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285 lines
10 KiB
Python
285 lines
10 KiB
Python
# Copyright 2026 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Contains commands to interact with datasets on the Hugging Face Hub.
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Usage:
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# list datasets on the Hub
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hf datasets ls
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# list datasets with a search query
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hf datasets ls --search "code"
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# get info about a dataset
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hf datasets info HuggingFaceFW/fineweb
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"""
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import enum
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from typing import Annotated, get_args
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import typer
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from huggingface_hub._dataset_viewer import execute_raw_sql_query
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from huggingface_hub.errors import CLIError, RepositoryNotFoundError, RevisionNotFoundError
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from huggingface_hub.hf_api import DatasetSort_T, ExpandDatasetProperty_T
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from huggingface_hub.repocard import DatasetCard
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from ._cli_utils import (
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REPO_LIST_DEFAULT_LIMIT,
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AuthorOpt,
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FilterOpt,
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LimitOpt,
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RevisionOpt,
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SearchOpt,
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TokenOpt,
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get_hf_api,
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make_expand_properties_parser,
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typer_factory,
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)
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from ._file_listing import list_repo_files_cmd
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from ._output import _dataclass_to_dict, out
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_EXPAND_PROPERTIES = sorted(get_args(ExpandDatasetProperty_T))
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_SORT_OPTIONS = get_args(DatasetSort_T)
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DatasetSortEnum = enum.Enum("DatasetSortEnum", {s: s for s in _SORT_OPTIONS}, type=str) # type: ignore[misc]
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ExpandOpt = Annotated[
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str | None,
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typer.Option(
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help=f"Comma-separated properties to return. When used, only the listed properties (and id) are returned. Example: '--expand=downloads,likes,tags'. Valid: {', '.join(_EXPAND_PROPERTIES)}.",
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callback=make_expand_properties_parser(_EXPAND_PROPERTIES),
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),
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]
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datasets_cli = typer_factory(help="Interact with datasets on the Hub.")
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@datasets_cli.command(
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"list | ls",
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examples=[
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"hf datasets ls",
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"hf datasets ls --sort downloads --limit 10",
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'hf datasets ls --search "code"',
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"hf datasets ls --filter benchmark:official",
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"hf datasets ls HuggingFaceFW/fineweb",
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"hf datasets ls HuggingFaceFW/fineweb -R",
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"hf datasets ls HuggingFaceFW/fineweb --tree -h",
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],
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)
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def datasets_ls(
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repo_id: Annotated[
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str | None,
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typer.Argument(help="Dataset ID (e.g. `username/repo-name`) to list files from. If omitted, lists datasets."),
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] = None,
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search: SearchOpt = None,
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author: AuthorOpt = None,
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filter: FilterOpt = None,
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sort: Annotated[
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DatasetSortEnum | None,
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typer.Option(help="Sort results."),
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] = None,
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limit: LimitOpt = REPO_LIST_DEFAULT_LIMIT,
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expand: ExpandOpt = None,
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human_readable: Annotated[
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bool,
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typer.Option("--human-readable", "-h", help="Show sizes in human readable format (only for listing files)."),
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] = False,
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as_tree: Annotated[
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bool,
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typer.Option("--tree", help="List files in tree format (only for listing files)."),
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] = False,
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recursive: Annotated[
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bool,
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typer.Option("--recursive", "-R", help="List files recursively (only for listing files)."),
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] = False,
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revision: RevisionOpt = None,
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token: TokenOpt = None,
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) -> None:
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"""List datasets on the Hub, or files in a dataset repo.
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When called with no argument, lists datasets on the Hub.
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When called with a dataset ID, lists files in that dataset repo.
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"""
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if repo_id is not None:
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if search is not None:
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raise typer.BadParameter("Cannot use --search when listing files.")
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if author is not None:
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raise typer.BadParameter("Cannot use --author when listing files.")
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if filter is not None:
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raise typer.BadParameter("Cannot use --filter when listing files.")
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if sort is not None:
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raise typer.BadParameter("Cannot use --sort when listing files.")
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if limit != REPO_LIST_DEFAULT_LIMIT:
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raise typer.BadParameter("Cannot use --limit when listing files.")
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if expand is not None:
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raise typer.BadParameter("Cannot use --expand when listing files.")
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return list_repo_files_cmd(
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repo_id=repo_id,
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repo_type="dataset",
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human_readable=human_readable,
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as_tree=as_tree,
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recursive=recursive,
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revision=revision,
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token=token,
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)
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if as_tree:
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raise typer.BadParameter("Cannot use --tree when listing datasets.")
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if recursive:
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raise typer.BadParameter("Cannot use --recursive when listing datasets.")
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if human_readable:
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raise typer.BadParameter("Cannot use --human-readable when listing datasets.")
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if revision is not None:
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raise typer.BadParameter("Cannot use --revision when listing datasets.")
