import unittest

import numpy as np

from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
   import torch

if is_pytesseract_available():
   from PIL import Image

   from transformers import LayoutLMvaImageProcessor







class __snake_case       (		unittest.TestCase	):




   def __init__(					self    :       Dict ,			_lowercase    :       Tuple ,			_lowercase    :       Union[str, Any]=7 ,			_lowercase    :       Tuple=3 ,			_lowercase    :       List[Any]=18 ,			_lowercase    :       Optional[int]=30 ,			_lowercase    :       Optional[int]=4_00 ,			_lowercase    :       Optional[Any]=True ,			_lowercase    :       Any=None ,			_lowercase    :       List[Any]=True ,			):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   size if size is not None else {"""height""": 18, """width""": 18}
     SCREAMING_SNAKE_CASE__    							=   parent
     SCREAMING_SNAKE_CASE__    							=   batch_size
     SCREAMING_SNAKE_CASE__    							=   num_channels
     SCREAMING_SNAKE_CASE__    							=   image_size
     SCREAMING_SNAKE_CASE__    							=   min_resolution
     SCREAMING_SNAKE_CASE__    							=   max_resolution
     SCREAMING_SNAKE_CASE__    							=   do_resize
     SCREAMING_SNAKE_CASE__    							=   size
     SCREAMING_SNAKE_CASE__    							=   apply_ocr




   def 			__a		(					self    :       Any   ):



     """simple docstring"""






     return {"do_resize": self.do_resize, "size": self.size, "apply_ocr": self.apply_ocr}







@require_torch
@require_pytesseract
class __snake_case       (		lowerCamelCase_     ,	unittest.TestCase	):
   lowerCAmelCase_														=							LayoutLMvaImageProcessor if is_pytesseract_available() else None




   def 			__a		(					self    :       List[str]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   LayoutLMvaImageProcessingTester(self   )




   @property
   def 			__a		(					self    :       List[Any]   ):



     """simple docstring"""






     return self.image_processor_tester.prepare_image_processor_dict()




   def 			__a		(					self    :       Optional[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.image_processing_class(**self.image_processor_dict   )
     self.assertTrue(hasattr(_lowercase ,			"""do_resize"""   )   )
     self.assertTrue(hasattr(_lowercase ,			"""size"""   )   )
     self.assertTrue(hasattr(_lowercase ,			"""apply_ocr"""   )   )




   def 			__a		(					self    :       Tuple   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.image_processing_class.from_dict(self.image_processor_dict   )
     self.assertEqual(image_processor.size ,			{"""height""": 18, """width""": 18}   )

     SCREAMING_SNAKE_CASE__    							=   self.image_processing_class.from_dict(self.image_processor_dict ,			size=42   )
     self.assertEqual(image_processor.size ,			{"""height""": 42, """width""": 42}   )




   def 			__a		(					self    :       Any   ):



     """simple docstring"""






     pass




   def 			__a		(					self    :       str   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.image_processing_class(**self.image_processor_dict   )
     # create random PIL images
     SCREAMING_SNAKE_CASE__    							=   prepare_image_inputs(self.image_processor_tester ,			equal_resolution=_lowercase   )
     for image in image_inputs:
       self.assertIsInstance(_lowercase ,			Image.Image   )

     # Test not batched input
     SCREAMING_SNAKE_CASE__    							=   image_processing(image_inputs[0] ,			return_tensors="""pt"""   )
     self.assertEqual(
         encoding.pixel_values.shape ,			(
             1,
             self.image_processor_tester.num_channels,
             self.image_processor_tester.size["""height"""],
             self.image_processor_tester.size["""width"""],
         ) ,			)

     self.assertIsInstance(encoding.words ,			_lowercase   )
     self.assertIsInstance(encoding.boxes ,			_lowercase   )

