
import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader

class __snake_case		(      lowerCAmelCase     ):
    def __init__(  self		,snake_case		,snake_case = None		,snake_case = None		,snake_case = None		,snake_case = False		,snake_case = False		,snake_case = None		,snake_case = None		,**snake_case		,):



           '''simple docstring'''







           super().__init__(
               snake_case		,split=snake_case		,features=snake_case		,cache_dir=snake_case		,keep_in_memory=snake_case		,streaming=snake_case		,num_proc=snake_case		,**snake_case		,)
           lowercase							:     Optional[Any]       	=      field
           lowercase							:     str       	=      path_or_paths if isinstance(snake_case		,snake_case      ) else {self.split: path_or_paths}
           lowercase							:     Dict       	=      Json(
               cache_dir=snake_case		,data_files=snake_case		,features=snake_case		,field=snake_case		,**snake_case		,)
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           if self.streaming:
                  lowercase							:     List[Any]       	=      self.builder.as_streaming_dataset(split=self.split      )
           # Build regular (map-style) dataset
           else:
                  lowercase							:     List[str]       	=      None
                  lowercase							:     Any       	=      None
                  lowercase							:     List[str]       	=      None
                  lowercase							:     str       	=      None

                  self.builder.download_and_prepare(
                      download_config=snake_case		,download_mode=snake_case		,verification_mode=snake_case		,base_path=snake_case		,num_proc=self.num_proc		,)
                  lowercase							:     Optional[int]       	=      self.builder.as_dataset(
                      split=self.split		,verification_mode=snake_case		,in_memory=self.keep_in_memory      )
           return dataset






class __snake_case		:
    def __init__(  self		,snake_case		,snake_case		,snake_case = None		,snake_case = None		,**snake_case		,):



           '''simple docstring'''







           if num_proc is not None and num_proc <= 0:
                  raise ValueError(f"num_proc {num_proc} must be an integer > 0."      )

           lowercase							:     Tuple       	=      dataset
           lowercase							:     Optional[int]       	=      path_or_buf
           lowercase							:     Optional[Any]       	=      batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
           lowercase							:     Optional[Any]       	=      num_proc
           lowercase							:     Tuple       	=      """utf-8"""
           lowercase							:     Tuple       	=      to_json_kwargs
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Dict       	=      self.to_json_kwargs.pop("""path_or_buf"""		,snake_case      )
           lowercase							:     Tuple       	=      self.to_json_kwargs.pop("""orient"""		,"""records"""      )
           lowercase							:     List[str]       	=      self.to_json_kwargs.pop("""lines"""		,True if orient == """records""" else False      )
           lowercase							:     Optional[int]       	=      self.to_json_kwargs.pop("""index"""		,False if orient in ["""split""", """table"""] else True      )
           lowercase							:     str       	=      self.to_json_kwargs.pop("""compression"""		,snake_case      )

           if compression not in [None, "infer", "gzip", "bz2", "xz"]:
                  raise NotImplementedError(f"`datasets` currently does not support {compression} compression"      )

           if isinstance(self.path_or_buf		,(str, bytes, os.PathLike)      ):
                  with fsspec.open(self.path_or_buf		,"""wb"""		,compression=snake_case      ) as buffer:
                         lowercase							:     Union[str, Any]       	=      self._write(file_obj=snake_case		,orient=snake_case		,lines=snake_case		,index=snake_case		,**self.to_json_kwargs      )
           else:
                  if compression:
                         raise NotImplementedError(
                             f"The compression parameter is not supported when writing to a buffer, but compression={compression}"
                             """ was passed. Please provide a local path instead."""      )
                  lowercase							:     Tuple       	=      self._write(
                      file_obj=self.path_or_buf		,orient=snake_case		,lines=snake_case		,index=snake_case		,**self.to_json_kwargs      )
           return written
    def       _SCREAMING_SNAKE_CASE       (  self		,snake_case      ):



           '''simple docstring'''







           lowercase	,			lowercase	,			lowercase	,			lowercase	,			lowercase							:     Any       	=      args

           lowercase							:     Optional[Any]       	=      query_table(
               table=self.dataset.data		,key=slice(snake_case		,offset + self.batch_size      )		,indices=self.dataset._indices		,)
           lowercase							:     Any       	=      batch.to_pandas().to_json(
               path_or_buf=snake_case		,orient=snake_case		,lines=snake_case		,index=snake_case		,**snake_case      )
           if not json_str.endswith("""\n"""      ):
                  json_str += "\n"
           return json_str.encode(self.encoding      )
    def       _SCREAMING_SNAKE_CASE       (  self		,snake_case		,snake_case		,snake_case		,snake_case		,**snake_case		,):



