"""Comprehensive page analysis data collection for LLM processing."""
from __future__ import annotations

import time
from datetime import UTC, datetime
from enum import Enum
from pathlib import Path
from typing import Any
from urllib.parse import urlparse

import structlog
from playwright.async_api import Page
from pydantic import BaseModel, Field

from legacy_web_mcp.browser.interaction import InteractionConfig, PageInteractionAutomator
from legacy_web_mcp.browser.navigation import PageContentData, PageNavigator
from legacy_web_mcp.browser.network import NetworkMonitor, NetworkMonitorConfig

_logger = structlog.get_logger("legacy_web_mcp.browser.analysis")


class PageType(str, Enum):
    """Types of web pages based on functionality."""

    HOMEPAGE = "homepage"
    LANDING_PAGE = "landing_page"
    PRODUCT_PAGE = "product_page"
    CATEGORY_PAGE = "category_page"
    ARTICLE = "article"
    BLOG_POST = "blog_post"
    FORM_PAGE = "form_page"
    LOGIN_PAGE = "login_page"
    DASHBOARD = "dashboard"
    ADMIN_PANEL = "admin_panel"
    SEARCH_RESULTS = "search_results"
    ERROR_PAGE = "error_page"
    DOCUMENTATION = "documentation"
    CONTACT_PAGE = "contact_page"
    ABOUT_PAGE = "about_page"
    UNKNOWN = "unknown"


class JSFramework(str, Enum):
    """Detected JavaScript frameworks."""

    REACT = "react"
    ANGULAR = "angular"
    VUE = "vue"
    JQUERY = "jquery"
    BACKBONE = "backbone"
    EMBER = "ember"
    SVELTE = "svelte"
    ALPINE = "alpine"
    STIMULUS = "stimulus"
    VANILLA = "vanilla"
    UNKNOWN = "unknown"


class DOMStructureAnalysis(BaseModel):
    """Analysis of DOM structure and elements."""

    total_elements: int = 0
    semantic_elements: int = 0
    interactive_elements: int = 0
    form_elements: int = 0
    link_elements: int = 0
    image_elements: int = 0
    video_elements: int = 0
    iframe_elements: int = 0
    script_elements: int = 0
    style_elements: int = 0

    # Element details
    forms: list[dict[str, Any]] = Field(default_factory=list)
    buttons: list[dict[str, Any]] = Field(default_factory=list)
    inputs: list[dict[str, Any]] = Field(default_factory=list)
    links: list[dict[str, Any]] = Field(default_factory=list)

    # Structure metrics
    max_nesting_depth: int = 0
    heading_structure: list[dict[str, Any]] = Field(default_factory=list)
    landmark_elements: list[str] = Field(default_factory=list)


class FunctionalityAnalysis(BaseModel):
    """Analysis of page functionality and workflows."""

    page_type: PageType = PageType.UNKNOWN
    primary_functions: list[str] = Field(default_factory=list)
    user_workflows: list[str] = Field(default_factory=list)
    interaction_patterns: list[str] = Field(default_factory=list)
    navigation_complexity: str = "simple"  # simple, moderate, complex
    content_density: str = "low"  # low, medium, high
    form_complexity: str = "none"  # none, simple, moderate, complex


class AccessibilityAnalysis(BaseModel):
    """Accessibility tree and semantic structure analysis."""

    accessibility_tree: dict[str, Any] = Field(default_factory=dict)
    semantic_roles: list[str] = Field(default_factory=list)
    aria_labels: list[dict[str, str]] = Field(default_factory=list)
    alt_texts: list[str] = Field(default_factory=list)
    heading_hierarchy: list[dict[str, Any]] = Field(default_factory=list)
    focus_order: list[str] = Field(default_factory=list)
    accessibility_violations: list[str] = Field(default_factory=list)


class TechnologyAnalysis(BaseModel):
    """JavaScript frameworks and technology detection."""

    js_frameworks: list[JSFramework] = Field(default_factory=list)
    js_libraries: list[str] = Field(default_factory=list)
    css_frameworks: list[str] = Field(default_factory=list)
    build_tools: list[str] = Field(default_factory=list)
    meta_frameworks: list[str] = Field(default_factory=list)
    cms_detection: str | None = None
    analytics_tools: list[str] = Field(default_factory=list)


class CSSAnalysis(BaseModel):
    """CSS styling patterns and responsive design analysis."""

