
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,
)


lowercase        =  '''\
    Text data.
    Second line of data.'''

lowercase        =  '''file'''



@pytest.fixture(scope="""session"""       )
def      __lowerCAmelCase						(							UpperCAmelCase__				:      Optional[Any]       )  ->    int:
							lowerCamelCase_							  =					tmp_path_factory.mktemp("""data"""       ) / (FILE_PATH + """.zstd""")
							lowerCamelCase_							  =					bytes(lowerCAmelCase__			,				"""utf-8"""       )
							with zstd.open(lowerCAmelCase__			,				"""wb"""       ) as f:
														f.write(lowerCAmelCase__       )
							return path



@pytest.fixture
def      __lowerCAmelCase						(							UpperCAmelCase__				:      Union[str, Any]       )  ->    List[str]:
							with open(os.path.join(tmpfs.local_root_dir			,				lowerCAmelCase__       )			,				"""w"""       ) as f:
														f.write(lowerCAmelCase__       )
							return FILE_PATH



@pytest.mark.parametrize("""compression_format"""			,				["""gzip""", """xz""", """zstd"""]       )
def      __lowerCAmelCase						(							UpperCAmelCase__				:      List[str]			,				UpperCAmelCase__				:      Dict			,				UpperCAmelCase__				:      List[str]			,				UpperCAmelCase__				:      Tuple			,				UpperCAmelCase__				:      List[str]			,				UpperCAmelCase__				:      Optional[Any]       )  ->    Tuple:
							lowerCamelCase_							  =					{"""gzip""": gz_file, """xz""": xz_file, """zstd""": zstd_path}
							lowerCamelCase_							  =					input_paths[compression_format]
							lowerCamelCase_							  =					tmp_path / """cache"""
							lowerCamelCase_							  =					DownloadConfig(cache_dir=lowerCAmelCase__			,				extract_compressed_file=lowerCAmelCase__       )
							lowerCamelCase_							  =					cached_path(lowerCAmelCase__			,				download_config=lowerCAmelCase__       )
							with open(lowerCAmelCase__       ) as f:
														lowerCamelCase_							  =					f.read()
							with open(lowerCAmelCase__       ) as f:
														lowerCamelCase_							  =					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      __lowerCAmelCase						(							UpperCAmelCase__				:      Tuple			,				UpperCAmelCase__				:      str			,				UpperCAmelCase__				:      Dict			,				UpperCAmelCase__				:      List[str]			,				UpperCAmelCase__				:      Any       )  ->    int:
							lowerCamelCase_							  =					"""custom_cache"""
							lowerCamelCase_							  =					"""custom_extracted_dir"""
							lowerCamelCase_							  =					tmp_path / """custom_extracted_path"""
							if default_extracted:
														lowerCamelCase_							  =					("""downloads""" if default_cache_dir else custom_cache_dir, """extracted""")
							else:
														monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_DIR"""			,				lowerCAmelCase__       )
														monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_PATH"""			,				str(lowerCAmelCase__       )       )
														lowerCamelCase_							  =					custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

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



def      __lowerCAmelCase						(							UpperCAmelCase__				:      int       )  ->    Any:
							# absolute path
							lowerCamelCase_							  =					str(Path(lowerCAmelCase__       ).resolve()       )
							assert cached_path(lowerCAmelCase__       ) == text_file
							# relative path
							lowerCamelCase_							  =					str(Path(lowerCAmelCase__       ).resolve().relative_to(Path(os.getcwd()       )       )       )
							assert cached_path(lowerCAmelCase__       ) == text_file



def      __lowerCAmelCase						(							UpperCAmelCase__				:      int       )  ->    List[Any]:
							# absolute path
							lowerCamelCase_							  =					str(tmp_path.resolve() / """__missing_file__.txt"""       )
							with pytest.raises(lowerCAmelCase__       ):
														cached_path(lowerCAmelCase__       )
							# relative path
							lowerCamelCase_							  =					"""./__missing_file__.txt"""
							with pytest.raises(lowerCAmelCase__       ):
														cached_path(lowerCAmelCase__       )



