In this post, I’ll walk through the journey of implementing unit testing, handling complex configuration challenges, and introducing robust code coverage in ReadmeGenie. From initial test design to setting up pre-commit hooks, this process involved a range of improvements in code quality, reliability, and developer workflow.
To start, I chose unittest as the primary framework for writing and executing tests. Python’s built-in unittest provides a structured approach for defining test cases, and its integration with mock makes it ideal for testing complex configurations and API calls.
I created a dedicated test runner (tests/test_runner.py) for automatic discovery and execution of all test files in the tests/ directory:
# tests/test_runner.py import unittest if __name__ == "__main__": loader = unittest.TestLoader() suite = loader.discover(start_dir="tests", pattern="test_*.py") runner = unittest.TextTestRunner(verbosity=2) runner.run(suite)
This setup ensures that running python tests/test_runner.py will automatically load and run all test files, making it easy to validate the project’s overall functionality.
The ReadmeGenie project required comprehensive testing for several components:
Each test file is named according to the module it tests (e.g., test_parse_arg.py for argument parsing and test_model.py for model functions), ensuring a clear, maintainable structure.
Setting up test_loadConfig.py turned out to be the most challenging part of this project. Initially, I encountered persistent issues related to environment variables and file path checks. Since load_config() is intended to handle various configuration sources (e.g., environment variables, .env files, JSON, and TOML files), the tests required extensive mocking to simulate these environments accurately.
The primary issues involved:
Environment Variable Conflicts: Existing environment variables sometimes interfered with mocked values. Using @patch.dict("os.environ", {}, clear=True), I cleared the environment variables within the test scope to ensure consistent results.
File Path Checks: Since load_config() checks for file existence, I used os.path.exists to simulate scenarios where configuration files were present or absent.
Mocking open and toml.load: These required precise mocking to handle cases of missing, empty, or populated configuration files. Using mock_open with patch on toml.load, I effectively simulated each situation.
After resolving these issues, test_loadConfig.py now covers three main scenarios:
Here’s the final version of test_loadConfig.py:
# tests/test_runner.py import unittest if __name__ == "__main__": loader = unittest.TestLoader() suite = loader.discover(start_dir="tests", pattern="test_*.py") runner = unittest.TextTestRunner(verbosity=2) runner.run(suite)
With our tests in place, we focused on measuring and improving coverage using coverage.py. By setting an 80% threshold, we aimed to ensure all critical parts of the code are tested.
I configured coverage.py with the following settings in pyproject.toml:
import unittest from unittest.mock import mock_open, patch from loadConfig import load_config class TestLoadConfig(unittest.TestCase): @patch.dict("os.environ", {}, clear=True) @patch("loadConfig.os.getenv", side_effect=lambda key, default=None: default) @patch("loadConfig.os.path.exists", return_value=False) @patch("builtins.open", new_callable=mock_open, read_data="{}") @patch("loadConfig.toml.load", return_value={}) def test_load_config_empty_file(self, mock_toml_load, mock_open_file, mock_exists, mock_getenv): config = load_config() self.assertEqual(config, {}) @patch.dict("os.environ", {}, clear=True) @patch("loadConfig.os.getenv", side_effect=lambda key, default=None: default) @patch("loadConfig.os.path.exists", return_value=True) @patch("builtins.open", new_callable=mock_open, read_data='{"api_key": "test_key"}') @patch("loadConfig.toml.load", return_value={"api_key": "test_key"}) def test_load_config_with_valid_data(self, mock_toml_load, mock_open_file, mock_exists, mock_getenv): config = load_config() self.assertEqual(config.get("api_key"), "test_key") @patch.dict("os.environ", {}, clear=True) @patch("loadConfig.os.getenv", side_effect=lambda key, default=None: default) @patch("loadConfig.os.path.exists", return_value=False) @patch("builtins.open", side_effect=FileNotFoundError) @patch("loadConfig.toml.load", return_value={}) def test_load_config_file_not_found(self, mock_toml_load, mock_open_file, mock_exists, mock_getenv): config = load_config() self.assertEqual(config, {})
This configuration includes branch coverage, highlights missing lines, and enforces a minimum 75% coverage threshold.
To integrate this into the development workflow, I added a pre-commit hook to ensure code coverage is checked on each commit. If coverage falls below 75%, the commit is blocked, prompting developers to improve coverage before proceeding:
[tool.coverage.run] source = [""] branch = true omit = ["tests/*"] [tool.coverage.report] show_missing = true fail_under = 75
Our recent coverage report shows:
- repo: local hooks: - id: check-coverage name: Check Coverage entry: bash -c "coverage run --source=. -m unittest discover -s tests && coverage report -m --fail-under=75" language: system
While coverage is strong in some areas (e.g., loadConfig.py at 100%), there are still opportunities for improvement in models/model.py and readme_genie.py. Focusing on untested branches and edge cases will be crucial to reaching our goal of 85% or higher overall coverage.
This project has taught me a lot about unit testing, mocking, and code coverage. Setting up test_loadConfig.py was a particularly valuable experience, pushing me to explore deeper levels of configuration mocking. The pre-commit hook for coverage has added a layer of quality assurance, enforcing consistent test standards.
Moving forward, I aim to refine these tests further by adding edge cases and improving branch coverage. This will not only make ReadmeGenie more robust but also lay a solid foundation for future development.
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