    external_stylesheets: list[str] = Field(default_factory=list)
    inline_styles_count: int = 0
    css_variables_count: int = 0
    media_queries: list[str] = Field(default_factory=list)
    responsive_breakpoints: list[int] = Field(default_factory=list)
    css_frameworks_detected: list[str] = Field(default_factory=list)
    critical_css_size: int = 0
    animation_properties: list[str] = Field(default_factory=list)


class PerformanceAnalysis(BaseModel):
    """Performance metrics and optimization opportunities."""

    navigation_timing: dict[str, float] = Field(default_factory=dict)
    resource_timing: dict[str, Any] = Field(default_factory=dict)
    core_web_vitals: dict[str, float] = Field(default_factory=dict)
    total_resource_size: int = 0
    render_blocking_resources: int = 0
    javascript_bundle_size: int = 0
    css_bundle_size: int = 0
    image_optimization_score: float = 0.0
    cache_utilization: dict[str, Any] = Field(default_factory=dict)


class PageAnalysisData(BaseModel):
    """Comprehensive analysis data for a single page."""

    # Basic page information
    url: str
    title: str
    description: str | None = None
    timestamp: datetime = Field(default_factory=lambda: datetime.now(UTC))

    # Core content
    page_content: dict[str, Any] = Field(default_factory=dict)
    network_traffic: dict[str, Any] = Field(default_factory=dict)
    user_interactions: dict[str, Any] = Field(default_factory=dict)

    # Analysis results
    dom_analysis: DOMStructureAnalysis = Field(default_factory=DOMStructureAnalysis)
    functionality_analysis: FunctionalityAnalysis = Field(default_factory=FunctionalityAnalysis)
    accessibility_analysis: AccessibilityAnalysis = Field(default_factory=AccessibilityAnalysis)
    technology_analysis: TechnologyAnalysis = Field(default_factory=TechnologyAnalysis)
    css_analysis: CSSAnalysis = Field(default_factory=CSSAnalysis)
    performance_analysis: PerformanceAnalysis = Field(default_factory=PerformanceAnalysis)

    # Processing metadata
    analysis_duration: float = 0.0
    analysis_version: str = "1.0.0"
    processing_errors: list[str] = Field(default_factory=list)

    def to_dict(self) -> dict[str, Any]:
        """Convert to dictionary for JSON serialization."""
        return {
            "url": self.url,
            "title": self.title,
            "description": self.description,
            "timestamp": self.timestamp.isoformat(),
            "page_content": self.page_content,
            "network_traffic": self.network_traffic,
            "user_interactions": self.user_interactions,
            "analysis": {
                "dom_structure": self.dom_analysis.model_dump(),
                "functionality": self.functionality_analysis.model_dump(),
                "accessibility": self.accessibility_analysis.model_dump(),
                "technology": self.technology_analysis.model_dump(),
                "css_styling": self.css_analysis.model_dump(),
                "performance": self.performance_analysis.model_dump(),
            },
            "metadata": {
                "analysis_duration": self.analysis_duration,
                "analysis_version": self.analysis_version,
                "processing_errors": self.processing_errors,
            }
        }


class PageAnalyzer:
    """Comprehensive page analyzer combining all analysis capabilities."""

    def __init__(
        self,
        include_network_analysis: bool = True,
        include_interaction_analysis: bool = True,
        performance_budget_seconds: float = 120.0,
    ):
        self.include_network_analysis = include_network_analysis
        self.include_interaction_analysis = include_interaction_analysis
        self.performance_budget_seconds = performance_budget_seconds

