






import os
from typing import BinaryIO, Optional, Union

import numpy as np
import pyarrow.parquet as pq

from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MODULES
from ..packaged_modules.parquet.parquet import Parquet
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
def 						_a    (      a :Features )							->			Optional[int]:
 a		  =      np.inf

 def set_batch_size(a :FeatureType ) -> None:
  nonlocal batch_size
  if isinstance(a	,							a ):
   a		  =      min(a	,							config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS )
  elif isinstance(a	,							a ):
   a		  =      min(a	,							config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS )
  elif isinstance(a	,							a ) and feature.dtype == "binary":
   a		  =      min(a	,							config.PARQUET_ROW_GROUP_SIZE_FOR_BINARY_DATASETS )

 _visit(a	,							a )

 return None if batch_size is np.inf else batch_size






class 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      def __init__(      self      :						str ,					__UpperCAmelCase      :						NestedDataStructureLike[PathLike] ,					__UpperCAmelCase      :						Optional[NamedSplit] = None ,					__UpperCAmelCase      :						Optional[Features] = None ,					__UpperCAmelCase      :						str = None ,					__UpperCAmelCase      :						bool = False ,					__UpperCAmelCase      :						bool = False ,					__UpperCAmelCase      :						Optional[int] = None ,					**__UpperCAmelCase      :						List[Any] ,					)    ->List[Any]:




       """simple docstring"""


       super().__init__(
           __UpperCAmelCase ,					split=__UpperCAmelCase ,					features=__UpperCAmelCase ,					cache_dir=__UpperCAmelCase ,					keep_in_memory=__UpperCAmelCase ,					streaming=__UpperCAmelCase ,					num_proc=__UpperCAmelCase ,					**__UpperCAmelCase ,					)
       a		  =      path_or_paths if isinstance(__UpperCAmelCase ,					__UpperCAmelCase  ) else {self.split: path_or_paths}
       a		  =      _PACKAGED_DATASETS_MODULES['''parquet'''][1]
       a		  =      Parquet(
           cache_dir=__UpperCAmelCase ,					data_files=__UpperCAmelCase ,					features=__UpperCAmelCase ,					hash=__UpperCAmelCase ,					**__UpperCAmelCase ,					)







      def       __lowerCAmelCase					(      self      :						List[Any]  )    ->Optional[int]:




       """simple docstring"""


       if self.streaming:
        a		  =      self.builder.as_streaming_dataset(split=self.split  )
       # Build regular (map-style) dataset
       else:
        a		  =      None
        a		  =      None
        a		  =      None
        a		  =      None

        self.builder.download_and_prepare(
            download_config=__UpperCAmelCase ,					download_mode=__UpperCAmelCase ,					verification_mode=__UpperCAmelCase ,					base_path=__UpperCAmelCase ,					num_proc=self.num_proc ,					)
        a		  =      self.builder.as_dataset(
            split=self.split ,					verification_mode=__UpperCAmelCase ,					in_memory=self.keep_in_memory  )
       return dataset






class 		lowercase_					:






      '''simple docstring'''




      def __init__(      self      :						Union[str, Any] ,					__UpperCAmelCase      :						Dataset ,					__UpperCAmelCase      :						Union[PathLike, BinaryIO] ,					__UpperCAmelCase      :						Optional[int] = None ,					**__UpperCAmelCase      :						List[str] ,					)    ->Any:




       """simple docstring"""


       a		  =      dataset
       a		  =      path_or_buf
       a		  =      batch_size or get_writer_batch_size(dataset.features  )
       a		  =      parquet_writer_kwargs







      def       __lowerCAmelCase					(      self      :						Tuple  )    ->int:




       """simple docstring"""


       a		  =      self.batch_size if self.batch_size else config.DEFAULT_MAX_BATCH_SIZE

       if isinstance(self.path_or_buf ,					(str, bytes, os.PathLike)  ):
        with open(self.path_or_buf ,					'''wb+'''  ) as buffer:
         a		  =      self._write(file_obj=__UpperCAmelCase ,					batch_size=__UpperCAmelCase ,					**self.parquet_writer_kwargs  )
       else:
        a		  =      self._write(file_obj=self.path_or_buf ,					batch_size=__UpperCAmelCase ,					**self.parquet_writer_kwargs  )
       return written







      def       __lowerCAmelCase					(      self      :						List[Any] ,					__UpperCAmelCase      :						BinaryIO ,					__UpperCAmelCase      :						int ,					**__UpperCAmelCase      :						List[str]  )    ->int:




       """simple docstring"""


       a		  =      0
       a		  =      parquet_writer_kwargs.pop('''path_or_buf''' ,					__UpperCAmelCase  )
       a		  =      self.dataset.features.arrow_schema

       a		  =      pq.ParquetWriter(__UpperCAmelCase ,					schema=__UpperCAmelCase ,					**__UpperCAmelCase  )

       for offset in logging.tqdm(
           range(0 ,					len(self.dataset  ) ,					__UpperCAmelCase  ) ,					unit='''ba''' ,					disable=not logging.is_progress_bar_enabled() ,					desc='''Creating parquet from Arrow format''' ,					):
        a		  =      query_table(
            table=self.dataset._data ,					key=slice(__UpperCAmelCase ,					offset + batch_size  ) ,					indices=self.dataset._indices if self.dataset._indices is not None else None ,					)
        writer.write_table(__UpperCAmelCase  )
        written += batch.nbytes
       writer.close()
       return written










from __future__ import annotations

UpperCAmelCase__				   =		"Muhammad Umer Farooq"
UpperCAmelCase__				   =		"MIT"
UpperCAmelCase__				   =		"1.0.0"
UpperCAmelCase__				   =		"Muhammad Umer Farooq"
UpperCAmelCase__				   =		"contact@muhammadumerfarooq.me"
UpperCAmelCase__				   =		"Alpha"

import re
from html.parser import HTMLParser
from urllib import parse

import requests






class 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      def __init__(      self      :						Union[str, Any] ,					__UpperCAmelCase      :						str  )    ->None:




       """simple docstring"""


       super().__init__()
       a		  =      []
       a		  =      domain







      def       __lowerCAmelCase					(      self      :						List[str] ,					__UpperCAmelCase      :						str ,					__UpperCAmelCase      :						list[tuple[str, str | None]]  )    ->None:




       """simple docstring"""


       if tag == "a":
        # Check the list of defined attributes.
        for name, value in attrs:
         # If href is defined, and not empty nor # print it.
         if name == "href" and value != "#" and value != "":
          # If not already in urls.
          if value not in self.urls:
           a		  =      parse.urljoin(self.domain ,					__UpperCAmelCase  )
           self.urls.append(__UpperCAmelCase  )
def 						_a    (      a :str )							->			str:
 return ".".join(get_sub_domain_name(a ).split('''.''' )[-2:] )
def 						_a    (      a :str )							->			str:
 return parse.urlparse(a ).netloc
def 						_a    (      a :str = "https://github.com" )							->			list[str]:
 a		  =      get_domain_name(a )

 # Initialize the parser
 a		  =      Parser(a )

 try:
  # Open URL
  a		  =      requests.get(a )

  # pass the raw HTML to the parser to get links
  parser.feed(r.text )

  # Get links and loop through
  a		  =      set()
  for link in parser.urls:
   # open URL.
   # read = requests.get(link)
   try:
    a		  =      requests.get(a )
    # Get the valid email.
    a		  =      re.findall('''[a-zA-Z0-9]+@''' + domain	,							read.text )
    # If not in list then append it.
    for email in emails:
     valid_emails.add(a )
   except ValueError:
    pass
 except ValueError:
  raise SystemExit(1 )

 # Finally return a sorted list of email addresses with no duplicates.
 return sorted(a )


if __name__ == "__main__":
     UpperCAmelCase__				   =		emails_from_url("https://github.com")
     print(f"""{len(emails)} emails found:""")
     print("\n".join(sorted(emails)))


