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oneaiguru / GenAICodeUpdater

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list of tests for depedancy #6

Open oneaiguru opened 3 weeks ago

oneaiguru commented 3 weeks ago

Good start with this what you told then we have to follow this : Below is a comprehensive suite of test cases for the Module Dependency Analyzer and Visualizer. These tests are meticulously categorized to ensure exhaustive coverage of all functionalities, edge cases, and potential scenarios the tool might encounter.

1. Module Discovery

a. File Traversal

b. Module Identification

2. Dependency Parsing

a. Import Statement Analysis

b. Dynamic Imports

c. Handling Edge Cases

3. Dependency Mapping

a. Accurate Mapping

b. Handling Missing Modules

c. Performance with Large Codebases

4. Visualization with Matplotlib

a. Graph Accuracy

b. Aesthetic and Readability

c. Customization Options

5. Reporting Mechanism

a. Output Generation

b. Real-time Feedback

c. Accessibility and Usability

6. Integration and Compatibility

a. Python Version Compatibility

b. Integration with Development Tools

c. Environment Constraints

7. Performance and Scalability

a. Large Codebases

b. Execution Speed

c. Resource Management

8. Error Handling and Robustness

a. Unexpected Scenarios

b. Input Validation

c. Recovery Mechanisms

9. Configuration and Customization

a. Custom Analysis Rules

b. Visualization Options

c. Execution Parameters

10. Security Considerations

a. Safe Parsing

b. Access Controls

11. Documentation and Help

a. Help Commands

b. Documentation Completeness

12. Test-Driven Development (TDD) Compliance

a. Test First Approach

b. Incremental Testing

13. Code Standards and Quality

a. PEP 8 Compliance

b. Type Hints

c. Documentation Quality

14. Advanced Features (If Applicable)

a. Dependency Cycle Detection

b. Integration with Version Control

c. Notification Systems

15. Regression Testing

a. Bug Fix Verification

b. Consistent Behavior

16. User Experience

a. Intuitive Interface

b. Feedback and Error Messages

17. Maintenance and Extensibility

a. Ease of Adding New Features

b. Code Maintainability

18. Internationalization and Localization (If Applicable)

a. Language Support

b. Locale-Specific Formatting

19. Backup and Recovery

a. Report Storage

b. Recovery from Crashes

20. Licensing and Legal Compliance

a. Open-Source Compliance

b. Attribution Requirements

21. Accessibility

a. Assistive Technologies

b. Color Contrast

To effectively expand Module Dependency Analyzer and Visualizer using Test-Driven Development (TDD), it's crucial to follow a structured, step-by-step approach. Below is a comprehensive plan outlining the order of implementation, the tests to write, and the corresponding code enhancements. This will ensure that your tool is robust, maintainable, and aligns with best practices.

1. Complete and Enhance Existing Functionality Tests

Before expanding, ensure that your current functions are thoroughly tested and handle various scenarios.

1.1. Test get_python_files Function

Tests to Implement:

Example Test:

import unittest
from unittest.mock import patch
from src.dependency_analysis import get_python_files

class GetPythonFilesTests(unittest.TestCase):
    @patch("os.walk")
    def test_get_python_files_discover_all_py_files(self, mock_walk):
        mock_walk.return_value = [
            ("/project", ["dir1"], ["module_a.py", "README.md"]),
            ("/project/dir1", [], ["module_b.py", "script.sh"])
        ]
        expected_files = [
            "/project/module_a.py",
            "/project/dir1/module_b.py"
        ]
        python_files = get_python_files("/project")
        self.assertEqual(python_files, expected_files)

    @patch("os.walk")
    def test_get_python_files_ignore_non_py_files(self, mock_walk):
        mock_walk.return_value = [
            ("/project", ["dir1"], ["module_a.txt", "README.md"]),
            ("/project/dir1", [], ["module_b.md", "script.sh"])
        ]
        expected_files = []
        python_files = get_python_files("/project")
        self.assertEqual(python_files, expected_files)

    # Additional tests for nested directories, empty directories, and hidden files...

Implementation Steps:

  1. Write the Tests: As shown above, create tests covering different scenarios for get_python_files.
  2. Run Tests and Implement Code: Implement any missing functionality or fix existing issues to pass the tests.

2. Enhance Dependency Parsing

Improve the extract_imports_from_content and analyze_project_dependencies_from_content functions to handle more complex import statements and edge cases.