        # Initialize component analyzers
        self.page_navigator = PageNavigator(
            timeout=30.0,
            max_retries=2,
            wait_for_network_idle=True,
            enable_screenshots=True,
        )

        if include_network_analysis:
            self.network_monitor = NetworkMonitor(
                NetworkMonitorConfig(
                    capture_request_payloads=True,
                    capture_response_payloads=False,  # Skip large responses for performance
                    max_payload_size=5000,
                    filter_static_assets=False,  # Keep assets for analysis
                    include_timing_data=True,
                ),
                base_domain=None,  # Will be set per page
            )

        if include_interaction_analysis:
            self.interaction_automator = PageInteractionAutomator(
                InteractionConfig(
                    enable_form_interactions=True,
                    enable_navigation_clicks=False,  # Skip navigation for analysis focus
                    enable_modal_handling=True,
                    enable_scrolling=True,
                    max_interactions_per_page=20,  # Limit for performance
                )
            )

    async def analyze_page(
        self,
        page: Page,
        url: str,
        project_root: Path | None = None,
    ) -> PageAnalysisData:
        """Perform comprehensive analysis of a single page.

        Args:
            page: Playwright page instance
            url: Target URL to analyze
            project_root: Optional project root for file storage

        Returns:
            Complete page analysis data
        """
        start_time = time.time()
        analysis_data = PageAnalysisData(url=url, title="")

        _logger.info(
            "page_analysis_started",
            url=url,
            include_network=self.include_network_analysis,
            include_interaction=self.include_interaction_analysis,
        )

        try:
            # Step 1: Basic page content extraction
            _logger.info("page_analysis_step", step="content_extraction", url=url)
            page_content = await self._extract_page_content(page, url, project_root)
            analysis_data.page_content = page_content.to_dict()
            analysis_data.title = page_content.title
            analysis_data.description = page_content.meta_data.get("meta_description")

            # Set base domain for network monitoring
            if self.include_network_analysis:
                parsed_url = urlparse(url)
                self.network_monitor.base_domain = parsed_url.netloc

            # Step 2: Network traffic monitoring (if enabled)
            if self.include_network_analysis:
                _logger.info("page_analysis_step", step="network_monitoring", url=url)
                network_data = await self._analyze_network_traffic(page, url)
                analysis_data.network_traffic = network_data

            # Step 3: User interaction simulation (if enabled)
            if self.include_interaction_analysis:
                _logger.info("page_analysis_step", step="interaction_simulation", url=url)
                interaction_data = await self._analyze_user_interactions(page, url)
                analysis_data.user_interactions = interaction_data

            # Step 4: DOM structure analysis
            _logger.info("page_analysis_step", step="dom_analysis", url=url)
            analysis_data.dom_analysis = await self._analyze_dom_structure(page)

            # Step 5: Functionality analysis
            _logger.info("page_analysis_step", step="functionality_analysis", url=url)
            analysis_data.functionality_analysis = await self._analyze_functionality(page, analysis_data)

            # Step 6: Accessibility analysis
            _logger.info("page_analysis_step", step="accessibility_analysis", url=url)
            analysis_data.accessibility_analysis = await self._analyze_accessibility(page)

            # Step 7: Technology detection
            _logger.info("page_analysis_step", step="technology_detection", url=url)
            analysis_data.technology_analysis = await self._analyze_technology(page)

            # Step 8: CSS analysis
            _logger.info("page_analysis_step", step="css_analysis", url=url)
            analysis_data.css_analysis = await self._analyze_css(page)

            # Step 9: Performance analysis
            _logger.info("page_analysis_step", step="performance_analysis", url=url)
            analysis_data.performance_analysis = await self._analyze_performance(page, analysis_data)

            # Calculate total analysis time
            analysis_data.analysis_duration = time.time() - start_time

            _logger.info(
                "page_analysis_completed",
                url=url,
                duration=analysis_data.analysis_duration,
                dom_elements=analysis_data.dom_analysis.total_elements,
                page_type=analysis_data.functionality_analysis.page_type.value,
                js_frameworks=len(analysis_data.technology_analysis.js_frameworks),
            )

            return analysis_data

        except Exception as e:
            analysis_data.processing_errors.append(f"Analysis failed: {str(e)}")
            analysis_data.analysis_duration = time.time() - start_time

