Search and Indexing

class SearchField:
    """
    Configures a field for full-text search indexing.
    
    Parameters:
        field_name (str): Name of the model field to index
        partial_match (bool): Whether to enable partial matching
        boost (int): Search result boost factor for this field
    """
    def __init__(self, field_name, partial_match=True, boost=1):
        """Initialize search field configuration."""

class AutocompleteField:
    """
    Configures a field for autocomplete search functionality.
    
    Parameters:
        field_name (str): Name of the model field for autocomplete
    """
    def __init__(self, field_name):
        """Initialize autocomplete field configuration."""

class FilterField:
    """
    Configures a field for exact match filtering in search results.
    
    Parameters:
        field_name (str): Name of the model field for filtering
    """
    def __init__(self, field_name):
        """Initialize filter field configuration."""

class RelatedFields:
    """
    Configures search through related model fields.
    
    Parameters:
        relation_name (str): Name of the relation to search through
        fields (list): List of SearchField objects for related model
    """
    def __init__(self, relation_name, fields):
        """Initialize related fields search configuration."""

class Indexed:
    """
    Mixin class that makes Django models searchable.
    
    Add this mixin to any model to enable search functionality.
    """
    search_fields: list  # List of SearchField, AutocompleteField, FilterField objects
    
    @classmethod
    def search(cls, query, backend=None):
        """
        Perform a search query on this model.
        
        Parameters:
            query (str): Search query string
            backend (str): Search backend to use (optional)
            
        Returns:
            SearchResults: Query results with ranking and filtering
        """

def get_search_backend(backend_name=None):
    """
    Get a search backend instance.
    
    Parameters:
        backend_name (str): Name of backend ('default', 'elasticsearch', etc.)
        
    Returns:
        SearchBackend: Configured search backend instance
    """

class SearchBackend:
    """
    Base class for search backends.
    
    All search backends inherit from this class.
    """
    def search(self, query, model_or_queryset, fields=None, filters=None, order_by_relevance=True):
        """
        Execute a search query.
        
        Parameters:
            query (str): Search query string
            model_or_queryset: Model class or QuerySet to search
            fields (list): Fields to search in
            filters (dict): Additional filters to apply
            order_by_relevance (bool): Whether to order by search relevance
            
        Returns:
            SearchResults: Search results with metadata
        """
    
    def autocomplete(self, query, model_or_queryset, fields=None):
        """
        Get autocomplete suggestions.
        
        Parameters:
            query (str): Partial query for autocomplete
            model_or_queryset: Model class or QuerySet for suggestions
            fields (list): Fields to use for autocomplete
            
        Returns:
            list: List of autocomplete suggestions
        """

class DatabaseSearchBackend(SearchBackend):
    """
    Search backend using Django's database with PostgreSQL full-text search.
    
    Default backend that works with any Django-supported database.
    """

class ElasticsearchSearchBackend(SearchBackend):
    """
    Search backend using Elasticsearch for advanced search capabilities.
    
    Provides better performance and advanced features for large datasets.
    """

class SearchResults:
    """
    Container for search results with metadata and filtering capabilities.
    """
    def __init__(self, model_or_queryset, query, backend):
        """Initialize search results container."""
    
    def __iter__(self):
        """Iterate over search results."""
    
    def __len__(self):
        """Get number of search results."""
    
    def __getitem__(self, index):
        """Get result at specific index or slice."""
    
    def filter(self, **kwargs):
        """Apply additional filters to search results."""
    
    def order_by(self, *fields):
        """Change the ordering of search results."""
    
    def annotate_score(self, field_name='_score'):
        """Add search relevance score to results."""

class SearchQuery:
    """
    Represents a search query with parsing and normalization.
    """
    def __init__(self, query_string, operator='and', boost=None):
        """
        Initialize search query.
        
        Parameters:
            query_string (str): Raw query string
            operator (str): Query operator ('and' or 'or')
            boost (dict): Field boost configuration
        """
    
    def get_terms(self):
        """Get individual search terms from query."""
    
    def get_filters(self):
        """Get filter conditions from query."""

def parse_query_string(query_string, operator='and'):
    """
    Parse a query string into structured query components.
    
    Parameters:
        query_string (str): Raw search query
        operator (str): Default operator between terms
        
    Returns:
        SearchQuery: Parsed query object
    """

class SearchPromotion:
    """
    Model for promoting specific content in search results.
    
    Allows administrators to boost certain pages for specific queries.
    """
    query: str
    page: Page
    sort_order: int
    description: str
    
    @classmethod
    def get_for_query(cls, query_string):
        """Get promotions for a specific query."""

def rebuild_search_index():
    """
    Rebuild the entire search index for all searchable models.
    
    Use this management command function to refresh search data.
    """

def update_search_index(model=None):
    """
    Update search index for specific model or all models.
    
