# ========= Copyright 2026 @ Strukto.AI All Rights Reserved. =========
# 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
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# 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.
# ========= Copyright 2026 @ Strukto.AI All Rights Reserved. =========

import dataclasses
from typing import Any

from mirage.accessor.hf_datasets import HfDatasetsAccessor, HfDatasetsConfig
from mirage.commands.builtin.hf_buckets import COMMANDS as HF_COMMANDS
from mirage.core.hf_buckets.constants import SCOPE_ERROR
from mirage.core.hf_buckets.create import create
from mirage.core.hf_buckets.du import entries as du_entries
from mirage.core.hf_buckets.du import size as du_size
from mirage.core.hf_buckets.exists import exists
from mirage.core.hf_buckets.find import find
from mirage.core.hf_buckets.mkdir import mkdir
from mirage.core.hf_buckets.read import read_bytes
from mirage.core.hf_buckets.readdir import readdir
from mirage.core.hf_buckets.stat import stat as hf_stat
from mirage.core.hf_buckets.stream import range_read, read_stream
from mirage.core.hf_buckets.unlink import unlink
from mirage.core.hf_buckets.watch import build_delta_hook
from mirage.core.hf_buckets.write import write_bytes
from mirage.ops.hf_buckets import OPS as HF_OPS
from mirage.resource.base import BaseResource
from mirage.resource.hf_datasets.prompt import PROMPT
from mirage.types import PathSpec, ResourceName
from mirage.utils.glob_walk import make_resolve_glob
from mirage.utils.key_prefix import mount_key
from mirage.watch.base import DeltaHook

_resolve_glob = make_resolve_glob(readdir, SCOPE_ERROR)

_OPS = {
    "read_bytes": read_bytes,
    "readdir": readdir,
    "stat": hf_stat,
    "read_stream": read_stream,
    "range_read": range_read,
    "du_size": du_size,
    "du_entries": du_entries,
    "exists": exists,
    "find_flat": find,
    "write": write_bytes,
    "create": create,
    "unlink": unlink,
    "mkdir": mkdir,
}


class HfDatasetsResource(BaseResource):

    accessor: HfDatasetsAccessor
    name: str = ResourceName.HF_DATASETS
    caches_reads: bool = True
    # Same size guarantees as HfBucketsResource: exact Hub tree sizes
    # plus the readdir stat backfill.
    SIZES_ALWAYS_KNOWN: bool = True
    _ops: dict[str, Any] = _OPS
    PROMPT: str = PROMPT
    SUPPORTS_SNAPSHOT: bool = True

    def __init__(self, config: HfDatasetsConfig) -> None:
        super().__init__()
        self.config = config
        self.accessor = HfDatasetsAccessor(self.config)
        for fn in HF_COMMANDS:
            self.register(fn)
        for op in HF_OPS:
            self.register_op(op)

    def delta_hook(self) -> DeltaHook:
        return build_delta_hook(self.accessor)

    async def resolve_glob(
        self,
        paths: list[PathSpec],
        prefix: str = '',
    ) -> list[PathSpec]:
        if prefix:
            paths = [
                dataclasses.replace(p,
                                    resource_path=mount_key(p.virtual, prefix))
                if isinstance(p, PathSpec) else p for p in paths
            ]
        return await _resolve_glob(self.accessor, paths, self._index)

    def get_state(self) -> dict[str, Any]:
        return self.config_state(self.config)

    def load_state(self, state: dict[str, Any]) -> None:
        pass
