



"""simple docstring"""





import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def 						__lowerCAmelCase    (		__UpperCamelCase   :      dict     ):


						'''simple docstring'''






						return (data["data"], data["target"])
def 						__lowerCAmelCase    (		__UpperCamelCase   :      np.ndarray       ,			__UpperCamelCase   :      np.ndarray       ,			__UpperCamelCase   :      np.ndarray     ):


						'''simple docstring'''






						snake_case_ :			Optional[Any]            =      XGBRegressor(verbosity=0       ,			random_state=4_2     )
						xgb.fit(__UpperCamelCase       ,			__UpperCamelCase     )
						# Predict target for test data
						snake_case_ :			List[str]            =      xgb.predict(__UpperCamelCase     )
						snake_case_ :			str            =      predictions.reshape(len(__UpperCamelCase     )       ,			1     )
						return predictions
def 						__lowerCAmelCase    (		):


						'''simple docstring'''






						snake_case_ :			Any            =      fetch_california_housing()
						snake_case_      ,		snake_case_ :			Dict            =      data_handling(__UpperCamelCase     )
						snake_case_      ,		snake_case_      ,		snake_case_      ,		snake_case_ :			int            =      train_test_split(
						    __UpperCamelCase       ,			__UpperCamelCase       ,			test_size=0.25       ,			random_state=1     )
						snake_case_ :			Union[str, Any]            =      xgboost(__UpperCamelCase       ,			__UpperCamelCase       ,			__UpperCamelCase     )
						# Error printing
						print(F'Mean Absolute Error : {mean_absolute_error(__UpperCamelCase       ,			__UpperCamelCase     )}'     )
						print(F'Mean Square Error  : {mean_squared_error(__UpperCamelCase       ,			__UpperCamelCase     )}'     )


if __name__ == "__main__":
					import doctest

					doctest.testmod(verbose=True)
					main()


'''simple docstring'''






import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


_UpperCAmelCase    :     Optional[int]         =       '''\
    Text data.
    Second line of data.'''

_UpperCAmelCase    :     Optional[Any]         =       '''file'''





@pytest.fixture(scope='session'				)
def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Any				):
     _A    		=  tmp_path_factory.mktemp('data'				) / (FILE_PATH + '.zstd')
     _A    		=  bytes(__snake_case   ,		'utf-8'				)
     with zstd.open(__snake_case   ,		'wb'				) as f:
          f.write(__snake_case				)
     return path





@pytest.fixture
def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Union[str, Any]				):
     with open(os.path.join(tmpfs.local_root_dir   ,		__snake_case				)   ,		'w'				) as f:
          f.write(__snake_case				)
     return FILE_PATH





@pytest.mark.parametrize('compression_format'   ,		['gzip', 'xz', 'zstd']				)
def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Dict   ,		__snake_case							:			str   ,		__snake_case							:			Any   ,		__snake_case							:			Any   ,		__snake_case							:			List[str]   ,		__snake_case							:			List[str]				):
     _A    		=  {'gzip': gz_file, 'xz': xz_file, 'zstd': zstd_path}
     _A    		=  input_paths[compression_format]
     _A    		=  tmp_path / 'cache'
     _A    		=  DownloadConfig(cache_dir=__snake_case   ,		extract_compressed_file=__snake_case				)
     _A    		=  cached_path(__snake_case   ,		download_config=__snake_case				)
     with open(__snake_case				) as f:
          _A    		=  f.read()
     with open(__snake_case				) as f:
          _A    		=  f.read()
     assert extracted_file_content == expected_file_content





@pytest.mark.parametrize('default_extracted'   ,		[True, False]				)
@pytest.mark.parametrize('default_cache_dir'   ,		[True, False]				)
def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Union[str, Any]   ,		__snake_case							:			List[str]   ,		__snake_case							:			Union[str, Any]   ,		__snake_case							:			int   ,		__snake_case							:			List[str]				):
     _A    		=  'custom_cache'
     _A    		=  'custom_extracted_dir'
     _A    		=  tmp_path / 'custom_extracted_path'
     if default_extracted:
          _A    		=  ('downloads' if default_cache_dir else custom_cache_dir, 'extracted')
     else:
          monkeypatch.setattr('datasets.config.EXTRACTED_DATASETS_DIR'   ,		__snake_case				)
          monkeypatch.setattr('datasets.config.EXTRACTED_DATASETS_PATH'   ,		str(__snake_case				)				)
          _A    		=  custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

     _A    		=  xz_file
     _A    		=  (
         DownloadConfig(extract_compressed_file=__snake_case				)
         if default_cache_dir
         else DownloadConfig(cache_dir=tmp_path / custom_cache_dir   ,		extract_compressed_file=__snake_case				)
     )
     _A    		=  cached_path(__snake_case   ,		download_config=__snake_case				)
     assert Path(__snake_case				).parent.parts[-2:] == expected





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			str				):
     # absolute path
     _A    		=  str(Path(__snake_case				).resolve()				)
     assert cached_path(__snake_case				) == text_file
     # relative path
     _A    		=  str(Path(__snake_case				).resolve().relative_to(Path(os.getcwd()				)				)				)
     assert cached_path(__snake_case				) == text_file





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			List[str]				):
     # absolute path
     _A    		=  str(tmp_path.resolve() / '__missing_file__.txt'				)
     with pytest.raises(__snake_case				):
          cached_path(__snake_case				)
     # relative path
     _A    		=  './__missing_file__.txt'
     with pytest.raises(__snake_case				):
          cached_path(__snake_case				)





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			int				):
     _A    		=  get_from_cache(F'tmp://{tmpfs_file}'				)
     with open(__snake_case				) as f:
          _A    		=  f.read()
     assert output_file_content == FILE_CONTENT





@patch('datasets.config.HF_DATASETS_OFFLINE'   ,		__snake_case				)
def  _SCREAMING_SNAKE_CASE		(      ):
     with pytest.raises(__snake_case				):
          cached_path('https://huggingface.co'				)





@patch('datasets.config.HF_DATASETS_OFFLINE'   ,		__snake_case				)
def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Tuple				):
     _A    		=  tmp_path_factory.mktemp('data'				) / 'file.html'
     with pytest.raises(__snake_case				):
          http_get('https://huggingface.co'   ,		temp_file=__snake_case				)
     with pytest.raises(__snake_case				):
          http_head('https://huggingface.co'				)





@patch('datasets.config.HF_DATASETS_OFFLINE'   ,		__snake_case				)
def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Optional[int]				):
     _A    		=  tmp_path_factory.mktemp('data'				) / 'file.html'
     with pytest.raises(__snake_case				):
          ftp_get('ftp://huggingface.co'   ,		temp_file=__snake_case				)
     with pytest.raises(__snake_case				):
          ftp_head('ftp://huggingface.co'				)





@patch('datasets.config.HF_DATASETS_OFFLINE'   ,		__snake_case				)
def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			List[str]				):
     _A    		=  tmp_path_factory.mktemp('data'				) / 'file.html'
     with pytest.raises(__snake_case				):
          fsspec_get('s3://huggingface.co'   ,		temp_file=__snake_case				)
     with pytest.raises(__snake_case				):
          fsspec_head('s3://huggingface.co'				)



