from __future__ import annotations

import re
from collections.abc import Sequence

import pandas as pd

from .classifier import CLASSES, address_classification
from .utils import any_of_in, create_token, is_valid_token, unfold_house_ranges


class AddressSplitter(Sequence):
    def __init__(self, address: str):
        self.input = address

        self.addresses = self.split()

    # Sequence abstract methods implementation

    def __getitem__(self, key: int):
        if key < len(self.addresses):
            return self.addresses[key]
        else:
            raise IndexError()

    def __len__(self):
        return len(self.addresses)

    # Address token class manipulations

    def next_class(self) -> str:
        return self.token["class"][0]

    def prev_class(self) -> str:
        return self.accumulator["class"][-1]

    def correct_order(self) -> bool:
        return (
            len(self.accumulator["class"]) > 0
            and CLASSES.index(self.prev_class()) < CLASSES.index(self.next_class())
            and self.accumulator["class"] != "w"
        )

    def next_class_is(self, comparing_class: str) -> bool:
        return len(self.token["class"]) > 0 and self.next_class() == comparing_class[0]

    def has_no_class(self, comparing_class: str) -> bool:
        return comparing_class[0] not in self.accumulator["class"]

    def pop_token_class(self):
        self.token["class"] = self.token["class"][1:]

    # Accumulator constrains

    def next_is_street_or_upper(self) -> bool:
        is_unknown_class = self.accumulator["class"] in ("", "w")

        return (
            CLASSES.index(self.next_class()) <= CLASSES.index("s") or is_unknown_class
        )

    def has_numbered_street(self) -> bool:
        return any_of_in(("-я", "-й", "-Я"), self.accumulator["address"])

    # Accumulator manipulation

    ## House

    def substitue_house(self) -> str:
        house_regex = re.compile(r"\d{1,4} ?[\/\-]?\d* ?")

        number = house_regex.findall(self.token["obj"])[0]

        if self.has_numbered_street():
            house_number_index = 1
        else:
            house_number_index = 0

        number_in_accumulator = house_regex.findall(self.accumulator["address"])

        if number_in_accumulator:
            return re.sub(
                number_in_accumulator[house_number_index],
                number,
                self.accumulator["address"],
            )
        else:
            return self.accumulator["address"]

    ## Building

    def append_building(self, number: int) -> pd.Series:
        self.accumulator["class"] += "b"
        self.accumulator["address"] += "к." + number

        return self.accumulator

    def substitue_building(self, number: int) -> str:
        return re.sub(r"\d$", number, self.accumulator["address"])

    def insert_building(self):
        number = re.findall(r"\d", self.token["obj"])[-1]

        if number and self.has_no_class("building"):
            self.accumulator = self.append_building(number)
        else:
            self.accumulator["address"] = self.substitue_building(number)

    ## Edifice

    def substitue_edifice(self, number: int) -> str:
        return re.sub(r"cтр\. ?\d", number, self.accumulator["address"].strip())

    def insert_edifice(self):
        number = re.findall("стр\.? ?\d", self.token["obj"])[-1]

        self.accumulator["address"] = self.substitue_edifice(number)

        if number and self.has_no_class("edifice"):
            self.accumulator["class"] += "e"

    ## Letter

    def without_letter(self) -> str:
        return re.sub(r"[А-Яа-я]$", "", self.accumulator["address"].strip())

    def substitue_letter(self, letter: str) -> str:
        address_without_letter = self.without_letter()

        return address_without_letter + letter

    def insert_letter(self):
        letter = re.findall(r"[А-Яа-я]", self.token["obj"])[-1]
        self.accumulator["address"] = self.substitue_letter(letter)

        if letter and self.has_no_class("litera"):
            self.accumulator["class"] += "l"

    def has_letter_in(self) -> bool:
        return re.search(r"\d{1,3}([А-Я]|[а-я])( |$)", self.accumulator["address"])

    ## Room

    def substitue_room(self, number: int) -> str:
        return re.sub(
            r"пом\. ?\d\-?\d*\w?", number, self.accumulator["address"].strip()
        )

    def insert_room(self):
        number = re.findall("пом\. ?\-?\d*\w?", self.token["obj"])[-1]
        self.accumulator["address"] = self.substitue_room(number)

        if number and self.has_no_class("room"):
            self.accumulator["class"] += "r"

