# MIT License
#
# Copyright (c) 2024 dataforgood
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

# Standard imports
import logging

# Local imports
from . import pagefilter, table_extraction
from .utils.utils import keep_pages


class ReportProcessor:
    def __init__(self, config: dict) -> None:
        # Report filter
        self.page_filter = pagefilter.from_config(config["pagefilter"])

        self.table_extractors = []
        self.table_cleaners = []

        # Tables extraction
        if "table_extraction" in config:
            table_extractors = config["table_extraction"]
            self.table_extractors = [
                table_extraction.from_config(name) for name in table_extractors
            ]

            # Table cleaning & reformatting
            # We can do this step only if we had table extraction algorithms
            # otherwise, the assets will not be available
            #if "table_cleaning" in config:
            #    table_cleaners = config["table_cleaning"]
            #    self.table_cleaners = [
            #        table_cleaning.from_config(name) for name in table_cleaners
            #    ]

    def process(self, pdf_filepath: str) -> dict:
        logging.info(f"Processing {pdf_filepath}")

        assets = {
            "pagefilter": {},
            "table_extractors": [],
            "table_cleaners": [],
        }

        # Identifying the pages to extract
        self.page_filter(pdf_filepath, assets)

        # Now that we identified the pages to be extracted, we extract them
        # Note, in a GUI, we could ask the user to the change the content of
        # assets["pagefilter"]["selected_pages"] before selecting the pages
        pdf_to_process = keep_pages(
            pdf_filepath,
            assets["pagefilter"]["selected_pages"],
        )

        # Process the selected pages to detect the tables and extract
        # their contents
        for table_extractor in self.table_extractors:
            new_asset = table_extractor(pdf_to_process)
            assets["table_extractors"].append(new_asset)

        # Give the parsed content to the cleaner stage for getting organized data
        #for table_cleaner in self.table_cleaners:
        #    for asset in assets["table_extractors"]:
        #        new_asset = table_cleaner(asset)
        #        assets["table_cleaners"].append(new_asset)

        return assets