     # Test batched
     SCREAMING_SNAKE_CASE__    							=   image_processing(_lowercase ,			return_tensors="""pt"""   ).pixel_values
     self.assertEqual(
         encoded_images.shape ,			(
             self.image_processor_tester.batch_size,
             self.image_processor_tester.num_channels,
             self.image_processor_tester.size["""height"""],
             self.image_processor_tester.size["""width"""],
         ) ,			)




   def 			__a		(					self    :       List[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.image_processing_class(**self.image_processor_dict   )
     # create random numpy tensors
     SCREAMING_SNAKE_CASE__    							=   prepare_image_inputs(self.image_processor_tester ,			equal_resolution=_lowercase ,			numpify=_lowercase   )
     for image in image_inputs:
       self.assertIsInstance(_lowercase ,			np.ndarray   )

     # Test not batched input
     SCREAMING_SNAKE_CASE__    							=   image_processing(image_inputs[0] ,			return_tensors="""pt"""   ).pixel_values
     self.assertEqual(
         encoded_images.shape ,			(
             1,
             self.image_processor_tester.num_channels,
             self.image_processor_tester.size["""height"""],
             self.image_processor_tester.size["""width"""],
         ) ,			)

     # Test batched
     SCREAMING_SNAKE_CASE__    							=   image_processing(_lowercase ,			return_tensors="""pt"""   ).pixel_values
     self.assertEqual(
         encoded_images.shape ,			(
             self.image_processor_tester.batch_size,
             self.image_processor_tester.num_channels,
             self.image_processor_tester.size["""height"""],
             self.image_processor_tester.size["""width"""],
         ) ,			)




   def 			__a		(					self    :       Optional[int]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.image_processing_class(**self.image_processor_dict   )
     # create random PyTorch tensors
     SCREAMING_SNAKE_CASE__    							=   prepare_image_inputs(self.image_processor_tester ,			equal_resolution=_lowercase ,			torchify=_lowercase   )
     for image in image_inputs:
       self.assertIsInstance(_lowercase ,			torch.Tensor   )

     # Test not batched input
     SCREAMING_SNAKE_CASE__    							=   image_processing(image_inputs[0] ,			return_tensors="""pt"""   ).pixel_values
     self.assertEqual(
         encoded_images.shape ,			(
             1,
             self.image_processor_tester.num_channels,
             self.image_processor_tester.size["""height"""],
             self.image_processor_tester.size["""width"""],
         ) ,			)

     # Test batched
     SCREAMING_SNAKE_CASE__    							=   image_processing(_lowercase ,			return_tensors="""pt"""   ).pixel_values
     self.assertEqual(
         encoded_images.shape ,			(
             self.image_processor_tester.batch_size,
             self.image_processor_tester.num_channels,
             self.image_processor_tester.size["""height"""],
             self.image_processor_tester.size["""width"""],
         ) ,			)




   def 			__a		(					self    :       int   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   LayoutLMvaImageProcessor()

     from datasets import load_dataset

     SCREAMING_SNAKE_CASE__    							=   load_dataset("""hf-internal-testing/fixtures_docvqa""" ,			split="""test"""   )

     SCREAMING_SNAKE_CASE__    							=   Image.open(ds[0]["""file"""]   ).convert("""RGB"""   )

     SCREAMING_SNAKE_CASE__    							=   image_processing(_lowercase ,			return_tensors="""pt"""   )

     self.assertEqual(encoding.pixel_values.shape ,			(1, 3, 2_24, 2_24)   )
     self.assertEqual(len(encoding.words   ) ,			len(encoding.boxes   )   )

