Add CLI function to convert script-dataset to Parquet (#6795)

* Add CLI function to convert script-dataset to Parquet

* Refactor code

* Fix quality

* Add trust_remote_code argument

src/datasets/commands/convert_to_parquet.py

@@ -0,0 +1,154 @@
+import time
+from argparse import ArgumentParser
+from typing import Optional
+
+from huggingface_hub import HfApi, get_repo_discussions
+
+from datasets import get_dataset_config_names, get_dataset_default_config_name, load_dataset
+from datasets.commands import BaseDatasetsCLICommand
+
+
+def _command_factory(args):
+    return ConvertToParquetCommand(
+        args.dataset_id,
+        args.token,
+        args.revision,
+        args.trust_remote_code,
+    )
+
+
+class ConvertToParquetCommand(BaseDatasetsCLICommand):
+    @staticmethod
+    def register_subcommand(parser):
+        parser: ArgumentParser = parser.add_parser("convert_to_parquet", help="Convert dataset to Parquet")
+        parser.add_argument("dataset_id", help="source dataset ID")
+        parser.add_argument("--token", help="access token to the Hugging Face Hub")
+        parser.add_argument("--revision", help="source revision")
+        parser.add_argument(
+            "--trust_remote_code", action="store_true", help="whether to trust the code execution of the load script"
+        )
+        parser.set_defaults(func=_command_factory)
+
+    def __init__(
+        self,
+        dataset_id: str,
+        token: Optional[str],
+        revision: Optional[str],
+        trust_remote_code: bool,
+    ):
+        self._dataset_id = dataset_id
+        self._token = token
+        self._revision = revision
+        self._trust_remote_code = trust_remote_code
+
+    def run(self) -> None:
+        dataset_id = self._dataset_id
+        token = self._token
+        revision = self._revision
+        trust_remote_code = self._trust_remote_code
+        print(f"{dataset_id}")
+        configs = get_dataset_config_names(
+            dataset_id, token=token, revision=revision, trust_remote_code=trust_remote_code
+        )
+        print(f"{configs = }")
+        default_config = get_dataset_default_config_name(
+            dataset_id, token=token, revision=revision, trust_remote_code=trust_remote_code
+        )
+        print(f"{default_config = }")
+        if default_config:
+            config = default_config
+            configs.remove(default_config)
+        else:
+            config = configs.pop(0)
+        print(f"{config = }")
+        dataset = load_dataset(dataset_id, config, revision=revision, trust_remote_code=trust_remote_code)
+        commit_info = dataset.push_to_hub(
+            dataset_id,
+            config_name=config,
+            commit_message="Convert dataset to Parquet",
+            commit_description="Convert dataset to Parquet.",
+            create_pr=True,
+            token=token,
+            set_default=default_config is not None,
+        )
+        time.sleep(5)
+        if commit_info:
+            pr_revision, pr_url = commit_info.pr_revision, commit_info.pr_url
+        else:
+            pr_revision, pr_url = infer_pr(dataset_id, token=token)
+        for config in configs:
+            print(f"{config = }")
+            dataset = load_dataset(dataset_id, config, revision=revision, trust_remote_code=trust_remote_code)
+            dataset.push_to_hub(
+                dataset_id,
+                config_name=config,
+                commit_message=f"Add {config} data files",
+                revision=pr_revision,
+                token=token,
+            )
+            time.sleep(5)
+        delete_files(dataset_id, revision=pr_revision, token=token)
+        print(f"You can find your PR to convert the dataset to Parquet at: {pr_url}")
+
+
+def infer_pr(dataset_id, token=None):
+    discussions = get_repo_discussions(dataset_id, repo_type="dataset", token=token)
+    prs = [discussion for discussion in discussions if discussion.is_pull_request and discussion.status == "open"]
+    pr = sorted(prs, key=lambda pr: pr.num)[-1]
+    return pr.git_reference, pr.url
+
+
+def delete_files(dataset_id, revision=None, token=None):
+    dataset_name = dataset_id.split("/")[-1]
+    hf_api = HfApi(token=token)
+    repo_files = hf_api.list_repo_files(
+        dataset_id,
+        repo_type="dataset",
+    )
+    if repo_files:
+        legacy_json_file = []
+        python_files = []
+        data_files = []
+        for filename in repo_files:
+            if filename in {".gitattributes", "README.md"}:
+                continue
+            elif filename == f"{dataset_name}.py":
+                hf_api.delete_file(
+                    filename,
+                    dataset_id,
+                    repo_type="dataset",
+                    revision=revision,
+                    commit_message="Delete loading script",
+                )
+            elif filename == "dataset_infos.json":
+                legacy_json_file.append(filename)
+            elif filename.endswith(".py"):
+                python_files.append(filename)
+            else:
+                data_files.append(filename)
+        if legacy_json_file:
+            hf_api.delete_file(
+                "dataset_infos.json",
+                dataset_id,
+                repo_type="dataset",
+                revision=revision,
+                commit_message="Delete legacy dataset_infos.json",
+            )
+        if python_files:
+            for filename in python_files:
+                hf_api.delete_file(
+                    filename,
+                    dataset_id,
+                    repo_type="dataset",
+                    revision=revision,
+                    commit_message="Delete loading script auxiliary file",
+                )
+        if data_files:
+            for filename in data_files:
+                hf_api.delete_file(
+                    filename,
+                    dataset_id,
+                    repo_type="dataset",
+                    revision=revision,
+                    commit_message="Delete data file",
+                )

src/datasets/commands/datasets_cli.py

@@ -2,6 +2,7 @@
 from argparse import ArgumentParser
 
 from datasets.commands.convert import ConvertCommand
+from datasets.commands.convert_to_parquet import ConvertToParquetCommand
 from datasets.commands.dummy_data import DummyDataCommand
 from datasets.commands.env import EnvironmentCommand
 from datasets.commands.run_beam import RunBeamCommand
@@ -26,6 +27,7 @@ def main():
     TestCommand.register_subcommand(commands_parser)
     RunBeamCommand.register_subcommand(commands_parser)
     DummyDataCommand.register_subcommand(commands_parser)
+    ConvertToParquetCommand.register_subcommand(commands_parser)
 
     # Parse args
     args, unknown_args = parser.parse_known_args()