2.1. Handle Relative Imports

Tests to Implement:

Example Test:

def test_extract_imports_relative_imports(self):
    content = "from .module_b import ClassB\nfrom ..module_c import ClassC"
    expected_imports = {"module_b", "module_c"}
    imports = extract_imports_from_content(content)
    self.assertEqual(imports, expected_imports)

Implementation Steps:

  1. Write the Tests: Implement tests for various relative import scenarios.
  2. Update Parsing Logic: Modify extract_imports_from_content to correctly parse relative imports.

2.2. Handle Dynamic Imports

Tests to Implement:

Example Test:

def test_extract_imports_dynamic_imports(self):
    content = "import importlib\nmodule = importlib.import_module('module_e')"
    expected_imports = {"importlib", "module_e"}
    imports = extract_imports_from_content(content)
    self.assertEqual(imports, expected_imports)

Implementation Steps:

  1. Write the Tests: Create tests for dynamic import scenarios.
  2. Update Parsing Logic: Enhance the AST parsing to detect dynamic imports or decide how to handle them.

3. Implement Reporting Features

Add functionality to generate reports based on the analyzed dependencies.

3.1. Generate Summary Report

Tests to Implement:

Example Test:

def test_generate_summary_report(self):
    dependencies = {
        "module_a": {"module_b", "module_c"},
        "module_b": {"module_c"},
        "module_c": {"module_d"},
        "module_d": {"module_a"}
    }
    expected_summary = {
        "total_modules": 4,
        "total_dependencies": 5,
        "circular_dependencies": [["module_a", "module_b", "module_c", "module_d", "module_a"]]
    }
    summary = generate_summary_report(dependencies)
    self.assertEqual(summary, expected_summary)

Implementation Steps:

  1. Write the Tests: Develop tests for summary report generation.
  2. Implement Reporting Functions: Create functions like generate_summary_report that compile and format the dependency data.

3.2. Export Reports

Tests to Implement:

Example Test:

def test_export_report_to_json(self):
    summary = {
        "total_modules": 4,
        "total_dependencies": 5,
        "circular_dependencies": [["module_a", "module_b", "module_c", "module_d", "module_a"]]
    }
    with patch("builtins.open", mock_open()) as mock_file:
        export_report(summary, "report.json", "json")
        mock_file.assert_called_with("report.json", "w")
        handle = mock_file()
        handle.write.assert_called_once_with(json.dumps(summary, indent=4))

Implementation Steps:

  1. Write the Tests: Create tests for exporting reports in different formats.
  2. Implement Export Functions: Develop functions like export_report to handle different export formats.

4. Improve Visualization Enhancements

Enhance the visualize_dependencies function to provide more insightful and user-friendly visualizations.

4.1. Highlight Circular Dependencies

Tests to Implement:

Example Test:

@patch("networkx.spring_layout")
@patch("networkx.draw")
def test_visualize_circular_dependencies(self, mock_draw, mock_layout):
    dependencies = {
        "module_a": {"module_b"},
        "module_b": {"module_a"}
    }
    visualize_dependencies(dependencies)
    mock_draw.assert_called()
    # Further assertions can be made to check the styling parameters

Implementation Steps:

  1. Write the Tests: Implement tests to verify cycle detection and visualization styling.
  2. Update Visualization Logic: Modify visualize_dependencies to detect cycles and apply distinct styles.

4.2. Customization Options

Tests to Implement:

Example Test:

def test_visualize_custom_layout(self):
    dependencies = {
        "module_a": {"module_b"},
        "module_b": {"module_c"},
        "module_c": {"module_a"}
    }
    with patch("networkx.spring_layout") as mock_layout:
        mock_layout.return_value = {}
        visualize_dependencies(dependencies, layout='circular')
        # Ensure that the correct layout algorithm is called

Implementation Steps:

  1. Write the Tests: Develop tests for different customization options.
  2. Implement Customization Features: Enhance visualize_dependencies to accept parameters for customization.

5. Develop Command-Line Interface (CLI)

Provide a user-friendly CLI to interact with the tool.

5.1. Parse Command-Line Arguments

Tests to Implement:

Example Test:

def test_cli_argument_parsing(self):
    test_args = ["script.py", "/project", "--output", "report.json"]
    with patch.object(sys, 'argv', test_args):
        args = parse_arguments()
        self.assertEqual(args.directory, "/project")
        self.assertEqual(args.output, "report.json")

Implementation Steps:

  1. Write the Tests: Create tests for argument parsing.
  2. Implement CLI Parsing: Develop functions using argparse to handle CLI inputs.