     # fmt: off
     # the words and boxes were obtained with Tesseract 4.1.1
     SCREAMING_SNAKE_CASE__    							=   [["""11:14""", """to""", """11:39""", """a.m""", """11:39""", """to""", """11:44""", """a.m.""", """11:44""", """a.m.""", """to""", """12:25""", """p.m.""", """12:25""", """to""", """12:58""", """p.m.""", """12:58""", """to""", """4:00""", """p.m.""", """2:00""", """to""", """5:00""", """p.m.""", """Coffee""", """Break""", """Coffee""", """will""", """be""", """served""", """for""", """men""", """and""", """women""", """in""", """the""", """lobby""", """adjacent""", """to""", """exhibit""", """area.""", """Please""", """move""", """into""", """exhibit""", """area.""", """(Exhibits""", """Open)""", """TRRF""", """GENERAL""", """SESSION""", """(PART""", """|)""", """Presiding:""", """Lee""", """A.""", """Waller""", """TRRF""", """Vice""", """President""", """“Introductory""", """Remarks”""", """Lee""", """A.""", """Waller,""", """TRRF""", """Vice""", """Presi-""", """dent""", """Individual""", """Interviews""", """with""", """TRRF""", """Public""", """Board""", """Members""", """and""", """Sci-""", """entific""", """Advisory""", """Council""", """Mem-""", """bers""", """Conducted""", """by""", """TRRF""", """Treasurer""", """Philip""", """G.""", """Kuehn""", """to""", """get""", """answers""", """which""", """the""", """public""", """refrigerated""", """warehousing""", """industry""", """is""", """looking""", """for.""", """Plus""", """questions""", """from""", """the""", """floor.""", """Dr.""", """Emil""", """M.""", """Mrak,""", """University""", """of""", """Cal-""", """ifornia,""", """Chairman,""", """TRRF""", """Board;""", """Sam""", """R.""", """Cecil,""", """University""", """of""", """Georgia""", """College""", """of""", """Agriculture;""", """Dr.""", """Stanley""", """Charm,""", """Tufts""", """University""", """School""", """of""", """Medicine;""", """Dr.""", """Robert""", """H.""", """Cotton,""", """ITT""", """Continental""", """Baking""", """Company;""", """Dr.""", """Owen""", """Fennema,""", """University""", """of""", """Wis-""", """consin;""", """Dr.""", """Robert""", """E.""", """Hardenburg,""", """USDA.""", """Questions""", """and""", """Answers""", """Exhibits""", """Open""", """Capt.""", """Jack""", """Stoney""", """Room""", """TRRF""", """Scientific""", """Advisory""", """Council""", """Meeting""", """Ballroom""", """Foyer"""]]  # noqa: E231
     SCREAMING_SNAKE_CASE__    							=   [[[1_41, 57, 2_14, 69], [2_28, 58, 2_52, 69], [1_41, 75, 2_16, 88], [2_30, 79, 2_80, 88], [1_42, 2_60, 2_18, 2_73], [2_30, 2_61, 2_55, 2_73], [1_43, 2_79, 2_18, 2_90], [2_31, 2_82, 2_90, 2_91], [1_43, 3_42, 2_18, 3_54], [2_31, 3_45, 2_89, 3_55], [2_02, 3_62, 2_27, 3_73], [1_43, 3_79, 2_20, 3_92], [2_31, 3_82, 2_91, 3_94], [1_44, 7_14, 2_20, 7_26], [2_31, 7_15, 2_56, 7_26], [1_44, 7_32, 2_20, 7_45], [2_32, 7_36, 2_91, 7_47], [1_44, 7_69, 2_18, 7_82], [2_31, 7_70, 2_56, 7_82], [1_41, 7_88, 2_02, 8_01], [2_15, 7_91, 2_74, 8_04], [1_43, 8_26, 2_04, 8_38], [2_15, 8_26, 2_40, 8_38], [1_42, 8_44, 2_02, 8_57], [2_15, 8_47, 2_74, 8_59], [3_34, 57, 4_27, 69], [4_40, 57, 5_22, 69], [3_69, 75, 4_61, 88], [4_69, 75, 5_16, 88], [5_28, 76, 5_62, 88], [5_70, 76, 6_67, 88], [6_75, 75, 7_11, 87], [7_21, 79, 7_78, 88], [7_89, 75, 8_40, 88], [3_69, 97, 4_70, 1_07], [4_84, 94, 5_07, 1_06], [5_18, 94, 5_62, 1_07], [5_76, 94, 6_55, 1_10], [6_68, 94, 7_92, 1_09], [8_04, 95, 8_29, 1_07], [3_69, 1_13, 