tegwick
3af6fb9935
## Major Integration - ✅ Integrated Requirements Engineering Agent into development workflow - ✅ Enhanced Makefile with requirements validation targets - ✅ Added pre-commit validation with mock compatibility checking - ✅ Enhanced TDD workflow to include foundation analysis ## Test Fixes - ✅ Fixed GiteaPlugin missing _add_comment_async method - ✅ Fixed LocalPlugin config.yml file not found errors in tests - ✅ Enhanced mock objects in CLI tests with proper domain model attributes - ✅ All Issue #59 tests now passing (38/38 tests pass) ## New Capabilities - `make validate-requirements` - Foundation analysis before development - `make check-interface-compatibility INTERFACE=Name` - Interface compatibility checking - `make generate-dev-checklist FEATURE='Name'` - Development checklist generation - `make validate-mocks` - Mock object compatibility validation - `make pre-commit-validate` - Complete pre-commit validation workflow ## Problem Prevention This integration prevents the exact interface compatibility issues and mock object mismatches that caused hours of debugging in Issue #59. The Requirements Engineering Agent provides proactive foundation analysis and catches problems before they occur. 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
478 lines
18 KiB
Python
478 lines
18 KiB
Python
#!/usr/bin/env python3
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"""
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Requirements Engineering and Incremental Development Planning Toolkit
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Practical tools to prevent interface compatibility issues and mock object mismatches.
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Designed to solve the problems encountered during Issue #59 development.
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"""
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import ast
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import inspect
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import importlib
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from pathlib import Path
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from typing import Dict, List, Any, Set, Optional, Type
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from dataclasses import dataclass
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from datetime import datetime
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import json
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import sys
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@dataclass
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class DomainModelInfo:
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"""Information about a domain model."""
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name: str
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module: str
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attributes: Dict[str, str]
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methods: List[str]
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base_classes: List[str]
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is_abstract: bool
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file_path: str
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@dataclass
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class InterfaceInfo:
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"""Information about an interface or abstract base class."""
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name: str
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module: str
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abstract_methods: List[str]
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methods: List[str]
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base_classes: List[str]
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file_path: str
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@dataclass
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class MockValidationResult:
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"""Result of mock validation."""
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is_valid: bool
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missing_attributes: List[str]
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extra_attributes: List[str]
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type_mismatches: Dict[str, str]
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errors: List[str]
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class DomainModelAnalyzer:
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"""Analyzes existing domain models to understand structure."""
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def __init__(self, project_root: Path):
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self.project_root = project_root
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self.domain_models: Dict[str, DomainModelInfo] = {}
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self.interfaces: Dict[str, InterfaceInfo] = {}
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def analyze_project(self) -> Dict[str, Any]:
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"""Analyze entire project for domain models and interfaces."""
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self._scan_domain_models()
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self._scan_interfaces()
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return {
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"domain_models": self.domain_models,
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"interfaces": self.interfaces,
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"analysis_timestamp": datetime.now().isoformat(),
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"summary": {
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"total_domain_models": len(self.domain_models),
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"total_interfaces": len(self.interfaces),
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"abstract_classes": len([i for i in self.interfaces.values() if i.abstract_methods])
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}
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}
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def _scan_domain_models(self):
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"""Scan for domain model classes."""
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domain_dirs = self.project_root.glob("domain/*/models.py")
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for model_file in domain_dirs:
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self._analyze_python_file(model_file, is_domain_model=True)
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def _scan_interfaces(self):
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"""Scan for interface and abstract base classes."""
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# Look in infrastructure, domain, and markitect modules
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search_patterns = [
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"infrastructure/**/interfaces.py",
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"infrastructure/**/base.py",
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"domain/**/repositories.py",
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"markitect/**/base.py"
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]
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for pattern in search_patterns:
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for file_path in self.project_root.glob(pattern):
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self._analyze_python_file(file_path, is_domain_model=False)
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def _analyze_python_file(self, file_path: Path, is_domain_model: bool = False):
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"""Analyze a Python file for classes and interfaces."""