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api = get_hf_api(token=token)
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sort_key = sort.value if sort else None
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results = [
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_dataclass_to_dict(dataset_info)
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for dataset_info in api.list_datasets(
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filter=filter,
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author=author,
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search=search,
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sort=sort_key,
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limit=limit,
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expand=expand, # type: ignore
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)
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]
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out.table(results)
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@datasets_cli.command(
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"leaderboard",
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examples=[
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"hf datasets leaderboard SWE-bench/SWE-bench_Verified",
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"hf datasets leaderboard SWE-bench/SWE-bench_Verified --limit 5 --format json",
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"hf datasets ls --filter benchmark:official # list available leaderboards",
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],
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)
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def datasets_leaderboard(
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dataset_id: Annotated[str, typer.Argument(help="The benchmark dataset ID (e.g. `SWE-bench/SWE-bench_Verified`).")],
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limit: LimitOpt = 20,
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token: TokenOpt = None,
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) -> None:
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"""List model scores from a dataset leaderboard. This command helps find the best models for a task or compare models by benchmark scores. Use 'hf datasets ls --filter benchmark:official' to list available leaderboards."""
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api = get_hf_api(token=token)
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leaderboard = api.get_dataset_leaderboard(repo_id=dataset_id)
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results = [_dataclass_to_dict(entry) for entry in leaderboard[:limit]]
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out.table(
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results,
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headers=["rank", "model_id", "value", "source"],
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id_key="model_id",
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)
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out.hint("Use 'hf datasets ls --filter benchmark:official' to list available leaderboards.")
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if leaderboard:
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out.hint(f"Use 'hf models info {leaderboard[0].model_id}' to get details about a model.")
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@datasets_cli.command(
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"info",
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examples=[
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"hf datasets info HuggingFaceFW/fineweb",
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"hf datasets info my-dataset --expand downloads,likes,tags",
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],
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)
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def datasets_info(
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dataset_id: Annotated[str, typer.Argument(help="The dataset ID (e.g. `username/repo-name`).")],
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revision: RevisionOpt = None,
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expand: ExpandOpt = None,
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token: TokenOpt = None,
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) -> None:
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"""Get info about a dataset on the Hub."""
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api = get_hf_api(token=token)
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try:
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info = api.dataset_info(repo_id=dataset_id, revision=revision, expand=expand) # type: ignore
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except RepositoryNotFoundError as e:
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raise CLIError(f"Dataset '{dataset_id}' not found.") from e
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except RevisionNotFoundError as e:
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raise CLIError(f"Revision '{revision}' not found on '{dataset_id}'.") from e
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out.dict(info)
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@datasets_cli.command(
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"parquet",
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examples=[
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"hf datasets parquet cfahlgren1/hub-stats",
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"hf datasets parquet cfahlgren1/hub-stats --subset models",
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"hf datasets parquet cfahlgren1/hub-stats --split train",
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"hf datasets parquet cfahlgren1/hub-stats --format json",
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],
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)
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def datasets_parquet(
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dataset_id: Annotated[str, typer.Argument(help="The dataset ID (e.g. `username/repo-name`).")],
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subset: Annotated[str | None, typer.Option("--subset", help="Filter parquet entries by subset/config.")] = None,
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split: Annotated[str | None, typer.Option(help="Filter parquet entries by split.")] = None,
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token: TokenOpt = None,
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) -> None:
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"""List parquet file URLs available for a dataset."""
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api = get_hf_api(token=token)
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entries = api.list_dataset_parquet_files(repo_id=dataset_id, config=subset)
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filtered = [entry for entry in entries if split is None or entry.split == split]
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results = [
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{"subset": entry.config, "split": entry.split, "url": entry.url, "size": entry.size} for entry in filtered
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]
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out.table(results, headers=["subset", "split", "url", "size"], id_key="url")
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@datasets_cli.command(
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"sql",
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examples=[
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"hf datasets sql \"SELECT COUNT(*) AS rows FROM read_parquet('https://huggingface.co/api/datasets/cfahlgren1/hub-stats/parquet/models/train/0.parquet')\"",
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"hf datasets sql \"SELECT * FROM read_parquet('https://huggingface.co/api/datasets/cfahlgren1/hub-stats/parquet/models/train/0.parquet') LIMIT 5\" --format json",
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],
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)
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def datasets_sql(
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sql: Annotated[str, typer.Argument(help="Raw SQL query to execute.")],
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token: TokenOpt = None,
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) -> None:
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"""Execute a raw SQL query with DuckDB against dataset parquet URLs."""
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try:
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result = execute_raw_sql_query(sql_query=sql, token=token)
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except ImportError as e:
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raise CLIError(str(e)) from e
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out.table(result)
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@datasets_cli.command(
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"card",
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examples=[
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"hf datasets card HuggingFaceFW/fineweb",
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"hf datasets card HuggingFaceFW/fineweb --metadata",
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"hf datasets card HuggingFaceFW/fineweb --metadata --format json",
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"hf datasets card HuggingFaceFW/fineweb --text",
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],
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)
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def datasets_card(
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dataset_id: Annotated[str, typer.Argument(help="The dataset ID (e.g. `username/repo-name`).")],
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metadata: Annotated[bool, typer.Option("--metadata", help="Output only the metadata from the card.")] = False,
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text: Annotated[bool, typer.Option("--text", help="Output only the text body (no metadata).")] = False,
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token: TokenOpt = None,
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) -> None:
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"""Get the dataset card (README) for a dataset on the Hub."""
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if metadata and text:
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raise CLIError("--metadata and --text are mutually exclusive.")
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card = DatasetCard.load(dataset_id, token=token)
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if metadata:
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out.dict(card.data.to_dict())
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elif text:
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out.text(card.text)
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else:
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out.text(card.content)
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out.hint(f"Use `hf datasets card {dataset_id} --metadata` to extract only the card metadata.")
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