# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the DataLab Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile, rmtree
from typing import Generator

import datalabs.config
from datalabs.builder import DatasetBuilder
from datalabs.commands import BaseDatasetsCLICommand
from datalabs.load import dataset_module_factory, import_main_class
from datalabs.utils.download_manager import GenerateMode
from datalabs.utils.filelock import logger as fl_logger
from datalabs.utils.logging import ERROR, get_logger


logger = get_logger(__name__)


def test_command_factory(args):
    return TestCommand(
        args.dataset,
        args.name,
        args.cache_dir,
        args.data_dir,
        args.all_configs,
        args.save_infos,
        args.ignore_verifications,
        args.force_redownload,
        args.clear_cache,
        args.proc_rank,
        args.num_proc,
    )


class TestCommand(BaseDatasetsCLICommand):
    @staticmethod
    def register_subcommand(parser: ArgumentParser):
        test_parser = parser.add_parser("test", help="Test dataset implementation.")
        test_parser.add_argument("--name", type=str, default=None, help="Dataset processing name")
        test_parser.add_argument(
            "--cache_dir",
            type=str,
            default=None,
            help="Cache directory where the datalab are stored.",
        )
        test_parser.add_argument(
            "--data_dir",
            type=str,
            default=None,
            help="Can be used to specify a manual directory to get the files from.",
        )
        test_parser.add_argument("--all_configs", action="store_true", help="Test all dataset configurations")
        test_parser.add_argument("--save_infos", action="store_true", help="Save the dataset infos file")
        test_parser.add_argument(
            "--ignore_verifications", action="store_true", help="Run the test without checksums and splits checks"
        )
        test_parser.add_argument("--force_redownload", action="store_true", help="Force dataset redownload")
        test_parser.add_argument(
            "--clear_cache",
            action="store_true",
            help="Remove downloaded files and cached datalab after each config test",
        )
        test_parser.add_argument(
            "--proc_rank",
            type=int,
            default=0,
            help="Rank of the current process for multiprocessing testing.",
        )
        test_parser.add_argument(
            "--num_proc",
            type=int,
            default=1,
            help="Number of processes to use for multiprocessing testing",
        )
        test_parser.add_argument("dataset", type=str, help="Name of the dataset to download")
        test_parser.set_defaults(func=test_command_factory)

    def __init__(
        self,
        dataset: str,
        name: str,
        cache_dir: str,
        data_dir: str,
        all_configs: bool,
        save_infos: bool,
        ignore_verifications: bool,
        force_redownload: bool,
        clear_cache: bool,
        proc_rank: int,
        num_proc: int,
    ):
        self._dataset = dataset
        self._name = name
        self._cache_dir = cache_dir
        self._data_dir = data_dir
        self._all_configs = all_configs
        self._save_infos = save_infos
        self._ignore_verifications = ignore_verifications
        self._force_redownload = force_redownload
        self._clear_cache = clear_cache
        self._proc_rank = proc_rank
        self._num_proc = num_proc
        if clear_cache and not cache_dir:
            print(
                "When --clear_cache is used, specifying a cache directory is mandatory.\n"
                "The 'download' folder of the cache directory and the dataset builder cache will be deleted after each configuration test.\n"
                "Please provide a --cache_dir that will be used to test the dataset script."
            )
            exit(1)
        if save_infos:
            self._ignore_verifications = True

    def run(self):
        fl_logger().setLevel(ERROR)
        if self._name is not None and self._all_configs:
            print("Both parameters `config` and `all_configs` can't be used at once.")
            exit(1)
        path, name = self._dataset, self._name
        module = dataset_module_factory(path)
        builder_cls = import_main_class(module.module_path)

        if self._all_configs and len(builder_cls.BUILDER_CONFIGS) > 0:
            n_builders = len(builder_cls.BUILDER_CONFIGS) // self._num_proc
            n_builders += (len(builder_cls.BUILDER_CONFIGS) % self._num_proc) > self._proc_rank
        else:
            n_builders = 1 if self._proc_rank == 0 else 0

        def get_builders() -> Generator[DatasetBuilder, None, None]:
            if self._all_configs and len(builder_cls.BUILDER_CONFIGS) > 0:
                for i, config in enumerate(builder_cls.BUILDER_CONFIGS):
                    if i % self._num_proc == self._proc_rank:
                        yield builder_cls(
                            name=config.name,
                            cache_dir=self._cache_dir,
                            data_dir=self._data_dir,
                            **module.builder_kwargs,
                        )
            else:
                if self._proc_rank == 0:
                    yield builder_cls(
                        name=name, cache_dir=self._cache_dir, data_dir=self._data_dir, **module.builder_kwargs
                    )

        for j, builder in enumerate(get_builders()):
            print(f"Testing builder '{builder.config.name}' ({j + 1}/{n_builders})")
            builder.download_and_prepare(
                download_mode=GenerateMode.REUSE_CACHE_IF_EXISTS
                if not self._force_redownload
                else GenerateMode.FORCE_REDOWNLOAD,
                ignore_verifications=self._ignore_verifications,
                try_from_hf_gcs=False,
            )
            builder.as_dataset()
            if self._save_infos:
                builder._save_infos()

            # If save_infos=True, the dataset infos file is created next to the loaded module file.
            # Let's move it to the original directory of the dataset script, to allow the user to
            # upload them on S3 at the same time afterwards.
            if self._save_infos:
                dataset_infos_path = os.path.join(
                    builder_cls.get_imported_module_dir(), datasets.config.DATASETDICT_INFOS_FILENAME
                )
                name = Path(path).name + ".py"
                combined_path = os.path.join(path, name)
                if os.path.isfile(path):
                    dataset_dir = os.path.dirname(path)
                elif os.path.isfile(combined_path):
                    dataset_dir = path
                else:  # in case of a remote dataset
                    dataset_dir = None
                    print(f"Dataset Infos file saved at {dataset_infos_path}")

                # Move dataset_info back to the user
                if dataset_dir is not None:
                    user_dataset_infos_path = os.path.join(dataset_dir, datasets.config.DATASETDICT_INFOS_FILENAME)
                    copyfile(dataset_infos_path, user_dataset_infos_path)
                    print(f"Dataset Infos file saved at {user_dataset_infos_path}")

            # If clear_cache=True, the download folder and the dataset builder cache directory are deleted
            if self._clear_cache:
                if os.path.isdir(builder._cache_dir):
                    logger.warning(f"Clearing cache at {builder._cache_dir}")
                    rmtree(builder._cache_dir)
                download_dir = os.path.join(self._cache_dir, datasets.config.DOWNLOADED_DATASETS_DIR)
                if os.path.isdir(download_dir):
                    logger.warning(f"Clearing cache at {download_dir}")
                    rmtree(download_dir)

        print("Test successful.")