            _logger.error(
                "page_analysis_failed",
                url=url,
                error=str(e),
                error_type=type(e).__name__,
                duration=analysis_data.analysis_duration,
            )

            return analysis_data

    async def _extract_page_content(
        self,
        page: Page,
        url: str,
        project_root: Path | None,
    ) -> PageContentData:
        """Extract basic page content using PageNavigator."""
        return await self.page_navigator.navigate_and_extract(page, url, project_root)

    async def _analyze_network_traffic(self, page: Page, url: str) -> dict[str, Any]:
        """Analyze network traffic during page load."""
        try:
            await self.network_monitor.start_monitoring(page)

            # Navigate to page to capture network requests
            await page.goto(url, timeout=30000)
            await page.wait_for_load_state("networkidle", timeout=30000)

            # Get network analysis
            summary = self.network_monitor.get_summary()
            requests = self.network_monitor.get_requests()

            await self.network_monitor.stop_monitoring(page)

            return {
                "summary": summary.to_dict(),
                "requests": [req.to_dict() for req in requests[:50]],  # Limit for performance
            }

        except Exception as e:
            _logger.warning("network_analysis_failed", error=str(e))
            return {"error": str(e)}

    async def _analyze_user_interactions(self, page: Page, url: str) -> dict[str, Any]:
        """Analyze page through user interaction simulation."""
        try:
            results = await self.interaction_automator.discover_and_interact(page, url)
            return {
                "summary": self.interaction_automator.get_interaction_summary(),
                "discovered_urls": list(self.interaction_automator.discovered_urls),
                "interaction_count": len(self.interaction_automator.interaction_logs),
            }
        except Exception as e:
            _logger.warning("interaction_analysis_failed", error=str(e))
            return {"error": str(e)}

    async def _analyze_dom_structure(self, page: Page) -> DOMStructureAnalysis:
        """Analyze DOM structure and element counts."""
        try:
            # Get element counts
            element_counts = await page.evaluate("""() => {
                const counts = {
                    total: document.querySelectorAll('*').length,
                    semantic: document.querySelectorAll('main, section, article, aside, header, footer, nav, figure').length,
                    interactive: document.querySelectorAll('button, input, select, textarea, a[href]').length,
                    forms: document.querySelectorAll('form').length,
                    links: document.querySelectorAll('a[href]').length,
                    images: document.querySelectorAll('img').length,
                    videos: document.querySelectorAll('video').length,
                    iframes: document.querySelectorAll('iframe').length,
                    scripts: document.querySelectorAll('script').length,
                    styles: document.querySelectorAll('style, link[rel="stylesheet"]').length,
                };
                return counts;
            }""")

            # Get form details
            forms_data = await page.evaluate("""() => {
                return Array.from(document.querySelectorAll('form')).map(form => ({
                    action: form.action || '',
                    method: form.method || 'GET',
                    inputs: Array.from(form.querySelectorAll('input')).length,
                    selects: Array.from(form.querySelectorAll('select')).length,
                    textareas: Array.from(form.querySelectorAll('textarea')).length,
                    buttons: Array.from(form.querySelectorAll('button, input[type="submit"]')).length,
                }));
            }""")

            # Get button details
            buttons_data = await page.evaluate("""() => {
                return Array.from(document.querySelectorAll('button, input[type="button"], input[type="submit"]')).map(btn => ({
                    type: btn.type || 'button',
                    text: btn.textContent?.trim() || btn.value || '',
                    disabled: btn.disabled,
                }));
            }""")

            # Get input details
            inputs_data = await page.evaluate("""() => {
                return Array.from(document.querySelectorAll('input')).map(input => ({
                    type: input.type || 'text',
                    name: input.name || '',
                    required: input.required,
                    placeholder: input.placeholder || '',
                }));
            }""")

            # Get heading structure
            heading_structure = await page.evaluate("""() => {
                return Array.from(document.querySelectorAll('h1, h2, h3, h4, h5, h6')).map(h => ({
                    level: parseInt(h.tagName.substring(1)),
                    text: h.textContent?.trim() || '',
                }));
            }""")