           '''simple docstring'''







           lowercase							:     Optional[int]       	=      0

           if self.num_proc is None or self.num_proc == 1:
                  for offset in logging.tqdm(
                      range(0		,len(self.dataset      )		,self.batch_size      )		,unit="""ba"""		,disable=not logging.is_progress_bar_enabled()		,desc="""Creating json from Arrow format"""		,):
                         lowercase							:     Any       	=      self._batch_json((offset, orient, lines, index, to_json_kwargs)      )
                         written += file_obj.write(snake_case      )
           else:
                  lowercase	,			lowercase							:     int       	=      len(self.dataset      ), self.batch_size
                  with multiprocessing.Pool(self.num_proc      ) as pool:
                         for json_str in logging.tqdm(
                             pool.imap(
                                 self._batch_json		,[(offset, orient, lines, index, to_json_kwargs) for offset in range(0		,snake_case		,snake_case      )]		,)		,total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size		,unit="""ba"""		,disable=not logging.is_progress_bar_enabled()		,desc="""Creating json from Arrow format"""		,):
                                written += file_obj.write(snake_case      )

           return written


import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Any:
       assert isinstance(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
       assert dataset.num_rows == 4
       assert dataset.num_columns == 3
       assert dataset.column_names == ["col_1", "col_2", "col_3"]
       for feature, expected_dtype in expected_features.items():
              assert dataset.features[feature].dtype == expected_dtype







@require_sqlalchemy
@pytest.mark.parametrize("""keep_in_memory"""					,	[False, True]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Union[str, Any]:
       lowercase							:     Union[str, Any]       	=      tmp_path / """cache"""
       lowercase							:     Optional[Any]       	=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
       with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
              lowercase							:     Any       	=      SqlDatasetReader(
                  """dataset"""					,	"""sqlite:///""" + sqlite_path					,	cache_dir=SCREAMING_SNAKE_CASE__					,	keep_in_memory=SCREAMING_SNAKE_CASE__				).read()
       _check_sql_dataset(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)







@require_sqlalchemy
@pytest.mark.parametrize(
    """features"""					,	[
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]					,	)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Tuple:
       lowercase							:     Union[str, Any]       	=      tmp_path / """cache"""
       lowercase							:     int       	=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
       lowercase							:     str       	=      features.copy() if features else default_expected_features
       lowercase							:     Optional[Any]       	=      (
           Features({feature: Value(SCREAMING_SNAKE_CASE__				) for feature, dtype in features.items()}				) if features is not None else None
       )
       lowercase							:     Optional[int]       	=      SqlDatasetReader("""dataset"""					,	"""sqlite:///""" + sqlite_path					,	features=SCREAMING_SNAKE_CASE__					,	cache_dir=SCREAMING_SNAKE_CASE__				).read()
       _check_sql_dataset(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    List[Any]:
       with contextlib.closing(sqlitea.connect(SCREAMING_SNAKE_CASE__				)				) as con:
              lowercase							:     Optional[int]       	=      con.cursor()
              cur.execute("""SELECT * FROM dataset"""				)
              for row in cur:
                     yield row







@require_sqlalchemy
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    int:
       lowercase							:     Any       	=      tmp_path / """cache"""
       lowercase							:     int       	=      os.path.join(SCREAMING_SNAKE_CASE__					,	"""tmp.sql"""				)
       lowercase							:     List[str]       	=      SqlDatasetReader("""dataset"""					,	"""sqlite:///""" + sqlite_path					,	cache_dir=SCREAMING_SNAKE_CASE__				).read()
       SqlDatasetWriter(SCREAMING_SNAKE_CASE__					,	"""dataset"""					,	"""sqlite:///""" + output_sqlite_path					,	num_proc=1				).write()

       lowercase							:     List[str]       	=      iter_sql_file(SCREAMING_SNAKE_CASE__				)
       lowercase							:     Tuple       	=      iter_sql_file(SCREAMING_SNAKE_CASE__				)

       for rowa, rowa in zip(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				):
              assert rowa == rowa







@require_sqlalchemy
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Dict:
       lowercase							:     Dict       	=      tmp_path / """cache"""
       lowercase							:     List[str]       	=      os.path.join(SCREAMING_SNAKE_CASE__					,	"""tmp.sql"""				)
       lowercase							:     List[str]       	=      SqlDatasetReader("""dataset"""					,	"""sqlite:///""" + sqlite_path					,	cache_dir=SCREAMING_SNAKE_CASE__				).read()
       SqlDatasetWriter(SCREAMING_SNAKE_CASE__					,	"""dataset"""					,	"""sqlite:///""" + output_sqlite_path					,	num_proc=2				).write()

       lowercase							:     Optional[int]       	=      iter_sql_file(SCREAMING_SNAKE_CASE__				)
       lowercase							:     List[Any]       	=      iter_sql_file(SCREAMING_SNAKE_CASE__				)

       for rowa, rowa in zip(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				):
              assert rowa == rowa







@require_sqlalchemy
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    List[str]:
       lowercase							:     str       	=      tmp_path / """cache"""
       lowercase							:     Optional[int]       	=      os.path.join(SCREAMING_SNAKE_CASE__					,	"""tmp.sql"""				)
       lowercase							:     Optional[Any]       	=      SqlDatasetReader("""dataset"""					,	"""sqlite:///""" + sqlite_path					,	cache_dir=SCREAMING_SNAKE_CASE__				).read()
       with pytest.raises(SCREAMING_SNAKE_CASE__				):
              SqlDatasetWriter(SCREAMING_SNAKE_CASE__					,	"""dataset"""					,	"""sqlite:///""" + output_sqlite_path					,	num_proc=0				).write()