5.2. Execute Analysis via CLI

Tests to Implement:

Example Test:

@patch("src.dependency_analysis.visualize_dependencies")
@patch("src.dependency_analysis.analyze_project_dependencies_from_content")
@patch("src.dependency_analysis.get_python_files")
def test_cli_execution(self, mock_get_files, mock_analyze, mock_visualize):
    mock_get_files.return_value = ["module_a.py", "module_b.py"]
    mock_analyze.return_value = {"module_a": {"module_b"}, "module_b": set()}

    with patch("builtins.print") as mock_print:
        run_cli(["script.py", "/project"])
        mock_visualize.assert_called_with({"module_a": {"module_b"}, "module_b": set()})
        mock_print.assert_called_with("Analysis complete.")

Implementation Steps:

  1. Write the Tests: Develop tests for the complete CLI workflow.
  2. Implement Execution Logic: Create a run_cli function that ties together file discovery, dependency analysis, reporting, and visualization.

6. Support Configuration Files

Allow users to customize tool behavior via configuration files.

6.1. Load Configuration from File

Tests to Implement:

Example Test:

def test_load_valid_configuration(self):
    config_content = '{"exclude_dirs": ["tests", "docs"], "report_format": "json"}'
    with patch("builtins.open", mock_open(read_data=config_content)):
        config = load_configuration("config.json")
        self.assertEqual(config['exclude_dirs'], ["tests", "docs"])
        self.assertEqual(config['report_format'], "json")

def test_load_invalid_configuration(self):
    config_content = '{"exclude_dirs": ["tests", "docs", "invalid"}'  # Malformed JSON
    with patch("builtins.open", mock_open(read_data=config_content)):
        with self.assertRaises(json.JSONDecodeError):
            load_configuration("config.json")

Implementation Steps:

  1. Write the Tests: Create tests for loading configurations.
  2. Implement Configuration Loading: Develop load_configuration to read and parse config files.

6.2. Apply Configuration Settings

Tests to Implement:

Example Test:

def test_apply_exclude_directories(self):
    config = {"exclude_dirs": ["tests", "docs"]}
    with patch("os.walk") as mock_walk:
        mock_walk.return_value = [
            ("/project", ["tests", "docs", "dir1"], ["module_a.py"]),
            ("/project/dir1", [], ["module_b.py"])
        ]
        python_files = get_python_files("/project", exclude_dirs=config["exclude_dirs"])
        self.assertEqual(python_files, ["/project/dir1/module_b.py"])

Implementation Steps:

  1. Write the Tests: Develop tests to ensure configuration settings are correctly applied.
  2. Implement Configuration Logic: Modify existing functions to accept and apply configuration parameters.

7. Enhance Error Handling

Ensure the tool can handle unexpected scenarios gracefully.

7.1. Handle Syntax Errors in Python Files

Tests to Implement:

Example Test:

def test_extract_imports_syntax_error(self):
    content = "import module_a\nimport module_b\n def faulty_syntax("
    with self.assertRaises(SyntaxError):
        extract_imports_from_content(content)

Implementation Steps:

  1. Write the Tests: Create tests for handling syntax errors.
  2. Implement Error Handling: Modify extract_imports_from_content to catch and report syntax errors without crashing.

7.2. Handle Missing Dependencies

Tests to Implement:

Example Test:

def test_analyze_missing_dependencies(self):
    mock_files = {
        "module_a.py": "import module_b",
        "module_b.py": "import module_x"  # module_x does not exist
    }
    dependencies = analyze_project_dependencies_from_content(mock_files)
    self.assertIn("module_x", dependencies["module_b"])

Implementation Steps:

  1. Write the Tests: Develop tests for missing dependencies.
  2. Implement Dependency Checks: Enhance analyze_project_dependencies_from_content to identify and report missing modules.

8. Optimize Performance

Ensure the tool performs efficiently, especially with large codebases.

8.1. Benchmark Execution Time

Tests to Implement:

Example Test:

import time

def test_performance_large_codebase(self):
    large_mock_files = {f"module_{i}.py": "import module_{j}" for i, j in zip(range(1000), range(1, 1001))}
    start_time = time.time()
    dependencies = analyze_project_dependencies_from_content(large_mock_files)
    end_time = time.time()
    self.assertLess(end_time - start_time, 5)  # Expect analysis to complete within 5 seconds

Implementation Steps:

  1. Write the Tests: Create performance benchmark tests.
  2. Implement Optimizations: Optimize file traversal, AST parsing, and data structures to improve speed and reduce memory usage.