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try:
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with open(file_path) as f:
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tree = ast.parse(f.read())
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for node in ast.walk(tree):
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if isinstance(node, ast.ClassDef):
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if is_domain_model:
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self._process_domain_model(node, file_path)
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else:
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self._process_interface(node, file_path)
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except Exception as e:
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print(f"Error analyzing {file_path}: {e}")
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def _process_domain_model(self, class_node: ast.ClassDef, file_path: Path):
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"""Process a domain model class."""
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attributes = {}
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methods = []
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base_classes = []
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# Extract base classes
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for base in class_node.bases:
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if isinstance(base, ast.Name):
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base_classes.append(base.id)
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# Extract attributes and methods
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for item in class_node.body:
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if isinstance(item, ast.AnnAssign) and isinstance(item.target, ast.Name):
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# Type annotated attribute
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attr_name = item.target.id
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if isinstance(item.annotation, ast.Name):
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attr_type = item.annotation.id
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else:
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attr_type = ast.unparse(item.annotation)
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attributes[attr_name] = attr_type
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elif isinstance(item, ast.FunctionDef):
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methods.append(item.name)
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module_path = str(file_path.relative_to(self.project_root)).replace('/', '.').replace('.py', '')
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model_info = DomainModelInfo(
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name=class_node.name,
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module=module_path,
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attributes=attributes,
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methods=methods,
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base_classes=base_classes,
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is_abstract=any('ABC' in base for base in base_classes),
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file_path=str(file_path)
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)
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self.domain_models[class_node.name] = model_info
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def _process_interface(self, class_node: ast.ClassDef, file_path: Path):
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"""Process an interface or abstract base class."""
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abstract_methods = []
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methods = []
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base_classes = []
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# Extract base classes
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for base in class_node.bases:
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if isinstance(base, ast.Name):
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base_classes.append(base.id)
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# Extract methods
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for item in class_node.body:
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if isinstance(item, ast.FunctionDef):
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methods.append(item.name)
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# Check for abstract methods
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for decorator in item.decorator_list:
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if isinstance(decorator, ast.Name) and decorator.id == 'abstractmethod':
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abstract_methods.append(item.name)
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module_path = str(file_path.relative_to(self.project_root)).replace('/', '.').replace('.py', '')
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interface_info = InterfaceInfo(
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name=class_node.name,
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module=module_path,
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abstract_methods=abstract_methods,
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methods=methods,
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base_classes=base_classes,
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file_path=str(file_path)
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)
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self.interfaces[class_node.name] = interface_info
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class MockValidator:
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"""Validates mock objects against real domain models."""
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def __init__(self, domain_analyzer: DomainModelAnalyzer):
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self.domain_analyzer = domain_analyzer
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def validate_mock_against_model(self, mock_obj: Any, model_name: str) -> MockValidationResult:
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"""Validate a mock object against a domain model."""
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if model_name not in self.domain_analyzer.domain_models:
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return MockValidationResult(
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is_valid=False,
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missing_attributes=[],
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extra_attributes=[],
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type_mismatches={},
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errors=[f"Domain model '{model_name}' not found"]
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)
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model_info = self.domain_analyzer.domain_models[model_name]
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return self._validate_mock_attributes(mock_obj, model_info)
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def _validate_mock_attributes(self, mock_obj: Any, model_info: DomainModelInfo) -> MockValidationResult:
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"""Validate mock object attributes against model."""
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mock_attrs = set(attr for attr in dir(mock_obj) if not attr.startswith('_'))
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model_attrs = set(model_info.attributes.keys()) | set(model_info.methods)
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missing_attrs = model_attrs - mock_attrs
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extra_attrs = mock_attrs - model_attrs
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# Check for critical missing attributes (non-methods)
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critical_missing = [attr for attr in missing_attrs if attr in model_info.attributes]
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is_valid = len(critical_missing) == 0
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errors = []
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if critical_missing:
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errors.append(f"Missing critical attributes: {critical_missing}")
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return MockValidationResult(
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is_valid=is_valid,
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missing_attributes=list(missing_attrs),
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extra_attributes=list(extra_attrs),
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type_mismatches={}, # Would need runtime inspection
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errors=errors
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)
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class InterfaceCompatibilityChecker:
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"""Checks interface compatibility between layers."""
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def __init__(self, domain_analyzer: DomainModelAnalyzer):
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self.domain_analyzer = domain_analyzer
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def check_plugin_interface_compatibility(self, plugin_interface: str, existing_repo: str) -> Dict[str, Any]:
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"""Check if a plugin interface is compatible with existing repository."""