    # Data preprocessing

    def split_tokens(self) -> list[pd.Series]:
        address = self.input.replace(";", ",")

        parts = address.split(",")
        parts = map(str.strip, parts)
        parts = filter(is_valid_token, parts)

        tokens = map(lambda part: create_token(part, ""), parts)

        return list(tokens)

    def cut_address(self) -> pd.Series:
        while len(self.accumulator["class"]) > 0 and CLASSES.index(
            self.prev_class()
        ) > CLASSES.index(self.next_class()):
            match self.accumulator["class"][-1]:
                case "h":
                    self.accumulator["addresses"] = re.sub(
                        r"[мкдтпучасток]*\.? ?\d{1,4} ?\/*\d* ?",
                        "",
                        self.accumulator["address"].lower(),
                    )
                case "b":
                    number = re.findall(r"к{0,1}\.? ?\d", self.accumulator["address"])[
                        -1
                    ]
                    self.accumulator["address"] = re.sub(
                        number, "", self.accumulator["address"]
                    )
                case "e":
                    self.accumulator["address"] = re.sub(
                        r"cтр\.? ?\d", "", self.accumulator["address"]
                    )
                case "l":
                    self.accumulator["address"] = re.sub(
                        r"[литера]*\.? ?[А-Яа-я]{1}$", "", self.accumulator["address"]
                    )
                case "r":
                    self.accumulator["address"] = re.sub(
                        r"пом\.? ?\d+", "", self.accumulator["address"]
                    )

            self.accumulator["class"] = self.accumulator["class"][:-1]

        return self.accumulator

    # Splitting

    def split(self):
        self.tokens = self.split_tokens()

        result = []

        self.accumulator = pd.Series({"address": "", "class": ""})

        prev_token = create_token()

        for cursor in self.tokens:
            self.token = address_classification(cursor, prev_token)
            prev_token = self.token.copy()

            if self.accumulator["class"] == "":
                self.accumulator = self.token.rename({"obj": "address"})
                continue

            if self.correct_order():
                self.accumulator["address"] += " "
                self.accumulator += self.token.rename({"obj": "address"})
            else:
                unfolded_address = unfold_house_ranges(self.accumulator["address"])
                self.accumulator["address"] = unfolded_address[-1]

                result.extend(unfolded_address)

                self.accumulator = self.cut_address()

                if self.next_is_street_or_upper():
                    self.accumulator = self.token.rename({"obj": "address"})

                if self.next_class_is("house"):
                    self.accumulator["address"] = self.substitue_house()
                    self.pop_token_class()

                if self.next_class_is("building"):
                    self.insert_building()
                    self.pop_token_class()

                if self.next_class_is("edifice"):
                    self.insert_edifice()
                    self.pop_token_class()

                if self.next_class_is("letter"):
                    self.insert_letter()
                elif self.has_letter_in():
                    self.accumulator["address"] = self.without_letter()

                if self.next_class_is("room"):
                    self.insert_room()
                    self.pop_token_class()

        result.extend(unfold_house_ranges(self.accumulator["address"]))

        return result


def split_pesoch_res(address: str) -> list[str]:
    t = re.sub(r",", " ", address)
    t = re.split(r"(Санкт-Петербург|Ленинградская обл|Л\.О)", t)
    t = list(map(str.strip, filter(lambda token: token != "", t)))
    tokens = [t[i] + " " + t[i + 1] for i in range(0, len(t) - 1, 2)]

    if tokens:
        return list(set(tokens))
    return [address]


def process_row(row: pd.Series[str]) -> pd.Series[str]:
    row = row.copy()

    if pd.isnull(row["Улица"]):
        row["Улица"] = [None]
    else:
        if row["РЭС"] == "Песочинский РЭС":
            addresses = split_pesoch_res(row["Улица"])
        else:
            addresses = AddressSplitter(row["Улица"])
        row["Улица"] = addresses

    return row


def split_addresses(df: pd.DataFrame) -> pd.DataFrame:
    merged_df = df.apply(process_row, axis=1).reset_index()

    return merged_df.explode("Улица", ignore_index=True)