src/wanderlust_ai/testing/api_tester.py

"""
API Testing Module for AI Travel Planner

This module demonstrates:
- Async API testing patterns
- Comprehensive error handling
- Response validation
- Retry logic implementation
- Step-by-step debugging techniques
"""

import asyncio
import json
import time
from contextlib import asynccontextmanager
from datetime import datetime, timedelta
from typing import Any, Dict, List, Optional, Union, Tuple
from dataclasses import dataclass
from enum import Enum

import httpx
from pydantic import BaseModel, Field, ValidationError

from ..utils.logging import get_logger
from ..utils.security import ErrorResponse, ErrorType


class APITestResult(BaseModel):
    """Standardized API test result."""
    api_name: str = Field(..., description="Name of the API being tested")
    endpoint: str = Field(..., description="API endpoint tested")
    success: bool = Field(..., description="Whether the test passed")
    response_time_ms: float = Field(..., description="Response time in milliseconds")
    status_code: Optional[int] = Field(None, description="HTTP status code")
    error_type: Optional[str] = Field(None, description="Type of error if any")
    error_message: Optional[str] = Field(None, description="Error message if any")
    response_data: Optional[Dict[str, Any]] = Field(None, description="Response data if successful")
    timestamp: datetime = Field(default_factory=datetime.now, description="Test timestamp")
    retry_count: int = Field(0, description="Number of retries attempted")


class APIErrorType(Enum):
    """Types of API errors for proper handling."""
    NETWORK_ERROR = "network_error"
    AUTHENTICATION_ERROR = "authentication_error"
    AUTHORIZATION_ERROR = "authorization_error"
    RATE_LIMIT_ERROR = "rate_limit_error"
    TIMEOUT_ERROR = "timeout_error"
    VALIDATION_ERROR = "validation_error"
    SERVER_ERROR = "server_error"
    UNKNOWN_ERROR = "unknown_error"


@dataclass
class APIConfig:
    """Configuration for API testing."""
    name: str
    base_url: str
    api_key: str
    timeout: int = 30
    max_retries: int = 3
    retry_delay: float = 1.0
    rate_limit_per_minute: int = 60


class APITester:
    """
    Comprehensive API testing class with debugging capabilities.
    
    This class demonstrates:
    - Async API testing patterns
    - Proper error handling and categorization
    - Response validation
    - Retry logic with exponential backoff
    - Step-by-step debugging techniques
    """
    
    def __init__(self, config: APIConfig):
        """Initialize the API tester."""
        self.config = config
        self.logger = get_logger(f"api_tester.{config.name}")
        self._client: Optional[httpx.AsyncClient] = None
        self._request_count = 0
        self._rate_limit_tokens = config.rate_limit_per_minute
        self._rate_limit_reset = datetime.now() + timedelta(minutes=1)
        
        self.logger.info(f"Initialized API tester for {config.name}")
    
    async def __aenter__(self):
        """Async context manager entry."""
        await self._setup_client()
        return self
    
    async def __aexit__(self, exc_type, exc_val, exc_tb):
        """Async context manager exit with cleanup."""
        await self._cleanup_client()
        if exc_type:
            self.logger.error(f"API tester exited with error: {exc_val}")
        else:
            self.logger.info(f"API tester completed successfully")
    
    async def _setup_client(self):
        """Setup HTTP client with proper configuration."""
        if self._client:
            return
        
        self._client = httpx.AsyncClient(
            base_url=self.config.base_url,
            timeout=httpx.Timeout(self.config.timeout),
            headers={
                "Authorization": f"Bearer {self.config.api_key}",
                "User-Agent": f"WanderlustAI-APITester/1.0",
                "Content-Type": "application/json"
            }
        )
        
        self.logger.info(f"HTTP client setup for {self.config.name}")
    
    async def _cleanup_client(self):
        """Cleanup HTTP client resources."""
        if self._client:
            await self._client.aclose()
            self._client = None
            self.logger.info(f"HTTP client cleaned up for {self.config.name}")
    
    async def _check_rate_limit(self):
        """Check and enforce rate limiting."""
        now = datetime.now()
        