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if plugin_interface not in self.domain_analyzer.interfaces:
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return {"compatible": False, "error": f"Plugin interface '{plugin_interface}' not found"}
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if existing_repo not in self.domain_analyzer.interfaces:
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return {"compatible": False, "error": f"Existing repository '{existing_repo}' not found"}
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plugin_info = self.domain_analyzer.interfaces[plugin_interface]
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repo_info = self.domain_analyzer.interfaces[existing_repo]
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# Compare abstract methods
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plugin_methods = set(plugin_info.abstract_methods)
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repo_methods = set(repo_info.methods)
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missing_methods = plugin_methods - repo_methods
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compatible = len(missing_methods) == 0
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return {
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"compatible": compatible,
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"plugin_methods": list(plugin_methods),
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"repo_methods": list(repo_methods),
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"missing_methods": list(missing_methods),
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"compatibility_score": len(plugin_methods & repo_methods) / max(len(plugin_methods), 1)
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}
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class RequirementsEngineeringAgent:
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"""Main agent for requirements engineering and incremental development planning."""
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def __init__(self, project_root: Path):
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self.project_root = project_root
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self.domain_analyzer = DomainModelAnalyzer(project_root)
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self.mock_validator = MockValidator(self.domain_analyzer)
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self.compatibility_checker = InterfaceCompatibilityChecker(self.domain_analyzer)
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self.analysis_cache = {}
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def analyze_project_foundations(self) -> Dict[str, Any]:
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"""Analyze project foundations before starting new development."""
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print("🔍 Analyzing project foundations...")
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analysis = self.domain_analyzer.analyze_project()
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self.analysis_cache = analysis
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return {
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"foundation_analysis": analysis,
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"recommendations": self._generate_foundation_recommendations(analysis),
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"risks": self._identify_foundation_risks(analysis)
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}
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def plan_interface_evolution(self, interface_name: str, planned_changes: Dict[str, Any]) -> Dict[str, Any]:
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"""Plan interface evolution with backward compatibility."""
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print(f"📋 Planning evolution for interface: {interface_name}")
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if interface_name not in self.domain_analyzer.interfaces:
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return {"error": f"Interface '{interface_name}' not found"}
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interface_info = self.domain_analyzer.interfaces[interface_name]
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# Analyze impact of planned changes
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impact_analysis = self._analyze_change_impact(interface_info, planned_changes)
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return {
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"interface": interface_name,
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"current_state": interface_info,
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"planned_changes": planned_changes,
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"impact_analysis": impact_analysis,
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"migration_plan": self._generate_migration_plan(interface_info, planned_changes),
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"compatibility_strategy": self._plan_compatibility_strategy(planned_changes)
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}
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def validate_test_mocks(self, test_file: Path) -> Dict[str, Any]:
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"""Validate mock objects in test files against actual domain models."""
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print(f"🧪 Validating mocks in: {test_file}")
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# This would require AST parsing of test files to extract mock usage
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# For now, return structure for manual implementation
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return {
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"test_file": str(test_file),
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"validation_status": "manual_check_required",
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"recommendations": [
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"Use Mock(spec=ActualClass) for all domain model mocks",
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"Verify all mock attributes match actual domain model attributes",
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"Use actual enums instead of string representations",
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"Include all required attributes with proper types"
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]
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}
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def generate_development_checklist(self, feature_name: str, requirements: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""Generate a comprehensive development checklist."""
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print(f"📝 Generating development checklist for: {feature_name}")
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checklist = [
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{
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"phase": "Foundation Analysis",
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"tasks": [
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"Analyze existing domain models",
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"Map current interface contracts",
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"Understand dependency graph",
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"Verify architectural foundations"
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]
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},
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{
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"phase": "Interface Contract Definition",
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"tasks": [
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"Define new interface contracts",
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"Verify compatibility with existing interfaces",
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"Plan interface evolution strategy",
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"Document contract specifications"
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]
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},
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{
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"phase": "Test Architecture Design",
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"tasks": [
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"Design test structure matching application architecture",
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"Create spec-compliant mock objects",
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"Plan integration test strategy",
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"Define validation checkpoints"
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]
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},
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{
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"phase": "Incremental Implementation",
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"tasks": [
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"Implement base interfaces",
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"Add concrete implementations",
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"Validate at each checkpoint",
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"Maintain backward compatibility"
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]
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},
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{
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"phase": "Integration Validation",
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"tasks": [
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"Test interface compatibility",
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"Validate mock object alignment",
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"Run integration tests",
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"Verify end-to-end workflows"
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]
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}
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]
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return checklist
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def _generate_foundation_recommendations(self, analysis: Dict[str, Any]) -> List[str]:
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"""Generate recommendations based on foundation analysis."""