            # Get nesting depth
            max_depth = await page.evaluate("""() => {
                let maxDepth = 0;
                function getDepth(element, depth = 0) {
                    maxDepth = Math.max(maxDepth, depth);
                    for (let child of element.children) {
                        getDepth(child, depth + 1);
                    }
                }
                getDepth(document.body);
                return maxDepth;
            }""")

            return DOMStructureAnalysis(
                total_elements=element_counts["total"],
                semantic_elements=element_counts["semantic"],
                interactive_elements=element_counts["interactive"],
                form_elements=element_counts["forms"],
                link_elements=element_counts["links"],
                image_elements=element_counts["images"],
                video_elements=element_counts["videos"],
                iframe_elements=element_counts["iframes"],
                script_elements=element_counts["scripts"],
                style_elements=element_counts["styles"],
                forms=forms_data,
                buttons=buttons_data,
                inputs=inputs_data,
                max_nesting_depth=max_depth,
                heading_structure=heading_structure,
            )

        except Exception as e:
            _logger.warning("dom_analysis_failed", error=str(e))
            return DOMStructureAnalysis()

    async def _analyze_functionality(self, page: Page, analysis_data: PageAnalysisData) -> FunctionalityAnalysis:
        """Analyze page functionality and categorize page type."""
        try:
            page_title = analysis_data.title.lower()
            page_url = analysis_data.url.lower()

            # Determine page type based on various indicators
            page_type = self._classify_page_type(page_title, page_url, analysis_data.dom_analysis)

            # Determine primary functions
            primary_functions = self._identify_primary_functions(analysis_data.dom_analysis)

            # Analyze complexity metrics
            nav_complexity = self._assess_navigation_complexity(analysis_data.dom_analysis)
            content_density = self._assess_content_density(analysis_data.dom_analysis)
            form_complexity = self._assess_form_complexity(analysis_data.dom_analysis)

            return FunctionalityAnalysis(
                page_type=page_type,
                primary_functions=primary_functions,
                navigation_complexity=nav_complexity,
                content_density=content_density,
                form_complexity=form_complexity,
            )

        except Exception as e:
            _logger.warning("functionality_analysis_failed", error=str(e))
            return FunctionalityAnalysis()

    async def _analyze_accessibility(self, page: Page) -> AccessibilityAnalysis:
        """Analyze accessibility features and semantic structure."""
        try:
            # Get accessibility tree (simplified)
            aria_elements = await page.evaluate("""() => {
                return Array.from(document.querySelectorAll('[role], [aria-label], [aria-describedby]')).map(el => ({
                    role: el.getAttribute('role') || '',
                    label: el.getAttribute('aria-label') || '',
                    tag: el.tagName.toLowerCase(),
                }));
            }""")

            # Get alt texts
            alt_texts = await page.evaluate("""() => {
                return Array.from(document.querySelectorAll('img[alt]')).map(img => img.alt);
            }""")

            # Get heading hierarchy
            headings = await page.evaluate("""() => {
                return Array.from(document.querySelectorAll('h1, h2, h3, h4, h5, h6')).map(h => ({
                    level: parseInt(h.tagName.substring(1)),
                    text: h.textContent?.trim() || '',
                    id: h.id || '',
                }));
            }""")

            return AccessibilityAnalysis(
                aria_labels=[{"role": el["role"], "label": el["label"], "tag": el["tag"]} for el in aria_elements],
                alt_texts=alt_texts,
                heading_hierarchy=headings,
                semantic_roles=list(set(el["role"] for el in aria_elements if el["role"])),
            )

        except Exception as e:
            _logger.warning("accessibility_analysis_failed", error=str(e))
            return AccessibilityAnalysis()

    async def _analyze_technology(self, page: Page) -> TechnologyAnalysis:
        """Detect JavaScript frameworks and technologies."""
        try:
            # Detect JavaScript frameworks and libraries
            js_detection = await page.evaluate("""() => {
                const frameworks = [];
                const libraries = [];

                // React
                if (window.React || document.querySelector('[data-reactroot]')) {
                    frameworks.push('react');
                }

                // Angular
                if (window.angular || window.ng || document.querySelector('[ng-app], [ng-controller]')) {
                    frameworks.push('angular');
                }

                // Vue
                if (window.Vue || document.querySelector('[v-app], [data-v-]')) {
                    frameworks.push('vue');
                }

