Feature/test branch

[selectdimensions]

Lets test what we have arranged

Summary by Sourcery

Enhance the VenvCreator class with type annotations and refactor its methods for better readability and maintainability. Update the CI workflow to include additional testing and linting steps, and convert tests to the unittest framework with expanded coverage.

New Features:

• Introduce type annotations to the VenvCreator class methods for improved code clarity and type safety.

Enhancements:

• Refactor the VenvCreator class to improve code readability and maintainability, including the addition of helper methods and restructuring of existing methods.

CI:

• Update the GitHub Actions workflow to include testing on both main and develop branches, add a linting job, and enhance the test matrix to include multiple Python versions and operating systems.

Tests:

• Convert existing pytest-based tests to unittest framework and expand test coverage for the VenvCreator class, including mocking subprocess calls and testing additional methods.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR introduces significant improvements to the virtual environment creation codebase, focusing on type safety, error handling, and test coverage. The changes include adding type hints throughout the code, improving error handling with better feedback, and implementing comprehensive unit tests.

Updated class diagram for VenvCreator

classDiagram
    class VenvCreator {
        -os_type: str
        -is_windows: bool
        -is_linux: bool
        -python_installations: List~str~
        -username: str
        -dependencies_folder: Optional~str~
        +__init__()
        +set_dependencies_folder(folder_path: str) bool
        +find_dependencies() List~str~
        +install_local_dependencies(venv_path: str) Optional~bool~
        +get_current_username() Optional~str~
        +_get_pip_path(venv_path: str) str
        +find_python_installations() List~str~
        +_find_windows_python() List~str~
        +_find_linux_python() List~str~
        +get_python_version(python_path: str) str
        +create_venv(python_path: str, venv_path: str) bool
        +install_requirements(venv_path: str, requirements_path: Optional~str~) Optional~bool~
        +get_project_details() Dict~str, str~
        +print_activation_instructions(project_path: str, venv_name: str) void
        +run() void
    }

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File-Level Changes

Change	Details	Files
Added comprehensive type hints and improved error handling	Added type hints for all function parameters and return values Enhanced error handling with detailed error messages and stderr capture Improved subprocess error handling with timeout and text output capture Added optional parameters and better type definitions	create_venv.py
Refactored and modernized the test suite	Migrated from pytest to unittest framework Added comprehensive test cases for all major functionality Implemented mock objects for system calls and user input Added setup and teardown methods for test environment management	test_venv_creator.py
Enhanced CI/CD pipeline configuration	Added support for multiple Python versions and OS combinations Implemented separate jobs for testing, linting, and security checks Added type checking with mypy in strict mode Improved test coverage reporting and Codecov integration	.github/workflows/python-ci.yml
Code organization and cleanup	Extracted common functionality into helper methods Improved code readability with consistent formatting Added gitignore file for better repository management	create_venv.py .gitignore

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[sourcery-ai]

Hey @selectdimensions - I've reviewed your changes - here's some feedback:

Overall Comments:

• Please update the PR title and description to better reflect the changes (adding type hints, improving error handling, expanding tests)

Here's what I looked at during the review

• 🟢 General issues: all looks good
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟡 Complexity: 1 issue found
• 🟢 Documentation: all looks good

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[sourcery-ai]

issue (complexity): Consider simplifying test implementations by reducing helper methods and nesting levels

The test implementation could be simplified while maintaining the same coverage. Here are specific suggestions:

1. Simplify the project details test by using a context manager approach:

def test_get_project_details(self):
    """Test getting project details"""
    with patch('builtins.input', side_effect=['test_project', self.temp_dir, 'venv', 'n', 'n']):
        details = self.venv_creator.get_project_details()

    self.assertEqual(details['name'], 'test_project')
    self.assertEqual(details['path'], self.temp_dir)

2. Remove the create_test_wheel helper and inline the wheel creation where needed:

def test_find_dependencies(self):
    """Test finding dependency files"""
    # Create test files directly
    wheel_path = os.path.join(self.test_dependencies, "package1-1.0-py3-none-any.whl")
    with open(wheel_path, 'w') as f:
        f.write('dummy wheel file')

    self.venv_creator.set_dependencies_folder(self.test_dependencies)
    dependencies = self.venv_creator.find_dependencies()
    self.assertIn(wheel_path, dependencies)

3. Simplify the install_local_dependencies test by reducing setup layers:

@patch('subprocess.run')
def test_install_local_dependencies(self, mock_run):
    """Test installing local dependencies"""
    mock_run.return_value.returncode = 0
    venv_path = os.path.join(self.temp_dir, 'venv')

    self.venv_creator.set_dependencies_folder(self.test_dependencies)
    self.assertTrue(self.venv_creator.install_local_dependencies(venv_path))
    mock_run.assert_called()

These changes maintain test coverage while reducing nesting and complexity.

[sourcery-ai]

issue (code-quality): Avoid conditionals in tests. (no-conditionals-in-tests)

Explanation

Avoid complex code, like conditionals, in test functions.

Google's software engineering guidelines says:
"Clear tests are trivially correct upon inspection"
To reach that avoid complex code in tests:

• loops
• conditionals

Some ways to fix this:

• Use parametrized tests to get rid of the loop.
• Move the complex logic into helpers.
• Move the complex part into pytest fixtures.

Complexity is most often introduced in the form of logic. Logic is defined via the imperative parts of programming languages such as operators, loops, and conditionals. When a piece of code contains logic, you need to do a bit of mental computation to determine its result instead of just reading it off of the screen. It doesn't take much logic to make a test more difficult to reason about.

Software Engineering at Google / Don't Put Logic in Tests

[sourcery-ai]

issue (code-quality): We've found these issues:

• Merge dictionary assignment with declaration (merge-dict-assign)
• Use named expression to simplify assignment and conditional [×2] (use-named-expression)
• Lift code into else after jump in control flow (reintroduce-else)
• Swap if/else branches (swap-if-else-branches)