        # Reset tokens if minute has passed
        if now >= self._rate_limit_reset:
            self._rate_limit_tokens = self.config.rate_limit_per_minute
            self._rate_limit_reset = now + timedelta(minutes=1)
            self.logger.debug(f"Rate limit reset for {self.config.name}")
        
        # Check if we have tokens available
        if self._rate_limit_tokens <= 0:
            wait_time = (self._rate_limit_reset - now).total_seconds()
            self.logger.warning(f"Rate limit exceeded for {self.config.name}, waiting {wait_time:.1f}s")
            await asyncio.sleep(wait_time)
            await self._check_rate_limit()
        
        # Consume a token
        self._rate_limit_tokens -= 1
        self.logger.debug(f"Rate limit: {self._rate_limit_tokens} tokens remaining for {self.config.name}")
    
    def _categorize_error(self, error: Exception, status_code: Optional[int] = None) -> APIErrorType:
        """
        Categorize API errors for proper handling.
        
        This is crucial for implementing appropriate retry strategies.
        """
        if isinstance(error, httpx.TimeoutException):
            return APIErrorType.TIMEOUT_ERROR
        elif isinstance(error, httpx.ConnectError):
            return APIErrorType.NETWORK_ERROR
        elif isinstance(error, httpx.HTTPStatusError):
            if status_code == 401:
                return APIErrorType.AUTHENTICATION_ERROR
            elif status_code == 403:
                return APIErrorType.AUTHORIZATION_ERROR
            elif status_code == 429:
                return APIErrorType.RATE_LIMIT_ERROR
            elif 500 <= status_code < 600:
                return APIErrorType.SERVER_ERROR
            else:
                return APIErrorType.UNKNOWN_ERROR
        elif isinstance(error, httpx.RequestError):
            return APIErrorType.NETWORK_ERROR
        else:
            return APIErrorType.UNKNOWN_ERROR
    
    def _should_retry(self, error_type: APIErrorType, retry_count: int) -> bool:
        """
        Determine if a request should be retried based on error type.
        
        This implements intelligent retry logic:
        - Network errors: Retry (temporary)
        - Timeout errors: Retry (temporary)
        - Server errors: Retry (temporary)
        - Auth errors: Don't retry (permanent)
        - Rate limit errors: Retry with longer delay
        """
        if retry_count >= self.config.max_retries:
            return False
        
        retryable_errors = {
            APIErrorType.NETWORK_ERROR,
            APIErrorType.TIMEOUT_ERROR,
            APIErrorType.SERVER_ERROR,
            APIErrorType.RATE_LIMIT_ERROR
        }
        
        return error_type in retryable_errors
    
    def _calculate_retry_delay(self, error_type: APIErrorType, retry_count: int) -> float:
        """
        Calculate retry delay with exponential backoff.
        
        Different error types get different retry strategies:
        - Rate limit errors: Longer delay
        - Network errors: Standard exponential backoff
        - Server errors: Standard exponential backoff
        """
        base_delay = self.config.retry_delay
        
        if error_type == APIErrorType.RATE_LIMIT_ERROR:
            # Rate limit errors need longer delays
            return base_delay * (2 ** retry_count) * 2
        else:
            # Standard exponential backoff
            return base_delay * (2 ** retry_count)
    
    async def test_api_call(
        self,
        method: str,
        endpoint: str,
        data: Optional[Dict[str, Any]] = None,
        params: Optional[Dict[str, Any]] = None,
        headers: Optional[Dict[str, str]] = None
    ) -> APITestResult:
        """
        Test an API call with comprehensive error handling and retry logic.
        
