B", "Item C"],
"Type": ["Report", "Dataset", "Report"],
})
def test_filter_function(sample_dataframe):
"""Test filtering function with sample data."""
from sempy_labs._helper_functions import filter_items
result = filter_items(sample_dataframe, type="Report")
assert len(result) == 2
assert all(result["Type"] == "Report")
@pytest.fixture(params=["Report", "Dataset", "Lakehouse"])
def item_type(request):
"""Parameterized fixture for item types."""
return request.param
def test_with_different_item_types(item_type):
"""Test function with different item types."""
from sempy_labs import my_function
result = my_function(item_type=item_type)
assert isinstance(result, pd.DataFrame)
from unittest.mock import patch, MagicMock
def test_function_with_mocked_api():
"""Test with mocked API response."""
mock_response = MagicMock()
mock_response.json.return_value = {
"value": [
{"id": "123", "name": "Test Item"}
]
}
mock_response.status_code = 200
with patch('sempy_labs._helper_functions._base_api') as mock_api:
mock_api.return_value = mock_response
from sempy_labs import list_items
result = list_items()
assert len(result) == 1
assert result.iloc[0]["Name"] == "Test Item"
from unittest.mock import patch
def test_function_with_mocked_fabric():
"""Test with mocked sempy.fabric calls."""
with patch('sempy.fabric.resolve_workspace_id') as mock_resolve:
mock_resolve.return_value = "12345678-1234-1234-1234-123456789012"
from sempy_labs._helper_functions import resolve_workspace_id
result = resolve_workspace_id("My Workspace")
mock_resolve.assert_called_once()
import pytest
@pytest.mark.parametrize("input_value,expected", [
("value1", "result1"),
("value2", "result2"),
("value3", "result3"),
])
def test_function_with_multiple_inputs(input_value, expected):
"""Test function with multiple input values."""
from sempy_labs import my_function
result = my_function(input_value)
assert result == expected
@pytest.mark.parametrize("workspace", [
None, # Default workspace
"My Workspace", # By name
"12345678-1234-1234-1234-123456789012", # By UUID string
])
def test_accepts_various_workspace_formats(workspace):
"""Test that function accepts various workspace formats."""
from sempy_labs import my_function
# Should not raise
result = my_function(workspace=workspace)
assert result is not None
def test_result_has_required_columns():
"""Test that result DataFrame has required columns."""
from sempy_labs import list_items
result = list_items()
required_columns = ["Id", "Name", "Type"]
for col in required_columns:
assert col in result.columns, f"Missing column: {col}"
def test_result_column_types():
"""Test that result columns have correct types."""
from sempy_labs import list_items
result = list_items()
assert result["Id"].dtype == "object" # string
assert result["Name"].dtype == "object" # string
def test_handles_empty_result():
"""Test that function handles empty results gracefully."""
from sempy_labs import list_items
result = list_items(item_type="NonExistentType")
assert isinstance(result, pd.DataFrame)
assert result.empty
# Columns should still exist even if empty
assert "Id" in result.columns
class TestWorkspaceFunctions:
"""Tests for workspace-related functions."""
def test_list_workspaces(self):
"""Test listing workspaces."""
pass
def test_resolve_workspace_id(self):
"""Test resolving workspace ID."""
pass
def test_resolve_workspace_name(self):
"""Test resolving workspace name."""
pass
class TestHelperFunctions:
"""Tests for helper utility functions."""
def test_is_valid_uuid(self):
"""Test UUID validation."""
pass
def test_create_dataframe(self):
"""Test DataFrame creation helper."""
pass
Before committing new tests:
Run the tests locally:
pytest -sv tests/ -k my_new_test
Verify tests pass consistently (run multiple times)
Check test coverage for the new code
Ensure tests are independent and don't rely on each other