                // jQuery
                if (window.jQuery || window.$) {
                    libraries.push('jquery');
                }

                // Other common libraries
                if (window._ || window.lodash) libraries.push('lodash');
                if (window.moment) libraries.push('moment');
                if (window.d3) libraries.push('d3');
                if (window.Chart) libraries.push('chartjs');

                return { frameworks, libraries };
            }""")

            # Detect CSS frameworks
            css_frameworks = await page.evaluate("""() => {
                const frameworks = [];
                const stylesheets = Array.from(document.querySelectorAll('link[rel="stylesheet"]'));

                for (const link of stylesheets) {
                    const href = link.href || '';
                    if (href.includes('bootstrap')) frameworks.push('bootstrap');
                    if (href.includes('tailwind')) frameworks.push('tailwind');
                    if (href.includes('bulma')) frameworks.push('bulma');
                    if (href.includes('foundation')) frameworks.push('foundation');
                }

                return frameworks;
            }""")

            # Detect meta tags for additional framework info
            meta_info = await page.evaluate("""() => {
                const generator = document.querySelector('meta[name="generator"]');
                return generator ? generator.content : '';
            }""")

            js_frameworks = []
            for fw in js_detection["frameworks"]:
                try:
                    js_frameworks.append(JSFramework(fw))
                except ValueError:
                    pass

            return TechnologyAnalysis(
                js_frameworks=js_frameworks,
                js_libraries=js_detection["libraries"],
                css_frameworks=css_frameworks,
                cms_detection=meta_info if meta_info else None,
            )

        except Exception as e:
            _logger.warning("technology_analysis_failed", error=str(e))
            return TechnologyAnalysis()

    async def _analyze_css(self, page: Page) -> CSSAnalysis:
        """Analyze CSS styling patterns and responsive design."""
        try:
            css_info = await page.evaluate("""() => {
                const external = Array.from(document.querySelectorAll('link[rel="stylesheet"]')).map(link => link.href);
                const inlineStyles = document.querySelectorAll('[style]').length;

                // Try to detect responsive breakpoints from common CSS patterns
                const breakpoints = [];
                const stylesheets = Array.from(document.styleSheets);

                for (const sheet of stylesheets) {
                    try {
                        const rules = Array.from(sheet.cssRules || []);
                        for (const rule of rules) {
                            if (rule.type === CSSRule.MEDIA_RULE) {
                                const mediaText = rule.media.mediaText;
                                const match = mediaText.match(/max-width:\s*(\d+)px|min-width:\s*(\d+)px/);
                                if (match) {
                                    const width = parseInt(match[1] || match[2]);
                                    if (width && !breakpoints.includes(width)) {
                                        breakpoints.push(width);
                                    }
                                }
                            }
                        }
                    } catch (e) {
                        // Cross-origin stylesheet access might fail
                    }
                }

                return {
                    external,
                    inlineStyles,
                    breakpoints: breakpoints.sort((a, b) => a - b),
                };
            }""")

            return CSSAnalysis(
                external_stylesheets=css_info["external"],
                inline_styles_count=css_info["inlineStyles"],
                responsive_breakpoints=css_info["breakpoints"],
            )

        except Exception as e:
            _logger.warning("css_analysis_failed", error=str(e))
            return CSSAnalysis()

    async def _analyze_performance(self, page: Page, analysis_data: PageAnalysisData) -> PerformanceAnalysis:
        """Analyze performance metrics and optimization opportunities."""
        try:
            # Get navigation timing
            navigation_timing = await page.evaluate("""() => {
                const timing = performance.timing;
                return {
                    dns_lookup: timing.domainLookupEnd - timing.domainLookupStart,
                    tcp_connect: timing.connectEnd - timing.connectStart,
                    request_response: timing.responseEnd - timing.requestStart,
                    dom_processing: timing.domComplete - timing.domLoading,
                    total_load: timing.loadEventEnd - timing.navigationStart,
                };
            }""")