        This is the main testing function that demonstrates:
        - Proper error handling
        - Retry logic with exponential backoff
        - Response validation
        - Performance monitoring
        """
        start_time = time.time()
        retry_count = 0
        
        # Rate limiting check
        await self._check_rate_limit()
        
        # Prepare request
        request_headers = {}
        if headers:
            request_headers.update(headers)
        
        self.logger.info(f"Testing {method} {endpoint} for {self.config.name}")
        
        while retry_count <= self.config.max_retries:
            try:
                async with self.get_client() as client:
                    self.logger.debug(f"{self.config.name}: {method} {endpoint} (attempt {retry_count + 1})")
                    
                    # Make the request
                    response = await client.request(
                        method=method,
                        url=endpoint,
                        json=data,
                        params=params,
                        headers=request_headers
                    )
                    
                    # Calculate response time
                    response_time = (time.time() - start_time) * 1000
                    
                    # Update request tracking
                    self._request_count += 1
                    
                    # Create test result
                    result = APITestResult(
                        api_name=self.config.name,
                        endpoint=endpoint,
                        success=response.status_code < 400,
                        response_time_ms=response_time,
                        status_code=response.status_code,
                        retry_count=retry_count
                    )
                    
                    if result.success:
                        try:
                            result.response_data = response.json()
                            self.logger.info(f"✅ {self.config.name}: {method} {endpoint} - {response.status_code} ({response_time:.1f}ms)")
                        except json.JSONDecodeError as e:
                            result.success = False
                            result.error_type = APIErrorType.VALIDATION_ERROR.value
                            result.error_message = f"Invalid JSON response: {e}"
                            self.logger.warning(f"❌ {self.config.name}: Invalid JSON response")
                    else:
                        result.error_type = APIErrorType.SERVER_ERROR.value
                        result.error_message = response.text
                        self.logger.warning(f"❌ {self.config.name}: {method} {endpoint} - {response.status_code}")
                    
                    return result
                    
            except Exception as e:
                error_type = self._categorize_error(e, getattr(e, 'response', {}).get('status_code'))
                response_time = (time.time() - start_time) * 1000
                
                self.logger.warning(f"❌ {self.config.name}: {method} {endpoint} - {error_type.value} (attempt {retry_count + 1})")
                
                # Check if we should retry
                if self._should_retry(error_type, retry_count):
                    retry_count += 1
                    delay = self._calculate_retry_delay(error_type, retry_count - 1)
                    
                    self.logger.info(f"🔄 Retrying {self.config.name} in {delay:.1f}s (attempt {retry_count + 1})")
                    await asyncio.sleep(delay)
                    continue
                else:
                    # Don't retry, return error result
                    return APITestResult(
                        api_name=self.config.name,
                        endpoint=endpoint,
                        success=False,
                        response_time_ms=response_time,
                        error_type=error_type.value,
                        error_message=str(e),
                        retry_count=retry_count
                    )
        
        # This should never be reached, but just in case
        return APITestResult(
            api_name=self.config.name,
            endpoint=endpoint,
            success=False,
            response_time_ms=(time.time() - start_time) * 1000,
            error_type=APIErrorType.UNKNOWN_ERROR.value,
            error_message="Max retries exceeded",
            retry_count=retry_count
        )
    
    @asynccontextmanager
    async def get_client(self):
        """Context manager for HTTP client."""
        if not self._client:
            await self._setup_client()
        
        try:
            yield self._client
        finally:
            pass
    
    # =========================================================================
    # SPECIFIC API TESTING METHODS
    # =========================================================================
    
    async def test_anthropic_api(self, test_message: str = "Hello, how are you?") -> APITestResult:
        """
        Test Anthropic Claude API with a simple message.
        
        This demonstrates testing a specific API with proper request structure.
        """
        self.logger.info(f"Testing Anthropic API with message: '{test_message}'")
        
        # Anthropic API request structure
        request_data = {
            "model": "claude-3-sonnet-20240229",
            "max_tokens": 100,
            "messages": [
                {
                    "role": "user",
                    "content": test_message
                }
            ]
        }
        
        result = await self.test_api_call(
            method="POST",
            endpoint="/v1/messages",
            data=request_data
        )
        
        # Validate Anthropic-specific response structure
        if result.success and result.response_data:
            result = self._validate_anthropic_response(result)
        
        return result
    
    async def test_tavily_api(self, query: str = "travel destinations") -> APITestResult:
        """
        Test Tavily search API with a simple query.
        
