backend/app/search/services/search.py

127 lines
5.1 KiB
Python

import string
from search.models import (
Product,
Characteristic,
ProductCharacteristic,
ProductUnitCharacteristic,
UnitCharacteristic,
)
from typing import List
from search.services.hints import get_hints
from search.services.spell_check import spell_check
from search.services.translate import translate_en_ru, translate_ru_en
def process_unit_operation(unit: ProductUnitCharacteristic.objects, operation: str):
if operation.startswith("<=") or operation.startswith("=<"):
return unit.filter(characteristic__numeric_value__lte=int(float(operation[2:])))
elif operation.startswith("=>") or operation.startswith(">="):
return unit.filter(characteristic__numeric_value__gte=int(float(operation[2:])))
elif operation.startswith(">"):
return unit.filter(characteristic__numeric_value__gt=int(float(operation[1:])))
elif operation.startswith("<"):
return unit.filter(characteristic__numeric_value__lt=int(float(operation[1:])))
elif operation.startswith("="):
return unit.filter(characteristic__numeric_value=int(float(operation[1:])))
return unit
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"]:
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,
)
else:
if x["type"].startswith("*"):
prep_dict_char_type[x["type"]] = UnitCharacteristic.objects.filter(
name__unaccent__trigram_similar=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"]
)
prep_dict[x["type"]] = ProductCharacteristic.objects.filter(
characteristic__in=prep_dict_char_type[x["type"]],
characteristic__value__unaccent__trigram_similar=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 = qs.filter(name__unaccent__trigram_similar=val)
elif typ == "Category":
qs = qs.filter(category__name__unaccent__trigram_similar=val)
elif typ == "Unknown":
if val[0] in string.printable:
val = "".join(translate_en_ru(val))
else:
val = "".join(translate_ru_en(val))
type = get_hints(val)
if type == "Name":
qs = qs.filter(name__unaccent__trigram_similar=val)
elif type == "Category":
qs = qs.filter(category__name__unaccent__trigram_similar=val)
elif type == "Unknown":
continue
else:
qs = qs.filter(
characteristics__characteristic__name__unaccent__trigram_similar=val
)
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[offset : offset + limit]]