






import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict



@pytest.mark.parametrize(
    """files"""			,				[
        ["""full:README.md""", """dataset_infos.json"""],
        ["""empty:README.md""", """dataset_infos.json"""],
        ["""dataset_infos.json"""],
        ["""full:README.md"""],
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Optional[Any]			,				__lowercase   :			Union[str, Any]    )						->      Dict:





    """simple docstring"""

    __A         =	tmp_path_factory.mktemp("""dset_infos_dir"""    )
    if "full:README.md" in files:
        with open(dataset_infos_dir / """README.md"""			,				"""w"""    ) as f:
            f.write("""---\ndataset_info:\n  dataset_size: 42\n---"""    )
    if "empty:README.md" in files:
        with open(dataset_infos_dir / """README.md"""			,				"""w"""    ) as f:
            f.write(""""""    )
    # we want to support dataset_infos.json for backward compatibility
    if "dataset_infos.json" in files:
        with open(dataset_infos_dir / """dataset_infos.json"""			,				"""w"""    ) as f:
            f.write("""{\"default\": {\"dataset_size\": 42}}"""    )
    __A         =	DatasetInfosDict.from_directory(__lowercase    )
    assert dataset_infos
    assert dataset_infos["default"].dataset_size == 4_2



@pytest.mark.parametrize(
    """dataset_info"""			,				[
        DatasetInfo(),
        DatasetInfo(
            description="""foo"""			,				features=Features({"""a""": Value("""int32"""    )}    )			,				builder_name="""builder"""			,				config_name="""config"""			,				version="""1.0.0"""			,				splits=[{"""name""": """train"""}]			,				download_size=4_2			,				),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Any			,				__lowercase   :			DatasetInfo    )						->      str:





    """simple docstring"""

    __A         =	str(__lowercase    )
    dataset_info.write_to_directory(__lowercase    )
    __A         =	DatasetInfo.from_directory(__lowercase    )
    assert dataset_info == reloaded
    assert os.path.exists(os.path.join(__lowercase			,				"""dataset_info.json"""    )    )



def 			_SCREAMING_SNAKE_CASE						( )						->      Any:





    """simple docstring"""

    __A         =	DatasetInfo(
        description="""foo"""			,				citation="""bar"""			,				homepage="""https://foo.bar"""			,				license="""CC0"""			,				features=Features({"""a""": Value("""int32"""    )}    )			,				post_processed={}			,				supervised_keys=()			,				task_templates=[]			,				builder_name="""builder"""			,				config_name="""config"""			,				version="""1.0.0"""			,				splits=[{"""name""": """train""", """num_examples""": 4_2}]			,				download_checksums={}			,				download_size=1_3_3_7			,				post_processing_size=4_4_2			,				dataset_size=1_2_3_4			,				size_in_bytes=1_3_3_7 + 4_4_2 + 1_2_3_4			,				)
    __A         =	dataset_info._to_yaml_dict()
    assert sorted(__lowercase    ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML    )
    for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
        assert key in dataset_info_yaml_dict
        assert isinstance(dataset_info_yaml_dict[key]			,				(list, dict, int, str)    )
    __A         =	yaml.safe_dump(__lowercase    )
    __A         =	yaml.safe_load(__lowercase    )
    assert dataset_info_yaml_dict == reloaded



def 			_SCREAMING_SNAKE_CASE						( )						->      int:





    """simple docstring"""

    __A         =	DatasetInfo()
    __A         =	dataset_info._to_yaml_dict()
    assert dataset_info_yaml_dict == {}






@pytest.mark.parametrize(
    """dataset_infos_dict"""			,				[
        DatasetInfosDict(),
        DatasetInfosDict({"""default""": DatasetInfo()}    ),
        DatasetInfosDict({"""my_config_name""": DatasetInfo()}    ),
        DatasetInfosDict(
            {
                """default""": DatasetInfo(
                    description="""foo"""			,				features=Features({"""a""": Value("""int32"""    )}    )			,				builder_name="""builder"""			,				config_name="""config"""			,				version="""1.0.0"""			,				splits=[{"""name""": """train"""}]			,				download_size=4_2			,				)
            }    ),
        DatasetInfosDict(
            {
                """v1""": DatasetInfo(dataset_size=4_2    ),
                """v2""": DatasetInfo(dataset_size=1_3_3_7    ),
            }    ),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Optional[int]			,				__lowercase   :			DatasetInfosDict    )						->      Dict:





    """simple docstring"""

    __A         =	str(__lowercase    )
    dataset_infos_dict.write_to_directory(__lowercase    )
    __A         =	DatasetInfosDict.from_directory(__lowercase    )

    # the config_name of the dataset_infos_dict take over the attribute
    for config_name, dataset_info in dataset_infos_dict.items():
        __A         =	config_name
        # the yaml representation doesn't include fields like description or citation
        # so we just test that we can recover what we can from the yaml
        __A         =	DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()    )
    assert dataset_infos_dict == reloaded

    if dataset_infos_dict:
        assert os.path.exists(os.path.join(__lowercase			,				"""README.md"""    )    )












import random
import sys

import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap

__a      :       List[Any]				  =   "Usage of script: script_name <size_of_canvas:int>"

__a      :       Dict				  =   [0] * 100 + [1] * 10
random.shuffle(choice)



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			int    )						->      list[list[bool]]:





    """simple docstring"""

    __A         =	[[False for i in range(__lowercase    )] for j in range(__lowercase    )]
    return canvas



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			list[list[bool]]    )						->      None:





    """simple docstring"""

    for i, row in enumerate(__lowercase    ):
        for j, _ in enumerate(__lowercase    ):
            __A         =	bool(random.getrandbits(1    )    )



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			list[list[bool]]    )						->      list[list[bool]]:





    """simple docstring"""

    __A         =	np.array(__lowercase    )
    __A         =	np.array(create_canvas(current_canvas.shape[0]    )    )
    for r, row in enumerate(__lowercase    ):
        for c, pt in enumerate(__lowercase    ):
            __A         =	__judge_point(
                __lowercase			,				current_canvas[r - 1 : r + 2, c - 1 : c + 2]    )

    __A         =	next_gen_canvas
    del next_gen_canvas  # cleaning memory as we move on.
    __A         =	current_canvas.tolist()
    return return_canvas



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			bool			,				__lowercase   :			list[list[bool]]    )						->      bool:





    """simple docstring"""

    __A         =	0
    __A         =	0
    # finding dead or alive neighbours count.
    for i in neighbours:
        for status in i:
            if status:
                alive += 1
            else:
                dead += 1

    # handling duplicate entry for focus pt.
    if pt:
        alive -= 1
    else:
        dead -= 1

    # running the rules of game here.
    __A         =	pt
    if pt:
        if alive < 2:
            __A         =	False
        elif alive == 2 or alive == 3:
            __A         =	True
        elif alive > 3:
            __A         =	False
    else:
        if alive == 3:
            __A         =	True

    return state


if __name__ == "__main__":
  if len(sys.argv) != 2:
    raise Exception(usage_doc)

  __a      :       str				  =   int(sys.argv[1])
  # main working structure of this module.
  __a      :       List[Any]				  =   create_canvas(canvas_size)
  seed(c)
  __a  ,__a      :       int				  =   plt.subplots()
  fig.show()
  __a      :       Union[str, Any]				  =   ListedColormap(["w", "k"])
  try:
    while True:
      __a      :       Dict				  =   run(c)
      ax.matshow(c, cmap=cmap)
      fig.canvas.draw()
      ax.cla()
  except KeyboardInterrupt:
    # do nothing.
    pass




