# 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
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

# Standard imports
import logging
import uuid

# External imports
from io import StringIO

import pandas as pd
from unstructured.partition.pdf import partition_pdf


class Unstructured:
    def __init__(self, **kwargs: dict) -> dict:
        """
        Builds a pdf page parser, looking for tables using
        the unstructured library.
        The kwargs given to the constructor are directly propagated
        to the partition_pdf function.
        You are free to define any parameter partition_pdf recognizes
        """
        self.kwargs = kwargs
        self.type = "unstructured"

    def __call__(self, pdf_filepath: str) -> dict:
        logging.info("\nKicking off extraction stage...")
        logging.info(f"Extraction type: {self.type}, with params: {self.kwargs}")

        elements = partition_pdf(
            pdf_filepath,
            infer_table_structure=True,
            strategy="hi_res",
            **self.kwargs,
        )
        tables_list = [el for el in elements if el.category == "Table"]
        tables_list = [
            pd.read_html(StringIO(t.metadata.text_as_html))[0] for t in tables_list
        ]

        # Create asset
        new_asset = {
            "id": uuid.uuid4(),
            "type": "unstructured",
            "params": self.kwargs,
            "tables": tables_list,
        }

        return new_asset