import pandas as pd
from docx import Document
from dataclasses import dataclass
import sys
from loguru import logger as log

logger = log
logger.remove()
logger.add("logs/wordparser.log", rotation="1 week", enqueue=True)
log.add(
    f"logs/application.log",
    rotation="1 day",
    compression="zip",
    enqueue=True,
)

# logger.add(sys.stderr, format="{time} {level} {message}", level="INFO")
logger.add(sys.stdout)


letters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"


@dataclass
class Book:
    author: str = None
    year: str = None
    edition: str = None
    title: str = None
    location: str = None
    publisher: str = None
    signature: str = None
    internal_notes: str = None

    @property
    def has_signature(self) -> bool:
        return self.signature is not None and self.signature != ""

    @property
    def is_empty(self) -> bool:
        return all(
            [
                self.author == "",
                self.year == "",
                self.edition == "",
                self.title == "",
                self.location == "",
                self.publisher == "",
                self.signature == "",
                self.internal_notes == "",
            ]
        )

    def from_dict(self, data: dict):
        for key, value in data.items():
            if value == "\u2002\u2002\u2002\u2002\u2002":
                value = ""

            if key == "Autorenname(n):Nachname, Vorname":
                self.author = value
            elif key == "Jahr/Auflage":
                self.year = value.split("/")[0] if "/" in value else value
                self.edition = value.split("/")[1] if "/" in value else ""
            elif key == "Titel":
                self.title = value
            elif key == "Ort und Verlag":
                self.location = value.split(",")[0] if "," in value else value
                self.publisher = value.split(",")[1] if "," in value else ""
            elif key == "Standnummer":
                self.signature = value
            elif key == "Interne Vermerke":
                self.internal_notes = value


@dataclass
class SemapDocument:
    subject: str = None
    phoneNumber: int = None
    mail: str = None
    title: str = None
    semester: str = None
    books: list[Book] = None

    @property
    def renameSemester(self) -> None:
        if self.semester is not None:
            if "sommersemester" in self.semester.lower():
                year = self.semester.split(" ")[-1]
                self.semester = f"SoSe {year}"
            elif "wintersemester" in self.semester.lower():
                year = self.semester.split(" ")[-1]
                self.semester = f"WiSe {year}"

    @property
    def signatures(self) -> list[str]:
        if self.books is not None:
            return [book.signature for book in self.books if book.has_signature]
        return []


def word_docx_to_csv(path: str) -> list[pd.DataFrame]:
    doc = Document(path)
    tables = doc.tables
    m_data = []
    for table in tables:
        data = []
        for row in table.rows:
            row_data = []
            for cell in row.cells:
                text = cell.text
                text = text.replace("\n", "")
                row_data.append(text)
            data.append(row_data)
        df = pd.DataFrame(data)
        df.columns = df.iloc[0]
        df = df.iloc[1:]

        m_data.append(df)

    # for df[0, 1]: merge i and i+1 as key, value

    return m_data


def makeDict():
    return {
        "work_author": None,
        "section_author": None,
        "year": None,
        "edition": None,
        "work_title": None,
        "chapter_title": None,
        "location": None,
        "publisher": None,
        "signature": None,
        "issue": None,
        "pages": None,
        "isbn": None,
        "type": None,
    }


def tuple_to_dict(tlist: tuple, type: str) -> dict:
    ret = []
    for line in tlist:
        data = makeDict()
        if type == "Monografien":
            data["type"] = type
            data["work_author"] = line[0]
            data["year"] = line[1]
            data["edition"] = line[2]
            data["work_title"] = line[3]
            data["location"] = line[4]
            data["publisher"] = line[5]
            data["signature"] = line[6]
            data["pages"] = line[7]
        elif type == "Herausgeberwerke":
            data["type"] = type
            data["section_author"] = line[0]
            data["year"] = line[1]
            data["edition"] = line[2]
            data["chapter_title"] = line[3]
            data["work_author"] = line[4]
            data["work_title"] = line[5]
            data["location"] = line[6]
            data["publisher"] = line[7]
            data["signature"] = line[9]
            data["pages"] = line[8]
        elif type == "Zeitschriftenaufsätze":
            data["type"] = type
            data["section_author"] = line[0]
            data["year"] = line[1]
            data["issue"] = line[2]
            data["chapter_title"] = line[3]
            data["work_title"] = line[4]
            data["location"] = line[5]
            data["publisher"] = line[6]
            data["signature"] = line[8]
            data["pages"] = line[7]
        ret.append(data)
    return ret


def elsa_word_to_csv(path):
    doc = Document(path)
    # # print all lines in doc
    doctype = [para.text for para in doc.paragraphs if para.text != ""][-1]
    tuples = {
        "Monografien": ("", "", "", "", "", "", "", "", ""),
        "Herausgeberwerke": ("", "", "", "", "", "", "", "", "", "", ""),
        "Zeitschriftenaufsätze": ("", "", "", "", "", "", "", "", "", ""),
    }
    tables = doc.tables

    m_data = []
    for table in tables:
        data = []
        for row in table.rows:
            row_data = []
            for cell in row.cells:
                text = cell.text
                text = text.replace("\n", "")
                text = text.replace("\u2002", "")
                row_data.append(text)
            data.append(row_data)
            df = pd.DataFrame(data)
        df.columns = df.iloc[0]
        df = df.iloc[1:]
        m_data.append(df)
    df = m_data[0]
    # split df to rows
    data = [
        row for row in df.itertuples(index=False, name=None) if row != tuples[doctype]
    ]
    # print(data)
    return tuple_to_dict(data, doctype), doctype


def word_to_semap(word_path: str) -> SemapDocument:
    logger.info("Parsing Word Document {}", word_path)
    semap = SemapDocument()
    df = word_docx_to_csv(word_path)
    apparatdata = df[0]
    apparatdata = apparatdata.to_dict()
    keys = list(apparatdata.keys())
    appdata = {keys[i]: keys[i + 1] for i in range(0, len(keys), 2)}
    semap.phoneNumber = appdata["Telefon:"]
    semap.subject = appdata["Ihr Fach:"]
    semap.mail = appdata["Mailadresse:"]
    apparatdata = df[1]
    apparatdata = apparatdata.to_dict()
    keys = list(apparatdata.keys())
    appdata = {keys[i]: keys[i + 1] for i in range(0, len(keys), 2)}
    semap.title = appdata["Veranstaltung:"]
    semap.semester = appdata["Semester:"]
    semap.renameSemester
    books = df[2]
    booklist = []
    for i in range(len(books)):
        if books.iloc[i].isnull().all():
            continue
        data = books.iloc[i].to_dict()
        book = Book()
        book.from_dict(data)
        if book.is_empty:
            continue
        elif not book.has_signature:
            continue
        else:
            booklist.append(book)
    logger.info("Found {} books", len(booklist))
    semap.books = booklist

    return semap


if __name__ == "__main__":
    else_df = word_to_semap(
        "C:/Users/aky547/Desktop/SA 80 titelmeldung_SoSe2025 Burth.docx"
    )