import logging
from datetime import datetime
from pathlib import Path
import pandas as pd

import pdfplumber

from pdf_oralia.pages import charge, locataire, patrimoine

extract_table_settings = {
    "vertical_strategy": "lines",
    "horizontal_strategy": "text",
}


def extract_date(page_text):
    """Extract date from a page

    :param page_text: text in the page
    :return: the extracted date
    """
    blocs = page_text.split("\n")
    for b in blocs:
        if "Lyon le" in b:
            words = b.split(" ")
            return datetime.strptime(words[-1], "%d/%m/%Y")


def extract_building(page_text, buildings=["bloch", "marietton", "servient"]):
    for building in buildings:
        if building in page_text.lower():
            return building
    raise ValueError("Pas d'immeuble trouvé")


def pdf_extract_tables_lines(pdf):
    loc_sink = locataire.fsm()
    next(loc_sink)
    charge_sink = charge.fsm()
    next(charge_sink)
    patrimoine_sink = patrimoine.fsm()
    next(patrimoine_sink)

    page_number = 1
    for page in pdf.pages:
        page_text = page.extract_text()
        date = extract_date(page_text)
        additionnal_fields = {
            "immeuble": extract_building(page_text),
            "mois": date.strftime("%m"),
            "annee": date.strftime("%Y"),
        }
        table_type = ""
        if locataire.is_it(page_text):
            table_type = "locataire"
        elif charge.is_it(page_text):
            table_type = "charge"
        elif patrimoine.is_it(page_text):
            table_type = "patrimoine"
        else:
            logging.warning(f"Page {page_number} non reconnu. Page ignorée.")

        for line in page.extract_table(extract_table_settings):
            if table_type == "locataire":
                res = loc_sink.send(line)
                if res:
                    res.update(additionnal_fields)
                    yield locataire.Line(**res)
            elif table_type == "charge":
                res = charge_sink.send(line)
                if res:
                    res.update(additionnal_fields)
                    yield charge.Line(**res)

            elif table_type == "patrimoine":
                res = patrimoine_sink.send(line)
                if res:
                    res.update(additionnal_fields)
                    yield patrimoine.Line(**res)

        page_number += 1


def from_pdf(pdf_file):
    """Build dataframes one about charges and another on loc"""
    pdf = pdfplumber.open(pdf_file)
    locataire_lines = []
    charge_lines = []
    patrimoine_lines = []
    for line in pdf_extract_tables_lines(pdf):
        if isinstance(line, locataire.Line):
            locataire_lines.append(line)
        elif isinstance(line, charge.Line):
            charge_lines.append(line)
        elif isinstance(line, patrimoine.Line):
            patrimoine_lines.append(line)
        else:
            logging.warning(f"Page {page_number+1} non reconnu. Page ignorée.")

    return (
        pd.DataFrame([c.__dict__ for c in charge_lines]),
        pd.DataFrame([c.__dict__ for c in locataire_lines]),
        pd.DataFrame([c.__dict__ for c in patrimoine_lines]),
    )


def extract_save(pdf_file, dest):
    """Extract charge and locataire for pdf_file and put xlsx file in dest"""
    pdf_file = Path(pdf_file)
    xls_charge = Path(dest) / f"{pdf_file.stem.replace(' ', '_')}_charge.xlsx"
    xls_locataire = Path(dest) / f"{pdf_file.stem.replace(' ', '_')}_locataire.xlsx"
    xls_patrimoine = Path(dest) / f"{pdf_file.stem.replace(' ', '_')}_patrimoine.xlsx"

    df_charge, df_loc, df_patrimoine = from_pdf(pdf_file)

    df_charge.to_excel(xls_charge, sheet_name="Charges", index=False)
    logging.info(f"{xls_charge} saved")
    df_loc.to_excel(xls_locataire, sheet_name="Location", index=False)
    logging.info(f"{xls_locataire} saved")
    df_patrimoine.to_excel(xls_patrimoine, sheet_name="Patrimoine", index=False)
    logging.info(f"{xls_patrimoine} saved")