            # Get resource timing summary
            resource_summary = await page.evaluate("""() => {
                const resources = performance.getEntriesByType('resource');
                let totalSize = 0;
                let jsSize = 0;
                let cssSize = 0;
                let imageSize = 0;

                resources.forEach(resource => {
                    const size = resource.transferSize || 0;
                    totalSize += size;

                    if (resource.initiatorType === 'script') jsSize += size;
                    else if (resource.initiatorType === 'css') cssSize += size;
                    else if (resource.initiatorType === 'img') imageSize += size;
                });

                return {
                    total_size: totalSize,
                    js_size: jsSize,
                    css_size: cssSize,
                    image_size: imageSize,
                    resource_count: resources.length,
                };
            }""")

            # Calculate scores based on analysis data
            total_elements = analysis_data.dom_analysis.total_elements
            complexity_score = min(100, (total_elements / 500) * 100)  # Scale based on element count

            return PerformanceAnalysis(
                navigation_timing=navigation_timing,
                resource_timing=resource_summary,
                total_resource_size=resource_summary["total_size"],
                javascript_bundle_size=resource_summary["js_size"],
                css_bundle_size=resource_summary["css_size"],
                image_optimization_score=100 - complexity_score,  # Simplified scoring
            )

        except Exception as e:
            _logger.warning("performance_analysis_failed", error=str(e))
            return PerformanceAnalysis()

    def _classify_page_type(self, title: str, url: str, dom_analysis: DOMStructureAnalysis) -> PageType:
        """Classify page type based on various indicators."""
        # Check URL patterns
        if "login" in url or "signin" in url:
            return PageType.LOGIN_PAGE
        elif "contact" in url:
            return PageType.CONTACT_PAGE
        elif "about" in url:
            return PageType.ABOUT_PAGE
        elif "blog" in url or "article" in url:
            return PageType.BLOG_POST
        elif "search" in url:
            return PageType.SEARCH_RESULTS
        elif "admin" in url or "dashboard" in url:
            return PageType.ADMIN_PANEL
        elif url.count("/") <= 2:  # Root or one level deep
            return PageType.HOMEPAGE

        # Check content patterns
        if dom_analysis.form_elements > 2:
            return PageType.FORM_PAGE
        elif "error" in title or "404" in title:
            return PageType.ERROR_PAGE
        elif dom_analysis.total_elements > 200:
            return PageType.CATEGORY_PAGE
        else:
            return PageType.UNKNOWN

    def _identify_primary_functions(self, dom_analysis: DOMStructureAnalysis) -> list[str]:
        """Identify primary page functions based on elements."""
        functions = []

        if dom_analysis.form_elements > 0:
            functions.append("data_collection")
        if dom_analysis.link_elements > 10:
            functions.append("navigation")
        if dom_analysis.image_elements > 5:
            functions.append("content_display")
        if dom_analysis.interactive_elements > 5:
            functions.append("user_interaction")
        if dom_analysis.video_elements > 0:
            functions.append("media_playback")

        return functions or ["information_display"]

    def _assess_navigation_complexity(self, dom_analysis: DOMStructureAnalysis) -> str:
        """Assess navigation complexity based on structure."""
        link_count = dom_analysis.link_elements
        if link_count > 50:
            return "complex"
        elif link_count > 15:
            return "moderate"
        else:
            return "simple"

    def _assess_content_density(self, dom_analysis: DOMStructureAnalysis) -> str:
        """Assess content density based on element count."""
        total_elements = dom_analysis.total_elements
        if total_elements > 300:
            return "high"
        elif total_elements > 100:
            return "medium"
        else:
            return "low"

    def _assess_form_complexity(self, dom_analysis: DOMStructureAnalysis) -> str:
        """Assess form complexity based on form elements."""
        if dom_analysis.form_elements == 0:
            return "none"

        total_inputs = len(dom_analysis.inputs)
        if total_inputs > 15:
            return "complex"
        elif total_inputs > 5:
            return "moderate"
        else:
            return "simple"


__all__ = [
    "PageType",
    "JSFramework",
    "DOMStructureAnalysis",
    "FunctionalityAnalysis",
    "AccessibilityAnalysis",
    "TechnologyAnalysis",
    "CSSAnalysis",
    "PerformanceAnalysis",
    "PageAnalysisData",
    "PageAnalyzer",
]