4_65, 1_25], [4_77, 1_16, 5_47, 1_25], [5_62, 1_13, 6_58, 1_25], [6_71, 1_16, 7_48, 1_25], [7_61, 1_13, 8_11, 1_25], [3_69, 1_31, 4_65, 1_43], [4_77, 1_33, 5_48, 1_43], [5_63, 1_30, 6_98, 1_45], [7_10, 1_30, 8_02, 1_46], [3_36, 1_71, 4_12, 1_83], [4_23, 1_71, 5_72, 1_83], [5_82, 1_70, 7_16, 1_84], [7_28, 1_71, 8_17, 1_87], [8_29, 1_71, 8_44, 1_86], [3_38, 1_97, 4_82, 2_12], [5_07, 1_96, 5_57, 2_09], [5_69, 1_96, 5_95, 2_08], [6_10, 1_96, 7_02, 2_09], [5_05, 2_14, 5_83, 2_26], [5_95, 2_14, 6_56, 2_27], [6_70, 2_15, 8_07, 2_27], [3_35, 2_59, 5_43, 2_74], [5_56, 2_59, 7_08, 2_72], [3_72, 2_79, 4_22, 2_91], [4_35, 2_79, 4_60, 2_91], [4_74, 2_79, 5_74, 2_92], [5_87, 2_78, 6_64, 2_91], [6_76, 2_78, 7_38, 2_91], [7_51, 2_79, 8_34, 2_91], [3_72, 2_98, 4_34, 3_10], [3_35, 3_41, 4_83, 3_54], [4_97, 3_41, 6_55, 3_54], [6_67, 3_41, 7_28, 3_54], [7_40, 3_41, 8_25, 3_54], [3_35, 3_60, 4_30, 3_72], [4_42, 3_60, 5_34, 3_72], [5_45, 3_59, 6_87, 3_72], [6_97, 3_60, 7_54, 3_72], [7_65, 3_60, 8_23, 3_73], [3_34, 3_78, 4_28, 3_91], [4_40, 3_78, 5_77, 3_94], [5_90, 3_78, 7_05, 3_91], [7_20, 3_78, 8_01, 3_91], [3_34, 3_97, 4_00, 4_09], [3_70, 4_16, 5_29, 4_29], [5_44, 4_16, 5_76, 4_32], [5_87, 4_16, 6_65, 4_28], [6_77, 4_16, 8_14, 4_29], [3_72, 4_35, 4_52, 4_50], [4_65, 4_34, 4_95, 4_47], [5_11, 4_34, 6_00, 4_47], [6_11, 4_36, 6_37, 4_47], [6_49, 4_36, 6_94, 4_51], [7_05, 4_38, 8_24, 4_47], [3_69, 4_53, 4_52, 4_66], [4_64, 4_54, 5_09, 4_66], [5_22, 4_53, 6_11, 4_69], [6_25, 4_53, 7_92, 4_69], [3_70, 4_72, 5_56, 4_88], [5_70, 4_72, 6_84, 4_87], [6_97, 4_72, 7_18, 4_85], [7_32, 4_72, 8_35, 4_88], [3_69, 4_90, 4_11, 5_03], [4_25, 4_90, 4_84, 5_03], [4_96, 4_90, 6_35, 5_06], [6_45, 4_90, 7_07, 5_03], [7_18, 4_91, 7_61, 5_03], [7_71, 4_90, 8_40, 5_03], [3_36, 5_10, 3_74, 5_21], [3_88, 5_10, 4_47, 5_22], [4_60, 5_10, 4_89, 5_21], [5_03, 5_10, 5_80, 5_22], [5_92, 5_09, 7_36, 5_25], [7_45, 5_09, 7_70, 5_22], [7_81, 5_09, 8_40, 5_22], [3_38, 5_28, 4_34, 5_41], [4_48, 5_28, 5_96, 5_41], [6_09, 5_27, 6_87, 5_40], [7_00, 5_28, 7_92, 5_41], [3_36, 5_46, 3_97, 5_59], [4_07, 5_46, 4_31, 5_59], [4_43, 5_46, 5_25, 5_60], [5_37, 5_46, 6_80, 5_62], [6_88, 5_46, 7_14, 5_59], [7_22, 5_46, 8_37, 5_62], [3_36, 5_65, 4_49, 5_81], [4_61, 5_65, 4_85, 5_77], [4_97, 5_65, 6_65, 5_81], [6_81, 5_65, 7_18, 5_77], [7_32, 5_65, 8_37, 5_80], [3_37, 5_84, 4_38, 5_97], [4_52, 5_83, 5_21, 5_96], [5_35, 5_84, 6_77, 5_99], [6_90, 5_83, 7_87, 5_96], [8_01, 5_83, 8_25, 5_96], [3_38, 6_02, 4_78, 6_15], [4_92, 6_02, 5_30, 6_14], [5_43, 6_02, 6_38, 6_15], [6_50, 6_02, 6_76, 6_14], [6_88, 6_02, 7_88, 6_15], [8_02, 6_02, 8_43, 6_14], [3_37, 6_21, 5_02, 6_33], [5_16, 6_21, 6_15, 6_37], [6_29, 6_21, 7_74, 6_36], [7_89, 6_21, 8_27, 6_33], [3_37, 6_39, 4_18, 6_52], [4_32, 6_40, 5_71, 6_53], [5_87, 6_39, 7_31, 6_55], [7_43, 6_39, 7_69, 6_52], [7_80, 6_39, 8_41, 6_52], [3_38, 6_58, 4_40, 6_73], [4_55, 6_58, 4_91, 6_70], [5_08, 6_58, 6_02, 6_71], [6_16, 6_58, 6_38, 6_70], [6_54, 6_58, 8_35, 6_74], [3_37, 6_77, 4_29, 6_89], [3_37, 7_14, 4_82, 7_26], [4_95, 7_14, 5_48, 7_26], [5_61, 7_14, 6_83, 7_26], [3_38, 7_70, 4_61, 7_82], [4_74, 7_69, 5_54, 7_85], [4_89, 7_88, 5_62, 8_03], [5_76, 7_88, 6_43, 8_01], [6_56, 7_87, 7_51, 8_04], [7_64, 7_88, 8_44, 8_01], [3_34, 8_25, 4_21, 8_38], [4_30, 8_24, 5_74, 8_38], [5_84, 8_24, 7_23, 8_41], [3_35, 8_44, 4_50, 8_57], [4_64, 8_43, 5_83, 8_60], [6_28, 8_62, 7_55, 8_75], [7_69, 8_61, 8_48, 8_78]]]  # noqa: E231
     # fmt: on

