country_by_country/table_extraction/from_csv.py

# 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
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# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
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# The above copyright notice and this permission notice shall be included in all
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# SOFTWARE.

# Standard imports
import glob
import uuid
from pathlib import Path

# External imports
import pandas as pd


class FromCSV:
    def __init__(self, csv_directory: str) -> None:
        self.csv_directory = csv_directory

    def __call__(self, pdf_filepath: str) -> dict:
        """
        Returns asset that contain:

        """
        # Load the tables from matching csv files
        # Given a report /path/to/{company_name}_{year}*.pdf
        # Tables are searched in /csv_directory/{company_name}_{year}*.csv
        report_basename = "_".join(Path(pdf_filepath).stem.split("_")[0:2])
        tables_files = glob.glob(f"{self.csv_directory}/{report_basename}*.csv")
        tables_list = [pd.read_csv(f) for f in tables_files]

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

        return new_asset