# encoding: utf-8
from django.utils.datetime_safe import datetime

from haystack.constants import DJANGO_CT, DJANGO_ID, ID
from haystack.exceptions import MissingDependency, SearchBackendError, SkipDocument
from haystack.models import SearchResult
from haystack.utils.app_loading import haystack_get_model
from haystack.backends.whoosh_backend import (WhooshHtmlFormatter,
                                              WhooshSearchBackend,
                                              WhooshEngine) # fixed

from whoosh.fields import ID as WHOOSH_ID
from whoosh.fields import BOOLEAN, DATETIME, IDLIST, KEYWORD, NGRAM, NGRAMWORDS, NUMERIC, Schema, TEXT
from whoosh.highlight import highlight as whoosh_highlight
from whoosh.highlight import ContextFragmenter, HtmlFormatter
from whoosh.analysis.analyzers import LanguageAnalyzer # fixed


# fixes: allow to customize analyzer for whoosh indexer
#        code of build_schema and _process_results methods completely taken
#        from haystack except lines marked "# fixed" comment
#        get_analyzer method created for extending and should return
#        any custom analyzer

class CustomAnalyzerWhooshSearchBackend(WhooshSearchBackend):
    def get_analyzer(self):
        # note: extend it to set custom analyzer
        raise NotImplementedError('No analyzer defined')

    def build_schema(self, fields):
        schema_fields = {
            ID: WHOOSH_ID(stored=True, unique=True),
            DJANGO_CT: WHOOSH_ID(stored=True),
            DJANGO_ID: WHOOSH_ID(stored=True),
        }
        # Grab the number of keys that are hard-coded into Haystack.
        # We'll use this to (possibly) fail slightly more gracefully later.
        initial_key_count = len(schema_fields)
        content_field_name = ''

        for field_name, field_class in fields.items():
            if field_class.is_multivalued:
                if field_class.indexed is False:
                    schema_fields[field_class.index_fieldname] = IDLIST(stored=True, field_boost=field_class.boost)
                else:
                    schema_fields[field_class.index_fieldname] = KEYWORD(stored=True, commas=True, scorable=True, field_boost=field_class.boost)
            elif field_class.field_type in ['date', 'datetime']:
                schema_fields[field_class.index_fieldname] = DATETIME(stored=field_class.stored, sortable=True)
            elif field_class.field_type == 'integer':
                schema_fields[field_class.index_fieldname] = NUMERIC(stored=field_class.stored, numtype=int, field_boost=field_class.boost)
            elif field_class.field_type == 'float':
                schema_fields[field_class.index_fieldname] = NUMERIC(stored=field_class.stored, numtype=float, field_boost=field_class.boost)
            elif field_class.field_type == 'boolean':
                # Field boost isn't supported on BOOLEAN as of 1.8.2.
                schema_fields[field_class.index_fieldname] = BOOLEAN(stored=field_class.stored)
            elif field_class.field_type == 'ngram':
                schema_fields[field_class.index_fieldname] = NGRAM(minsize=3, maxsize=15, stored=field_class.stored, field_boost=field_class.boost)
            elif field_class.field_type == 'edge_ngram':
                schema_fields[field_class.index_fieldname] = NGRAMWORDS(minsize=2, maxsize=15, at='start', stored=field_class.stored, field_boost=field_class.boost)
            else:
                schema_fields[field_class.index_fieldname] = TEXT(stored=True, analyzer=self.get_analyzer(), field_boost=field_class.boost, sortable=True) # fixed

            if field_class.document is True:
                content_field_name = field_class.index_fieldname
                schema_fields[field_class.index_fieldname].spelling = True

        # Fail more gracefully than relying on the backend to die if no fields
        # are found.
        if len(schema_fields) <= initial_key_count:
            raise SearchBackendError("No fields were found in any search_indexes. Please correct this before attempting to search.")

        return (content_field_name, Schema(**schema_fields))

    def _process_results(self, raw_page, highlight=False, query_string='', spelling_query=None, result_class=None):
        from haystack import connections
        results = []

        # It's important to grab the hits first before slicing. Otherwise, this
        # can cause pagination failures.
        hits = len(raw_page)

        if result_class is None:
            result_class = SearchResult

        facets = {}
        spelling_suggestion = None
        unified_index = connections[self.connection_alias].get_unified_index()
        indexed_models = unified_index.get_indexed_models()

        for doc_offset, raw_result in enumerate(raw_page):
            score = raw_page.score(doc_offset) or 0
            app_label, model_name = raw_result[DJANGO_CT].split('.')
            additional_fields = {}
            model = haystack_get_model(app_label, model_name)

            if model and model in indexed_models:
                for key, value in raw_result.items():
                    index = unified_index.get_index(model)
                    string_key = str(key)

                    if string_key in index.fields and hasattr(index.fields[string_key], 'convert'):
                        # Special-cased due to the nature of KEYWORD fields.
                        if index.fields[string_key].is_multivalued:
                            if value is None or len(value) is 0:
                                additional_fields[string_key] = []
                            else:
                                additional_fields[string_key] = value.split(',')
                        else:
                            additional_fields[string_key] = index.fields[string_key].convert(value)
                    else:
                        additional_fields[string_key] = self._to_python(value)

                del(additional_fields[DJANGO_CT])
                del(additional_fields[DJANGO_ID])

                if highlight:
                    sa = self.get_analyzer() # fixed
                    formatter = WhooshHtmlFormatter('em')
                    terms = [token.text for token in sa(query_string)]

                    whoosh_result = whoosh_highlight(
                        additional_fields.get(self.content_field_name),
                        terms,
                        sa,
                        ContextFragmenter(),
                        formatter
                    )
                    additional_fields['highlighted'] = {
                        self.content_field_name: [whoosh_result],
                    }

                result = result_class(app_label, model_name, raw_result[DJANGO_ID], score, **additional_fields)
                results.append(result)
            else:
                hits -= 1

        if self.include_spelling:
            if spelling_query:
                spelling_suggestion = self.create_spelling_suggestion(spelling_query)
            else:
                spelling_suggestion = self.create_spelling_suggestion(query_string)

        return {
            'results': results,
            'hits': hits,
            'facets': facets,
            'spelling_suggestion': spelling_suggestion,
        }


# sample usage
class RussianAnalyzerWhooshSearchBackend(CustomAnalyzerWhooshSearchBackend):
    def get_analyzer(self):
        return LanguageAnalyzer('ru')


class CustomAnalyzerWhooshEngine(WhooshEngine):
    backend = RussianAnalyzerWhooshSearchBackend