     self.assertListEqual(encoding.words ,			_lowercase   )
     self.assertListEqual(encoding.boxes ,			_lowercase   )

     # with apply_OCR = False
     SCREAMING_SNAKE_CASE__    							=   LayoutLMvaImageProcessor(apply_ocr=_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   image_processing(_lowercase ,			return_tensors="""pt"""   )

     self.assertEqual(encoding.pixel_values.shape ,			(1, 3, 2_24, 2_24)   )

import re
import tempfile
from pathlib import Path

import pytest
import yaml

from datasets.utils.readme import ReadMe


# @pytest.fixture
# def example_yaml_structure():

__lowerCamelCase    :				str							     =	yaml.safe_load(
    '''\
name: ""
allow_empty: false
allow_empty_text: true
subsections:
  - name: "Dataset Card for X" # First-level markdown heading
    allow_empty: false
    allow_empty_text: true
    subsections:
      - name: "Table of Contents"
        allow_empty: false
        allow_empty_text: false
        subsections: null
      - name: "Dataset Description"
        allow_empty: false
        allow_empty_text: false
        subsections:
          - name: "Dataset Summary"
            allow_empty: false
            allow_empty_text: false
            subsections: null
          - name: "Supported Tasks and Leaderboards"
            allow_empty: true
            allow_empty_text: true
            subsections: null
          - name: Languages
            allow_empty: false
            allow_empty_text: true
            subsections: null
'''
)


__lowerCamelCase    :				str							     =	{
    '''name''': '''root''',
    '''text''': '''''',
    '''is_empty_text''': True,
    '''subsections''': [
        {
            '''name''': '''Dataset Card for My Dataset''',
            '''text''': '''''',
            '''is_empty_text''': True,
            '''subsections''': [
                {'''name''': '''Table of Contents''', '''text''': '''Some text here.''', '''is_empty_text''': False, '''subsections''': []},
                {
                    '''name''': '''Dataset Description''',
                    '''text''': '''Some text here.''',
                    '''is_empty_text''': False,
                    '''subsections''': [
                        {
                            '''name''': '''Dataset Summary''',
                            '''text''': '''Some text here.''',
                            '''is_empty_text''': False,
                            '''subsections''': [],
                        },
                        {
                            '''name''': '''Supported Tasks and Leaderboards''',
                            '''text''': '''''',
                            '''is_empty_text''': True,
                            '''subsections''': [],
                        },
                        {'''name''': '''Languages''', '''text''': '''Language Text''', '''is_empty_text''': False, '''subsections''': []},
                    ],
                },
            ],
        }
    ],
}