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recommendations = []
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if analysis["summary"]["total_domain_models"] == 0:
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recommendations.append("⚠️ No domain models found - start with domain model design")
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if analysis["summary"]["total_interfaces"] == 0:
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recommendations.append("⚠️ No interfaces found - define interface contracts first")
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if analysis["summary"]["abstract_classes"] == 0:
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recommendations.append("💡 Consider adding abstract base classes for plugin system")
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recommendations.append("✅ Run mock validation before writing tests")
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recommendations.append("✅ Verify interface compatibility before implementation")
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return recommendations
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def _identify_foundation_risks(self, analysis: Dict[str, Any]) -> List[str]:
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"""Identify risks in current foundation."""
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risks = []
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if analysis["summary"]["total_domain_models"] > 20:
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risks.append("⚠️ Large number of domain models - complexity risk")
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if analysis["summary"]["total_interfaces"] < analysis["summary"]["total_domain_models"] * 0.3:
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risks.append("⚠️ Few interfaces relative to domain models - tight coupling risk")
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return risks
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def _analyze_change_impact(self, interface_info: InterfaceInfo, changes: Dict[str, Any]) -> Dict[str, Any]:
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"""Analyze impact of planned interface changes."""
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return {
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"breaking_changes": changes.get("breaking_changes", []),
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"affected_implementations": [], # Would need to scan for implementations
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"migration_complexity": "medium", # Would analyze based on change type
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"estimated_effort": "2-4 hours" # Would calculate based on impact
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}
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def _generate_migration_plan(self, interface_info: InterfaceInfo, changes: Dict[str, Any]) -> List[str]:
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"""Generate step-by-step migration plan."""
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return [
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"1. Create new interface with backward compatibility",
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"2. Update existing implementations incrementally",
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"3. Add deprecation warnings to old interface",
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"4. Update tests to use new interface",
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"5. Remove deprecated interface after transition period"
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]
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def _plan_compatibility_strategy(self, changes: Dict[str, Any]) -> Dict[str, Any]:
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"""Plan backward compatibility strategy."""
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return {
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"strategy": "adapter_pattern",
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"transition_period": "2 development cycles",
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"deprecation_warnings": True,
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"migration_guide": "Will be generated"
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}
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def main():
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"""CLI interface for the requirements engineering agent."""
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import argparse
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parser = argparse.ArgumentParser(description="Requirements Engineering and Development Planning Agent")
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parser.add_argument("command", choices=["analyze", "validate-mocks", "plan-interface", "checklist"])
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parser.add_argument("--project-root", default=".", help="Project root directory")
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parser.add_argument("--interface", help="Interface name for planning")
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parser.add_argument("--feature", help="Feature name for checklist")
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parser.add_argument("--test-file", help="Test file to validate")
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args = parser.parse_args()
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project_root = Path(args.project_root)
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agent = RequirementsEngineeringAgent(project_root)
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if args.command == "analyze":
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result = agent.analyze_project_foundations()
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print(json.dumps(result, indent=2, default=str))
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elif args.command == "validate-mocks" and args.test_file:
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result = agent.validate_test_mocks(Path(args.test_file))
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print(json.dumps(result, indent=2))
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elif args.command == "plan-interface" and args.interface:
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changes = {"new_methods": ["example_method"], "breaking_changes": []}
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result = agent.plan_interface_evolution(args.interface, changes)
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print(json.dumps(result, indent=2, default=str))
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elif args.command == "checklist" and args.feature:
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result = agent.generate_development_checklist(args.feature, {})
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print(json.dumps(result, indent=2))
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else:
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parser.print_help()
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if __name__ == "__main__":
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main() |