



'''simple docstring'''



import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil



@pytest.fixture
def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[Any]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "file.csv"
	__lowerCAmelCase												=  textwrap.dedent(
	    "\\n        header1,header2\n        1,2\n        10,20\n        "					)
	with open(lowerCamelCase				,		"w"					) as f:
		f.write(lowerCamelCase					)
	return str(lowerCamelCase					)



@pytest.fixture
def   __lowerCAmelCase					(							lowerCamelCase   :						Tuple					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "malformed_file.csv"
	__lowerCAmelCase												=  textwrap.dedent(
	    "\\n        header1,header2\n        1,2\n        10,20,\n        "					)
	with open(lowerCamelCase				,		"w"					) as f:
		f.write(lowerCamelCase					)
	return str(lowerCamelCase					)



@pytest.fixture
def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						List[str]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "csv_with_image.csv"
	__lowerCAmelCase												=  textwrap.dedent(
	    f'''\
        image
        {image_file}
        '''					)
	with open(lowerCamelCase				,		"w"					) as f:
		f.write(lowerCamelCase					)
	return str(lowerCamelCase					)



@pytest.fixture
def   __lowerCAmelCase					(							lowerCamelCase   :						int					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "csv_with_label.csv"
	__lowerCAmelCase												=  textwrap.dedent(
	    "\\n        label\n        good\n        bad\n        good\n        "					)
	with open(lowerCamelCase				,		"w"					) as f:
		f.write(lowerCamelCase					)
	return str(lowerCamelCase					)



@pytest.fixture
def   __lowerCAmelCase					(							lowerCamelCase   :						Dict					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "csv_with_int_list.csv"
	__lowerCAmelCase												=  textwrap.dedent(
	    "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        "					)
	with open(lowerCamelCase				,		"w"					) as f:
		f.write(lowerCamelCase					)
	return str(lowerCamelCase					)



def   __lowerCAmelCase					(							lowerCamelCase   :						Dict				,		lowerCamelCase   :						str				,		lowerCamelCase   :						Any					):






	'''simple docstring'''




	__lowerCAmelCase												=  Csv()
	__lowerCAmelCase												=  csv._generate_tables([[csv_file, malformed_csv_file]]					)
	with pytest.raises(lowerCamelCase				,		match="Error tokenizing data"					):
		for _ in generator:
			pass
	assert any(
	    record.levelname == "ERROR"
	    and "Failed to read file" in record.message
	    and os.path.basename(lowerCamelCase					) in record.message
	    for record in caplog.records					)



@require_pil
def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[int]					):






	'''simple docstring'''




	with open(lowerCamelCase				,		encoding="utf-8"					) as f:
		__lowerCAmelCase												=  f.read().splitlines()[1]
	__lowerCAmelCase												=  Csv(encoding="utf-8"				,		features=Features({"image": Image()}					)					)
	__lowerCAmelCase												=  csv._generate_tables([[csv_file_with_image]]					)
	__lowerCAmelCase												=  pa.concat_tables([table for _, table in generator]					)
	assert pa_table.schema.field("image"					).type == Image()()
	__lowerCAmelCase												=  pa_table.to_pydict()["image"]
	assert generated_content == [{"path": image_file, "bytes": None}]



def   __lowerCAmelCase					(							lowerCamelCase   :						Tuple					):






	'''simple docstring'''




	with open(lowerCamelCase				,		encoding="utf-8"					) as f:
		__lowerCAmelCase												=  f.read().splitlines()[1:]
	__lowerCAmelCase												=  Csv(encoding="utf-8"				,		features=Features({"label": ClassLabel(names=["good", "bad"]					)}					)					)
	__lowerCAmelCase												=  csv._generate_tables([[csv_file_with_label]]					)
	__lowerCAmelCase												=  pa.concat_tables([table for _, table in generator]					)
	assert pa_table.schema.field("label"					).type == ClassLabel(names=["good", "bad"]					)()
	__lowerCAmelCase												=  pa_table.to_pydict()["label"]
	assert generated_content == [ClassLabel(names=["good", "bad"]					).straint(lowerCamelCase					) for label in labels]




def   __lowerCAmelCase					(							lowerCamelCase   :						Dict					):






	'''simple docstring'''




	__lowerCAmelCase												=  Csv(encoding="utf-8"				,		sep=","				,		converters={"int_list": lambda lowerCamelCase					: [int(lowerCamelCase					) for i in x.split()]}					)
	__lowerCAmelCase												=  csv._generate_tables([[csv_file_with_int_list]]					)
	__lowerCAmelCase												=  pa.concat_tables([table for _, table in generator]					)
	assert pa.types.is_list(pa_table.schema.field("int_list"					).type					)
	__lowerCAmelCase												=  pa_table.to_pydict()["int_list"]
	assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]




'''simple docstring'''



import requests
from bsa import BeautifulSoup



def   __lowerCAmelCase					(							lowerCamelCase   :						str = "https://www.worldometers.info/coronavirus"					):






	'''simple docstring'''




	__lowerCAmelCase												=  BeautifulSoup(requests.get(lowerCamelCase					).text				,		"html.parser"					)
	__lowerCAmelCase												=  soup.findAll("h1"					)
	__lowerCAmelCase												=  soup.findAll("div"				,		{"class": "maincounter-number"}					)
	keys += soup.findAll("span"				,		{"class": "panel-title"}					)
	values += soup.findAll("div"				,		{"class": "number-table-main"}					)
	return {key.text.strip(): value.text.strip() for key, value in zip(lowerCamelCase				,		lowerCamelCase					)}


if __name__ == "__main__":
	print('''\033[1m''' + '''COVID-19 Status of the World''' + '''\033[0m\n''')
	for key, value in world_covidaa_stats().items():
		print(f'{key}\n{value}\n')