9. Develop Comprehensive Documentation and Help

Ensure that users can easily understand and utilize the tool.

9.1. Implement Help Command

Tests to Implement:

Example Test:

def test_help_command(self):
    with patch("builtins.print") as mock_print:
        run_cli(["script.py", "--help"])
        mock_print.assert_called()
        # Further assertions can check the content of the help message

Implementation Steps:

  1. Write the Tests: Develop tests for the help command.
  2. Implement Help Messaging: Use argparse to automatically generate and display help messages based on CLI arguments.

9.2. Create User Documentation

Tests to Implement:

Implementation Steps:

  1. Write the Tests: While documentation itself isn't typically tested via unit tests, ensure via code reviews that documentation covers all features.
  2. Develop Documentation: Create detailed documentation in formats like Markdown or HTML, including usage examples, configuration options, and troubleshooting guides.

10. Maintain Code Standards and Quality

Ensure that the codebase adheres to best practices for maintainability and readability.

10.1. Enforce PEP 8 Compliance

Tests to Implement:

Example Test:

def test_pep8_compliance(self):
    import subprocess
    result = subprocess.run(['flake8', 'src/dependency_analysis.py'], capture_output=True, text=True)
    self.assertEqual(result.returncode, 0, f"PEP 8 violations found:\n{result.stdout}")

Implementation Steps:

  1. Write the Tests: Implement tests that run linting tools and fail if violations are found.
  2. Integrate Linting Tools: Set up tools like flake8 and black in your development workflow to maintain code quality.

10.2. Ensure Type Hinting

Tests to Implement:

Example Test:

def test_type_hints(self):
    import subprocess
    result = subprocess.run(['mypy', 'src/dependency_analysis.py'], capture_output=True, text=True)
    self.assertEqual(result.returncode, 0, f"Type hinting errors found:\n{result.stdout}")

Implementation Steps:

  1. Write the Tests: Develop tests that run mypy and fail if type errors are detected.
  2. Add Type Hints: Ensure all functions and modules include appropriate type hints.

11. Implement Advanced Features

If applicable, add advanced functionalities to enhance the tool's capabilities.

11.1. Detect Dependency Cycles

Tests to Implement:

Example Test:

def test_detect_dependency_cycles(self):
    dependencies = {
        "module_a": {"module_b"},
        "module_b": {"module_c"},
        "module_c": {"module_a"}
    }
    cycles = detect_cycles(dependencies)
    expected_cycles = [["module_a", "module_b", "module_c", "module_a"]]
    self.assertEqual(cycles, expected_cycles)

Implementation Steps:

  1. Write the Tests: Create tests for cycle detection.
  2. Implement Cycle Detection: Develop a detect_cycles function using algorithms like Tarjan's to find cycles in the dependency graph.

11.2. Integration with Version Control

Tests to Implement:

Example Test:

@patch("subprocess.run")
def test_analyze_specific_git_branch(self, mock_run):
    mock_run.return_value = subprocess.CompletedProcess(args=[], returncode=0, stdout="module_a.py\nmodule_b.py", stderr="")
    files = get_python_files("/project")
    self.assertEqual(files, ["module_a.py", "module_b.py"])

Implementation Steps:

  1. Write the Tests: Develop tests for integrating with version control systems like Git.
  2. Implement Integration Logic: Add functionalities to checkout specific branches or commits and analyze dependencies accordingly.

12. Ensure Security Considerations

Protect the tool and its users from potential security vulnerabilities.

12.1. Safe Parsing of Code

Tests to Implement:

Example Test:

def test_safe_parsing_no_code_execution(self):
    content = "import os\nos.system('echo malicious code')"
    imports = extract_imports_from_content(content)
    self.assertIn("os", imports)
    # Ensure that no code is executed during parsing

Implementation Steps:

  1. Write the Tests: Create tests to ensure that code parsing is safe and does not execute any code.
  2. Implement Safe Parsing: Use the ast module appropriately to parse imports without executing any code.

12.2. Handle File Permissions

Tests to Implement:

Example Test:

@patch("os.walk")
def test_handle_restricted_files(self, mock_walk):
    mock_walk.side_effect = [OSError("Permission denied")]
    with self.assertRaises(OSError):
        get_python_files("/restricted_dir")

Implementation Steps:

  1. Write the Tests: Develop tests for handling permission-related errors.
  2. Implement Error Handling: Modify file traversal functions to catch and report permission errors gracefully.

