knmi_api_pull.py

"""
Download data from KNMI API.
Copyright (C) 2024 Maximilian Pierzyna, except when indicated otherwise
in the docstring of the functions.

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.
"""
import concurrent.futures
import pathlib
import sys
from typing import List, Tuple, Union

import requests

# Set API key
API_KEY = ""

# Define available datasets (name, version)
DS_TOWER_UNVAL = ("cesar_tower_meteo_la1_t10", "v1.2")
DS_SURFACE_UNVAL = ("cesar_surface_meteo_la1_t10", "v1.0")
DS_FLUX_UNVAL = ("cesar_surface_flux_la1_t10", "v1.0")
DS_CLOUD = ("cesar_nubiscope_cldcov_la1_t10", "v1.0")
DS_RAD = ("cesar_surface_radiation_la1_t10", "v1.0")


class OpenDataAPI:
    """Wrapper to access KNMI API
    From KNMI tutorial: https://developer.dataplatform.knmi.nl/open-data-api#example-last
    """

    def __init__(self, api_token: str):
        self.base_url = "https://api.dataplatform.knmi.nl/open-data/v1"
        self.headers = {"Authorization": api_token}

    def __get_data(self, url, params=None):
        return requests.get(url, headers=self.headers, params=params).json()

    def list_files(self, dataset_name: str, dataset_version: str, begin: str, end: str, **params):
        # Translate begin and end dates into filenames for API filtering
        params = {
            **params,
            "begin": f"{dataset_name}_{dataset_version}_{begin}.nc",
            "end": f"{dataset_name}_{dataset_version}_{end}.nc"
        }

        # Query API and get file list
        res = self.__get_data(
            f"{self.base_url}/datasets/{dataset_name}/versions/{dataset_version}/files",
            params=params,
        )
        try:
            files = res["files"]
        except KeyError:
            print(res)
            raise

        # If result is trunacted, submit again with nextPageToken, to retreive all data
        if res["isTruncated"]:
            files += self.list_files(dataset_name, dataset_version, begin, end, nextPageToken=res["nextPageToken"])

        # Return full file list
        return files

    def get_file_url(self, dataset_name: str, dataset_version: str, filename: str):
        return self.__get_data(
            f"{self.base_url}/datasets/{dataset_name}/versions/{dataset_version}/files/{filename}/url"
        )


def download_file(url: str, local_dst: pathlib.Path, chunk_size: int = 16384) -> None:
    """ Streaming download for large files 
    Source: https://stackoverflow.com/questions/16694907/download-large-file-in-python-with-requests.
    """
    with requests.get(url, stream=True) as r:
        r.raise_for_status()
        with local_dst.open("wb") as f:
            for chunk in r.iter_content(chunk_size=chunk_size):
                f.write(chunk)


def download_dataset_subset(api: OpenDataAPI, dataset_name: str, dataset_version: str, begin: str, end: str,
                            output_path: pathlib.Path):
    # Retrieve file list
    print("Retrieving file list...")
    files = api.list_files(dataset_name, dataset_version, begin, end)
    filenames = [f["filename"] for f in files]
    print(f"-> {len(filenames)} files.")

    # Check if files are already downloaded
    filenames = [f for f in filenames if not (output_path / f).exists()]
    if len(filenames) == 0:
        print("No new files to download. ")
        print("-> Done.")
        return

    # Get download urls
    print("Retrieving download urls for each file...")
    with concurrent.futures.ThreadPoolExecutor(max_workers=20) as executor:
        futures = [
            executor.submit(api.get_file_url, dataset_name=dataset_name, dataset_version=dataset_version, filename=f)
            for f in filenames
        ]
    file_urls = [f.result()["temporaryDownloadUrl"] for f in futures]
    print("-> Done")

    # Download files
    print("Downloading files...")
    with concurrent.futures.ThreadPoolExecutor(max_workers=8) as executor:
        for f, u in zip(filenames, file_urls):
            print(f"Downloading {f}...")
            try:
                executor.submit(download_file, url=u, local_dst=output_path / f)
            except Exception as e:
                print(f"Error downloading {f}: {e}")

    print(f"-> Done. Check {output_path}.")


if __name__ == "__main__":
    # Define datasets to download (based on available datasets defined above)
    datasets = [
        DS_TOWER_UNVAL,
        DS_SURFACE_UNVAL,
        DS_FLUX_UNVAL,
        DS_RAD
    ]
    # Define periods to download for each dataset.
    periods_datasets = [
        ("20211221", "20211224", datasets),
        ("20220418", "20220423", datasets),
        ("20220726", "20220729", datasets),
        ("20221007", "20221010", datasets),
    ]
    # Make output directory
    output = pathlib.Path("knmi_data")
    output.mkdir(exist_ok=True)

    # Query API and download files
    api = OpenDataAPI(API_KEY)
    for begin, end, datasets in periods_datasets:
        for ds in datasets:
            download_dataset_subset(api, *ds, begin=begin, end=end, output_path=output)