





# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


UpperCAmelCase	:	Optional[Any]		     =       subprocess.check_output("""git merge-base main HEAD""".split()).decode("""utf-8""")
UpperCAmelCase	:	Optional[Any]		     =       subprocess.check_output(F"""git diff --name-only {fork_point_sha}""".split()).decode("""utf-8""").split()

UpperCAmelCase	:	Dict		     =       """|""".join(sys.argv[1:])
UpperCAmelCase	:	Optional[Any]		     =       re.compile(rF"""^({joined_dirs}).*?\.py$""")

UpperCAmelCase	:	List[str]		     =       [x for x in modified_files if regex.match(x)]
print(""" """.join(relevant_modified_files), end="""""")













from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader







class 				__lowerCAmelCase       (    UpperCamelCase__):







      def __init__(    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None		,      lowerCAmelCase__ = None		,      lowerCAmelCase__ = True		,      lowerCAmelCase__ = None		,      lowerCAmelCase__ = False		,      lowerCAmelCase__ = None		,      lowerCAmelCase__ = True		,      lowerCAmelCase__ = "arrow"		,      **lowerCAmelCase__		,      )   ->						Optional[int]:



        '''simple docstring'''




        super().__init__(
            split=lowerCAmelCase__		,      features=lowerCAmelCase__		,      cache_dir=lowerCAmelCase__		,      keep_in_memory=lowerCAmelCase__		,      streaming=lowerCAmelCase__		,      **lowerCAmelCase__		,      )
        a__	:					int										=load_from_cache_file
        a__	:					Tuple										=file_format
        a__	:					List[Any]										=Spark(
            df=lowerCAmelCase__		,      features=lowerCAmelCase__		,      cache_dir=lowerCAmelCase__		,      working_dir=lowerCAmelCase__		,      **lowerCAmelCase__		,      )







      def    _lowercase  (    self							)   ->						str:



        '''simple docstring'''




        if self.streaming:
          return self.builder.as_streaming_dataset(split=self.split							)
        a__	:					str										=None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
        self.builder.download_and_prepare(
            download_mode=lowerCAmelCase__		,      file_format=self._file_format		,      )
        return self.builder.as_dataset(split=self.split							)