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Any       )  ->    int:
							lowerCamelCase_							  =					get_from_cache(F'''tmp://{tmpfs_file}'''       )
							with open(lowerCAmelCase__       ) as f:
														lowerCamelCase_							  =					f.read()
							assert output_file_content == FILE_CONTENT



@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,				lowerCAmelCase__       )
def      __lowerCAmelCase						(							)  ->    Union[str, Any]:
							with pytest.raises(lowerCAmelCase__       ):
														cached_path("""https://huggingface.co"""       )



@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,				lowerCAmelCase__       )
def      __lowerCAmelCase						(							UpperCAmelCase__				:      Dict       )  ->    List[str]:
							lowerCamelCase_							  =					tmp_path_factory.mktemp("""data"""       ) / """file.html"""
							with pytest.raises(lowerCAmelCase__       ):
														http_get("""https://huggingface.co"""			,				temp_file=lowerCAmelCase__       )
							with pytest.raises(lowerCAmelCase__       ):
														http_head("""https://huggingface.co"""       )



@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,				lowerCAmelCase__       )
def      __lowerCAmelCase						(							UpperCAmelCase__				:      Tuple       )  ->    Tuple:
							lowerCamelCase_							  =					tmp_path_factory.mktemp("""data"""       ) / """file.html"""
							with pytest.raises(lowerCAmelCase__       ):
														ftp_get("""ftp://huggingface.co"""			,				temp_file=lowerCAmelCase__       )
							with pytest.raises(lowerCAmelCase__       ):
														ftp_head("""ftp://huggingface.co"""       )



@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,				lowerCAmelCase__       )
def      __lowerCAmelCase						(							UpperCAmelCase__				:      Dict       )  ->    Union[str, Any]:
							lowerCamelCase_							  =					tmp_path_factory.mktemp("""data"""       ) / """file.html"""
							with pytest.raises(lowerCAmelCase__       ):
														fsspec_get("""s3://huggingface.co"""			,				temp_file=lowerCAmelCase__       )
							with pytest.raises(lowerCAmelCase__       ):
														fsspec_head("""s3://huggingface.co"""       )






import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier



def      __lowerCAmelCase						(							UpperCAmelCase__				:      dict       )  ->    tuple:
							return (data["data"], data["target"])



def      __lowerCAmelCase						(							UpperCAmelCase__				:      np.ndarray			,				UpperCAmelCase__				:      np.ndarray       )  ->    XGBClassifier:
							lowerCamelCase_							  =					XGBClassifier()
							classifier.fit(UpperCAmelCase__			,				UpperCAmelCase__       )
							return classifier



def      __lowerCAmelCase						(							)  ->    None:
							lowerCamelCase_							  =					load_iris()
							lowerCamelCase_  ,   lowerCamelCase_							  =					data_handling(UpperCAmelCase__       )
							lowerCamelCase_  ,   lowerCamelCase_  ,   lowerCamelCase_  ,   lowerCamelCase_							  =					train_test_split(
							    UpperCAmelCase__			,				UpperCAmelCase__			,				test_size=0.2_5       )

							lowerCamelCase_							  =					iris["""target_names"""]

							# Create an XGBoost Classifier from the training data
							lowerCamelCase_							  =					xgboost(UpperCAmelCase__			,				UpperCAmelCase__       )

							# Display the confusion matrix of the classifier with both training and test sets
							ConfusionMatrixDisplay.from_estimator(
							    UpperCAmelCase__			,				UpperCAmelCase__			,				UpperCAmelCase__			,				display_labels=UpperCAmelCase__			,				cmap="""Blues"""			,				normalize="""true"""			,				)
							plt.title("""Normalized Confusion Matrix - IRIS Dataset"""       )
							plt.show()


if __name__ == "__main__":
		import doctest

		doctest.testmod(verbose=True)
		main()