    Parameters:
        model (Model): Specific model to update (None for all models)
    """

from wagtail.models import Page
from wagtail.search import index
from django.db import models

class BlogPage(Page):
    """Blog page with comprehensive search configuration."""
    date = models.DateField("Post date")
    intro = models.CharField(max_length=250)
    body = models.TextField()
    tags = models.CharField(max_length=255, blank=True)
    
    # Configure search fields
    search_fields = Page.search_fields + [
        index.SearchField('intro', partial_match=True, boost=2),
        index.SearchField('body'),
        index.SearchField('tags', partial_match=True),
        index.AutocompleteField('title'),
        index.FilterField('date'),
        index.FilterField('live'),
    ]

class Author(models.Model):
    """Author model with search fields."""
    name = models.CharField(max_length=100)
    bio = models.TextField()
    email = models.EmailField()
    
    # Make non-page models searchable
    search_fields = [
        index.SearchField('name', partial_match=True, boost=3),
        index.SearchField('bio'),
        index.AutocompleteField('name'),
    ]
    
    class Meta:
        # Add Indexed mixin functionality
        # In practice, inherit from index.Indexed
        pass

# Add Indexed mixin to existing model
Author.__bases__ = (index.Indexed,) + Author.__bases__

from wagtail.models import Page
from wagtail.search.models import Query

# Basic page search
search_results = Page.objects.live().search('django cms')

# Advanced search with filtering
blog_results = BlogPage.objects.live().search(
    'web development'
).filter(
    date__gte='2023-01-01'
).order_by('-date')

# Search with specific backend
from wagtail.search.backends import get_search_backend

elasticsearch_backend = get_search_backend('elasticsearch')
results = elasticsearch_backend.search(
    'python tutorial',
    BlogPage.objects.live(),
    fields=['title', 'intro', 'body']
)

# Autocomplete search
suggestions = Page.objects.live().autocomplete('wagtai')

# Track search queries
Query.get('django cms').add_hit()  # Record search analytics
popular_queries = Query.objects.filter(
    hits__gte=10
).order_by('-hits')

from django.shortcuts import render
from django.core.paginator import Paginator
from wagtail.models import Page
from wagtail.search.models import Query

def search_view(request):
    """Custom search view with pagination and analytics."""
    query_string = request.GET.get('q', '')
    page_number = request.GET.get('page', 1)
    
    if query_string:
        # Perform search
        search_results = Page.objects.live().search(query_string)
        
        # Track search query
        query = Query.get(query_string)
        query.add_hit()
        
        # Add pagination
        paginator = Paginator(search_results, 10)
        results_page = paginator.get_page(page_number)
        
        # Get search suggestions
        suggestions = Page.objects.live().autocomplete(query_string)[:5]
    else:
        results_page = None
        suggestions = []
    
    return render(request, 'search/search.html', {
        'query_string': query_string,
        'results': results_page,
        'suggestions': suggestions,
    })

def faceted_search_view(request):
    """Search view with faceted filtering."""
    query_string = request.GET.get('q', '')
    content_type = request.GET.get('type', '')
    date_filter = request.GET.get('date', '')
    
    if query_string:
        results = Page.objects.live().search(query_string)
        
        # Apply facet filters
        if content_type:
            results = results.type(eval(content_type))
        
        if date_filter:
            results = results.filter(first_published_at__gte=date_filter)
        
        # Get facet counts
        facets = {
            'types': results.facet('content_type'),
            'dates': results.facet('first_published_at__year'),
        }
    else:
        results = Page.objects.none()
        facets = {}
    
    return render(request, 'search/faceted_search.html', {
        'query_string': query_string,
        'results': results,
        'facets': facets,
    })

from wagtail.models import Page
from wagtail.search import index
from django.db import models
from modelcluster.fields import ParentalKey

class BlogCategory(models.Model):
    """Blog category model."""
    name = models.CharField(max_length=100)
    description = models.TextField()
    
    search_fields = [
        index.SearchField('name', boost=2),
        index.SearchField('description'),
    ]

class BlogPage(Page):
    """Blog page with category relationship."""
    category = models.ForeignKey(
        BlogCategory,
        on_delete=models.SET_NULL,
        null=True,
        blank=True
    )
    body = models.TextField()
    
    # Search through related fields
    search_fields = Page.search_fields + [
        index.SearchField('body'),
        index.RelatedFields('category', [
            index.SearchField('name', boost=2),
            index.SearchField('description'),
        ]),
    ]

# Search will now find pages by category name/description
results = BlogPage.objects.search('python')  # Finds pages in "Python" category

# settings.py
WAGTAILSEARCH_BACKENDS = {
    'default': {
        'BACKEND': 'wagtail.search.backends.database',
        'SEARCH_CONFIG': 'english',  # PostgreSQL text search config
    },
    'elasticsearch': {
        'BACKEND': 'wagtail.search.backends.elasticsearch7',
        'URLS': ['http://localhost:9200'],
        'INDEX': 'wagtail',
        'TIMEOUT': 5,
        'OPTIONS': {},
        'INDEX_SETTINGS': {
            'settings': {
                'analysis': {
                    'analyzer': {
                        'ngram_analyzer': {
                            'tokenizer': 'ngram_tokenizer',
                        }
                    }
                }
            }
        }
    }
}

# Use specific backend
from wagtail.search.backends import get_search_backend

elasticsearch = get_search_backend('elasticsearch')
database = get_search_backend('default')

# Backend-specific search
es_results = elasticsearch.search('query', MyModel)
db_results = database.search('query', MyModel)

# Management commands for search index
from django.core.management import call_command

# Rebuild entire search index
call_command('update_index')

# Update specific model
call_command('update_index', 'blog.BlogPage')

# Clear search index
call_command('clear_index')

# Programmatic index updates
from wagtail.search.signal_handlers import post_save_signal_handler
from wagtail.search import index

# Manual index update
page = BlogPage.objects.get(pk=1)
index.insert_or_update_object(page)

# Remove from index
index.remove_object(page)

# Bulk index operations
pages = BlogPage.objects.all()
for page in pages:
    index.insert_or_update_object(page)