__lowerCamelCase    :				Any							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''


__lowerCamelCase    :				List[Any]							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
#### Extra Ignored Subsection
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

__lowerCamelCase    :				Dict							     =	{
    '''name''': '''root''',
    '''text''': '''''',
    '''is_empty_text''': True,
    '''subsections''': [
        {
            '''name''': '''Dataset Card for My Dataset''',
            '''text''': '''''',
            '''is_empty_text''': True,
            '''subsections''': [
                {'''name''': '''Table of Contents''', '''text''': '''Some text here.''', '''is_empty_text''': False, '''subsections''': []},
                {
                    '''name''': '''Dataset Description''',
                    '''text''': '''Some text here.''',
                    '''is_empty_text''': False,
                    '''subsections''': [
                        {
                            '''name''': '''Dataset Summary''',
                            '''text''': '''Some text here.''',
                            '''is_empty_text''': False,
                            '''subsections''': [
                                {
                                    '''name''': '''Extra Ignored Subsection''',
                                    '''text''': '''''',
                                    '''is_empty_text''': True,
                                    '''subsections''': [],
                                }
                            ],
                        },
                        {
                            '''name''': '''Supported Tasks and Leaderboards''',
                            '''text''': '''''',
                            '''is_empty_text''': True,
                            '''subsections''': [],
                        },
                        {'''name''': '''Languages''', '''text''': '''Language Text''', '''is_empty_text''': False, '''subsections''': []},
                    ],
                },
            ],
        }
    ],
}

__lowerCamelCase    :				int							     =	'''\
---
---
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

__lowerCamelCase    :				Any							     =	(
    '''The following issues were found for the README at `{path}`:\n-\tEmpty YAML markers are present in the README.'''
)

__lowerCamelCase    :				List[Any]							     =	'''\
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

__lowerCamelCase    :				List[str]							     =	(
    '''The following issues were found for the README at `{path}`:\n-\tNo YAML markers are present in the README.'''
)

__lowerCamelCase    :				List[str]							     =	'''\
---
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

__lowerCamelCase    :				List[Any]							     =	'''The following issues were found for the README at `{path}`:\n-\tOnly the start of YAML tags present in the README.'''

__lowerCamelCase    :				str							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
### Supported Tasks and Leaderboards
### Languages
Language Text
'''
__lowerCamelCase    :				Any							     =	'''The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Dataset Summary` but it is empty.\n-\tExpected some text in section `Dataset Summary` but it is empty (text in subsections are ignored).'''


__lowerCamelCase    :				List[Any]							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
'''
__lowerCamelCase    :				int							     =	'''The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Dataset Card for My Dataset` but it is empty.\n-\tSection `Dataset Card for My Dataset` expected the following subsections: `Table of Contents`, `Dataset Description`. Found \'None\'.'''

__lowerCamelCase    :				Optional[int]							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Languages
Language Text
'''

__lowerCamelCase    :				Union[str, Any]							     =	'''The following issues were found for the README at `{path}`:\n-\tSection `Dataset Description` is missing subsection: `Supported Tasks and Leaderboards`.'''


__lowerCamelCase    :				Optional[Any]							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
'''

__lowerCamelCase    :				Tuple							     =	'''The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Languages` but it is empty.'''

__lowerCamelCase    :				List[str]							     =	'''\
---
language:
- zh
- en
---

## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''
__lowerCamelCase    :				List[str]							     =	'''The following issues were found for the README at `{path}`:\n-\tThe README has no first-level headings. One heading is expected. Skipping further validation for this README.'''

