FAOSTAT_data_primap/scripts/download_all_domains.py

"""Downloads all domain data sets from FAOSTAT website."""


from faostat_data_primap.download import (
    download_all_domains,
)

# def download_all_domains(
#     domains: list[tuple[str]] = domains,
#     downloaded_data_path: str = downloaded_data_path,
# ) -> list[str]:
#     """
#     Download and unpack all climate-related domains from the FAO stat website.
#
#     Extract the date when the data set was last updated and create a directory
#     with the same name. Download the zip files for each domain if
#     it does not already exist. Unpack the zip file and save in
#     the same directory.
#
#     Parameters
#     ----------
#     sources
#         Name of data set, url to domain overview,
#         and download url
#
#     Returns
#     -------
#         List of input files that have been fetched or found locally.
#
#     """
#     downloaded_files = []
#     for ds_name, urls in domains.items():
#         url = urls["url_domain"]
#         url_download = urls["url_download"]
#         url_methodology = urls["url_methodology"]
#
#         soup = get_html_content(url)
#
#         last_updated = get_last_updated_date(soup, url)
#
#         if not downloaded_data_path.exists():
#             downloaded_data_path.mkdir()
#
#         ds_path = downloaded_data_path / ds_name
#         if not ds_path.exists():
#             ds_path.mkdir()
#
#         local_data_dir = ds_path / last_updated
#         if not local_data_dir.exists():
#             local_data_dir.mkdir()
#
#         download_methodology(save_path=local_data_dir, url_download=url_methodology)
#
#         local_filename = local_data_dir / f"{ds_name}.zip"
#
#         download_file(url_download=url_download, save_path=local_filename)
#
#         downloaded_files.append(str(local_filename))
#
#         unzip_file(local_filename)
#
#     return downloaded_files

if __name__ == "__main__":
    download_all_domains()