        This demonstrates testing a different API with different request structure.
        """
        self.logger.info(f"Testing Tavily API with query: '{query}'")
        
        # Tavily API request structure
        request_data = {
            "query": query,
            "search_depth": "basic",
            "include_answer": True,
            "include_raw_content": False,
            "max_results": 5
        }
        
        result = await self.test_api_call(
            method="POST",
            endpoint="/search",
            data=request_data
        )
        
        # Validate Tavily-specific response structure
        if result.success and result.response_data:
            result = self._validate_tavily_response(result)
        
        return result
    
    def _validate_anthropic_response(self, result: APITestResult) -> APITestResult:
        """
        Validate Anthropic API response structure.
        
        This demonstrates response validation for specific APIs.
        """
        try:
            data = result.response_data
            
            # Check required fields
            required_fields = ["id", "type", "role", "content"]
            for field in required_fields:
                if field not in data:
                    result.success = False
                    result.error_type = APIErrorType.VALIDATION_ERROR.value
                    result.error_message = f"Missing required field: {field}"
                    return result
            
            # Check content structure
            if not isinstance(data.get("content"), list):
                result.success = False
                result.error_type = APIErrorType.VALIDATION_ERROR.value
                result.error_message = "Content field must be a list"
                return result
            
            # Check usage information
            if "usage" in data:
                usage = data["usage"]
                if not all(key in usage for key in ["input_tokens", "output_tokens"]):
                    result.success = False
                    result.error_type = APIErrorType.VALIDATION_ERROR.value
                    result.error_message = "Usage field missing required token information"
                    return result
            
            self.logger.info(f"✅ Anthropic response validation passed")
            
        except Exception as e:
            result.success = False
            result.error_type = APIErrorType.VALIDATION_ERROR.value
            result.error_message = f"Response validation error: {e}"
            self.logger.error(f"❌ Anthropic response validation failed: {e}")
        
        return result
    
    def _validate_tavily_response(self, result: APITestResult) -> APITestResult:
        """
        Validate Tavily API response structure.
        
        This demonstrates response validation for a different API.
        """
        try:
            data = result.response_data
            
            # Check required fields
            required_fields = ["query", "follow_up_questions", "images", "results"]
            for field in required_fields:
                if field not in data:
                    result.success = False
                    result.error_type = APIErrorType.VALIDATION_ERROR.value
                    result.error_message = f"Missing required field: {field}"
                    return result
            
            # Check results structure
            results = data.get("results", [])
            if not isinstance(results, list):
                result.success = False
                result.error_type = APIErrorType.VALIDATION_ERROR.value
                result.error_message = "Results field must be a list"
                return result
            
            # Check individual result structure
            for i, result_item in enumerate(results):
                if not isinstance(result_item, dict):
                    result.success = False
                    result.error_type = APIErrorType.VALIDATION_ERROR.value
                    result.error_message = f"Result {i} must be a dictionary"
                    return result
                
                if not all(key in result_item for key in ["title", "url", "content"]):
                    result.success = False
                    result.error_type = APIErrorType.VALIDATION_ERROR.value
                    result.error_message = f"Result {i} missing required fields"
                    return result
            
            self.logger.info(f"✅ Tavily response validation passed")
            
        except Exception as e:
            result.success = False
            result.error_type = APIErrorType.VALIDATION_ERROR.value
            result.error_message = f"Response validation error: {e}"
            self.logger.error(f"❌ Tavily response validation failed: {e}")
        
        return result
    
    # =========================================================================
    # DEBUGGING UTILITIES
    # =========================================================================
    
    def debug_api_issue(self, result: APITestResult) -> Dict[str, Any]:
        """
        Provide step-by-step debugging information for API issues.
        
        This demonstrates comprehensive debugging techniques.
        """
        debug_info = {
            "api_name": result.api_name,
            "endpoint": result.endpoint,
            "success": result.success,
            "response_time_ms": result.response_time_ms,
            "timestamp": result.timestamp,
            "retry_count": result.retry_count
        }
        
        if not result.success:
            debug_info["error_analysis"] = self._analyze_error(result)
            debug_info["troubleshooting_steps"] = self._get_troubleshooting_steps(result)
            debug_info["recommendations"] = self._get_recommendations(result)
        
        return debug_info
    
    def _analyze_error(self, result: APITestResult) -> Dict[str, Any]:
        """Analyze the error and provide detailed information."""
        analysis = {
            "error_type": result.error_type,
            "error_message": result.error_message,
            "status_code": result.status_code
        }
        