__lowerCamelCase    :				int							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
# Dataset Card My Dataset
'''

__lowerCamelCase    :				int							     =	'''The following issues were found for the README at `{path}`:\n-\tThe README has several first-level headings: `Dataset Card for My Dataset`, `Dataset Card My Dataset`. Only one heading is expected. Skipping further validation for this README.'''

__lowerCamelCase    :				List[Any]							     =	'''\
---
language:
- zh
- en
---

# Dataset Card My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

__lowerCamelCase    :				int							     =	'''The following issues were found for the README at `{path}`:\n-\tNo first-level heading starting with `Dataset Card for` found in README. Skipping further validation for this README.'''

__lowerCamelCase    :				Optional[Any]							     =	''''''

__lowerCamelCase    :				Any							     =	'''The following issues were found for the README at `{path}`:\n-\tThe README has no first-level headings. One heading is expected. Skipping further validation for this README.\n-\tNo YAML markers are present in the README.'''

__lowerCamelCase    :				str							     =	'''\
---
language:
- zh
- en
---

# Dataset Card for My Dataset
# Dataset Card for My Dataset
## Table of Contents
Some text here.
## Dataset Description
Some text here.
### Dataset Summary
Some text here.
### Supported Tasks and Leaderboards
### Languages
Language Text
'''

__lowerCamelCase    :				Dict							     =	'''The following issues were found while parsing the README at `{path}`:\n-\tMultiple sections with the same heading `Dataset Card for My Dataset` have been found. Please keep only one of these sections.'''



@pytest.mark.parametrize(
    """readme_md, expected_dict"""				,  [
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: Union[str, Any]				,  __UpperCamelCase					: Union[str, Any]			)							->      Dict:







  """simple docstring"""





  assert ReadMe.from_string(__UpperCamelCase				,  __UpperCamelCase			).to_dict() == expected_dict



@pytest.mark.parametrize(
    """readme_md, expected_error"""				,  [
        (README_NO_YAML, EXPECTED_ERROR_README_NO_YAML),
        (README_EMPTY_YAML, EXPECTED_ERROR_README_EMPTY_YAML),
        (README_INCORRECT_YAML, EXPECTED_ERROR_README_INCORRECT_YAML),
        (README_EMPTY, EXPECTED_ERROR_README_EMPTY),
        (README_NONE_SUBSECTION, EXPECTED_ERROR_README_NONE_SUBSECTION),
        (README_MISSING_FIRST_LEVEL, EXPECTED_ERROR_README_MISSING_FIRST_LEVEL),
        (README_MISSING_SUBSECTION, EXPECTED_ERROR_README_MISSING_SUBSECTION),
        (README_MISSING_TEXT, EXPECTED_ERROR_README_MISSING_TEXT),
        (README_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_WRONG_FIRST_LEVEL),
        (README_MULTIPLE_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_MULTIPLE_WRONG_FIRST_LEVEL),
        (README_MISSING_CONTENT, EXPECTED_ERROR_README_MISSING_CONTENT),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: Optional[Any]				,  __UpperCamelCase					: Dict			)							->      Union[str, Any]:







  """simple docstring"""





  with pytest.raises(__UpperCamelCase				,  match=re.escape(expected_error.format(path="""root"""			)			)			):
    SCREAMING_SNAKE_CASE__    							=   ReadMe.from_string(__UpperCamelCase				,  __UpperCamelCase			)
    readme.validate()



@pytest.mark.parametrize(
    """readme_md, expected_error"""				,  [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: Optional[int]				,  __UpperCamelCase					: Optional[Any]			)							->      Any:







  """simple docstring"""





  with pytest.raises(__UpperCamelCase				,  match=re.escape(expected_error.format(path="""root"""			)			)			):
    ReadMe.from_string(__UpperCamelCase				,  __UpperCamelCase			)



@pytest.mark.parametrize(
    """readme_md,"""				,  [
        (README_MULTIPLE_SAME_HEADING_1),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: Optional[int]			)							->      List[Any]:







  """simple docstring"""





  ReadMe.from_string(__UpperCamelCase				,  __UpperCamelCase				,  suppress_parsing_errors=__UpperCamelCase			)



@pytest.mark.parametrize(
    """readme_md, expected_dict"""				,  [
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: Any				,  __UpperCamelCase					: Union[str, Any]			)							->      Dict:







