import string from django.db.models import QuerySet from search.models import ( Product, Characteristic, ProductCharacteristic, ProductUnitCharacteristic, UnitCharacteristic, Category, ) from typing import List from search.services.hints import get_hints from search.services.spell_check import spell_check_ru as spell_check def process_unit_operation(unit: ProductUnitCharacteristic.objects, operation: str): if operation.startswith("<=") or operation.startswith("=<"): return unit.filter( characteristic__numeric_value_max__lte=int(float(operation[2:])) ) elif operation.startswith("=>") or operation.startswith(">="): return unit.filter( characteristic__numeric_value_min__gte=int(float(operation[2:])) ) elif operation.startswith(">"): return unit.filter( characteristic__numeric_value_min__gt=int(float(operation[1:])) ) elif operation.startswith("<"): return unit.filter( characteristic__numeric_value_max__lt=int(float(operation[1:])) ) elif operation.startswith("="): return unit.filter( characteristic__numeric_value_min__gte=int(float(operation[1:])), characteristic__numeric_value_max__lte=int(float(operation[1:])), ) return unit def _clean_text(text: str) -> List[str]: for st in [".", ",", "!", "?"]: text = text.replace(st, " ") text = text.split() return text def apply_qs_search(qs: Product.objects, text: str): text = _clean_text(text) words = Product.objects.none() for word in text: words = ( words | Product.objects.filter(name__unaccent__trigram_similar=word) | Product.objects.filter(name__unaccent__icontains=word) ) print(words) qs = qs | words print(qs) return qs def apply_all_qs_search(orig_qs, text: str): # words qs = apply_qs_search(Product.objects.none(), text) text = _clean_text(text) # categories cats = Category.objects.none() for word in text: cats = cats | cats.filter(name__icontains=word) qs = qs | Product.objects.filter(category__in=cats) # characteristics chars = Characteristic.objects.none() for word in text: chars = chars | chars.filter( value__icontains=word, ) qs = qs | Product.objects.filter(characteristics__characteristic__in=chars) # print(qs) return qs & orig_qs def process_search(data: List[dict], limit=5, offset=0) -> List[dict]: prep_data = [] prep_dict = {} prep_dict_char_type = {} # --------------------------------------- prepare filters -------------------------------------------------------- # for x in data: dat = dict(x) if x["type"] in ["Name", "Category", "Characteristic", "All"]: prep_data.append( { "type": dat["type"], "value": spell_check( dat["value"], ), } ) elif x["type"] == "Unknown": type = get_hints(dat["value"]) prep_data.append( { "type": type, "value": spell_check( dat["value"], ), } ) else: val = spell_check( dat["value"], ) if x["type"] in list(prep_dict.keys()): if x["type"].startswith("*"): unit = ProductUnitCharacteristic.objects.filter( characteristic__in=prep_dict_char_type[x["type"]], ) prep_dict[x["type"]] = prep_dict[ x["type"] ] | process_unit_operation(unit, x["value"]) else: prep_dict[x["type"]] = ( prep_dict[x["type"]] | ProductCharacteristic.objects.filter( characteristic__in=prep_dict_char_type[x["type"]], characteristic__value__unaccent__trigram_similar=val, ) | ProductCharacteristic.objects.filter( characteristic__in=prep_dict_char_type[x["type"]], characteristic__value__icontains=val, ) ) else: if x["type"].startswith("*"): prep_dict_char_type[x["type"]] = UnitCharacteristic.objects.filter( name__unaccent__trigram_similar=x["type"] ) | UnitCharacteristic.objects.filter(name__icontains=x["type"]) unit = ProductUnitCharacteristic.objects.filter( characteristic__in=prep_dict_char_type[x["type"]], ) prep_dict[x["type"]] = process_unit_operation(unit, x["value"]) else: prep_dict_char_type[x["type"]] = Characteristic.objects.filter( name__unaccent__trigram_similar=x["type"] ) | Characteristic.objects.filter(name__icontains=x["type"]) prep_dict[x["type"]] = ProductCharacteristic.objects.filter( characteristic__in=prep_dict_char_type[x["type"]], characteristic__value__unaccent__trigram_similar=val, ) | ProductCharacteristic.objects.filter( characteristic__in=prep_dict_char_type[x["type"]], characteristic__value__icontains=val, ) for el, val in prep_dict.items(): prep_data.append({"type": el, "value": val}) # ----------------------------------- apply filters on QuerySet -------------------------------------------------- # qs = Product.objects.filter() for x in prep_data: typ = x["type"] val = x["value"] if typ == "Name": qs = apply_qs_search(qs, val) elif typ == "All": qs = apply_all_qs_search(qs, val) elif typ == "Category": qs = qs.filter(category__name__unaccent__trigram_similar=val) | qs.filter( category__name__icontains=val ) elif typ == "Characteristic": char = ProductCharacteristic.objects.filter(product__in=qs) char = char.filter(characteristic__value__icontains=val) | char.filter( characteristic__value__unaccent__trigram_similar=val ) qs = qs.filter(characteristics__in=char) elif typ == "Unknown": continue else: if typ.startswith("*"): qs = qs.filter(unit_characteristics__in=val) else: qs = qs.filter(characteristics__in=val) return [ x.serialize_self() for x in qs.distinct().order_by("-score")[offset : offset + limit] ]