        # Add specific analysis based on error type
        if result.error_type == APIErrorType.AUTHENTICATION_ERROR.value:
            analysis["likely_causes"] = [
                "Invalid API key",
                "Expired API key",
                "Incorrect authentication header format",
                "API key not activated"
            ]
        elif result.error_type == APIErrorType.RATE_LIMIT_ERROR.value:
            analysis["likely_causes"] = [
                "Too many requests per minute",
                "Exceeded daily quota",
                "Rate limit not properly handled"
            ]
        elif result.error_type == APIErrorType.NETWORK_ERROR.value:
            analysis["likely_causes"] = [
                "Internet connection issues",
                "DNS resolution problems",
                "Firewall blocking requests",
                "API server down"
            ]
        elif result.error_type == APIErrorType.TIMEOUT_ERROR.value:
            analysis["likely_causes"] = [
                "Request timeout too short",
                "API server overloaded",
                "Network latency issues"
            ]
        
        return analysis
    
    def _get_troubleshooting_steps(self, result: APITestResult) -> List[str]:
        """Get step-by-step troubleshooting steps."""
        steps = []
        
        if result.error_type == APIErrorType.AUTHENTICATION_ERROR.value:
            steps = [
                "1. Verify your API key is correct",
                "2. Check if the API key is activated",
                "3. Ensure the authentication header format is correct",
                "4. Test with a simple curl command",
                "5. Check API documentation for authentication requirements"
            ]
        elif result.error_type == APIErrorType.RATE_LIMIT_ERROR.value:
            steps = [
                "1. Check your current rate limit usage",
                "2. Implement proper rate limiting in your code",
                "3. Consider upgrading your API plan",
                "4. Add delays between requests",
                "5. Use exponential backoff for retries"
            ]
        elif result.error_type == APIErrorType.NETWORK_ERROR.value:
            steps = [
                "1. Check your internet connection",
                "2. Test with a different network",
                "3. Verify the API endpoint URL",
                "4. Check if there are firewall restrictions",
                "5. Test with a simple ping to the API server"
            ]
        elif result.error_type == APIErrorType.TIMEOUT_ERROR.value:
            steps = [
                "1. Increase the timeout value",
                "2. Check if the API server is responding",
                "3. Test with a smaller request",
                "4. Check network latency",
                "5. Consider using a different API endpoint"
            ]
        
        return steps
    
    def _get_recommendations(self, result: APITestResult) -> List[str]:
        """Get recommendations for fixing the issue."""
        recommendations = []
        
        if result.error_type == APIErrorType.AUTHENTICATION_ERROR.value:
            recommendations = [
                "Double-check your API key configuration",
                "Review the API documentation for authentication examples",
                "Test with a minimal request first"
            ]
        elif result.error_type == APIErrorType.RATE_LIMIT_ERROR.value:
            recommendations = [
                "Implement proper rate limiting",
                "Consider using a queue system for requests",
                "Monitor your API usage regularly"
            ]
        elif result.error_type == APIErrorType.NETWORK_ERROR.value:
            recommendations = [
                "Check your network configuration",
                "Consider using a VPN if there are regional restrictions",
                "Test from a different location"
            ]
        elif result.error_type == APIErrorType.TIMEOUT_ERROR.value:
            recommendations = [
                "Optimize your request size",
                "Implement proper timeout handling",
                "Consider using async requests for better performance"
            ]
        
        return recommendations
    
    # =========================================================================
    # UTILITY METHODS
    # =========================================================================
    
    def get_stats(self) -> Dict[str, Any]:
        """Get API tester statistics."""
        return {
            "api_name": self.config.name,
            "request_count": self._request_count,
            "rate_limit_tokens": self._rate_limit_tokens,
            "rate_limit_reset": self._rate_limit_reset
        }
    
    async def health_check(self) -> bool:
        """Check if the API is healthy."""
        try:
            # Try a simple request to check connectivity
            result = await self.test_api_call("GET", "/health")
            return result.success
        except Exception as e:
            self.logger.error(f"Health check failed for {self.config.name}: {e}")
            return False