  """simple docstring"""





  with tempfile.TemporaryDirectory() as tmp_dir:
    SCREAMING_SNAKE_CASE__    							=   Path(__UpperCamelCase			) / """README.md"""
    with open(__UpperCamelCase				,  """w+"""			) as readme_file:
      readme_file.write(__UpperCamelCase			)
    SCREAMING_SNAKE_CASE__    							=   ReadMe.from_readme(__UpperCamelCase				,  __UpperCamelCase			).to_dict()
    assert out["name"] == path
    assert out["text"] == ""
    assert out["is_empty_text"]
    assert out["subsections"] == expected_dict["subsections"]



@pytest.mark.parametrize(
    """readme_md, expected_error"""				,  [
        (README_NO_YAML, EXPECTED_ERROR_README_NO_YAML),
        (README_EMPTY_YAML, EXPECTED_ERROR_README_EMPTY_YAML),
        (README_INCORRECT_YAML, EXPECTED_ERROR_README_INCORRECT_YAML),
        (README_EMPTY, EXPECTED_ERROR_README_EMPTY),
        (README_NONE_SUBSECTION, EXPECTED_ERROR_README_NONE_SUBSECTION),
        (README_MISSING_FIRST_LEVEL, EXPECTED_ERROR_README_MISSING_FIRST_LEVEL),
        (README_MISSING_SUBSECTION, EXPECTED_ERROR_README_MISSING_SUBSECTION),
        (README_MISSING_TEXT, EXPECTED_ERROR_README_MISSING_TEXT),
        (README_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_WRONG_FIRST_LEVEL),
        (README_MULTIPLE_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_MULTIPLE_WRONG_FIRST_LEVEL),
        (README_MISSING_CONTENT, EXPECTED_ERROR_README_MISSING_CONTENT),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: List[str]				,  __UpperCamelCase					: Any			)							->      Optional[Any]:







  """simple docstring"""





  with tempfile.TemporaryDirectory() as tmp_dir:
    SCREAMING_SNAKE_CASE__    							=   Path(__UpperCamelCase			) / """README.md"""
    with open(__UpperCamelCase				,  """w+"""			) as readme_file:
      readme_file.write(__UpperCamelCase			)
    SCREAMING_SNAKE_CASE__    							=   expected_error.format(path=__UpperCamelCase			)
    with pytest.raises(__UpperCamelCase				,  match=re.escape(__UpperCamelCase			)			):
      SCREAMING_SNAKE_CASE__    							=   ReadMe.from_readme(__UpperCamelCase				,  __UpperCamelCase			)
      readme.validate()



@pytest.mark.parametrize(
    """readme_md, expected_error"""				,  [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: List[Any]				,  __UpperCamelCase					: Optional[int]			)							->      Optional[Any]:







  """simple docstring"""





  with tempfile.TemporaryDirectory() as tmp_dir:
    SCREAMING_SNAKE_CASE__    							=   Path(__UpperCamelCase			) / """README.md"""
    with open(__UpperCamelCase				,  """w+"""			) as readme_file:
      readme_file.write(__UpperCamelCase			)
    SCREAMING_SNAKE_CASE__    							=   expected_error.format(path=__UpperCamelCase			)
    with pytest.raises(__UpperCamelCase				,  match=re.escape(__UpperCamelCase			)			):
      ReadMe.from_readme(__UpperCamelCase				,  __UpperCamelCase			)






@pytest.mark.parametrize(
    """readme_md,"""				,  [
        (README_MULTIPLE_SAME_HEADING_1),
    ]				,  )
def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: Optional[Any]			)							->      List[Any]:







  """simple docstring"""





  with tempfile.TemporaryDirectory() as tmp_dir:
    SCREAMING_SNAKE_CASE__    							=   Path(__UpperCamelCase			) / """README.md"""
    with open(__UpperCamelCase				,  """w+"""			) as readme_file:
      readme_file.write(__UpperCamelCase			)
    ReadMe.from_readme(__UpperCamelCase				,  __UpperCamelCase				,  suppress_parsing_errors=__UpperCamelCase			)
