
"""simple docstring"""





import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata







def 			__a  (	__lowerCamelCase						):
   UpperCAmelCase_      :      List[str]      =					min(re.search("^ +",	__lowerCamelCase						).end() if t.startswith(" "						) else 0 for t in string.splitlines()						)
   return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(__lowerCamelCase						)]						)


_a	 =							'\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n'

_a	 =							'\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n'


_a	 =							'\\n# Begin of markdown\n\nSome cool dataset card\n'


class A_			(unittest.TestCase   ):




  '''simple docstring'''







  def  UpperCamelCase__      (	self						):

     """simple docstring"""
     with tempfile.TemporaryDirectory() as tmp_dir:
        UpperCAmelCase_      :      Optional[int]      =					Path(lowercase_						) / "README.md"
        with open(lowercase_       ,     "w+"						) as readme_file:
           readme_file.write(lowercase_						)
        UpperCAmelCase_      :      Dict      =					DatasetMetadata.from_readme(lowercase_						)
        self.assertDictEqual(lowercase_       ,     {"language": ["zh", "en"], "task_ids": ["sentiment-classification"]}						)

        with open(lowercase_       ,     "w+"						) as readme_file:
           readme_file.write(lowercase_						)
        UpperCAmelCase_      :      Dict      =					DatasetMetadata.from_readme(lowercase_						)
        self.assertDictEqual(lowercase_       ,     {}						)

        with open(lowercase_       ,     "w+"						) as readme_file:
           readme_file.write(lowercase_						)
        UpperCAmelCase_      :      str      =					DatasetMetadata.from_readme(lowercase_						)
        self.assertEqual(lowercase_       ,     {}						)







  def  UpperCamelCase__      (	self						):

     """simple docstring"""
     UpperCAmelCase_      :      Tuple      =					_dedent(
         "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            "						)
     assert DatasetMetadata.from_yaml_string(lowercase_						)

     UpperCAmelCase_      :      int      =					_dedent(
         "\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            "						)
     with self.assertRaises(lowercase_						):
        DatasetMetadata.from_yaml_string(lowercase_						)

     UpperCAmelCase_      :      Any      =					_dedent(
         "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the \"Researcher\") has requested permission to use the ImageNet database (the \"Database\") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            "						)
     assert DatasetMetadata.from_yaml_string(lowercase_						)




"""simple docstring"""





from __future__ import annotations

from typing import Any


class A_			:




  '''simple docstring'''







  def __init__(	self       ,     lowercase_       ,     lowercase_						):  # noqa: A002

     """simple docstring"""
     UpperCAmelCase_      :      Optional[Any]      =					item
     UpperCAmelCase_      :      Optional[Any]      =					next




class A_			:




  '''simple docstring'''







  def __init__(	self						):

     """simple docstring"""
     UpperCAmelCase_      :      Node | None      =					None
     UpperCAmelCase_      :      Optional[int]      =					0







  def  UpperCamelCase__      (	self       ,     lowercase_						):

     """simple docstring"""
     UpperCAmelCase_      :      int      =					Node(lowercase_       ,     self.head						)
     self.size += 1







  def  UpperCamelCase__      (	self						):

     """simple docstring"""
     # Switched 'self.is_empty()' to 'self.head is None'
     # because mypy was considering the possibility that 'self.head'
     # can be None in below else part and giving error
     if self.head is None:
        return None
     else:
        UpperCAmelCase_      :      int      =					self.head.item
        UpperCAmelCase_      :      str      =					self.head.next
        self.size -= 1
        return item







  def  UpperCamelCase__      (	self						):

     """simple docstring"""
     return self.head is None







  def __str__(	self						):

     """simple docstring"""
     if self.is_empty():
        return ""
     else:
        UpperCAmelCase_      :      str      =					self.head
        UpperCAmelCase_      :      str      =					""
        UpperCAmelCase_      :      list[str]      =					[]
        while iterate:
           item_list.append(str(iterate.item						)						)
           UpperCAmelCase_      :      Tuple      =					iterate.next

        UpperCAmelCase_      :      Optional[Any]      =					" --> ".join(lowercase_						)

        return item_str







  def __len__(	self						):

     """simple docstring"""
     return self.size


