



import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def 	snake_case__       (					__lowercase							,     __lowercase       )		->		Union[str, Any]:







      """simple docstring"""

      assert isinstance(__lowercase							,     __lowercase       )
      assert dataset.num_rows == 4
      assert dataset.num_columns == 1
      assert dataset.column_names == ["text"]
      for feature, expected_dtype in expected_features.items():
            assert dataset.features[feature].dtype == expected_dtype
@pytest.mark.parametrize("keep_in_memory"							,     [False, True]       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		Dict:







      """simple docstring"""

      A__	:							str						    = tmp_path / "cache"
      A__	:							int						    = {"text": "string"}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            A__	:							Dict						    = TextDatasetReader(__lowercase							,     cache_dir=__lowercase							,     keep_in_memory=__lowercase       ).read()
      _check_text_dataset(__lowercase							,     __lowercase       )
@pytest.mark.parametrize(
    "features"							,     [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]							,     )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		Tuple:







      """simple docstring"""

      A__	:							List[str]						    = tmp_path / "cache"
      A__	:							str						    = {"text": "string"}
      A__	:							int						    = features.copy() if features else default_expected_features
      A__	:							Any						    = (
          Features({feature: Value(__lowercase       ) for feature, dtype in features.items()}       ) if features is not None else None
      )
      A__	:							Optional[int]						    = TextDatasetReader(__lowercase							,     features=__lowercase							,     cache_dir=__lowercase       ).read()
      _check_text_dataset(__lowercase							,     __lowercase       )
@pytest.mark.parametrize("split"							,     [None, NamedSplit("train"       ), "train", "test"]       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		Tuple:







      """simple docstring"""

      A__	:							Any						    = tmp_path / "cache"
      A__	:							Tuple						    = {"text": "string"}
      A__	:							str						    = TextDatasetReader(__lowercase							,     cache_dir=__lowercase							,     split=__lowercase       ).read()
      _check_text_dataset(__lowercase							,     __lowercase       )
      assert dataset.split == split if split else "train"
@pytest.mark.parametrize("path_type"							,     [str, list]       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		int:







      """simple docstring"""

      if issubclass(__lowercase							,     __lowercase       ):
            A__	:							List[str]						    = text_path
      elif issubclass(__lowercase							,     __lowercase       ):
            A__	:							Union[str, Any]						    = [text_path]
      A__	:							Optional[Any]						    = tmp_path / "cache"
      A__	:							Dict						    = {"text": "string"}
      A__	:							List[Any]						    = TextDatasetReader(__lowercase							,     cache_dir=__lowercase       ).read()
      _check_text_dataset(__lowercase							,     __lowercase       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase=("train",)       )		->		str:







      """simple docstring"""

      assert isinstance(__lowercase							,     __lowercase       )
      for split in splits:
            A__	:							str						    = dataset_dict[split]
            assert dataset.num_rows == 4
            assert dataset.num_columns == 1
            assert dataset.column_names == ["text"]
            for feature, expected_dtype in expected_features.items():
                  assert dataset.features[feature].dtype == expected_dtype
@pytest.mark.parametrize("keep_in_memory"							,     [False, True]       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		str:







      """simple docstring"""

      A__	:							Optional[int]						    = tmp_path / "cache"
      A__	:							str						    = {"text": "string"}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            A__	:							Dict						    = TextDatasetReader({"train": text_path}							,     cache_dir=__lowercase							,     keep_in_memory=__lowercase       ).read()
      _check_text_datasetdict(__lowercase							,     __lowercase       )
@pytest.mark.parametrize(
    "features"							,     [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]							,     )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		Optional[int]:







      """simple docstring"""

      A__	:							int						    = tmp_path / "cache"
      # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
      A__	:							List[str]						    = {"text": "string"}
      A__	:							int						    = features.copy() if features else default_expected_features
      A__	:							List[Any]						    = (
          Features({feature: Value(__lowercase       ) for feature, dtype in features.items()}       ) if features is not None else None
      )
      A__	:							Union[str, Any]						    = TextDatasetReader({"train": text_path}							,     features=__lowercase							,     cache_dir=__lowercase       ).read()
      _check_text_datasetdict(__lowercase							,     __lowercase       )




@pytest.mark.parametrize("split"							,     [None, NamedSplit("train"       ), "train", "test"]       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		int:







      """simple docstring"""

      if split:
            A__	:							Dict						    = {split: text_path}
      else:
            A__	:							Dict						    = "train"
            A__	:							int						    = {"train": text_path, "test": text_path}
      A__	:							List[str]						    = tmp_path / "cache"
      A__	:							Any						    = {"text": "string"}
      A__	:							Dict						    = TextDatasetReader(__lowercase							,     cache_dir=__lowercase       ).read()
      _check_text_datasetdict(__lowercase							,     __lowercase							,     splits=list(path.keys()       )       )
      assert all(dataset[split].split == split for split in path.keys()       )




snake_case    :						Tuple  =						'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def 	snake_case__       (					)		->		None:







						"""simple docstring"""

						A__	:							Union[str, Any]						    = input("Enter message: "       )
						A__	:							Tuple						    = input("Enter key [alphanumeric]: "       )
						A__	:							Optional[Any]						    = input("Encrypt/Decrypt [e/d]: "       )

						if mode.lower().startswith("e"       ):
												A__	:							Tuple						    = "encrypt"
												A__	:							str						    = encrypt_message(__lowercase							,     __lowercase       )
						elif mode.lower().startswith("d"       ):
												A__	:							Optional[Any]						    = "decrypt"
												A__	:							Union[str, Any]						    = decrypt_message(__lowercase							,     __lowercase       )

						print(F'\n{mode.title()}ed message:'       )
						print(__lowercase       )
def 	snake_case__       (					__lowercase							,     __lowercase       )		->		str:







						"""simple docstring"""

						return translate_message(__lowercase							,     __lowercase							,     "encrypt"       )
def 	snake_case__       (					__lowercase							,     __lowercase       )		->		str:







						"""simple docstring"""

						return translate_message(__lowercase							,     __lowercase							,     "decrypt"       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase       )		->		str:







						"""simple docstring"""

						A__	:							Dict						    = []
						A__	:							Union[str, Any]						    = 0
						A__	:							List[Any]						    = key.upper()

						for symbol in message:
												A__	:							List[str]						    = LETTERS.find(symbol.upper()       )
												if num != -1:
																		if mode == "encrypt":
																								num += LETTERS.find(key[key_index]       )
																		elif mode == "decrypt":
																								num -= LETTERS.find(key[key_index]       )

																		num %= len(__lowercase       )

																		if symbol.isupper():
																								translated.append(LETTERS[num]       )
																		elif symbol.islower():
																								translated.append(LETTERS[num].lower()       )

																		key_index += 1
																		if key_index == len(__lowercase       ):
																								A__	:							Optional[int]						    = 0
												else:
																		translated.append(__lowercase       )
						return "".join(__lowercase       )


if __name__ == "__main__":
		main()