13. Regression Testing

Ensure that new changes do not break existing functionality.

13.1. Maintain Test Coverage

Tests to Implement:

Implementation Steps:

  1. Write the Tests: Continuously add tests to cover new and existing functionalities.
  2. Integrate CI Tools: Use tools like GitHub Actions, Travis CI, or Jenkins to automate testing on commits and pull requests.

14. Maintenance and Extensibility

Design the tool to be easily maintainable and extensible for future enhancements.

14.1. Modular Code Structure

Tests to Implement:

Implementation Steps:

  1. Write the Tests: Develop tests for modular components to ensure independence.
  2. Implement Modular Design: Refactor code to follow a modular architecture, allowing easy addition of new features.

15. Final Steps and Best Practices

15.1. Continuous Refactoring

Regularly refactor code to improve readability, reduce complexity, and eliminate redundancy.

15.2. Documentation and Examples

Provide comprehensive documentation and usage examples to help users understand and effectively use the tool.

15.3. User Feedback and Iteration

Collect feedback from users to identify areas for improvement and iteratively enhance the tool based on real-world usage.

Summary of Implementation Order

  1. Complete Tests for Existing Functions:

    • Finalize tests for get_python_files.
    • Ensure current tests pass reliably.

  2. Enhance Dependency Parsing:

    • Implement handling for relative and dynamic imports.
    • Write corresponding tests.

  3. Add Reporting Features:

    • Develop summary and detailed reporting functionalities.
    • Create and pass tests for report generation.

  4. Improve Visualization:

    • Enhance graph visualization with cycle highlighting and customization.
    • Write tests to ensure visual accuracy and aesthetics.

  5. Develop CLI:

    • Implement argument parsing and CLI execution.
    • Test CLI functionality thoroughly.

  6. Support Configuration Files:

    • Enable configuration via files.
    • Ensure tests cover various configuration scenarios.

  7. Enhance Error Handling:

    • Robustly handle syntax errors and missing dependencies.
    • Create tests to verify graceful error handling.

  8. Optimize Performance:

    • Benchmark and optimize for large codebases.
    • Ensure tests validate performance improvements.

  9. Develop Documentation and Help:

    • Implement help commands and comprehensive user documentation.
    • Ensure documentation is clear and up-to-date.

  10. Maintain Code Standards and Quality:

    • Enforce PEP 8 compliance and type hinting.
    • Use automated tools and tests to maintain standards.

  11. Implement Advanced Features:

    • Add cycle detection and version control integration.
    • Ensure thorough testing of new advanced features.

  12. Ensure Security Considerations:

    • Implement safe parsing and handle file permissions.
    • Write tests to validate security measures.

  13. Regression Testing:

    • Maintain full test coverage and integrate with CI pipelines.
    • Regularly run all tests to catch regressions.

  14. Maintenance and Extensibility:

    • Design for modularity and easy extension.
    • Continuously refactor and improve code structure.

Final Recommendations

By following this structured approach, you'll ensure that your Module Dependency Analyzer and Visualizer is not only feature-rich but also robust, maintainable, and user-friendly. Happy coding! start with simple python db where we can save code snippets i gave above next to tasks description so we can mark off task when we move, please save everythin from this message that you feel is useful as we won't see this message latere due to context limitatinos.

oneaiguru commented 3 weeks ago

probably last

1. Module Discovery

a. File Traversal

b. Module Identification

2. Dependency Parsing

a. Import Statement Analysis

b. Dynamic Imports

c. Handling Edge Cases

3. Dependency Mapping

a. Accurate Mapping

b. Handling Missing Modules

4. Visualization with Matplotlib

a. Graph Accuracy

b. Aesthetic and Readability

c. Customization Options

5. Reporting Mechanism

a. Output Generation

b. Real-time Feedback

6. Integration and Compatibility

a. Python Version Compatibility

b. Integration with Development Tools

8. Error Handling and Robustness

a. Unexpected Scenarios

b. Input Validation

9. Configuration and Customization

a. Custom Analysis Rules

10. Security Considerations

a. Safe Parsing

11. Documentation and Help

a. Help Commands

13. Code Standards and Quality

a. PEP 8 Compliance

15. Regression Testing

a. Bug Fix Verification

16. User Experience

a. Intuitive Interface

17. Maintenance and Extensibility

a. Ease of Adding New Features

21. Accessibility

a. Assistive Technologies

Current Step: Step 1 – Provided the shortened list of tests excluding performance tests, already implemented tests, and irrelevant tests.